From 7e80afb604c4a55a227c12ca79b96b142de0e8c8 Mon Sep 17 00:00:00 2001
From: Derek <dcaustin33@gmail.com>
Date: Thu, 11 May 2023 07:59:21 -0700
Subject: [PATCH 01/16] Initial refactor and dep polygon changes

---
 .../model_logger/semantic_segmentation.py     |  81 +++++-
 dataquality/schemas/semantic_segmentation.py  |   1 +
 .../utils/semantic_segmentation/errors.py     |  59 +++++
 .../utils/semantic_segmentation/metrics.py    |   6 +-
 docs/cv/coco_deeplab_hooks.ipynb              | 232 +++++++++++-------
 5 files changed, 280 insertions(+), 99 deletions(-)

diff --git a/dataquality/loggers/model_logger/semantic_segmentation.py b/dataquality/loggers/model_logger/semantic_segmentation.py
index b824d72c9..1efa3b4a8 100644
--- a/dataquality/loggers/model_logger/semantic_segmentation.py
+++ b/dataquality/loggers/model_logger/semantic_segmentation.py
@@ -1,4 +1,4 @@
-from typing import Dict, List, Optional, Union
+from typing import Dict, List, Optional, Union, Tuple, Any
 
 import numpy as np
 import torch
@@ -13,6 +13,7 @@
 from dataquality.utils.semantic_segmentation.errors import (
     calculate_misclassified_polygons_batch,
     calculate_undetected_polygons_batch,
+    calculate_dep_polygons_batch
 )
 from dataquality.utils.semantic_segmentation.lm import upload_mislabeled_pixels
 from dataquality.utils.semantic_segmentation.metrics import (
@@ -103,6 +104,67 @@ def dep_path(self) -> str:
     @property
     def contours_path(self) -> str:
         return f"{self.proj_run}/{self.split_name_path}/contours"
+    
+    
+    def get_polygon_data(
+        self,
+        pred_polygons_batch:  Tuple[List, List],
+        gold_polygons_batch:  Tuple[List, List],
+    ) -> Dict[str, Any]:
+        """Returns polygon data for a batch of images in a dictionary
+        that can then be used for our polygon df
+
+        Args:
+            pred_polygons_batch (Tuple[List, List]): polygon data for predictions
+                in a minibatch of images
+            gold_polygons_batch (Tuple[List, List]): polygon  data for ground truth
+                in a minibatch of images
+
+        Returns:
+            Dict[str, Any]: a dict that can be used to create a polygon df
+        """
+        image_ids = []
+        polygon_ids = []
+        preds = []
+        golds = []
+        data_error_potentials = []
+        errors = []
+        for i, image_id in enumerate(self.image_ids):
+            pred_polygons = pred_polygons_batch[i]
+            for polygon in pred_polygons:
+                image_ids.append(image_id)
+                preds.append(polygon.label_idx)
+                golds.append(-1)
+                data_error_potentials.append(0.0)
+                errors.append(polygon.error_type.value)
+                upload_polygon_contours(
+                    polygon, self.logger_config.polygon_idx, self.contours_path
+                )
+                polygon_ids.append(self.logger_config.polygon_idx)
+                self.logger_config.polygon_idx += 1
+            gold_polygons = gold_polygons_batch[i]
+            for polygon in gold_polygons:
+                image_ids.append(image_id)
+                preds.append(-1)
+                golds.append(polygon.label_idx)
+                data_error_potentials.append(polygon.data_error_potential)
+                errors.append(polygon.error_type.value)
+                upload_polygon_contours(
+                    polygon, self.logger_config.polygon_idx, self.contours_path
+                )
+                polygon_ids.append(self.logger_config.polygon_idx)
+                self.logger_config.polygon_idx += 1
+
+        polygon_data = {
+            "id": polygon_ids,
+            "image_id": image_ids,
+            "pred": preds,
+            "gold": golds,
+            "data_error_potential": data_error_potentials,
+            "galileo_error_type": errors,
+            "split": [self.split] * len(image_ids),
+        }
+        return polygon_data
 
     def _get_data_dict(self) -> Dict:
         """Returns a dictionary of data to be logged as a DataFrame"""
@@ -112,7 +174,7 @@ def _get_data_dict(self) -> Dict:
             self.mislabled_pixels, self.image_ids, prefix=self.lm_path
         )
 
-        image_dep = calculate_and_upload_dep(
+        image_dep, dep_heatmaps = calculate_and_upload_dep(
             self.output_probs,
             self.gold_masks,
             self.image_ids,
@@ -132,6 +194,13 @@ def _get_data_dict(self) -> Dict:
         # Errors
         calculate_misclassified_polygons_batch(self.pred_masks, gold_polygons_batch)
         calculate_undetected_polygons_batch(self.pred_masks, gold_polygons_batch)
+        
+        '''gold_polygons_batch = calculate_dep_polygons_batch(
+            gold_polygons_batch,
+            dep_heatmaps,
+            height = [img.shape[-1] for img in self.gold_masks],
+            width = [img.shape[-2] for img in self.gold_masks],
+        )'''
 
         image_data = {
             "image": [
@@ -157,6 +226,7 @@ def _get_data_dict(self) -> Dict:
             meta=meta_keys,
         )
 
+        # polygon_data = self.get_polygon_data(pred_polygons_batch, gold_polygons_batch)
         image_ids = []
         polygon_ids = []
         preds = []
@@ -181,7 +251,7 @@ def _get_data_dict(self) -> Dict:
                 image_ids.append(image_id)
                 preds.append(-1)
                 golds.append(polygon.label_idx)
-                data_error_potentials.append(0.0)
+                data_error_potentials.append(0)
                 errors.append(polygon.error_type.value)
                 upload_polygon_contours(
                     polygon, self.logger_config.polygon_idx, self.contours_path
@@ -198,9 +268,10 @@ def _get_data_dict(self) -> Dict:
             "galileo_error_type": errors,
             "split": [self.split] * len(image_ids),
         }
+        
         if self.split == Split.inference:
-            polygon_data["inference_name"] = [self.inference_name] * len(image_ids)
+            polygon_data["inference_name"] = [self.inference_name] * len(self.image_ids)
         else:
-            polygon_data["epoch"] = [self.epoch] * len(image_ids)
+            polygon_data["epoch"] = [self.epoch] * len(self.image_ids)
 
         return polygon_data
diff --git a/dataquality/schemas/semantic_segmentation.py b/dataquality/schemas/semantic_segmentation.py
index faec845bc..76104f796 100644
--- a/dataquality/schemas/semantic_segmentation.py
+++ b/dataquality/schemas/semantic_segmentation.py
@@ -52,6 +52,7 @@ class Polygon(BaseModel):
     misclassified_class_label: Optional[int] = None
     error_type: ErrorType = ErrorType.none
     contours: List[Contour]
+    # data_error_potential: float = 0.0
 
     @property
     def contours_opencv(self) -> List[np.ndarray]:
diff --git a/dataquality/utils/semantic_segmentation/errors.py b/dataquality/utils/semantic_segmentation/errors.py
index 516c4f823..0930b76a0 100644
--- a/dataquality/utils/semantic_segmentation/errors.py
+++ b/dataquality/utils/semantic_segmentation/errors.py
@@ -2,6 +2,8 @@
 
 import numpy as np
 import torch
+import cv2
+from PIL import Image
 
 from dataquality.schemas.semantic_segmentation import ErrorType, Polygon
 from dataquality.utils.semantic_segmentation.polygons import draw_polygon
@@ -155,3 +157,60 @@ def calculate_undetected_polygons_batch(
         pred_mask = pred_masks[idx].numpy()
         gold_polygons = gold_polygons_batch[idx]
         calculate_undetected_polygons(pred_mask, gold_polygons)
+        
+
+def calculate_dep_polygon(
+    dep_map: np.ndarray,
+    polygon_img: np.ndarray,
+) -> None:
+    """Calculate the mean dep score for one polygon drawn onto an image of all
+    zero's. We can then take the polygon's dep score by only selecting those pixels
+    with a value greater than 0 and averageing them.
+
+    Args:
+        dep_map (np.ndarray): heatmap of dep scores for an image
+        polygon_img (np.ndarray): image of all zeros with a polygon drawn on it
+    
+    Returns:
+        dep_score (float): mean dep score for the polygon
+    """
+    relevant_region = polygon_img != 0
+    dep_score = dep_map[relevant_region].mean()
+    return dep_score
+        
+
+        
+def calculate_dep_polygons_batch(
+    gold_polygons_batch: List[List[Polygon]],
+    dep_heatmaps: np.ndarray,
+    height: List[int],
+    width: List[int],
+) -> List[List[Polygon]]:
+    """Takes the mean dep score within a polygon and sets the polygon's
+    dep score to the mean dep score
+
+    Args:
+        gold_polygons_batch (List[List[[Polygon]]): list of the gold polygons 
+            for an image
+        dep_heatmaps (np.ndarray): heatmaps of DEP scores for an image
+        height (int): height of original image to resize the dep map to the correct 
+            dims
+        width (int): width of original image to resize the dep map to the correct 
+            dims
+    """
+    resized_dep_maps = []
+    for i, dep_map in enumerate(dep_heatmaps):
+        resized_dep_maps.append(Image.fromarray(dep_map).resize((width[i], height[i])))
+        
+    for idx in range(len(resized_dep_maps)):
+        dep_map = resized_dep_maps[idx]
+        gold_polygons = gold_polygons_batch[idx]
+        for polygon in gold_polygons:
+            polygon_img = draw_polygon(polygon, dep_map.size)
+            polygon.data_error_potential = calculate_dep_polygon(dep_map, polygon_img)
+            
+    return gold_polygons_batch
+    
+    
+     
+
diff --git a/dataquality/utils/semantic_segmentation/metrics.py b/dataquality/utils/semantic_segmentation/metrics.py
index 29ec933e6..3cc495c09 100644
--- a/dataquality/utils/semantic_segmentation/metrics.py
+++ b/dataquality/utils/semantic_segmentation/metrics.py
@@ -19,16 +19,16 @@ def calculate_and_upload_dep(
     gold_masks: torch.Tensor,
     image_ids: List[int],
     obj_prefix: str,
-) -> List[float]:
+) -> Tuple[List[float], np.ndarray]:
     """Calculates the Data Error Potential (DEP) for each image in the batch
 
     Uploads the heatmap to Minio as a png.
-    Returns the image DEP for each image in the batch.
+    Returns the image DEP for each image in the batch. As well as the dep_heatmaps.
         Image dep is calculated by the average pixel dep.
     """
     dep_heatmaps = calculate_dep_heatmaps(probs, gold_masks)
     upload_dep_heatmaps(dep_heatmaps, image_ids, obj_prefix)
-    return calculate_image_dep(dep_heatmaps)
+    return calculate_image_dep(dep_heatmaps), dep_heatmaps
 
 
 def calculate_dep_heatmaps(
diff --git a/docs/cv/coco_deeplab_hooks.ipynb b/docs/cv/coco_deeplab_hooks.ipynb
index 62d9826f3..8a9838cf8 100644
--- a/docs/cv/coco_deeplab_hooks.ipynb
+++ b/docs/cv/coco_deeplab_hooks.ipynb
@@ -40,23 +40,94 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['cat.jpeg',\n",
+       " 'ui',\n",
+       " 'Screenshot 2023-05-10 at 4.22.31 PM.png',\n",
+       " 'Screenshot 2023-05-10 at 4.22.52 PM.png',\n",
+       " 'hackathon.py',\n",
+       " 'screenshot',\n",
+       " '.DS_Store',\n",
+       " 'Screenshot 2023-05-10 at 4.21.57 PM.png',\n",
+       " 'Hyatt _ Reservation Confirmation.pdf',\n",
+       " '.localized',\n",
+       " '.bashrc',\n",
+       " 'val2017',\n",
+       " 'lease.pdf',\n",
+       " 'Screenshot 2023-05-10 at 4.23.40 PM.png',\n",
+       " 'OD',\n",
+       " 'CV_datasets',\n",
+       " '14D46FBC-BBC7-446D-B6CF-C3924EA12735.jpeg',\n",
+       " 'datasets',\n",
+       " 'tests',\n",
+       " 'recreate',\n",
+       " 'dojo',\n",
+       " 'Screenshot 2023-05-10 at 4.21.43 PM.png',\n",
+       " 'all_images',\n",
+       " 'Screenshot 2023-04-14 at 10.48.39 AM.png',\n",
+       " 'rungalileo',\n",
+       " 'test.py',\n",
+       " 'Screen Shot 2023-03-24 at 2.14.57 PM.png',\n",
+       " 'Screenshot 2023-03-29 at 2.13.50 PM.png',\n",
+       " 'annotations',\n",
+       " 'Screenshot 2023-05-10 at 4.23.28 PM.png',\n",
+       " 'dataquality',\n",
+       " 'Screenshot 2023-05-10 at 4.22.41 PM.png',\n",
+       " 'keypair',\n",
+       " 'Screenshot 2023-05-10 at 4.22.18 PM.png',\n",
+       " 'Hackathon.ipynb',\n",
+       " 'dep',\n",
+       " 'docker_images',\n",
+       " 'beard_pic.jpeg',\n",
+       " 'segmentation_datasets',\n",
+       " 'api',\n",
+       " 'ml papers',\n",
+       " 'runners',\n",
+       " 'ultralytics',\n",
+       " 'random_scripts',\n",
+       " 'cat_pic.jpeg',\n",
+       " 'survey.csv',\n",
+       " 'test.ipynb',\n",
+       " 'Screenshot 2023-05-10 at 4.23.04 PM.png',\n",
+       " 'Screen Shot 2023-02-22 at 1.52.33 PM.png',\n",
+       " 'semantic_segmentation',\n",
+       " 'llama',\n",
+       " 'gpt4all']"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "os.listdir('../../..')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Found dataset, there are 4031 images and 4031 masks\n"
+      "Found dataset, there are 4030 images and 4030 masks\n"
      ]
     }
    ],
    "source": [
     "# download the data from our public gcs bucket and save it to disk\n",
     "# dataset_path, img_path, mask_path = download_gcs_data()\n",
-    "dataset_path = \"./CV_datasets/\"\n",
-    "img_path = \"all_images\"\n",
-    "mask_path = \"all_masks\"\n",
+    "dataset_path = \"/Users/derek/Desktop/CV_datasets\"\n",
+    "img_path = \"COCO_seg_val_5000/all_images\"\n",
+    "mask_path = \"COCO_seg_val_5000/all_masks\"\n",
     "\n",
     "IMG_SIZE = 128\n",
     "NC = 21  # Number of classes\n",
@@ -84,7 +155,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/"
@@ -98,10 +169,10 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Using cache found in /Users/elliottchartock/.cache/torch/hub/pytorch_vision_v0.10.0\n",
-      "/Users/elliottchartock/Code/dataquality/.venv/lib/python3.9/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and will be removed in 0.15, please use 'weights' instead.\n",
+      "Using cache found in /Users/derek/.cache/torch/hub/pytorch_vision_v0.10.0\n",
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.\n",
       "  warnings.warn(\n",
-      "/Users/elliottchartock/Code/dataquality/.venv/lib/python3.9/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and will be removed in 0.15. The current behavior is equivalent to passing `weights=DeepLabV3_ResNet50_Weights.COCO_WITH_VOC_LABELS_V1`. You can also use `weights=DeepLabV3_ResNet50_Weights.DEFAULT` to get the most up-to-date weights.\n",
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=DeepLabV3_ResNet50_Weights.COCO_WITH_VOC_LABELS_V1`. You can also use `weights=DeepLabV3_ResNet50_Weights.DEFAULT` to get the most up-to-date weights.\n",
       "  warnings.warn(msg)\n"
      ]
     }
@@ -119,14 +190,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/elliottchartock/Code/dataquality/.venv/lib/python3.9/site-packages/dataquality/core/__init__.py:27: GalileoWarning: configure is deprecated, use dq.set_console_url and dq.login\n",
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/core/__init__.py:27: GalileoWarning: configure is deprecated, use dq.set_console_url and dq.login\n",
       "  warnings.warn(\n"
      ]
     },
@@ -139,8 +210,22 @@
       "\n",
       "🚀 You're logged in to Galileo as galileo@rungalileo.io!\n",
       "✨ Initializing existing public project 'Derek-Elliott-Proj'\n",
-      "🏃‍♂️ Creating new run 'test-polygon-df'\n",
-      "🛰 Connected to existing project 'Derek-Elliott-Proj', and new run 'test-polygon-df'.\n"
+      "🏃‍♂️ Fetching existing run 'test800'\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/core/init.py:148: GalileoWarning: Run: Derek-Elliott-Proj/test800 already exists! The existing run will get overwritten on call to finish()!\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "🛰 Connected to existing project 'Derek-Elliott-Proj', and existing run 'test800'.\n"
      ]
     }
    ],
@@ -162,7 +247,7 @@
     "import dataquality as dq\n",
     "dq.configure()\n",
     "\n",
-    "dq.init(\"semantic_segmentation\", \"Derek-Elliott-Proj\", 'test-polygon-df')\n",
+    "dq.init(\"semantic_segmentation\", \"Derek-Elliott-Proj\", 'test800')\n",
     "class_dict = { 'background': 0,\n",
     "                            'airplane': 1,\n",
     "                            'bicycle': 2,\n",
@@ -190,9 +275,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2023-05-11 07:57:24.556151: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
+      "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
+     ]
+    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -209,11 +302,13 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torch/cuda/amp/grad_scaler.py:118: UserWarning: torch.cuda.amp.GradScaler is enabled, but CUDA is not available.  Disabling.\n",
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).\n",
+      "  warnings.warn(\n",
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torch/cuda/amp/grad_scaler.py:120: UserWarning: torch.cuda.amp.GradScaler is enabled, but CUDA is not available.  Disabling.\n",
       "  warnings.warn(\"torch.cuda.amp.GradScaler is enabled, but CUDA is not available.  Disabling.\")\n",
-      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torch/amp/autocast_mode.py:202: UserWarning: User provided device_type of 'cuda', but CUDA is not available. Disabling\n",
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torch/amp/autocast_mode.py:204: UserWarning: User provided device_type of 'cuda', but CUDA is not available. Disabling\n",
       "  warnings.warn('User provided device_type of \\'cuda\\', but CUDA is not available. Disabling')\n",
-      " 50%|█████     | 1/2 [00:02<00:02,  2.77s/it]\n"
+      " 50%|█████     | 1/2 [00:02<00:02,  2.91s/it]\n"
      ]
     }
    ],
@@ -253,7 +348,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -270,91 +365,46 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "☁️ Uploading Data\n",
-      "CuML libraries not found, running standard process. For faster Galileo processing, consider installing\n",
-      "`pip install 'dataquality[cuda]' --extra-index-url=https://pypi.nvidia.com/`\n"
+      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.27s =  0.0m =  0.0h\n",
+      " "
      ]
     },
     {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "f1d760def4cc4279b8fb58824ab5801b",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Processing data for upload:   0%|          | 0/2 [00:00<?, ?it/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "37c13aaf9fe8420aa87ffcea1ccbf505",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Uploading data to Galileo:   0%|          | 0.00/29.3k [00:00<?, ?B/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "1ba9803294324f35a7bdf72b7790a432",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Processing data for upload:   0%|          | 0/2 [00:00<?, ?it/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "91270f3e55c84961ae94381c3ea087d0",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Uploading data to Galileo:   0%|          | 0.00/29.3k [00:00<?, ?B/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/model_logger/base_model_logger.py:87: UserWarning: An issue occurred while logging model outputs. Address any issues in your logging and make sure to call dq.init before restarting:\n",
+      "OSError('Unable to create file (unable to truncate a file which is already open)')\n",
+      "  warnings.warn(err_msg)\n"
+     ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Job default successfully submitted. Results will be available soon at https://console.dev.rungalileo.io/insights?projectId=7e78e642-cc40-4f5c-8f45-b2cadd8d674a&runId=42d8a7f3-6891-416f-ac77-e57905193da4&split=training&metric=f1&depHigh=1&depLow=0&taskType=6\n",
-      "Waiting for job (you can safely close this window)...\n",
-      "Done! Job finished with status completed\n",
-      "Click here to see your run! https://console.dev.rungalileo.io/insights?projectId=7e78e642-cc40-4f5c-8f45-b2cadd8d674a&runId=42d8a7f3-6891-416f-ac77-e57905193da4&split=training&metric=f1&depHigh=1&depLow=0&taskType=6\n",
-      "🧹 Cleaning up\n",
-      "🧹 Cleaning up\n"
+      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.17s =  0.0m =  0.0h\n",
+      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.15s =  0.0m =  0.0h\n",
+      " "
      ]
     },
     {
-     "data": {
-      "text/plain": [
-       "'https://console.dev.rungalileo.io/insights?projectId=7e78e642-cc40-4f5c-8f45-b2cadd8d674a&runId=42d8a7f3-6891-416f-ac77-e57905193da4&split=training&metric=f1&depHigh=1&depLow=0&taskType=6'"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
+     "ename": "GalileoException",
+     "evalue": "An issue occurred while logging model outputs. Address any issues in your logging and make sure to call dq.init before restarting:\nOSError('Unable to create file (unable to truncate a file which is already open)')",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mGalileoException\u001b[0m                          Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[7], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m dq\u001b[39m.\u001b[39menable_galileo_verbose()\n\u001b[0;32m----> 2\u001b[0m dq\u001b[39m.\u001b[39;49mfinish()\n",
+      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/utils/helpers.py:25\u001b[0m, in \u001b[0;36mcheck_noop.<locals>.decorator\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     23\u001b[0m \u001b[39mif\u001b[39;00m galileo_disabled():\n\u001b[1;32m     24\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mNone\u001b[39;00m\n\u001b[0;32m---> 25\u001b[0m \u001b[39mreturn\u001b[39;00m func(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n",
+      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/core/finish.py:61\u001b[0m, in \u001b[0;36mfinish\u001b[0;34m(last_epoch, wait, create_data_embs)\u001b[0m\n\u001b[1;32m     58\u001b[0m \u001b[39m# Certain tasks require extra finish logic\u001b[39;00m\n\u001b[1;32m     59\u001b[0m data_logger\u001b[39m.\u001b[39mlogger_config\u001b[39m.\u001b[39mfinish()\n\u001b[0;32m---> 61\u001b[0m data_logger\u001b[39m.\u001b[39;49mupload(last_epoch, create_data_embs\u001b[39m=\u001b[39;49mcreate_data_embs)\n\u001b[1;32m     62\u001b[0m upload_dq_log_file()\n\u001b[1;32m     63\u001b[0m body \u001b[39m=\u001b[39m \u001b[39mdict\u001b[39m(\n\u001b[1;32m     64\u001b[0m     project_id\u001b[39m=\u001b[39m\u001b[39mstr\u001b[39m(config\u001b[39m.\u001b[39mcurrent_project_id),\n\u001b[1;32m     65\u001b[0m     run_id\u001b[39m=\u001b[39m\u001b[39mstr\u001b[39m(config\u001b[39m.\u001b[39mcurrent_run_id),\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     70\u001b[0m     feature_names\u001b[39m=\u001b[39mdata_logger\u001b[39m.\u001b[39mlogger_config\u001b[39m.\u001b[39mfeature_names,\n\u001b[1;32m     71\u001b[0m )\n",
+      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/data_logger/base_data_logger.py:229\u001b[0m, in \u001b[0;36mBaseGalileoDataLogger.upload\u001b[0;34m(self, last_epoch, create_data_embs)\u001b[0m\n\u001b[1;32m    225\u001b[0m \u001b[39massert\u001b[39;00m (\n\u001b[1;32m    226\u001b[0m     config\u001b[39m.\u001b[39mcurrent_project_id \u001b[39mand\u001b[39;00m config\u001b[39m.\u001b[39mcurrent_run_id\n\u001b[1;32m    227\u001b[0m ), \u001b[39m\"\u001b[39m\u001b[39mYou must call dq.init and train a model before calling finish\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m    228\u001b[0m ThreadPoolManager\u001b[39m.\u001b[39mwait_for_threads()\n\u001b[0;32m--> 229\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mcheck_for_logging_failures()\n\u001b[1;32m    230\u001b[0m \u001b[39mprint\u001b[39m(\u001b[39m\"\u001b[39m\u001b[39m☁️ Uploading Data\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[1;32m    231\u001b[0m object_store \u001b[39m=\u001b[39m ObjectStore()\n",
+      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/base_logger.py:354\u001b[0m, in \u001b[0;36mBaseGalileoLogger.check_for_logging_failures\u001b[0;34m(cls)\u001b[0m\n\u001b[1;32m    352\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mcls\u001b[39m\u001b[39m.\u001b[39mlogger_config\u001b[39m.\u001b[39mexception:\n\u001b[1;32m    353\u001b[0m     upload_dq_log_file()\n\u001b[0;32m--> 354\u001b[0m     \u001b[39mraise\u001b[39;00m GalileoException(\u001b[39mcls\u001b[39m\u001b[39m.\u001b[39mlogger_config\u001b[39m.\u001b[39mexception)\n",
+      "\u001b[0;31mGalileoException\u001b[0m: An issue occurred while logging model outputs. Address any issues in your logging and make sure to call dq.init before restarting:\nOSError('Unable to create file (unable to truncate a file which is already open)')"
+     ]
     }
    ],
    "source": [
+    "dq.enable_galileo_verbose()\n",
     "dq.finish()"
    ]
   },
@@ -888,7 +938,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.6"
+   "version": "3.9.10"
   },
   "toc-autonumbering": false,
   "toc-showmarkdowntxt": false,

From e201fffb9f02108126523a2c18b004cee3c3da55 Mon Sep 17 00:00:00 2001
From: Derek <dcaustin33@gmail.com>
Date: Thu, 11 May 2023 11:42:26 -0700
Subject: [PATCH 02/16] Revert notebook

---
 docs/cv/coco_deeplab_hooks.ipynb | 254 +------------------------------
 1 file changed, 2 insertions(+), 252 deletions(-)

diff --git a/docs/cv/coco_deeplab_hooks.ipynb b/docs/cv/coco_deeplab_hooks.ipynb
index af996a4ae..c51512882 100644
--- a/docs/cv/coco_deeplab_hooks.ipynb
+++ b/docs/cv/coco_deeplab_hooks.ipynb
@@ -29,94 +29,6 @@
   },
   {
    "cell_type": "code",
-<<<<<<< HEAD
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['cat.jpeg',\n",
-       " 'ui',\n",
-       " 'Screenshot 2023-05-10 at 4.22.31 PM.png',\n",
-       " 'Screenshot 2023-05-10 at 4.22.52 PM.png',\n",
-       " 'hackathon.py',\n",
-       " 'screenshot',\n",
-       " '.DS_Store',\n",
-       " 'Screenshot 2023-05-10 at 4.21.57 PM.png',\n",
-       " 'Hyatt _ Reservation Confirmation.pdf',\n",
-       " '.localized',\n",
-       " '.bashrc',\n",
-       " 'val2017',\n",
-       " 'lease.pdf',\n",
-       " 'Screenshot 2023-05-10 at 4.23.40 PM.png',\n",
-       " 'OD',\n",
-       " 'CV_datasets',\n",
-       " '14D46FBC-BBC7-446D-B6CF-C3924EA12735.jpeg',\n",
-       " 'datasets',\n",
-       " 'tests',\n",
-       " 'recreate',\n",
-       " 'dojo',\n",
-       " 'Screenshot 2023-05-10 at 4.21.43 PM.png',\n",
-       " 'all_images',\n",
-       " 'Screenshot 2023-04-14 at 10.48.39 AM.png',\n",
-       " 'rungalileo',\n",
-       " 'test.py',\n",
-       " 'Screen Shot 2023-03-24 at 2.14.57 PM.png',\n",
-       " 'Screenshot 2023-03-29 at 2.13.50 PM.png',\n",
-       " 'annotations',\n",
-       " 'Screenshot 2023-05-10 at 4.23.28 PM.png',\n",
-       " 'dataquality',\n",
-       " 'Screenshot 2023-05-10 at 4.22.41 PM.png',\n",
-       " 'keypair',\n",
-       " 'Screenshot 2023-05-10 at 4.22.18 PM.png',\n",
-       " 'Hackathon.ipynb',\n",
-       " 'dep',\n",
-       " 'docker_images',\n",
-       " 'beard_pic.jpeg',\n",
-       " 'segmentation_datasets',\n",
-       " 'api',\n",
-       " 'ml papers',\n",
-       " 'runners',\n",
-       " 'ultralytics',\n",
-       " 'random_scripts',\n",
-       " 'cat_pic.jpeg',\n",
-       " 'survey.csv',\n",
-       " 'test.ipynb',\n",
-       " 'Screenshot 2023-05-10 at 4.23.04 PM.png',\n",
-       " 'Screen Shot 2023-02-22 at 1.52.33 PM.png',\n",
-       " 'semantic_segmentation',\n",
-       " 'llama',\n",
-       " 'gpt4all']"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "os.listdir('../../..')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Found dataset, there are 4030 images and 4030 masks\n"
-     ]
-    }
-   ],
-   "source": [
-    "# download the data from our public gcs bucket and save it to disk\n",
-    "# dataset_path, img_path, mask_path = download_gcs_data()\n",
-    "dataset_path = \"/Users/derek/Desktop/CV_datasets\"\n",
-=======
    "execution_count": null,
    "metadata": {},
    "outputs": [],
@@ -124,7 +36,6 @@
     "# download the data from our public gcs bucket and save it to disk\n",
     "# dataset_path, img_path, mask_path = download_gcs_data()\n",
     "dataset_path = \"../../../CV_datasets/\"\n",
->>>>>>> main
     "img_path = \"COCO_seg_val_5000/all_images\"\n",
     "mask_path = \"COCO_seg_val_5000/all_masks\"\n",
     "\n",
@@ -154,11 +65,7 @@
   },
   {
    "cell_type": "code",
-<<<<<<< HEAD
-   "execution_count": 4,
-=======
    "execution_count": null,
->>>>>>> main
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/"
@@ -167,23 +74,7 @@
     "outputId": "85d91dc9-405e-4f02-a6bf-6a88f9502412",
     "tags": []
    },
-<<<<<<< HEAD
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Using cache found in /Users/derek/.cache/torch/hub/pytorch_vision_v0.10.0\n",
-      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.\n",
-      "  warnings.warn(\n",
-      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=DeepLabV3_ResNet50_Weights.COCO_WITH_VOC_LABELS_V1`. You can also use `weights=DeepLabV3_ResNet50_Weights.DEFAULT` to get the most up-to-date weights.\n",
-      "  warnings.warn(msg)\n"
-     ]
-    }
-   ],
-=======
    "outputs": [],
->>>>>>> main
    "source": [
     "\n",
     "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
@@ -197,51 +88,9 @@
   },
   {
    "cell_type": "code",
-<<<<<<< HEAD
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/core/__init__.py:27: GalileoWarning: configure is deprecated, use dq.set_console_url and dq.login\n",
-      "  warnings.warn(\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "📡 https://console.dev.rungalileo.io\n",
-      "🔭 Logging you into Galileo\n",
-      "\n",
-      "🚀 You're logged in to Galileo as galileo@rungalileo.io!\n",
-      "✨ Initializing existing public project 'Derek-Elliott-Proj'\n",
-      "🏃‍♂️ Fetching existing run 'test800'\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/core/init.py:148: GalileoWarning: Run: Derek-Elliott-Proj/test800 already exists! The existing run will get overwritten on call to finish()!\n",
-      "  warnings.warn(\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "🛰 Connected to existing project 'Derek-Elliott-Proj', and existing run 'test800'.\n"
-     ]
-    }
-   ],
-=======
    "execution_count": null,
    "metadata": {},
    "outputs": [],
->>>>>>> main
    "source": [
     "try:\n",
     "    import dataquality as dq\n",
@@ -260,7 +109,7 @@
     "import dataquality as dq\n",
     "dq.configure()\n",
     "\n",
-    "dq.init(\"semantic_segmentation\", \"Derek-Elliott-Proj\", 'test800')\n",
+    "dq.init(\"semantic_segmentation\", \"Derek-Elliott-Proj\", 'test-polygon-df')\n",
     "class_dict = { 'background': 0,\n",
     "                            'airplane': 1,\n",
     "                            'bicycle': 2,\n",
@@ -288,49 +137,9 @@
   },
   {
    "cell_type": "code",
-<<<<<<< HEAD
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "2023-05-11 07:57:24.556151: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
-      "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "We assume the dataloaders passed only have transforms that Tensor, Resize,         and Normalize the image and mask\n",
-      "‼ Any cropping or shearing transforms passed will lead to unexpected         results\n",
-      "See docs at https://dq.readthedocs.io/en/latest/ (placeholder) for more info         \n",
-      " \n",
-      "\n",
-      "Found layer classifier in model layers: backbone, classifier\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).\n",
-      "  warnings.warn(\n",
-      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torch/cuda/amp/grad_scaler.py:120: UserWarning: torch.cuda.amp.GradScaler is enabled, but CUDA is not available.  Disabling.\n",
-      "  warnings.warn(\"torch.cuda.amp.GradScaler is enabled, but CUDA is not available.  Disabling.\")\n",
-      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torch/amp/autocast_mode.py:204: UserWarning: User provided device_type of 'cuda', but CUDA is not available. Disabling\n",
-      "  warnings.warn('User provided device_type of \\'cuda\\', but CUDA is not available. Disabling')\n",
-      " 50%|█████     | 1/2 [00:02<00:02,  2.91s/it]\n"
-     ]
-    }
-   ],
-=======
    "execution_count": null,
    "metadata": {},
    "outputs": [],
->>>>>>> main
    "source": [
     "from dataquality.integrations.cv.torch.semantic_segmentation import watch\n",
     "watch(\n",
@@ -367,69 +176,10 @@
   },
   {
    "cell_type": "code",
-<<<<<<< HEAD
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/derek/.cache/huggingface/modules/evaluate_modules/metrics/evaluate-metric--mean_iou/08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9/mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
-      "  iou = total_area_intersect / total_area_union\n",
-      "/Users/derek/.cache/huggingface/modules/evaluate_modules/metrics/evaluate-metric--mean_iou/08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9/mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
-      "  acc = total_area_intersect / total_area_label\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.27s =  0.0m =  0.0h\n",
-      " "
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/model_logger/base_model_logger.py:87: UserWarning: An issue occurred while logging model outputs. Address any issues in your logging and make sure to call dq.init before restarting:\n",
-      "OSError('Unable to create file (unable to truncate a file which is already open)')\n",
-      "  warnings.warn(err_msg)\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.17s =  0.0m =  0.0h\n",
-      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.15s =  0.0m =  0.0h\n",
-      " "
-     ]
-    },
-    {
-     "ename": "GalileoException",
-     "evalue": "An issue occurred while logging model outputs. Address any issues in your logging and make sure to call dq.init before restarting:\nOSError('Unable to create file (unable to truncate a file which is already open)')",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mGalileoException\u001b[0m                          Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[7], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m dq\u001b[39m.\u001b[39menable_galileo_verbose()\n\u001b[0;32m----> 2\u001b[0m dq\u001b[39m.\u001b[39;49mfinish()\n",
-      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/utils/helpers.py:25\u001b[0m, in \u001b[0;36mcheck_noop.<locals>.decorator\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     23\u001b[0m \u001b[39mif\u001b[39;00m galileo_disabled():\n\u001b[1;32m     24\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mNone\u001b[39;00m\n\u001b[0;32m---> 25\u001b[0m \u001b[39mreturn\u001b[39;00m func(\u001b[39m*\u001b[39;49margs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n",
-      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/core/finish.py:61\u001b[0m, in \u001b[0;36mfinish\u001b[0;34m(last_epoch, wait, create_data_embs)\u001b[0m\n\u001b[1;32m     58\u001b[0m \u001b[39m# Certain tasks require extra finish logic\u001b[39;00m\n\u001b[1;32m     59\u001b[0m data_logger\u001b[39m.\u001b[39mlogger_config\u001b[39m.\u001b[39mfinish()\n\u001b[0;32m---> 61\u001b[0m data_logger\u001b[39m.\u001b[39;49mupload(last_epoch, create_data_embs\u001b[39m=\u001b[39;49mcreate_data_embs)\n\u001b[1;32m     62\u001b[0m upload_dq_log_file()\n\u001b[1;32m     63\u001b[0m body \u001b[39m=\u001b[39m \u001b[39mdict\u001b[39m(\n\u001b[1;32m     64\u001b[0m     project_id\u001b[39m=\u001b[39m\u001b[39mstr\u001b[39m(config\u001b[39m.\u001b[39mcurrent_project_id),\n\u001b[1;32m     65\u001b[0m     run_id\u001b[39m=\u001b[39m\u001b[39mstr\u001b[39m(config\u001b[39m.\u001b[39mcurrent_run_id),\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     70\u001b[0m     feature_names\u001b[39m=\u001b[39mdata_logger\u001b[39m.\u001b[39mlogger_config\u001b[39m.\u001b[39mfeature_names,\n\u001b[1;32m     71\u001b[0m )\n",
-      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/data_logger/base_data_logger.py:229\u001b[0m, in \u001b[0;36mBaseGalileoDataLogger.upload\u001b[0;34m(self, last_epoch, create_data_embs)\u001b[0m\n\u001b[1;32m    225\u001b[0m \u001b[39massert\u001b[39;00m (\n\u001b[1;32m    226\u001b[0m     config\u001b[39m.\u001b[39mcurrent_project_id \u001b[39mand\u001b[39;00m config\u001b[39m.\u001b[39mcurrent_run_id\n\u001b[1;32m    227\u001b[0m ), \u001b[39m\"\u001b[39m\u001b[39mYou must call dq.init and train a model before calling finish\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m    228\u001b[0m ThreadPoolManager\u001b[39m.\u001b[39mwait_for_threads()\n\u001b[0;32m--> 229\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mcheck_for_logging_failures()\n\u001b[1;32m    230\u001b[0m \u001b[39mprint\u001b[39m(\u001b[39m\"\u001b[39m\u001b[39m☁️ Uploading Data\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[1;32m    231\u001b[0m object_store \u001b[39m=\u001b[39m ObjectStore()\n",
-      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/base_logger.py:354\u001b[0m, in \u001b[0;36mBaseGalileoLogger.check_for_logging_failures\u001b[0;34m(cls)\u001b[0m\n\u001b[1;32m    352\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mcls\u001b[39m\u001b[39m.\u001b[39mlogger_config\u001b[39m.\u001b[39mexception:\n\u001b[1;32m    353\u001b[0m     upload_dq_log_file()\n\u001b[0;32m--> 354\u001b[0m     \u001b[39mraise\u001b[39;00m GalileoException(\u001b[39mcls\u001b[39m\u001b[39m.\u001b[39mlogger_config\u001b[39m.\u001b[39mexception)\n",
-      "\u001b[0;31mGalileoException\u001b[0m: An issue occurred while logging model outputs. Address any issues in your logging and make sure to call dq.init before restarting:\nOSError('Unable to create file (unable to truncate a file which is already open)')"
-     ]
-    }
-   ],
-=======
    "execution_count": null,
    "metadata": {},
    "outputs": [],
->>>>>>> main
    "source": [
-    "dq.enable_galileo_verbose()\n",
     "dq.finish()"
    ]
   },
@@ -954,7 +704,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.10"
+   "version": "3.9.6"
   },
   "toc-autonumbering": false,
   "toc-showmarkdowntxt": false,

From a0006b0fb7f364f77944ff1340ae725761ad9936 Mon Sep 17 00:00:00 2001
From: Derek <dcaustin33@gmail.com>
Date: Thu, 11 May 2023 11:50:45 -0700
Subject: [PATCH 03/16] intermediate commits

---
 .../model_logger/semantic_segmentation.py     |  43 +-
 dataquality/schemas/semantic_segmentation.py  |   2 +-
 docs/cv/coco_deeplab_hooks.ipynb              | 892 +++++++++++++++++-
 3 files changed, 882 insertions(+), 55 deletions(-)

diff --git a/dataquality/loggers/model_logger/semantic_segmentation.py b/dataquality/loggers/model_logger/semantic_segmentation.py
index 1efa3b4a8..96dbe03ef 100644
--- a/dataquality/loggers/model_logger/semantic_segmentation.py
+++ b/dataquality/loggers/model_logger/semantic_segmentation.py
@@ -226,48 +226,7 @@ def _get_data_dict(self) -> Dict:
             meta=meta_keys,
         )
 
-        # polygon_data = self.get_polygon_data(pred_polygons_batch, gold_polygons_batch)
-        image_ids = []
-        polygon_ids = []
-        preds = []
-        golds = []
-        data_error_potentials = []
-        errors = []
-        for i, image_id in enumerate(self.image_ids):
-            pred_polygons = pred_polygons_batch[i]
-            for polygon in pred_polygons:
-                image_ids.append(image_id)
-                preds.append(polygon.label_idx)
-                golds.append(-1)
-                data_error_potentials.append(0.0)
-                errors.append(polygon.error_type.value)
-                upload_polygon_contours(
-                    polygon, self.logger_config.polygon_idx, self.contours_path
-                )
-                polygon_ids.append(self.logger_config.polygon_idx)
-                self.logger_config.polygon_idx += 1
-            gold_polygons = gold_polygons_batch[i]
-            for polygon in gold_polygons:
-                image_ids.append(image_id)
-                preds.append(-1)
-                golds.append(polygon.label_idx)
-                data_error_potentials.append(0)
-                errors.append(polygon.error_type.value)
-                upload_polygon_contours(
-                    polygon, self.logger_config.polygon_idx, self.contours_path
-                )
-                polygon_ids.append(self.logger_config.polygon_idx)
-                self.logger_config.polygon_idx += 1
-
-        polygon_data = {
-            "id": polygon_ids,
-            "image_id": image_ids,
-            "pred": preds,
-            "gold": golds,
-            "data_error_potential": data_error_potentials,
-            "galileo_error_type": errors,
-            "split": [self.split] * len(image_ids),
-        }
+        polygon_data = self.get_polygon_data(pred_polygons_batch, gold_polygons_batch)
         
         if self.split == Split.inference:
             polygon_data["inference_name"] = [self.inference_name] * len(self.image_ids)
diff --git a/dataquality/schemas/semantic_segmentation.py b/dataquality/schemas/semantic_segmentation.py
index 76104f796..064d7de7c 100644
--- a/dataquality/schemas/semantic_segmentation.py
+++ b/dataquality/schemas/semantic_segmentation.py
@@ -52,7 +52,7 @@ class Polygon(BaseModel):
     misclassified_class_label: Optional[int] = None
     error_type: ErrorType = ErrorType.none
     contours: List[Contour]
-    # data_error_potential: float = 0.0
+    data_error_potential: float = 0.0
 
     @property
     def contours_opencv(self) -> List[np.ndarray]:
diff --git a/docs/cv/coco_deeplab_hooks.ipynb b/docs/cv/coco_deeplab_hooks.ipynb
index c51512882..0a740579d 100644
--- a/docs/cv/coco_deeplab_hooks.ipynb
+++ b/docs/cv/coco_deeplab_hooks.ipynb
@@ -2,9 +2,20 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'ds = load_dataset(\\n    \"CVdatasets/CocoSegmentationOnlyVal5000\",\\n    use_auth_token=\"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\"\\n)'"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# !pip install datasets evaluate torch torchvision \n",
     "import os\n",
@@ -29,9 +40,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Found dataset, there are 4030 images and 4030 masks\n"
+     ]
+    }
+   ],
    "source": [
     "# download the data from our public gcs bucket and save it to disk\n",
     "# dataset_path, img_path, mask_path = download_gcs_data()\n",
@@ -65,7 +84,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/"
@@ -74,7 +93,19 @@
     "outputId": "85d91dc9-405e-4f02-a6bf-6a88f9502412",
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Using cache found in /Users/derek/.cache/torch/hub/pytorch_vision_v0.10.0\n",
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.\n",
+      "  warnings.warn(\n",
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=DeepLabV3_ResNet50_Weights.COCO_WITH_VOC_LABELS_V1`. You can also use `weights=DeepLabV3_ResNet50_Weights.DEFAULT` to get the most up-to-date weights.\n",
+      "  warnings.warn(msg)\n"
+     ]
+    }
+   ],
    "source": [
     "\n",
     "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
@@ -88,9 +119,45 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/core/__init__.py:27: GalileoWarning: configure is deprecated, use dq.set_console_url and dq.login\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "📡 https://console.dev.rungalileo.io\n",
+      "🔭 Logging you into Galileo\n",
+      "\n",
+      "🚀 You're logged in to Galileo as galileo@rungalileo.io!\n",
+      "✨ Initializing existing public project 'Derek-Elliott-Proj'\n",
+      "🏃‍♂️ Fetching existing run 'test-polygon-df'\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/core/init.py:171: GalileoWarning: Run: Derek-Elliott-Proj/test-polygon-df already exists! The existing run will get overwritten on call to finish()!\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "🛰 Connected to existing project 'Derek-Elliott-Proj', and existing run 'test-polygon-df'.\n"
+     ]
+    }
+   ],
    "source": [
     "try:\n",
     "    import dataquality as dq\n",
@@ -137,9 +204,43 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2023-05-11 11:49:01.215830: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
+      "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "We assume the dataloaders passed only have transforms that Tensor, Resize,         and Normalize the image and mask\n",
+      "‼ Any cropping or shearing transforms passed will lead to unexpected         results\n",
+      "See docs at https://dq.readthedocs.io/en/latest/ (placeholder) for more info         \n",
+      " \n",
+      "\n",
+      "Found layer classifier in model layers: backbone, classifier\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).\n",
+      "  warnings.warn(\n",
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torch/cuda/amp/grad_scaler.py:120: UserWarning: torch.cuda.amp.GradScaler is enabled, but CUDA is not available.  Disabling.\n",
+      "  warnings.warn(\"torch.cuda.amp.GradScaler is enabled, but CUDA is not available.  Disabling.\")\n",
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torch/amp/autocast_mode.py:204: UserWarning: User provided device_type of 'cuda', but CUDA is not available. Disabling\n",
+      "  warnings.warn('User provided device_type of \\'cuda\\', but CUDA is not available. Disabling')\n",
+      " 50%|█████     | 1/2 [00:02<00:02,  2.83s/it]\n"
+     ]
+    }
+   ],
    "source": [
     "from dataquality.integrations.cv.torch.semantic_segmentation import watch\n",
     "watch(\n",
@@ -176,9 +277,776 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/derek/.cache/huggingface/modules/evaluate_modules/metrics/evaluate-metric--mean_iou/08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9/mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "/Users/derek/.cache/huggingface/modules/evaluate_modules/metrics/evaluate-metric--mean_iou/08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9/mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.29s =  0.0m =  0.0h\n",
+      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.16s =  0.0m =  0.0h\n",
+      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.22s =  0.0m =  0.0h \n",
+      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.27s =  0.0m =  0.0h\n",
+      " ☁️ Uploading Data\n",
+      "CuML libraries not found, running standard process. For faster Galileo processing, consider installing\n",
+      "`pip install 'dataquality[cuda]' --extra-index-url=https://pypi.nvidia.com/`\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "aba6e837e4d14c1693c3b963f64de2a6",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Uploading data to Galileo:   0%|          | 0.00/25.8k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[05/11/23 11:49:23] </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">ERROR   </span> error opening                                                          <a href=\"file:///Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/__init__.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">__init__.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/__init__.py#271\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">271</span></a>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">'/Users/derek/.galileo/logs/7e78e642-cc40-4f5c-8f45-b2cadd8d674a/f9855</span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">eea-4121-4a24-bd68-132d3346a89a/training/0/80e887398eb1.hdf5'</span>          <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         Traceback <span style=\"font-weight: bold\">(</span>most recent call last<span style=\"font-weight: bold\">)</span>:                                     <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>           File                                                                 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va</span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">ex/__init__.py\"</span>, line <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">244</span>, in open                                     <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>             ds = <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">vaex.dataset.open</span><span style=\"font-weight: bold\">(</span>path, <span style=\"color: #808000; text-decoration-color: #808000\">fs_options</span>=<span style=\"color: #800080; text-decoration-color: #800080\">fs_options</span>, <span style=\"color: #808000; text-decoration-color: #808000\">fs</span>=<span style=\"color: #800080; text-decoration-color: #800080\">fs</span>,         <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         **kwargs<span style=\"font-weight: bold\">)</span>                                                              <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>           File                                                                 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va</span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">ex/dataset.py\"</span>, line <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">81</span>, in open                                       <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>             return <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">opener.open</span><span style=\"font-weight: bold\">(</span>path, <span style=\"color: #808000; text-decoration-color: #808000\">fs_options</span>=<span style=\"color: #800080; text-decoration-color: #800080\">fs_options</span>, <span style=\"color: #808000; text-decoration-color: #808000\">fs</span>=<span style=\"color: #800080; text-decoration-color: #800080\">fs</span>, *args,      <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         **kwargs<span style=\"font-weight: bold\">)</span>                                                              <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>           File                                                                 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va</span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">ex/dataset.py\"</span>, line <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1457</span>, in open                                     <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>             return <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">cls</span><span style=\"font-weight: bold\">(</span>path, *args, **kwargs<span style=\"font-weight: bold\">)</span>                                  <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>           File                                                                 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va</span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">ex/hdf5/dataset.py\"</span>, line <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">73</span>, in __init__                              <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>             <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">self._freeze</span><span style=\"font-weight: bold\">()</span>                                                     <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>           File                                                                 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va</span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">ex/dataset.py\"</span>, line <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1501</span>, in _freeze                                  <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>             <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">self._set_row_count</span><span style=\"font-weight: bold\">()</span>                                              <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>           File                                                                 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va</span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">ex/dataset.py\"</span>, line <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">423</span>, in _set_row_count                            <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>             raise <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">ValueError</span><span style=\"font-weight: bold\">(</span>f'First columns has length <span style=\"font-weight: bold\">{</span>self._row_count<span style=\"font-weight: bold\">}</span>,     <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         while column <span style=\"font-weight: bold\">{</span>name<span style=\"font-weight: bold\">}</span> has length <span style=\"font-weight: bold\">{</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">len</span><span style=\"font-weight: bold\">(</span>value<span style=\"font-weight: bold\">)}</span>'<span style=\"font-weight: bold\">)</span>                          <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         ValueError: First columns has length <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>, while column epoch has length  <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>                                                                      <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[2;36m[05/11/23 11:49:23]\u001b[0m\u001b[2;36m \u001b[0m\u001b[1;31mERROR   \u001b[0m error opening                                                          \u001b]8;id=155436;file:///Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=520318;file:///Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/__init__.py#271\u001b\\\u001b[2m271\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[2;36m                    \u001b[0m         \u001b[32m'/Users/derek/.galileo/logs/7e78e642-cc40-4f5c-8f45-b2cadd8d674a/f9855\u001b[0m \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         \u001b[32meea-4121-4a24-bd68-132d3346a89a/training/0/80e887398eb1.hdf5'\u001b[0m          \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         Traceback \u001b[1m(\u001b[0mmost recent call last\u001b[1m)\u001b[0m:                                     \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m           File                                                                 \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         \u001b[32m\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va\u001b[0m \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         \u001b[32mex/__init__.py\"\u001b[0m, line \u001b[1;36m244\u001b[0m, in open                                     \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m             ds = \u001b[1;35mvaex.dataset.open\u001b[0m\u001b[1m(\u001b[0mpath, \u001b[33mfs_options\u001b[0m=\u001b[35mfs_options\u001b[0m, \u001b[33mfs\u001b[0m=\u001b[35mfs\u001b[0m,         \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         **kwargs\u001b[1m)\u001b[0m                                                              \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m           File                                                                 \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         \u001b[32m\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va\u001b[0m \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         \u001b[32mex/dataset.py\"\u001b[0m, line \u001b[1;36m81\u001b[0m, in open                                       \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m             return \u001b[1;35mopener.open\u001b[0m\u001b[1m(\u001b[0mpath, \u001b[33mfs_options\u001b[0m=\u001b[35mfs_options\u001b[0m, \u001b[33mfs\u001b[0m=\u001b[35mfs\u001b[0m, *args,      \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         **kwargs\u001b[1m)\u001b[0m                                                              \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m           File                                                                 \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         \u001b[32m\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va\u001b[0m \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         \u001b[32mex/dataset.py\"\u001b[0m, line \u001b[1;36m1457\u001b[0m, in open                                     \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m             return \u001b[1;35mcls\u001b[0m\u001b[1m(\u001b[0mpath, *args, **kwargs\u001b[1m)\u001b[0m                                  \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m           File                                                                 \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         \u001b[32m\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va\u001b[0m \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         \u001b[32mex/hdf5/dataset.py\"\u001b[0m, line \u001b[1;36m73\u001b[0m, in __init__                              \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m             \u001b[1;35mself._freeze\u001b[0m\u001b[1m(\u001b[0m\u001b[1m)\u001b[0m                                                     \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m           File                                                                 \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         \u001b[32m\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va\u001b[0m \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         \u001b[32mex/dataset.py\"\u001b[0m, line \u001b[1;36m1501\u001b[0m, in _freeze                                  \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m             \u001b[1;35mself._set_row_count\u001b[0m\u001b[1m(\u001b[0m\u001b[1m)\u001b[0m                                              \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m           File                                                                 \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         \u001b[32m\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va\u001b[0m \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         \u001b[32mex/dataset.py\"\u001b[0m, line \u001b[1;36m423\u001b[0m, in _set_row_count                            \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m             raise \u001b[1;35mValueError\u001b[0m\u001b[1m(\u001b[0mf'First columns has length \u001b[1m{\u001b[0mself._row_count\u001b[1m}\u001b[0m,     \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         while column \u001b[1m{\u001b[0mname\u001b[1m}\u001b[0m has length \u001b[1m{\u001b[0m\u001b[1;35mlen\u001b[0m\u001b[1m(\u001b[0mvalue\u001b[1m)\u001b[0m\u001b[1m}\u001b[0m'\u001b[1m)\u001b[0m                          \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         ValueError: First columns has length \u001b[1;36m3\u001b[0m, while column epoch has length  \u001b[2m               \u001b[0m\n",
+       "\u001b[2;36m                    \u001b[0m         \u001b[1;36m2\u001b[0m                                                                      \u001b[2m               \u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Custom TB Handler failed, unregistering\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n",
+      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)\n",
+      "    \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n",
+      "\n",
+      "Cell \u001b[0;32mIn[6], line 1\u001b[0m\n",
+      "\u001b[0;32m----> 1\u001b[0m \u001b[43mdq\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfinish\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\n",
+      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/utils/helpers.py:25\u001b[0m, in \u001b[0;36mcheck_noop.<locals>.decorator\u001b[0;34m(*args, **kwargs)\u001b[0m\n",
+      "\u001b[1;32m     24\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n",
+      "\u001b[0;32m---> 25\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\n",
+      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/core/finish.py:61\u001b[0m, in \u001b[0;36mfinish\u001b[0;34m(last_epoch, wait, create_data_embs)\u001b[0m\n",
+      "\u001b[1;32m     59\u001b[0m data_logger\u001b[38;5;241m.\u001b[39mlogger_config\u001b[38;5;241m.\u001b[39mfinish()\n",
+      "\u001b[0;32m---> 61\u001b[0m \u001b[43mdata_logger\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mupload\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlast_epoch\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcreate_data_embs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcreate_data_embs\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\u001b[1;32m     62\u001b[0m upload_dq_log_file()\n",
+      "\n",
+      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/data_logger/base_data_logger.py:267\u001b[0m, in \u001b[0;36mBaseGalileoDataLogger.upload\u001b[0;34m(self, last_epoch, create_data_embs)\u001b[0m\n",
+      "\u001b[1;32m    266\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m split \u001b[38;5;129;01min\u001b[39;00m Split\u001b[38;5;241m.\u001b[39mget_valid_attributes():\n",
+      "\u001b[0;32m--> 267\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mupload_split\u001b[49m\u001b[43m(\u001b[49m\n",
+      "\u001b[1;32m    268\u001b[0m \u001b[43m        \u001b[49m\u001b[43mlocation\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msplit\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mobject_store\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlast_epoch\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcreate_data_embs\u001b[49m\n",
+      "\u001b[1;32m    269\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n",
+      "\n",
+      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/data_logger/base_data_logger.py:295\u001b[0m, in \u001b[0;36mBaseGalileoDataLogger.upload_split\u001b[0;34m(self, location, split, object_store, last_epoch, create_data_embs)\u001b[0m\n",
+      "\u001b[1;32m    294\u001b[0m in_frame_split \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconvert_large_string(in_frame_split)\n",
+      "\u001b[0;32m--> 295\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mupload_split_from_in_frame\u001b[49m\u001b[43m(\u001b[49m\n",
+      "\u001b[1;32m    296\u001b[0m \u001b[43m    \u001b[49m\u001b[43mobject_store\u001b[49m\u001b[43m,\u001b[49m\n",
+      "\u001b[1;32m    297\u001b[0m \u001b[43m    \u001b[49m\u001b[43min_frame_split\u001b[49m\u001b[43m,\u001b[49m\n",
+      "\u001b[1;32m    298\u001b[0m \u001b[43m    \u001b[49m\u001b[43msplit\u001b[49m\u001b[43m,\u001b[49m\n",
+      "\u001b[1;32m    299\u001b[0m \u001b[43m    \u001b[49m\u001b[43msplit_loc\u001b[49m\u001b[43m,\u001b[49m\n",
+      "\u001b[1;32m    300\u001b[0m \u001b[43m    \u001b[49m\u001b[43mlast_epoch\u001b[49m\u001b[43m,\u001b[49m\n",
+      "\u001b[1;32m    301\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcreate_data_embs\u001b[49m\u001b[43m,\u001b[49m\n",
+      "\u001b[1;32m    302\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\u001b[1;32m    303\u001b[0m in_frame_split\u001b[38;5;241m.\u001b[39mclose()\n",
+      "\n",
+      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/data_logger/semantic_segmentation.py:166\u001b[0m, in \u001b[0;36mSemanticSegmentationDataLogger.upload_split_from_in_frame\u001b[0;34m(cls, object_store, in_frame, split, split_loc, last_epoch, create_data_embs)\u001b[0m\n",
+      "\u001b[1;32m    165\u001b[0m dir_name \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00msplit_loc\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m/0\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
+      "\u001b[0;32m--> 166\u001b[0m out_frame \u001b[38;5;241m=\u001b[39m \u001b[43mget_output_df\u001b[49m\u001b[43m(\u001b[49m\n",
+      "\u001b[1;32m    167\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdir_name\u001b[49m\u001b[43m,\u001b[49m\n",
+      "\u001b[1;32m    168\u001b[0m \u001b[43m    \u001b[49m\u001b[43mprob_only\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n",
+      "\u001b[1;32m    169\u001b[0m \u001b[43m    \u001b[49m\u001b[43msplit\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msplit\u001b[49m\u001b[43m,\u001b[49m\n",
+      "\u001b[1;32m    170\u001b[0m \u001b[43m    \u001b[49m\u001b[43mepoch_or_inf\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\n",
+      "\u001b[1;32m    171\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\u001b[1;32m    173\u001b[0m polygon_minio_file \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mproj_run\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m/\u001b[39m\u001b[38;5;132;01m{\u001b[39;00msplit\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m/0/prob/prob.hdf5\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
+      "\n",
+      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/utils/vaex.py:192\u001b[0m, in \u001b[0;36mget_output_df\u001b[0;34m(dir_name, prob_only, split, epoch_or_inf)\u001b[0m\n",
+      "\u001b[1;32m    191\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m vaex\u001b[38;5;241m.\u001b[39mopen(out_frame_path)\n",
+      "\u001b[0;32m--> 192\u001b[0m str_cols \u001b[38;5;241m=\u001b[39m \u001b[43mconcat_hdf5_files\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdir_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mprob_only\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\u001b[1;32m    193\u001b[0m out_frame \u001b[38;5;241m=\u001b[39m vaex\u001b[38;5;241m.\u001b[39mopen(out_frame_path)\n",
+      "\n",
+      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/utils/hdf5_store.py:129\u001b[0m, in \u001b[0;36mconcat_hdf5_files\u001b[0;34m(location, prob_only)\u001b[0m\n",
+      "\u001b[1;32m    128\u001b[0m files \u001b[38;5;241m=\u001b[39m os\u001b[38;5;241m.\u001b[39mlistdir(location)\n",
+      "\u001b[0;32m--> 129\u001b[0m df \u001b[38;5;241m=\u001b[39m \u001b[43mvaex\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mlocation\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m/\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mfiles\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
+      "\u001b[1;32m    131\u001b[0m \u001b[38;5;66;03m# Construct a store per column\u001b[39;00m\n",
+      "\n",
+      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/__init__.py:244\u001b[0m, in \u001b[0;36mopen\u001b[0;34m(path, convert, progress, shuffle, fs_options, fs, *args, **kwargs)\u001b[0m\n",
+      "\u001b[1;32m    243\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
+      "\u001b[0;32m--> 244\u001b[0m     ds \u001b[38;5;241m=\u001b[39m \u001b[43mvaex\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdataset\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfs_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfs_options\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\u001b[1;32m    245\u001b[0m df \u001b[38;5;241m=\u001b[39m vaex\u001b[38;5;241m.\u001b[39mfrom_dataset(ds)\n",
+      "\n",
+      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/dataset.py:81\u001b[0m, in \u001b[0;36mopen\u001b[0;34m(path, fs_options, fs, *args, **kwargs)\u001b[0m\n",
+      "\u001b[1;32m     80\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m opener\u001b[38;5;241m.\u001b[39mcan_open(path, fs_options\u001b[38;5;241m=\u001b[39mfs_options, fs\u001b[38;5;241m=\u001b[39mfs, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n",
+      "\u001b[0;32m---> 81\u001b[0m             \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mopener\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfs_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfs_options\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\u001b[1;32m     83\u001b[0m \u001b[38;5;66;03m# otherwise try all openers\u001b[39;00m\n",
+      "\n",
+      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/dataset.py:1457\u001b[0m, in \u001b[0;36mDatasetFile.open\u001b[0;34m(cls, path, *args, **kwargs)\u001b[0m\n",
+      "\u001b[1;32m   1455\u001b[0m \u001b[38;5;129m@classmethod\u001b[39m\n",
+      "\u001b[1;32m   1456\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mopen\u001b[39m(\u001b[38;5;28mcls\u001b[39m, path, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n",
+      "\u001b[0;32m-> 1457\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\n",
+      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/hdf5/dataset.py:73\u001b[0m, in \u001b[0;36mHdf5MemoryMapped.__init__\u001b[0;34m(self, path, write, fs_options, fs, nommap, group, _fingerprint)\u001b[0m\n",
+      "\u001b[1;32m     72\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m write:  \u001b[38;5;66;03m# in write mode, call freeze yourself, so the hashes are computed\u001b[39;00m\n",
+      "\u001b[0;32m---> 73\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_freeze\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\u001b[1;32m     74\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
+      "\u001b[1;32m     75\u001b[0m     \u001b[38;5;66;03m# make sure we set the row count, which otherwise freeze would do\u001b[39;00m\n",
+      "\n",
+      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/dataset.py:1501\u001b[0m, in \u001b[0;36mDatasetFile._freeze\u001b[0;34m(self)\u001b[0m\n",
+      "\u001b[1;32m   1500\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_columns \u001b[38;5;241m=\u001b[39m frozendict(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_columns)\n",
+      "\u001b[0;32m-> 1501\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_set_row_count\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\u001b[1;32m   1502\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_frozen \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n",
+      "\n",
+      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/dataset.py:423\u001b[0m, in \u001b[0;36mDataset._set_row_count\u001b[0;34m(self)\u001b[0m\n",
+      "\u001b[1;32m    422\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(value) \u001b[38;5;241m!=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_row_count:\n",
+      "\u001b[0;32m--> 423\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mFirst columns has length \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_row_count\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m, while column \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mname\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m has length \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mlen\u001b[39m(value)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n",
+      "\n",
+      "\u001b[0;31mValueError\u001b[0m: First columns has length 3, while column epoch has length 2\n",
+      "\n",
+      "During handling of the above exception, another exception occurred:\n",
+      "\n",
+      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)\n",
+      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/analytics.py:149\u001b[0m, in \u001b[0;36mAnalytics.ipython_exception_handler\u001b[0;34m(self, shell, etype, evalue, tb, tb_offset)\u001b[0m\n",
+      "\u001b[1;32m    147\u001b[0m     \u001b[38;5;28;01mpass\u001b[39;00m\n",
+      "\u001b[1;32m    148\u001b[0m \u001b[38;5;66;03m# We need to call the default ipython exception handler to raise the error\u001b[39;00m\n",
+      "\u001b[0;32m--> 149\u001b[0m \u001b[43mshell\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mshowtraceback\u001b[49m\u001b[43m(\u001b[49m\u001b[43m(\u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mevalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtb\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtb_offset\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtb_offset\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\n",
+      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/rich/traceback.py:130\u001b[0m, in \u001b[0;36minstall.<locals>.ipy_excepthook_closure.<locals>.ipy_show_traceback\u001b[0;34m(*args, **kwargs)\u001b[0m\n",
+      "\u001b[1;32m    128\u001b[0m \u001b[38;5;28;01mnonlocal\u001b[39;00m tb_data\n",
+      "\u001b[1;32m    129\u001b[0m tb_data \u001b[38;5;241m=\u001b[39m kwargs\n",
+      "\u001b[0;32m--> 130\u001b[0m \u001b[43mdefault_showtraceback\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\n",
+      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/interactiveshell.py:2116\u001b[0m, in \u001b[0;36mInteractiveShell.showtraceback\u001b[0;34m(self, exc_tuple, filename, tb_offset, exception_only, running_compiled_code)\u001b[0m\n",
+      "\u001b[1;32m   2113\u001b[0m     traceback\u001b[38;5;241m.\u001b[39mprint_exc()\n",
+      "\u001b[1;32m   2114\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n",
+      "\u001b[0;32m-> 2116\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_showtraceback\u001b[49m\u001b[43m(\u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstb\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\u001b[1;32m   2117\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_pdb:\n",
+      "\u001b[1;32m   2118\u001b[0m     \u001b[38;5;66;03m# drop into debugger\u001b[39;00m\n",
+      "\u001b[1;32m   2119\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdebugger(force\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n",
+      "\n",
+      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/rich/traceback.py:146\u001b[0m, in \u001b[0;36minstall.<locals>.ipy_excepthook_closure.<locals>.ipy_display_traceback\u001b[0;34m(is_syntax, *args, **kwargs)\u001b[0m\n",
+      "\u001b[1;32m    144\u001b[0m tb_offset \u001b[38;5;241m=\u001b[39m tb_data\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtb_offset\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;241m1\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m compiled \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;241m0\u001b[39m)\n",
+      "\u001b[1;32m    145\u001b[0m \u001b[38;5;66;03m# remove ipython internal frames from trace with tb_offset\u001b[39;00m\n",
+      "\u001b[0;32m--> 146\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m _ \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28;43mrange\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mtb_offset\u001b[49m\u001b[43m)\u001b[49m:\n",
+      "\u001b[1;32m    147\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m tb \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
+      "\u001b[1;32m    148\u001b[0m         \u001b[38;5;28;01mbreak\u001b[39;00m\n",
+      "\n",
+      "\u001b[0;31mTypeError\u001b[0m: 'NoneType' object cannot be interpreted as an integer\n",
+      "The original exception:\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800000; text-decoration-color: #800000\">╭─────────────────────────────── </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">Traceback </span><span style=\"color: #bf7f7f; text-decoration-color: #bf7f7f; font-weight: bold\">(most recent call last)</span><span style=\"color: #800000; text-decoration-color: #800000\"> ────────────────────────────────╮</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">interactiveshell</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">3508</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">run_code</span>                                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3505 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> async_:                                                                <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3506 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">await</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">eval</span>(code_obj, <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.user_global_ns, <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.user_ns)               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3507 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">else</span>:                                                                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>3508 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span>exec(code_obj, <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.user_global_ns, <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.user_ns)                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3509 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">finally</span>:                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3510 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># Reset our crash handler in place</span>                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3511 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>sys.excepthook = old_excepthook                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">&lt;module&gt;</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">1</span>                                                                                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>1 dq.finish()                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">2 </span>                                                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/utils/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">helpers.py</span>: <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">25</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">decorator</span>                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 22 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">decorator</span>(*args: P.args, **kwargs: P.kwargs) -&gt; Optional[T]:                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 23 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> galileo_disabled():                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 24 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>                                                                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span> 25 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> func(*args, **kwargs)                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 26 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 27 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> decorator                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 28 </span>                                                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/core/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">finish.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">61</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">finish</span>                                                                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 58 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># Certain tasks require extra finish logic</span>                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 59 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>data_logger.logger_config.finish()                                                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 60 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span> 61 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>data_logger.upload(last_epoch, create_data_embs=create_data_embs)                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 62 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>upload_dq_log_file()                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 63 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>body = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">dict</span>(                                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 64 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>project_id=<span style=\"color: #00ffff; text-decoration-color: #00ffff\">str</span>(config.current_project_id),                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/data_logg</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">er/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">base_data_logger.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">267</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">upload</span>                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">264 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>create_data_embs = <span style=\"color: #0000ff; text-decoration-color: #0000ff\">False</span>                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">265 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>                                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">266 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">for</span> split <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">in</span> Split.get_valid_attributes():                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>267 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.upload_split(                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">268 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>location, split, object_store, last_epoch, create_data_embs                <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">269 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>)                                                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">270 </span>                                                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/data_logg</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">er/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">base_data_logger.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">295</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">upload_split</span>                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">292 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span>                                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">293 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>in_frame_split = vaex.open(<span style=\"color: #808000; text-decoration-color: #808000\">f\"{</span>in_frame_path<span style=\"color: #808000; text-decoration-color: #808000\">}/*.{</span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.INPUT_DATA_FILE_EXT<span style=\"color: #808000; text-decoration-color: #808000\">}\"</span>)        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">294 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>in_frame_split = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.convert_large_string(in_frame_split)                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>295 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.upload_split_from_in_frame(                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">296 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>object_store,                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">297 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>in_frame_split,                                                                <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">298 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>split,                                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/data_logg</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">er/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">semantic_segmentation.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">166</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">upload_split_from_in_frame</span>                                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">163 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>)                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">164 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>                                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">165 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>dir_name = <span style=\"color: #808000; text-decoration-color: #808000\">f\"{</span>split_loc<span style=\"color: #808000; text-decoration-color: #808000\">}/0\"</span>                                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>166 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>out_frame = get_output_df(                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">167 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>dir_name,                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">168 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>prob_only=<span style=\"color: #0000ff; text-decoration-color: #0000ff\">False</span>,                                                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">169 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>split=split,                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/utils/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">vaex.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">192</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">get_output_df</span>                                                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">189 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># just open the processed file</span>                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">190 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> os.path.isfile(out_frame_path):                                                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">191 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> vaex.open(out_frame_path)                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>192 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>str_cols = concat_hdf5_files(dir_name, prob_only)                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">193 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>out_frame = vaex.open(out_frame_path)                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">194 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">195 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> split == Split.inference:                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/utils/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">hdf5_store.</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">129</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">concat_hdf5_files</span>                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">126 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>str_cols = []                                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">127 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>stores = {}                                                                            <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">128 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>files = os.listdir(location)                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>129 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>df = vaex.open(<span style=\"color: #808000; text-decoration-color: #808000\">f\"{</span>location<span style=\"color: #808000; text-decoration-color: #808000\">}/{</span>files[<span style=\"color: #0000ff; text-decoration-color: #0000ff\">0</span>]<span style=\"color: #808000; text-decoration-color: #808000\">}\"</span>)                                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">130 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">131 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># Construct a store per column</span>                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">132 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> prob_only:                                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">__init__.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">244</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">open</span>  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">241 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>)                                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">242 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>ds = vaex.dataset.open(path_output, fs_options=fs_options, fs=fs)          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">243 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">else</span>:                                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>244 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>ds = vaex.dataset.open(path, fs_options=fs_options, fs=fs, **kwargs)       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">245 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>df = vaex.from_dataset(ds)                                                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">246 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> df <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">is</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>:                                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">247 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> os.path.exists(path):                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">dataset.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">81</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">open</span>    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">  78 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">for</span> opener <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">in</span> opener_classes:                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">  79 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> opener.quick_test(path, fs_options=fs_options, fs=fs):                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">  80 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> opener.can_open(path, fs_options=fs_options, fs=fs, *args, **kwargs):      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>  81 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> opener.open(path, fs_options=fs_options, fs=fs, *args, **kwargs)   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">  82 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">  83 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># otherwise try all openers</span>                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">  84 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">for</span> opener <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">in</span> opener_classes:                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">dataset.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">1457</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">open</span>  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1454 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1455 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff; font-weight: bold\">@classmethod</span>                                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1456 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">open</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">cls</span>, path, *args, **kwargs):                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>1457 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">cls</span>(path, *args, **kwargs)                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1458 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1459 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">chunk_iterator</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>, columns, chunk_size=<span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>, reverse=<span style=\"color: #0000ff; text-decoration-color: #0000ff\">False</span>):                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1460 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">yield from</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._default_chunk_iterator(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._columns, columns, chunk_size, reve  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/hdf5/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">dataset.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">73</span> in    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">__init__</span>                                                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 70 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._version = <span style=\"color: #0000ff; text-decoration-color: #0000ff\">1</span>                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 71 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._load()                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 72 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">not</span> write:  <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># in write mode, call freeze yourself, so the hashes are computed</span>   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span> 73 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._freeze()                                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 74 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">else</span>:                                                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 75 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># make sure we set the row count, which otherwise freeze would do</span>              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 76 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._set_row_count()                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">dataset.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">1501</span> in       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">_freeze</span>                                                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1498 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">_freeze</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>):                                                                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1499 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._ids = frozendict(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._ids)                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1500 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._columns = frozendict(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._columns)                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>1501 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._set_row_count()                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1502 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._frozen = <span style=\"color: #0000ff; text-decoration-color: #0000ff\">True</span>                                                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1503 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._hash_cache_needs_write:                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1504 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._write_hash_info()                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">dataset.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">423</span> in        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">_set_row_count</span>                                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 420 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._row_count = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">len</span>(values[<span style=\"color: #0000ff; text-decoration-color: #0000ff\">0</span>])                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 421 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">for</span> name, value <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">in</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">list</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._columns.items())[<span style=\"color: #0000ff; text-decoration-color: #0000ff\">1</span>:]:                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 422 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">len</span>(value) != <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._row_count:                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span> 423 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">raise</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">ValueError</span>(<span style=\"color: #808000; text-decoration-color: #808000\">f'First columns has length {</span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._row_count<span style=\"color: #808000; text-decoration-color: #808000\">}, while col</span>  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 424 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 425 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff; font-weight: bold\">@property</span>                                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 426 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">row_count</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>):                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">╰──────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
+       "<span style=\"color: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ValueError: </span>First columns has length <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>, while column epoch has length <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>\n",
+       "\n",
+       "<span style=\"font-style: italic\">During handling of the above exception, another exception occurred:</span>\n",
+       "\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">╭─────────────────────────────── </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">Traceback </span><span style=\"color: #bf7f7f; text-decoration-color: #bf7f7f; font-weight: bold\">(most recent call last)</span><span style=\"color: #800000; text-decoration-color: #800000\"> ────────────────────────────────╮</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">interactiveshell</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">1975</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">wrapped</span>                                                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1972 </span><span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">│   │   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">handlers to crash IPython.</span>                                                <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1973 </span><span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">│   │   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">\"\"\"</span>                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1974 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">try</span>:                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>1975 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span>stb = handler(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>,etype,value,tb,tb_offset=tb_offset)                <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1976 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> validate_stb(stb)                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1977 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">except</span>:                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1978 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># clear custom handler immediately</span>                                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">analytics.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">149</span>  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">ipython_exception_handler</span>                                                                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">146 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># TODO: create internal logging endpoint</span>                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">147 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">pass</span>                                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">148 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># We need to call the default ipython exception handler to raise the error</span>         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>149 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>shell.showtraceback((etype, evalue, tb), tb_offset=tb_offset)                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">150 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">151 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">track_exception_ipython</span>(                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">152 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>,                                                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/rich/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">traceback.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">130</span> in      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">ipy_show_traceback</span>                                                                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">127 </span><span style=\"color: #bfbfbf; text-decoration-color: #bfbfbf\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">\"\"\"wrap the default ip.showtraceback to store info for ip._showtraceback\"\"\"</span>    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">128 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">nonlocal</span> tb_data                                                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">129 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>tb_data = kwargs                                                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>130 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>default_showtraceback(*args, **kwargs)                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">131 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>                                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">132 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">ipy_display_traceback</span>(                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">133 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>*args: Any, is_syntax: <span style=\"color: #00ffff; text-decoration-color: #00ffff\">bool</span> = <span style=\"color: #0000ff; text-decoration-color: #0000ff\">False</span>, **kwargs: Any                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">interactiveshell</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">2116</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">showtraceback</span>                                                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">2113 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   │   </span>traceback.print_exc()                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">2114 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">2115 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span>                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>2116 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._showtraceback(etype, value, stb)                                <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">2117 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.call_pdb:                                                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">2118 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># drop into debugger</span>                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">2119 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.debugger(force=<span style=\"color: #0000ff; text-decoration-color: #0000ff\">True</span>)                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/rich/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">traceback.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">146</span> in      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">ipy_display_traceback</span>                                                                            <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">143 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>compiled = tb_data.get(<span style=\"color: #808000; text-decoration-color: #808000\">\"running_compiled_code\"</span>, <span style=\"color: #0000ff; text-decoration-color: #0000ff\">False</span>)                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">144 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>tb_offset = tb_data.get(<span style=\"color: #808000; text-decoration-color: #808000\">\"tb_offset\"</span>, <span style=\"color: #0000ff; text-decoration-color: #0000ff\">1</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> compiled <span style=\"color: #0000ff; text-decoration-color: #0000ff\">else</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">0</span>)                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">145 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># remove ipython internal frames from trace with tb_offset</span>                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>146 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">for</span> _ <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">in</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">range</span>(tb_offset):                                                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">147 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> tb <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">is</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>:                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">148 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">break</span>                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">149 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>tb = tb.tb_next                                                            <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">╰──────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
+       "<span style=\"color: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">TypeError: </span><span style=\"color: #008000; text-decoration-color: #008000\">'NoneType'</span> object cannot be interpreted as an integer\n",
+       "\n",
+       "<span style=\"font-style: italic\">During handling of the above exception, another exception occurred:</span>\n",
+       "\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">╭─────────────────────────────── </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">Traceback </span><span style=\"color: #bf7f7f; text-decoration-color: #bf7f7f; font-weight: bold\">(most recent call last)</span><span style=\"color: #800000; text-decoration-color: #800000\"> ────────────────────────────────╮</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">interactiveshell</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">3448</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">run_ast_nodes</span>                                                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3445 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>):                                                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3446 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span>code = compiler(mod, cell_name, mode)                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3447 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span>asy = compare(code)                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>3448 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">await</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.run_code(code, result, async_=asy):                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3449 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">True</span>                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3450 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>                                                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3451 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># Flush softspace</span>                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">interactiveshell</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">3526</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">run_code</span>                                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3523 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>etype, value, tb = sys.exc_info()                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3524 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> result <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">is</span> <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">not</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>:                                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3525 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>result.error_in_exec = value                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>3526 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.CustomTB(etype, value, tb)                                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3527 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">except</span>:                                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3528 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> result <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">is</span> <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">not</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>:                                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3529 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>result.error_in_exec = sys.exc_info()[<span style=\"color: #0000ff; text-decoration-color: #0000ff\">1</span>]                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">interactiveshell</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">1985</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">wrapped</span>                                                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1982 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span>stb = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.InteractiveTB.structured_traceback(*sys.exc_info())        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1983 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">print</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.InteractiveTB.stb2text(stb))                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1984 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">print</span>(<span style=\"color: #808000; text-decoration-color: #808000\">\"The original exception:\"</span>)                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>1985 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span>stb = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.InteractiveTB.structured_traceback(                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1986 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   │   │   │   │   │   │   </span>(etype,value,tb), tb_offset=tb_offset         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1987 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span>)                                                                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1988 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> stb                                                                <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
+       "<span style=\"color: #800000; text-decoration-color: #800000\">╰──────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
+       "<span style=\"color: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">TypeError: </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">structured_traceback</span><span style=\"font-weight: bold\">()</span> missing <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span> required positional argument: <span style=\"color: #008000; text-decoration-color: #008000\">'evalue'</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[31m╭─\u001b[0m\u001b[31m──────────────────────────────\u001b[0m\u001b[31m \u001b[0m\u001b[1;31mTraceback \u001b[0m\u001b[1;2;31m(most recent call last)\u001b[0m\u001b[31m \u001b[0m\u001b[31m───────────────────────────────\u001b[0m\u001b[31m─╮\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/\u001b[0m\u001b[1;33minteractiveshell\u001b[0m \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[1;33m.py\u001b[0m:\u001b[94m3508\u001b[0m in \u001b[92mrun_code\u001b[0m                                                                             \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m3505 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mif\u001b[0m async_:                                                                \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m3506 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[94mawait\u001b[0m \u001b[96meval\u001b[0m(code_obj, \u001b[96mself\u001b[0m.user_global_ns, \u001b[96mself\u001b[0m.user_ns)               \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m3507 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94melse\u001b[0m:                                                                     \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m3508 \u001b[2m│   │   │   │   │   \u001b[0mexec(code_obj, \u001b[96mself\u001b[0m.user_global_ns, \u001b[96mself\u001b[0m.user_ns)                     \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m3509 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mfinally\u001b[0m:                                                                      \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m3510 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[2m# Reset our crash handler in place\u001b[0m                                        \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m3511 \u001b[0m\u001b[2m│   │   │   │   \u001b[0msys.excepthook = old_excepthook                                           \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m in \u001b[92m<module>\u001b[0m:\u001b[94m1\u001b[0m                                                                                    \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m1 dq.finish()                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m2 \u001b[0m                                                                                             \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/utils/\u001b[0m\u001b[1;33mhelpers.py\u001b[0m: \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[94m25\u001b[0m in \u001b[92mdecorator\u001b[0m                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 22 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92mdecorator\u001b[0m(*args: P.args, **kwargs: P.kwargs) -> Optional[T]:                       \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 23 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mif\u001b[0m galileo_disabled():                                                             \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 24 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mreturn\u001b[0m \u001b[94mNone\u001b[0m                                                                    \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m 25 \u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m func(*args, **kwargs)                                                       \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 26 \u001b[0m\u001b[2m│   \u001b[0m                                                                                       \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 27 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mreturn\u001b[0m decorator                                                                       \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 28 \u001b[0m                                                                                           \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/core/\u001b[0m\u001b[1;33mfinish.py\u001b[0m:\u001b[94m61\u001b[0m \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m in \u001b[92mfinish\u001b[0m                                                                                        \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 58 \u001b[0m\u001b[2m│   \u001b[0m\u001b[2m# Certain tasks require extra finish logic\u001b[0m                                             \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 59 \u001b[0m\u001b[2m│   \u001b[0mdata_logger.logger_config.finish()                                                     \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 60 \u001b[0m\u001b[2m│   \u001b[0m                                                                                       \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m 61 \u001b[2m│   \u001b[0mdata_logger.upload(last_epoch, create_data_embs=create_data_embs)                      \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 62 \u001b[0m\u001b[2m│   \u001b[0mupload_dq_log_file()                                                                   \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 63 \u001b[0m\u001b[2m│   \u001b[0mbody = \u001b[96mdict\u001b[0m(                                                                           \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 64 \u001b[0m\u001b[2m│   │   \u001b[0mproject_id=\u001b[96mstr\u001b[0m(config.current_project_id),                                         \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/data_logg\u001b[0m \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33mer/\u001b[0m\u001b[1;33mbase_data_logger.py\u001b[0m:\u001b[94m267\u001b[0m in \u001b[92mupload\u001b[0m                                                             \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m264 \u001b[0m\u001b[2m│   │   │   \u001b[0mcreate_data_embs = \u001b[94mFalse\u001b[0m                                                       \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m265 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                   \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m266 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mfor\u001b[0m split \u001b[95min\u001b[0m Split.get_valid_attributes():                                         \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m267 \u001b[2m│   │   │   \u001b[0m\u001b[96mself\u001b[0m.upload_split(                                                             \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m268 \u001b[0m\u001b[2m│   │   │   │   \u001b[0mlocation, split, object_store, last_epoch, create_data_embs                \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m269 \u001b[0m\u001b[2m│   │   │   \u001b[0m)                                                                              \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m270 \u001b[0m                                                                                           \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/data_logg\u001b[0m \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33mer/\u001b[0m\u001b[1;33mbase_data_logger.py\u001b[0m:\u001b[94m295\u001b[0m in \u001b[92mupload_split\u001b[0m                                                       \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m292 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mreturn\u001b[0m                                                                         \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m293 \u001b[0m\u001b[2m│   │   \u001b[0min_frame_split = vaex.open(\u001b[33mf\u001b[0m\u001b[33m\"\u001b[0m\u001b[33m{\u001b[0min_frame_path\u001b[33m}\u001b[0m\u001b[33m/*.\u001b[0m\u001b[33m{\u001b[0m\u001b[96mself\u001b[0m.INPUT_DATA_FILE_EXT\u001b[33m}\u001b[0m\u001b[33m\"\u001b[0m)        \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m294 \u001b[0m\u001b[2m│   │   \u001b[0min_frame_split = \u001b[96mself\u001b[0m.convert_large_string(in_frame_split)                         \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m295 \u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m.upload_split_from_in_frame(                                                   \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m296 \u001b[0m\u001b[2m│   │   │   \u001b[0mobject_store,                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m297 \u001b[0m\u001b[2m│   │   │   \u001b[0min_frame_split,                                                                \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m298 \u001b[0m\u001b[2m│   │   │   \u001b[0msplit,                                                                         \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/data_logg\u001b[0m \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33mer/\u001b[0m\u001b[1;33msemantic_segmentation.py\u001b[0m:\u001b[94m166\u001b[0m in \u001b[92mupload_split_from_in_frame\u001b[0m                                    \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m163 \u001b[0m\u001b[2m│   │   \u001b[0m)                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m164 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                   \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m165 \u001b[0m\u001b[2m│   │   \u001b[0mdir_name = \u001b[33mf\u001b[0m\u001b[33m\"\u001b[0m\u001b[33m{\u001b[0msplit_loc\u001b[33m}\u001b[0m\u001b[33m/0\u001b[0m\u001b[33m\"\u001b[0m                                                        \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m166 \u001b[2m│   │   \u001b[0mout_frame = get_output_df(                                                         \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m167 \u001b[0m\u001b[2m│   │   │   \u001b[0mdir_name,                                                                      \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m168 \u001b[0m\u001b[2m│   │   │   \u001b[0mprob_only=\u001b[94mFalse\u001b[0m,                                                               \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m169 \u001b[0m\u001b[2m│   │   │   \u001b[0msplit=split,                                                                   \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/utils/\u001b[0m\u001b[1;33mvaex.py\u001b[0m:\u001b[94m192\u001b[0m \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m in \u001b[92mget_output_df\u001b[0m                                                                                 \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m189 \u001b[0m\u001b[2m│   \u001b[0m\u001b[2m# just open the processed file\u001b[0m                                                         \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m190 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mif\u001b[0m os.path.isfile(out_frame_path):                                                     \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m191 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m vaex.open(out_frame_path)                                                   \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m192 \u001b[2m│   \u001b[0mstr_cols = concat_hdf5_files(dir_name, prob_only)                                      \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m193 \u001b[0m\u001b[2m│   \u001b[0mout_frame = vaex.open(out_frame_path)                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m194 \u001b[0m\u001b[2m│   \u001b[0m                                                                                       \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m195 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mif\u001b[0m split == Split.inference:                                                           \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/utils/\u001b[0m\u001b[1;33mhdf5_store.\u001b[0m \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[1;33mpy\u001b[0m:\u001b[94m129\u001b[0m in \u001b[92mconcat_hdf5_files\u001b[0m                                                                      \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m126 \u001b[0m\u001b[2m│   \u001b[0mstr_cols = []                                                                          \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m127 \u001b[0m\u001b[2m│   \u001b[0mstores = {}                                                                            \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m128 \u001b[0m\u001b[2m│   \u001b[0mfiles = os.listdir(location)                                                           \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m129 \u001b[2m│   \u001b[0mdf = vaex.open(\u001b[33mf\u001b[0m\u001b[33m\"\u001b[0m\u001b[33m{\u001b[0mlocation\u001b[33m}\u001b[0m\u001b[33m/\u001b[0m\u001b[33m{\u001b[0mfiles[\u001b[94m0\u001b[0m]\u001b[33m}\u001b[0m\u001b[33m\"\u001b[0m)                                               \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m130 \u001b[0m\u001b[2m│   \u001b[0m                                                                                       \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m131 \u001b[0m\u001b[2m│   \u001b[0m\u001b[2m# Construct a store per column\u001b[0m                                                         \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m132 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mif\u001b[0m prob_only:                                                                          \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/\u001b[0m\u001b[1;33m__init__.py\u001b[0m:\u001b[94m244\u001b[0m in \u001b[92mopen\u001b[0m  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m241 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m)                                                                          \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m242 \u001b[0m\u001b[2m│   │   │   │   \u001b[0mds = vaex.dataset.open(path_output, fs_options=fs_options, fs=fs)          \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m243 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94melse\u001b[0m:                                                                          \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m244 \u001b[2m│   │   │   │   \u001b[0mds = vaex.dataset.open(path, fs_options=fs_options, fs=fs, **kwargs)       \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m245 \u001b[0m\u001b[2m│   │   │   \u001b[0mdf = vaex.from_dataset(ds)                                                     \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m246 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mif\u001b[0m df \u001b[95mis\u001b[0m \u001b[94mNone\u001b[0m:                                                                 \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m247 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mif\u001b[0m os.path.exists(path):                                                   \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/\u001b[0m\u001b[1;33mdataset.py\u001b[0m:\u001b[94m81\u001b[0m in \u001b[92mopen\u001b[0m    \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m  78 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mfor\u001b[0m opener \u001b[95min\u001b[0m opener_classes:                                                         \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m  79 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mif\u001b[0m opener.quick_test(path, fs_options=fs_options, fs=fs):                         \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m  80 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mif\u001b[0m opener.can_open(path, fs_options=fs_options, fs=fs, *args, **kwargs):      \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m  81 \u001b[2m│   │   │   │   \u001b[0m\u001b[94mreturn\u001b[0m opener.open(path, fs_options=fs_options, fs=fs, *args, **kwargs)   \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m  82 \u001b[0m\u001b[2m│   \u001b[0m                                                                                      \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m  83 \u001b[0m\u001b[2m│   \u001b[0m\u001b[2m# otherwise try all openers\u001b[0m                                                           \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m  84 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mfor\u001b[0m opener \u001b[95min\u001b[0m opener_classes:                                                         \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/\u001b[0m\u001b[1;33mdataset.py\u001b[0m:\u001b[94m1457\u001b[0m in \u001b[92mopen\u001b[0m  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1454 \u001b[0m\u001b[2m│   \u001b[0m                                                                                      \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1455 \u001b[0m\u001b[2m│   \u001b[0m\u001b[1;95m@classmethod\u001b[0m                                                                          \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1456 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92mopen\u001b[0m(\u001b[96mcls\u001b[0m, path, *args, **kwargs):                                                 \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m1457 \u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m \u001b[96mcls\u001b[0m(path, *args, **kwargs)                                                 \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1458 \u001b[0m\u001b[2m│   \u001b[0m                                                                                      \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1459 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92mchunk_iterator\u001b[0m(\u001b[96mself\u001b[0m, columns, chunk_size=\u001b[94mNone\u001b[0m, reverse=\u001b[94mFalse\u001b[0m):                    \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1460 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94myield from\u001b[0m \u001b[96mself\u001b[0m._default_chunk_iterator(\u001b[96mself\u001b[0m._columns, columns, chunk_size, reve  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/hdf5/\u001b[0m\u001b[1;33mdataset.py\u001b[0m:\u001b[94m73\u001b[0m in    \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[92m__init__\u001b[0m                                                                                         \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 70 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m._version = \u001b[94m1\u001b[0m                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 71 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m._load()                                                                       \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 72 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mif\u001b[0m \u001b[95mnot\u001b[0m write:  \u001b[2m# in write mode, call freeze yourself, so the hashes are computed\u001b[0m   \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m 73 \u001b[2m│   │   │   \u001b[0m\u001b[96mself\u001b[0m._freeze()                                                                 \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 74 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94melse\u001b[0m:                                                                              \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 75 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[2m# make sure we set the row count, which otherwise freeze would do\u001b[0m              \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 76 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[96mself\u001b[0m._set_row_count()                                                          \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/\u001b[0m\u001b[1;33mdataset.py\u001b[0m:\u001b[94m1501\u001b[0m in       \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[92m_freeze\u001b[0m                                                                                          \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1498 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92m_freeze\u001b[0m(\u001b[96mself\u001b[0m):                                                                    \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1499 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m._ids = frozendict(\u001b[96mself\u001b[0m._ids)                                                 \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1500 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m._columns = frozendict(\u001b[96mself\u001b[0m._columns)                                         \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m1501 \u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m._set_row_count()                                                             \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1502 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m._frozen = \u001b[94mTrue\u001b[0m                                                               \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1503 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mif\u001b[0m \u001b[96mself\u001b[0m._hash_cache_needs_write:                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1504 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[96mself\u001b[0m._write_hash_info()                                                       \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/\u001b[0m\u001b[1;33mdataset.py\u001b[0m:\u001b[94m423\u001b[0m in        \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[92m_set_row_count\u001b[0m                                                                                   \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 420 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m._row_count = \u001b[96mlen\u001b[0m(values[\u001b[94m0\u001b[0m])                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 421 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mfor\u001b[0m name, value \u001b[95min\u001b[0m \u001b[96mlist\u001b[0m(\u001b[96mself\u001b[0m._columns.items())[\u001b[94m1\u001b[0m:]:                               \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 422 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mif\u001b[0m \u001b[96mlen\u001b[0m(value) != \u001b[96mself\u001b[0m._row_count:                                             \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m 423 \u001b[2m│   │   │   │   \u001b[0m\u001b[94mraise\u001b[0m \u001b[96mValueError\u001b[0m(\u001b[33mf\u001b[0m\u001b[33m'\u001b[0m\u001b[33mFirst columns has length \u001b[0m\u001b[33m{\u001b[0m\u001b[96mself\u001b[0m._row_count\u001b[33m}\u001b[0m\u001b[33m, while col\u001b[0m  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 424 \u001b[0m\u001b[2m│   \u001b[0m                                                                                      \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 425 \u001b[0m\u001b[2m│   \u001b[0m\u001b[1;95m@property\u001b[0m                                                                             \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m 426 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92mrow_count\u001b[0m(\u001b[96mself\u001b[0m):                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n",
+       "\u001b[1;91mValueError: \u001b[0mFirst columns has length \u001b[1;36m3\u001b[0m, while column epoch has length \u001b[1;36m2\u001b[0m\n",
+       "\n",
+       "\u001b[3mDuring handling of the above exception, another exception occurred:\u001b[0m\n",
+       "\n",
+       "\u001b[31m╭─\u001b[0m\u001b[31m──────────────────────────────\u001b[0m\u001b[31m \u001b[0m\u001b[1;31mTraceback \u001b[0m\u001b[1;2;31m(most recent call last)\u001b[0m\u001b[31m \u001b[0m\u001b[31m───────────────────────────────\u001b[0m\u001b[31m─╮\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/\u001b[0m\u001b[1;33minteractiveshell\u001b[0m \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[1;33m.py\u001b[0m:\u001b[94m1975\u001b[0m in \u001b[92mwrapped\u001b[0m                                                                              \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1972 \u001b[0m\u001b[2;33m│   │   │   │   \u001b[0m\u001b[33mhandlers to crash IPython.\u001b[0m                                                \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1973 \u001b[0m\u001b[2;33m│   │   │   │   \u001b[0m\u001b[33m\"\"\"\u001b[0m                                                                       \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1974 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mtry\u001b[0m:                                                                      \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m1975 \u001b[2m│   │   │   │   │   \u001b[0mstb = handler(\u001b[96mself\u001b[0m,etype,value,tb,tb_offset=tb_offset)                \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1976 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[94mreturn\u001b[0m validate_stb(stb)                                              \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1977 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mexcept\u001b[0m:                                                                   \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1978 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[2m# clear custom handler immediately\u001b[0m                                    \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/\u001b[0m\u001b[1;33manalytics.py\u001b[0m:\u001b[94m149\u001b[0m  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m in \u001b[92mipython_exception_handler\u001b[0m                                                                     \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m146 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[2m# TODO: create internal logging endpoint\u001b[0m                                       \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m147 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mpass\u001b[0m                                                                           \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m148 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[2m# We need to call the default ipython exception handler to raise the error\u001b[0m         \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m149 \u001b[2m│   │   \u001b[0mshell.showtraceback((etype, evalue, tb), tb_offset=tb_offset)                      \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m150 \u001b[0m\u001b[2m│   \u001b[0m                                                                                       \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m151 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92mtrack_exception_ipython\u001b[0m(                                                           \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m152 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m,                                                                              \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/rich/\u001b[0m\u001b[1;33mtraceback.py\u001b[0m:\u001b[94m130\u001b[0m in      \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[92mipy_show_traceback\u001b[0m                                                                               \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m127 \u001b[0m\u001b[2;90m│   │   │   \u001b[0m\u001b[33m\"\"\"wrap the default ip.showtraceback to store info for ip._showtraceback\"\"\"\u001b[0m    \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m128 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mnonlocal\u001b[0m tb_data                                                               \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m129 \u001b[0m\u001b[2m│   │   │   \u001b[0mtb_data = kwargs                                                               \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m130 \u001b[2m│   │   │   \u001b[0mdefault_showtraceback(*args, **kwargs)                                         \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m131 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                   \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m132 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92mipy_display_traceback\u001b[0m(                                                         \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m133 \u001b[0m\u001b[2m│   │   │   \u001b[0m*args: Any, is_syntax: \u001b[96mbool\u001b[0m = \u001b[94mFalse\u001b[0m, **kwargs: Any                             \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/\u001b[0m\u001b[1;33minteractiveshell\u001b[0m \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[1;33m.py\u001b[0m:\u001b[94m2116\u001b[0m in \u001b[92mshowtraceback\u001b[0m                                                                        \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m2113 \u001b[0m\u001b[2m│   │   │   │   │   │   \u001b[0mtraceback.print_exc()                                             \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m2114 \u001b[0m\u001b[2m│   │   │   │   │   │   \u001b[0m\u001b[94mreturn\u001b[0m \u001b[94mNone\u001b[0m                                                       \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m2115 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m                                                                      \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m2116 \u001b[2m│   │   │   │   │   \u001b[0m\u001b[96mself\u001b[0m._showtraceback(etype, value, stb)                                \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m2117 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[94mif\u001b[0m \u001b[96mself\u001b[0m.call_pdb:                                                     \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m2118 \u001b[0m\u001b[2m│   │   │   │   │   │   \u001b[0m\u001b[2m# drop into debugger\u001b[0m                                              \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m2119 \u001b[0m\u001b[2m│   │   │   │   │   │   \u001b[0m\u001b[96mself\u001b[0m.debugger(force=\u001b[94mTrue\u001b[0m)                                         \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/rich/\u001b[0m\u001b[1;33mtraceback.py\u001b[0m:\u001b[94m146\u001b[0m in      \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[92mipy_display_traceback\u001b[0m                                                                            \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m143 \u001b[0m\u001b[2m│   │   │   \u001b[0mcompiled = tb_data.get(\u001b[33m\"\u001b[0m\u001b[33mrunning_compiled_code\u001b[0m\u001b[33m\"\u001b[0m, \u001b[94mFalse\u001b[0m)                         \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m144 \u001b[0m\u001b[2m│   │   │   \u001b[0mtb_offset = tb_data.get(\u001b[33m\"\u001b[0m\u001b[33mtb_offset\u001b[0m\u001b[33m\"\u001b[0m, \u001b[94m1\u001b[0m \u001b[94mif\u001b[0m compiled \u001b[94melse\u001b[0m \u001b[94m0\u001b[0m)                     \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m145 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[2m# remove ipython internal frames from trace with tb_offset\u001b[0m                     \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m146 \u001b[2m│   │   │   \u001b[0m\u001b[94mfor\u001b[0m _ \u001b[95min\u001b[0m \u001b[96mrange\u001b[0m(tb_offset):                                                     \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m147 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mif\u001b[0m tb \u001b[95mis\u001b[0m \u001b[94mNone\u001b[0m:                                                             \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m148 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[94mbreak\u001b[0m                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m149 \u001b[0m\u001b[2m│   │   │   │   \u001b[0mtb = tb.tb_next                                                            \u001b[31m│\u001b[0m\n",
+       "\u001b[31m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n",
+       "\u001b[1;91mTypeError: \u001b[0m\u001b[32m'NoneType'\u001b[0m object cannot be interpreted as an integer\n",
+       "\n",
+       "\u001b[3mDuring handling of the above exception, another exception occurred:\u001b[0m\n",
+       "\n",
+       "\u001b[31m╭─\u001b[0m\u001b[31m──────────────────────────────\u001b[0m\u001b[31m \u001b[0m\u001b[1;31mTraceback \u001b[0m\u001b[1;2;31m(most recent call last)\u001b[0m\u001b[31m \u001b[0m\u001b[31m───────────────────────────────\u001b[0m\u001b[31m─╮\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/\u001b[0m\u001b[1;33minteractiveshell\u001b[0m \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[1;33m.py\u001b[0m:\u001b[94m3448\u001b[0m in \u001b[92mrun_ast_nodes\u001b[0m                                                                        \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m3445 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m):                                                                        \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m3446 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0mcode = compiler(mod, cell_name, mode)                                 \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m3447 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0masy = compare(code)                                                   \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m3448 \u001b[2m│   │   │   │   \u001b[0m\u001b[94mif\u001b[0m \u001b[94mawait\u001b[0m \u001b[96mself\u001b[0m.run_code(code, result, async_=asy):                         \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m3449 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[94mreturn\u001b[0m \u001b[94mTrue\u001b[0m                                                           \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m3450 \u001b[0m\u001b[2m│   │   │   \u001b[0m                                                                              \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m3451 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[2m# Flush softspace\u001b[0m                                                             \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/\u001b[0m\u001b[1;33minteractiveshell\u001b[0m \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[1;33m.py\u001b[0m:\u001b[94m3526\u001b[0m in \u001b[92mrun_code\u001b[0m                                                                             \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m3523 \u001b[0m\u001b[2m│   │   │   \u001b[0metype, value, tb = sys.exc_info()                                             \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m3524 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mif\u001b[0m result \u001b[95mis\u001b[0m \u001b[95mnot\u001b[0m \u001b[94mNone\u001b[0m:                                                        \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m3525 \u001b[0m\u001b[2m│   │   │   │   \u001b[0mresult.error_in_exec = value                                              \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m3526 \u001b[2m│   │   │   \u001b[0m\u001b[96mself\u001b[0m.CustomTB(etype, value, tb)                                               \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m3527 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mexcept\u001b[0m:                                                                           \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m3528 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mif\u001b[0m result \u001b[95mis\u001b[0m \u001b[95mnot\u001b[0m \u001b[94mNone\u001b[0m:                                                        \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m3529 \u001b[0m\u001b[2m│   │   │   │   \u001b[0mresult.error_in_exec = sys.exc_info()[\u001b[94m1\u001b[0m]                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/\u001b[0m\u001b[1;33minteractiveshell\u001b[0m \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[1;33m.py\u001b[0m:\u001b[94m1985\u001b[0m in \u001b[92mwrapped\u001b[0m                                                                              \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1982 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0mstb = \u001b[96mself\u001b[0m.InteractiveTB.structured_traceback(*sys.exc_info())        \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1983 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[96mprint\u001b[0m(\u001b[96mself\u001b[0m.InteractiveTB.stb2text(stb))                               \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1984 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[96mprint\u001b[0m(\u001b[33m\"\u001b[0m\u001b[33mThe original exception:\u001b[0m\u001b[33m\"\u001b[0m)                                      \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m1985 \u001b[2m│   │   │   │   │   \u001b[0mstb = \u001b[96mself\u001b[0m.InteractiveTB.structured_traceback(                        \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1986 \u001b[0m\u001b[2m│   │   │   │   │   │   │   │   │   │   │   \u001b[0m(etype,value,tb), tb_offset=tb_offset         \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1987 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m)                                                                     \u001b[31m│\u001b[0m\n",
+       "\u001b[31m│\u001b[0m   \u001b[2m1988 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mreturn\u001b[0m stb                                                                \u001b[31m│\u001b[0m\n",
+       "\u001b[31m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n",
+       "\u001b[1;91mTypeError: \u001b[0m\u001b[1;35mstructured_traceback\u001b[0m\u001b[1m(\u001b[0m\u001b[1m)\u001b[0m missing \u001b[1;36m1\u001b[0m required positional argument: \u001b[32m'evalue'\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "dq.finish()"
    ]

From ac8c901672a25814b06340e5509f955b5ebac8bd Mon Sep 17 00:00:00 2001
From: Derek <dcaustin33@gmail.com>
Date: Thu, 11 May 2023 13:52:06 -0700
Subject: [PATCH 04/16] Linting and typing

---
 .../loggers/model_logger/base_model_logger.py |   4 +-
 .../model_logger/semantic_segmentation.py     |  33 +-
 .../utils/semantic_segmentation/errors.py     |  31 +-
 .../utils/semantic_segmentation/metrics.py    |   2 +-
 docs/cv/coco_deeplab_hooks.ipynb              | 789 ++----------------
 5 files changed, 109 insertions(+), 750 deletions(-)

diff --git a/dataquality/loggers/model_logger/base_model_logger.py b/dataquality/loggers/model_logger/base_model_logger.py
index b82001f03..7dbd6ba6b 100644
--- a/dataquality/loggers/model_logger/base_model_logger.py
+++ b/dataquality/loggers/model_logger/base_model_logger.py
@@ -17,7 +17,6 @@
 from dataquality.utils.ampli import AmpliMetric
 from dataquality.utils.dq_logger import get_dq_logger
 from dataquality.utils.hdf5_store import _save_hdf5_file
-from dataquality.utils.thread_pool import ThreadPoolManager
 
 analytics = Analytics(ApiClient, config)  # type: ignore
 
@@ -99,7 +98,8 @@ def log(self) -> None:
         # global variables (cur_split and cur_epoch) that are subject to change
         # between subsequent threads
         self.set_split_epoch()
-        ThreadPoolManager.add_thread(target=self._add_threaded_log)
+        # ThreadPoolManager.add_thread(target=self._add_threaded_log)
+        self._add_threaded_log()
 
     def write_model_output(self, data: Dict) -> None:
         """Creates an hdf5 file from the data dict"""
diff --git a/dataquality/loggers/model_logger/semantic_segmentation.py b/dataquality/loggers/model_logger/semantic_segmentation.py
index 96dbe03ef..f8b411ab6 100644
--- a/dataquality/loggers/model_logger/semantic_segmentation.py
+++ b/dataquality/loggers/model_logger/semantic_segmentation.py
@@ -1,4 +1,4 @@
-from typing import Dict, List, Optional, Union, Tuple, Any
+from typing import Any, Dict, List, Optional, Union
 
 import numpy as np
 import torch
@@ -9,11 +9,12 @@
     semantic_segmentation_logger_config,
 )
 from dataquality.loggers.model_logger.base_model_logger import BaseGalileoModelLogger
+from dataquality.schemas.semantic_segmentation import Polygon
 from dataquality.schemas.split import Split
 from dataquality.utils.semantic_segmentation.errors import (
+    calculate_dep_polygons_batch,
     calculate_misclassified_polygons_batch,
     calculate_undetected_polygons_batch,
-    calculate_dep_polygons_batch
 )
 from dataquality.utils.semantic_segmentation.lm import upload_mislabeled_pixels
 from dataquality.utils.semantic_segmentation.metrics import (
@@ -104,12 +105,11 @@ def dep_path(self) -> str:
     @property
     def contours_path(self) -> str:
         return f"{self.proj_run}/{self.split_name_path}/contours"
-    
-    
+
     def get_polygon_data(
         self,
-        pred_polygons_batch:  Tuple[List, List],
-        gold_polygons_batch:  Tuple[List, List],
+        pred_polygons_batch: List[List[Polygon]],
+        gold_polygons_batch: List[List[Polygon]],
     ) -> Dict[str, Any]:
         """Returns polygon data for a batch of images in a dictionary
         that can then be used for our polygon df
@@ -147,7 +147,7 @@ def get_polygon_data(
                 image_ids.append(image_id)
                 preds.append(-1)
                 golds.append(polygon.label_idx)
-                data_error_potentials.append(polygon.data_error_potential)
+                data_error_potentials.append(0.0)
                 errors.append(polygon.error_type.value)
                 upload_polygon_contours(
                     polygon, self.logger_config.polygon_idx, self.contours_path
@@ -194,13 +194,13 @@ def _get_data_dict(self) -> Dict:
         # Errors
         calculate_misclassified_polygons_batch(self.pred_masks, gold_polygons_batch)
         calculate_undetected_polygons_batch(self.pred_masks, gold_polygons_batch)
-        
-        '''gold_polygons_batch = calculate_dep_polygons_batch(
+
+        calculate_dep_polygons_batch(
             gold_polygons_batch,
-            dep_heatmaps,
-            height = [img.shape[-1] for img in self.gold_masks],
-            width = [img.shape[-2] for img in self.gold_masks],
-        )'''
+            dep_heatmaps.numpy(),
+            height=[img.shape[-1] for img in self.gold_masks],
+            width=[img.shape[-2] for img in self.gold_masks],
+        )
 
         image_data = {
             "image": [
@@ -227,10 +227,11 @@ def _get_data_dict(self) -> Dict:
         )
 
         polygon_data = self.get_polygon_data(pred_polygons_batch, gold_polygons_batch)
-        
         if self.split == Split.inference:
-            polygon_data["inference_name"] = [self.inference_name] * len(self.image_ids)
+            polygon_data["inference_name"] = [self.inference_name] * len(
+                polygon_data["image_id"]
+            )
         else:
-            polygon_data["epoch"] = [self.epoch] * len(self.image_ids)
+            polygon_data["epoch"] = [self.epoch] * len(polygon_data["image_id"])
 
         return polygon_data
diff --git a/dataquality/utils/semantic_segmentation/errors.py b/dataquality/utils/semantic_segmentation/errors.py
index 0930b76a0..cade28744 100644
--- a/dataquality/utils/semantic_segmentation/errors.py
+++ b/dataquality/utils/semantic_segmentation/errors.py
@@ -2,7 +2,6 @@
 
 import numpy as np
 import torch
-import cv2
 from PIL import Image
 
 from dataquality.schemas.semantic_segmentation import ErrorType, Polygon
@@ -157,12 +156,12 @@ def calculate_undetected_polygons_batch(
         pred_mask = pred_masks[idx].numpy()
         gold_polygons = gold_polygons_batch[idx]
         calculate_undetected_polygons(pred_mask, gold_polygons)
-        
+
 
 def calculate_dep_polygon(
     dep_map: np.ndarray,
     polygon_img: np.ndarray,
-) -> None:
+) -> float:
     """Calculate the mean dep score for one polygon drawn onto an image of all
     zero's. We can then take the polygon's dep score by only selecting those pixels
     with a value greater than 0 and averageing them.
@@ -170,47 +169,41 @@ def calculate_dep_polygon(
     Args:
         dep_map (np.ndarray): heatmap of dep scores for an image
         polygon_img (np.ndarray): image of all zeros with a polygon drawn on it
-    
+
     Returns:
         dep_score (float): mean dep score for the polygon
     """
     relevant_region = polygon_img != 0
     dep_score = dep_map[relevant_region].mean()
     return dep_score
-        
 
-        
+
 def calculate_dep_polygons_batch(
     gold_polygons_batch: List[List[Polygon]],
     dep_heatmaps: np.ndarray,
     height: List[int],
     width: List[int],
-) -> List[List[Polygon]]:
+) -> None:
     """Takes the mean dep score within a polygon and sets the polygon's
     dep score to the mean dep score
 
     Args:
-        gold_polygons_batch (List[List[[Polygon]]): list of the gold polygons 
+        gold_polygons_batch (List[List[[Polygon]]): list of the gold polygons
             for an image
         dep_heatmaps (np.ndarray): heatmaps of DEP scores for an image
-        height (int): height of original image to resize the dep map to the correct 
+        height (int): height of original image to resize the dep map to the correct
             dims
-        width (int): width of original image to resize the dep map to the correct 
+        width (int): width of original image to resize the dep map to the correct
             dims
     """
     resized_dep_maps = []
     for i, dep_map in enumerate(dep_heatmaps):
-        resized_dep_maps.append(Image.fromarray(dep_map).resize((width[i], height[i])))
-        
+        resized_image = Image.fromarray(dep_map).resize((width[i], height[i]))
+        resized_dep_maps.append(np.array(resized_image))
+
     for idx in range(len(resized_dep_maps)):
         dep_map = resized_dep_maps[idx]
         gold_polygons = gold_polygons_batch[idx]
         for polygon in gold_polygons:
-            polygon_img = draw_polygon(polygon, dep_map.size)
+            polygon_img = draw_polygon(polygon, dep_map.shape)
             polygon.data_error_potential = calculate_dep_polygon(dep_map, polygon_img)
-            
-    return gold_polygons_batch
-    
-    
-     
-
diff --git a/dataquality/utils/semantic_segmentation/metrics.py b/dataquality/utils/semantic_segmentation/metrics.py
index 3cc495c09..5eceb4690 100644
--- a/dataquality/utils/semantic_segmentation/metrics.py
+++ b/dataquality/utils/semantic_segmentation/metrics.py
@@ -19,7 +19,7 @@ def calculate_and_upload_dep(
     gold_masks: torch.Tensor,
     image_ids: List[int],
     obj_prefix: str,
-) -> Tuple[List[float], np.ndarray]:
+) -> Tuple[List[float], torch.Tensor]:
     """Calculates the Data Error Potential (DEP) for each image in the batch
 
     Uploads the heatmap to Minio as a png.
diff --git a/docs/cv/coco_deeplab_hooks.ipynb b/docs/cv/coco_deeplab_hooks.ipynb
index 0a740579d..74188ee25 100644
--- a/docs/cv/coco_deeplab_hooks.ipynb
+++ b/docs/cv/coco_deeplab_hooks.ipynb
@@ -154,7 +154,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "🛰 Connected to existing project 'Derek-Elliott-Proj', and existing run 'test-polygon-df'.\n"
+      "🛰 Connected to existing project 'Derek-Elliott-Proj', and existing run 'test-polygon-df'.\n",
+      "🚀 Found existing run labels. Setting labels for run to ['background', 'airplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car', 'cat', 'chair', 'cow', 'dining table', 'dog', 'horse', 'motorcycle', 'person', 'potted plant', 'sheep', 'couch', 'train', 'tv']. You do not need to set labels for this run.\n"
      ]
     }
    ],
@@ -211,7 +212,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2023-05-11 11:49:01.215830: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
+      "2023-05-11 13:49:23.693790: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
       "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
      ]
     },
@@ -237,7 +238,7 @@
       "  warnings.warn(\"torch.cuda.amp.GradScaler is enabled, but CUDA is not available.  Disabling.\")\n",
       "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torch/amp/autocast_mode.py:204: UserWarning: User provided device_type of 'cuda', but CUDA is not available. Disabling\n",
       "  warnings.warn('User provided device_type of \\'cuda\\', but CUDA is not available. Disabling')\n",
-      " 50%|█████     | 1/2 [00:02<00:02,  2.83s/it]\n"
+      " 50%|█████     | 1/2 [00:03<00:03,  3.26s/it]\n"
      ]
     }
    ],
@@ -296,8 +297,8 @@
      "text": [
       "Logging 2 samples [########################################] 100.00% elapsed time  :     0.29s =  0.0m =  0.0h\n",
       "Logging 2 samples [########################################] 100.00% elapsed time  :     0.16s =  0.0m =  0.0h\n",
-      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.22s =  0.0m =  0.0h \n",
-      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.27s =  0.0m =  0.0h\n",
+      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.34s =  0.0m =  0.0h  \n",
+      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.24s =  0.0m =  0.0h\n",
       " ☁️ Uploading Data\n",
       "CuML libraries not found, running standard process. For faster Galileo processing, consider installing\n",
       "`pip install 'dataquality[cuda]' --extra-index-url=https://pypi.nvidia.com/`\n"
@@ -306,7 +307,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "aba6e837e4d14c1693c3b963f64de2a6",
+       "model_id": "20400cf290fb49ac999011f681c1d08a",
        "version_major": 2,
        "version_minor": 0
       },
@@ -319,732 +320,96 @@
     },
     {
      "data": {
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-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">'/Users/derek/.galileo/logs/7e78e642-cc40-4f5c-8f45-b2cadd8d674a/f9855</span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">eea-4121-4a24-bd68-132d3346a89a/training/0/80e887398eb1.hdf5'</span>          <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         Traceback <span style=\"font-weight: bold\">(</span>most recent call last<span style=\"font-weight: bold\">)</span>:                                     <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>           File                                                                 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va</span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">ex/__init__.py\"</span>, line <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">244</span>, in open                                     <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>             ds = <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">vaex.dataset.open</span><span style=\"font-weight: bold\">(</span>path, <span style=\"color: #808000; text-decoration-color: #808000\">fs_options</span>=<span style=\"color: #800080; text-decoration-color: #800080\">fs_options</span>, <span style=\"color: #808000; text-decoration-color: #808000\">fs</span>=<span style=\"color: #800080; text-decoration-color: #800080\">fs</span>,         <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         **kwargs<span style=\"font-weight: bold\">)</span>                                                              <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>           File                                                                 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va</span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">ex/dataset.py\"</span>, line <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">81</span>, in open                                       <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>             return <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">opener.open</span><span style=\"font-weight: bold\">(</span>path, <span style=\"color: #808000; text-decoration-color: #808000\">fs_options</span>=<span style=\"color: #800080; text-decoration-color: #800080\">fs_options</span>, <span style=\"color: #808000; text-decoration-color: #808000\">fs</span>=<span style=\"color: #800080; text-decoration-color: #800080\">fs</span>, *args,      <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         **kwargs<span style=\"font-weight: bold\">)</span>                                                              <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>           File                                                                 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va</span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">ex/dataset.py\"</span>, line <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1457</span>, in open                                     <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>             return <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">cls</span><span style=\"font-weight: bold\">(</span>path, *args, **kwargs<span style=\"font-weight: bold\">)</span>                                  <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>           File                                                                 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va</span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">ex/hdf5/dataset.py\"</span>, line <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">73</span>, in __init__                              <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>             <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">self._freeze</span><span style=\"font-weight: bold\">()</span>                                                     <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>           File                                                                 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va</span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">ex/dataset.py\"</span>, line <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1501</span>, in _freeze                                  <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>             <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">self._set_row_count</span><span style=\"font-weight: bold\">()</span>                                              <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>           File                                                                 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va</span> <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008000; text-decoration-color: #008000\">ex/dataset.py\"</span>, line <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">423</span>, in _set_row_count                            <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>             raise <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">ValueError</span><span style=\"font-weight: bold\">(</span>f'First columns has length <span style=\"font-weight: bold\">{</span>self._row_count<span style=\"font-weight: bold\">}</span>,     <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         while column <span style=\"font-weight: bold\">{</span>name<span style=\"font-weight: bold\">}</span> has length <span style=\"font-weight: bold\">{</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">len</span><span style=\"font-weight: bold\">(</span>value<span style=\"font-weight: bold\">)}</span>'<span style=\"font-weight: bold\">)</span>                          <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         ValueError: First columns has length <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>, while column epoch has length  <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">                    </span>         <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>                                                                      <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
-       "</pre>\n"
-      ],
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "296d767ead8b41e99c30c6a9485aec73",
+       "version_major": 2,
+       "version_minor": 0
+      },
       "text/plain": [
-       "\u001b[2;36m[05/11/23 11:49:23]\u001b[0m\u001b[2;36m \u001b[0m\u001b[1;31mERROR   \u001b[0m error opening                                                          \u001b]8;id=155436;file:///Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=520318;file:///Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/__init__.py#271\u001b\\\u001b[2m271\u001b[0m\u001b]8;;\u001b\\\n",
-       "\u001b[2;36m                    \u001b[0m         \u001b[32m'/Users/derek/.galileo/logs/7e78e642-cc40-4f5c-8f45-b2cadd8d674a/f9855\u001b[0m \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         \u001b[32meea-4121-4a24-bd68-132d3346a89a/training/0/80e887398eb1.hdf5'\u001b[0m          \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         Traceback \u001b[1m(\u001b[0mmost recent call last\u001b[1m)\u001b[0m:                                     \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m           File                                                                 \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         \u001b[32m\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va\u001b[0m \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         \u001b[32mex/__init__.py\"\u001b[0m, line \u001b[1;36m244\u001b[0m, in open                                     \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m             ds = \u001b[1;35mvaex.dataset.open\u001b[0m\u001b[1m(\u001b[0mpath, \u001b[33mfs_options\u001b[0m=\u001b[35mfs_options\u001b[0m, \u001b[33mfs\u001b[0m=\u001b[35mfs\u001b[0m,         \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         **kwargs\u001b[1m)\u001b[0m                                                              \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m           File                                                                 \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         \u001b[32m\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va\u001b[0m \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         \u001b[32mex/dataset.py\"\u001b[0m, line \u001b[1;36m81\u001b[0m, in open                                       \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m             return \u001b[1;35mopener.open\u001b[0m\u001b[1m(\u001b[0mpath, \u001b[33mfs_options\u001b[0m=\u001b[35mfs_options\u001b[0m, \u001b[33mfs\u001b[0m=\u001b[35mfs\u001b[0m, *args,      \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         **kwargs\u001b[1m)\u001b[0m                                                              \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m           File                                                                 \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         \u001b[32m\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va\u001b[0m \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         \u001b[32mex/dataset.py\"\u001b[0m, line \u001b[1;36m1457\u001b[0m, in open                                     \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m             return \u001b[1;35mcls\u001b[0m\u001b[1m(\u001b[0mpath, *args, **kwargs\u001b[1m)\u001b[0m                                  \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m           File                                                                 \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         \u001b[32m\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va\u001b[0m \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         \u001b[32mex/hdf5/dataset.py\"\u001b[0m, line \u001b[1;36m73\u001b[0m, in __init__                              \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m             \u001b[1;35mself._freeze\u001b[0m\u001b[1m(\u001b[0m\u001b[1m)\u001b[0m                                                     \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m           File                                                                 \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         \u001b[32m\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va\u001b[0m \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         \u001b[32mex/dataset.py\"\u001b[0m, line \u001b[1;36m1501\u001b[0m, in _freeze                                  \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m             \u001b[1;35mself._set_row_count\u001b[0m\u001b[1m(\u001b[0m\u001b[1m)\u001b[0m                                              \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m           File                                                                 \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         \u001b[32m\"/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/va\u001b[0m \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         \u001b[32mex/dataset.py\"\u001b[0m, line \u001b[1;36m423\u001b[0m, in _set_row_count                            \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m             raise \u001b[1;35mValueError\u001b[0m\u001b[1m(\u001b[0mf'First columns has length \u001b[1m{\u001b[0mself._row_count\u001b[1m}\u001b[0m,     \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         while column \u001b[1m{\u001b[0mname\u001b[1m}\u001b[0m has length \u001b[1m{\u001b[0m\u001b[1;35mlen\u001b[0m\u001b[1m(\u001b[0mvalue\u001b[1m)\u001b[0m\u001b[1m}\u001b[0m'\u001b[1m)\u001b[0m                          \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         ValueError: First columns has length \u001b[1;36m3\u001b[0m, while column epoch has length  \u001b[2m               \u001b[0m\n",
-       "\u001b[2;36m                    \u001b[0m         \u001b[1;36m2\u001b[0m                                                                      \u001b[2m               \u001b[0m\n"
+       "Processing data for upload:   0%|          | 0/2 [00:00<?, ?it/s]"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
     },
     {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Custom TB Handler failed, unregistering\n"
-     ]
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "2180f3a91509488c96df48b96554616f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Uploading data to Galileo:   0%|          | 0.00/20.1k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "604fe792fcd74222b5eb2cf8b1ff695f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Uploading data to Galileo:   0%|          | 0.00/25.8k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a761f4731e834ba8bc14beeafd4f3743",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Processing data for upload:   0%|          | 0/2 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1aec32edc98c4b32a40da5aa172403ed",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Uploading data to Galileo:   0%|          | 0.00/20.1k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n",
-      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)\n",
-      "    \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n",
-      "\n",
-      "Cell \u001b[0;32mIn[6], line 1\u001b[0m\n",
-      "\u001b[0;32m----> 1\u001b[0m \u001b[43mdq\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfinish\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
-      "\n",
-      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/utils/helpers.py:25\u001b[0m, in \u001b[0;36mcheck_noop.<locals>.decorator\u001b[0;34m(*args, **kwargs)\u001b[0m\n",
-      "\u001b[1;32m     24\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n",
-      "\u001b[0;32m---> 25\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
-      "\n",
-      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/core/finish.py:61\u001b[0m, in \u001b[0;36mfinish\u001b[0;34m(last_epoch, wait, create_data_embs)\u001b[0m\n",
-      "\u001b[1;32m     59\u001b[0m data_logger\u001b[38;5;241m.\u001b[39mlogger_config\u001b[38;5;241m.\u001b[39mfinish()\n",
-      "\u001b[0;32m---> 61\u001b[0m \u001b[43mdata_logger\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mupload\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlast_epoch\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcreate_data_embs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcreate_data_embs\u001b[49m\u001b[43m)\u001b[49m\n",
-      "\u001b[1;32m     62\u001b[0m upload_dq_log_file()\n",
-      "\n",
-      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/data_logger/base_data_logger.py:267\u001b[0m, in \u001b[0;36mBaseGalileoDataLogger.upload\u001b[0;34m(self, last_epoch, create_data_embs)\u001b[0m\n",
-      "\u001b[1;32m    266\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m split \u001b[38;5;129;01min\u001b[39;00m Split\u001b[38;5;241m.\u001b[39mget_valid_attributes():\n",
-      "\u001b[0;32m--> 267\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mupload_split\u001b[49m\u001b[43m(\u001b[49m\n",
-      "\u001b[1;32m    268\u001b[0m \u001b[43m        \u001b[49m\u001b[43mlocation\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msplit\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mobject_store\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlast_epoch\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcreate_data_embs\u001b[49m\n",
-      "\u001b[1;32m    269\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n",
-      "\n",
-      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/data_logger/base_data_logger.py:295\u001b[0m, in \u001b[0;36mBaseGalileoDataLogger.upload_split\u001b[0;34m(self, location, split, object_store, last_epoch, create_data_embs)\u001b[0m\n",
-      "\u001b[1;32m    294\u001b[0m in_frame_split \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconvert_large_string(in_frame_split)\n",
-      "\u001b[0;32m--> 295\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mupload_split_from_in_frame\u001b[49m\u001b[43m(\u001b[49m\n",
-      "\u001b[1;32m    296\u001b[0m \u001b[43m    \u001b[49m\u001b[43mobject_store\u001b[49m\u001b[43m,\u001b[49m\n",
-      "\u001b[1;32m    297\u001b[0m \u001b[43m    \u001b[49m\u001b[43min_frame_split\u001b[49m\u001b[43m,\u001b[49m\n",
-      "\u001b[1;32m    298\u001b[0m \u001b[43m    \u001b[49m\u001b[43msplit\u001b[49m\u001b[43m,\u001b[49m\n",
-      "\u001b[1;32m    299\u001b[0m \u001b[43m    \u001b[49m\u001b[43msplit_loc\u001b[49m\u001b[43m,\u001b[49m\n",
-      "\u001b[1;32m    300\u001b[0m \u001b[43m    \u001b[49m\u001b[43mlast_epoch\u001b[49m\u001b[43m,\u001b[49m\n",
-      "\u001b[1;32m    301\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcreate_data_embs\u001b[49m\u001b[43m,\u001b[49m\n",
-      "\u001b[1;32m    302\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
-      "\u001b[1;32m    303\u001b[0m in_frame_split\u001b[38;5;241m.\u001b[39mclose()\n",
-      "\n",
-      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/data_logger/semantic_segmentation.py:166\u001b[0m, in \u001b[0;36mSemanticSegmentationDataLogger.upload_split_from_in_frame\u001b[0;34m(cls, object_store, in_frame, split, split_loc, last_epoch, create_data_embs)\u001b[0m\n",
-      "\u001b[1;32m    165\u001b[0m dir_name \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00msplit_loc\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m/0\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
-      "\u001b[0;32m--> 166\u001b[0m out_frame \u001b[38;5;241m=\u001b[39m \u001b[43mget_output_df\u001b[49m\u001b[43m(\u001b[49m\n",
-      "\u001b[1;32m    167\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdir_name\u001b[49m\u001b[43m,\u001b[49m\n",
-      "\u001b[1;32m    168\u001b[0m \u001b[43m    \u001b[49m\u001b[43mprob_only\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n",
-      "\u001b[1;32m    169\u001b[0m \u001b[43m    \u001b[49m\u001b[43msplit\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msplit\u001b[49m\u001b[43m,\u001b[49m\n",
-      "\u001b[1;32m    170\u001b[0m \u001b[43m    \u001b[49m\u001b[43mepoch_or_inf\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\n",
-      "\u001b[1;32m    171\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
-      "\u001b[1;32m    173\u001b[0m polygon_minio_file \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mproj_run\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m/\u001b[39m\u001b[38;5;132;01m{\u001b[39;00msplit\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m/0/prob/prob.hdf5\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
-      "\n",
-      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/utils/vaex.py:192\u001b[0m, in \u001b[0;36mget_output_df\u001b[0;34m(dir_name, prob_only, split, epoch_or_inf)\u001b[0m\n",
-      "\u001b[1;32m    191\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m vaex\u001b[38;5;241m.\u001b[39mopen(out_frame_path)\n",
-      "\u001b[0;32m--> 192\u001b[0m str_cols \u001b[38;5;241m=\u001b[39m \u001b[43mconcat_hdf5_files\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdir_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mprob_only\u001b[49m\u001b[43m)\u001b[49m\n",
-      "\u001b[1;32m    193\u001b[0m out_frame \u001b[38;5;241m=\u001b[39m vaex\u001b[38;5;241m.\u001b[39mopen(out_frame_path)\n",
-      "\n",
-      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/utils/hdf5_store.py:129\u001b[0m, in \u001b[0;36mconcat_hdf5_files\u001b[0;34m(location, prob_only)\u001b[0m\n",
-      "\u001b[1;32m    128\u001b[0m files \u001b[38;5;241m=\u001b[39m os\u001b[38;5;241m.\u001b[39mlistdir(location)\n",
-      "\u001b[0;32m--> 129\u001b[0m df \u001b[38;5;241m=\u001b[39m \u001b[43mvaex\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mlocation\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m/\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mfiles\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
-      "\u001b[1;32m    131\u001b[0m \u001b[38;5;66;03m# Construct a store per column\u001b[39;00m\n",
-      "\n",
-      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/__init__.py:244\u001b[0m, in \u001b[0;36mopen\u001b[0;34m(path, convert, progress, shuffle, fs_options, fs, *args, **kwargs)\u001b[0m\n",
-      "\u001b[1;32m    243\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
-      "\u001b[0;32m--> 244\u001b[0m     ds \u001b[38;5;241m=\u001b[39m \u001b[43mvaex\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdataset\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfs_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfs_options\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
-      "\u001b[1;32m    245\u001b[0m df \u001b[38;5;241m=\u001b[39m vaex\u001b[38;5;241m.\u001b[39mfrom_dataset(ds)\n",
-      "\n",
-      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/dataset.py:81\u001b[0m, in \u001b[0;36mopen\u001b[0;34m(path, fs_options, fs, *args, **kwargs)\u001b[0m\n",
-      "\u001b[1;32m     80\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m opener\u001b[38;5;241m.\u001b[39mcan_open(path, fs_options\u001b[38;5;241m=\u001b[39mfs_options, fs\u001b[38;5;241m=\u001b[39mfs, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n",
-      "\u001b[0;32m---> 81\u001b[0m             \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mopener\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfs_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfs_options\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
-      "\u001b[1;32m     83\u001b[0m \u001b[38;5;66;03m# otherwise try all openers\u001b[39;00m\n",
-      "\n",
-      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/dataset.py:1457\u001b[0m, in \u001b[0;36mDatasetFile.open\u001b[0;34m(cls, path, *args, **kwargs)\u001b[0m\n",
-      "\u001b[1;32m   1455\u001b[0m \u001b[38;5;129m@classmethod\u001b[39m\n",
-      "\u001b[1;32m   1456\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mopen\u001b[39m(\u001b[38;5;28mcls\u001b[39m, path, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n",
-      "\u001b[0;32m-> 1457\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
-      "\n",
-      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/hdf5/dataset.py:73\u001b[0m, in \u001b[0;36mHdf5MemoryMapped.__init__\u001b[0;34m(self, path, write, fs_options, fs, nommap, group, _fingerprint)\u001b[0m\n",
-      "\u001b[1;32m     72\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m write:  \u001b[38;5;66;03m# in write mode, call freeze yourself, so the hashes are computed\u001b[39;00m\n",
-      "\u001b[0;32m---> 73\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_freeze\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
-      "\u001b[1;32m     74\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
-      "\u001b[1;32m     75\u001b[0m     \u001b[38;5;66;03m# make sure we set the row count, which otherwise freeze would do\u001b[39;00m\n",
-      "\n",
-      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/dataset.py:1501\u001b[0m, in \u001b[0;36mDatasetFile._freeze\u001b[0;34m(self)\u001b[0m\n",
-      "\u001b[1;32m   1500\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_columns \u001b[38;5;241m=\u001b[39m frozendict(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_columns)\n",
-      "\u001b[0;32m-> 1501\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_set_row_count\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
-      "\u001b[1;32m   1502\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_frozen \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n",
-      "\n",
-      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/dataset.py:423\u001b[0m, in \u001b[0;36mDataset._set_row_count\u001b[0;34m(self)\u001b[0m\n",
-      "\u001b[1;32m    422\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(value) \u001b[38;5;241m!=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_row_count:\n",
-      "\u001b[0;32m--> 423\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mFirst columns has length \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_row_count\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m, while column \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mname\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m has length \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mlen\u001b[39m(value)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n",
-      "\n",
-      "\u001b[0;31mValueError\u001b[0m: First columns has length 3, while column epoch has length 2\n",
-      "\n",
-      "During handling of the above exception, another exception occurred:\n",
-      "\n",
-      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)\n",
-      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/analytics.py:149\u001b[0m, in \u001b[0;36mAnalytics.ipython_exception_handler\u001b[0;34m(self, shell, etype, evalue, tb, tb_offset)\u001b[0m\n",
-      "\u001b[1;32m    147\u001b[0m     \u001b[38;5;28;01mpass\u001b[39;00m\n",
-      "\u001b[1;32m    148\u001b[0m \u001b[38;5;66;03m# We need to call the default ipython exception handler to raise the error\u001b[39;00m\n",
-      "\u001b[0;32m--> 149\u001b[0m \u001b[43mshell\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mshowtraceback\u001b[49m\u001b[43m(\u001b[49m\u001b[43m(\u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mevalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtb\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtb_offset\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtb_offset\u001b[49m\u001b[43m)\u001b[49m\n",
-      "\n",
-      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/rich/traceback.py:130\u001b[0m, in \u001b[0;36minstall.<locals>.ipy_excepthook_closure.<locals>.ipy_show_traceback\u001b[0;34m(*args, **kwargs)\u001b[0m\n",
-      "\u001b[1;32m    128\u001b[0m \u001b[38;5;28;01mnonlocal\u001b[39;00m tb_data\n",
-      "\u001b[1;32m    129\u001b[0m tb_data \u001b[38;5;241m=\u001b[39m kwargs\n",
-      "\u001b[0;32m--> 130\u001b[0m \u001b[43mdefault_showtraceback\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
-      "\n",
-      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/interactiveshell.py:2116\u001b[0m, in \u001b[0;36mInteractiveShell.showtraceback\u001b[0;34m(self, exc_tuple, filename, tb_offset, exception_only, running_compiled_code)\u001b[0m\n",
-      "\u001b[1;32m   2113\u001b[0m     traceback\u001b[38;5;241m.\u001b[39mprint_exc()\n",
-      "\u001b[1;32m   2114\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n",
-      "\u001b[0;32m-> 2116\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_showtraceback\u001b[49m\u001b[43m(\u001b[49m\u001b[43metype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstb\u001b[49m\u001b[43m)\u001b[49m\n",
-      "\u001b[1;32m   2117\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcall_pdb:\n",
-      "\u001b[1;32m   2118\u001b[0m     \u001b[38;5;66;03m# drop into debugger\u001b[39;00m\n",
-      "\u001b[1;32m   2119\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdebugger(force\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n",
-      "\n",
-      "File \u001b[0;32m~/Desktop/dataquality/.venv/lib/python3.9/site-packages/rich/traceback.py:146\u001b[0m, in \u001b[0;36minstall.<locals>.ipy_excepthook_closure.<locals>.ipy_display_traceback\u001b[0;34m(is_syntax, *args, **kwargs)\u001b[0m\n",
-      "\u001b[1;32m    144\u001b[0m tb_offset \u001b[38;5;241m=\u001b[39m tb_data\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtb_offset\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;241m1\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m compiled \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;241m0\u001b[39m)\n",
-      "\u001b[1;32m    145\u001b[0m \u001b[38;5;66;03m# remove ipython internal frames from trace with tb_offset\u001b[39;00m\n",
-      "\u001b[0;32m--> 146\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m _ \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28;43mrange\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mtb_offset\u001b[49m\u001b[43m)\u001b[49m:\n",
-      "\u001b[1;32m    147\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m tb \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
-      "\u001b[1;32m    148\u001b[0m         \u001b[38;5;28;01mbreak\u001b[39;00m\n",
-      "\n",
-      "\u001b[0;31mTypeError\u001b[0m: 'NoneType' object cannot be interpreted as an integer\n",
-      "The original exception:\n"
+      "Job default successfully submitted. Results will be available soon at https://console.dev.rungalileo.io/insights?projectId=7e78e642-cc40-4f5c-8f45-b2cadd8d674a&runId=617746f8-14a0-4e45-b27a-903492fe7343&split=training&metric=f1&depHigh=1&depLow=0&taskType=6\n",
+      "Waiting for job (you can safely close this window)...\n",
+      "\tUploading processed validation data\n",
+      "Done! Job finished with status completed\n",
+      "Click here to see your run! https://console.dev.rungalileo.io/insights?projectId=7e78e642-cc40-4f5c-8f45-b2cadd8d674a&runId=617746f8-14a0-4e45-b27a-903492fe7343&split=training&metric=f1&depHigh=1&depLow=0&taskType=6\n",
+      "🧹 Cleaning up\n",
+      "🧹 Cleaning up\n"
      ]
     },
     {
      "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800000; text-decoration-color: #800000\">╭─────────────────────────────── </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">Traceback </span><span style=\"color: #bf7f7f; text-decoration-color: #bf7f7f; font-weight: bold\">(most recent call last)</span><span style=\"color: #800000; text-decoration-color: #800000\"> ────────────────────────────────╮</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">interactiveshell</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">3508</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">run_code</span>                                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3505 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> async_:                                                                <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3506 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">await</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">eval</span>(code_obj, <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.user_global_ns, <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.user_ns)               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3507 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">else</span>:                                                                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>3508 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span>exec(code_obj, <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.user_global_ns, <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.user_ns)                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3509 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">finally</span>:                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3510 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># Reset our crash handler in place</span>                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3511 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>sys.excepthook = old_excepthook                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">&lt;module&gt;</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">1</span>                                                                                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>1 dq.finish()                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">2 </span>                                                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/utils/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">helpers.py</span>: <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">25</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">decorator</span>                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 22 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">decorator</span>(*args: P.args, **kwargs: P.kwargs) -&gt; Optional[T]:                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 23 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> galileo_disabled():                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 24 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>                                                                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span> 25 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> func(*args, **kwargs)                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 26 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 27 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> decorator                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 28 </span>                                                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/core/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">finish.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">61</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">finish</span>                                                                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 58 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># Certain tasks require extra finish logic</span>                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 59 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>data_logger.logger_config.finish()                                                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 60 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span> 61 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>data_logger.upload(last_epoch, create_data_embs=create_data_embs)                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 62 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>upload_dq_log_file()                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 63 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>body = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">dict</span>(                                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 64 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>project_id=<span style=\"color: #00ffff; text-decoration-color: #00ffff\">str</span>(config.current_project_id),                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/data_logg</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">er/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">base_data_logger.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">267</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">upload</span>                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">264 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>create_data_embs = <span style=\"color: #0000ff; text-decoration-color: #0000ff\">False</span>                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">265 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>                                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">266 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">for</span> split <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">in</span> Split.get_valid_attributes():                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>267 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.upload_split(                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">268 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>location, split, object_store, last_epoch, create_data_embs                <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">269 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>)                                                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">270 </span>                                                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/data_logg</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">er/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">base_data_logger.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">295</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">upload_split</span>                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">292 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span>                                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">293 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>in_frame_split = vaex.open(<span style=\"color: #808000; text-decoration-color: #808000\">f\"{</span>in_frame_path<span style=\"color: #808000; text-decoration-color: #808000\">}/*.{</span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.INPUT_DATA_FILE_EXT<span style=\"color: #808000; text-decoration-color: #808000\">}\"</span>)        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">294 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>in_frame_split = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.convert_large_string(in_frame_split)                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>295 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.upload_split_from_in_frame(                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">296 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>object_store,                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">297 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>in_frame_split,                                                                <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">298 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>split,                                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/data_logg</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">er/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">semantic_segmentation.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">166</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">upload_split_from_in_frame</span>                                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">163 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>)                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">164 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>                                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">165 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>dir_name = <span style=\"color: #808000; text-decoration-color: #808000\">f\"{</span>split_loc<span style=\"color: #808000; text-decoration-color: #808000\">}/0\"</span>                                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>166 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>out_frame = get_output_df(                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">167 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>dir_name,                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">168 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>prob_only=<span style=\"color: #0000ff; text-decoration-color: #0000ff\">False</span>,                                                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">169 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>split=split,                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/utils/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">vaex.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">192</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">get_output_df</span>                                                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">189 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># just open the processed file</span>                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">190 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> os.path.isfile(out_frame_path):                                                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">191 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> vaex.open(out_frame_path)                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>192 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>str_cols = concat_hdf5_files(dir_name, prob_only)                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">193 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>out_frame = vaex.open(out_frame_path)                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">194 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">195 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> split == Split.inference:                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/utils/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">hdf5_store.</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">129</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">concat_hdf5_files</span>                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">126 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>str_cols = []                                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">127 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>stores = {}                                                                            <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">128 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>files = os.listdir(location)                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>129 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>df = vaex.open(<span style=\"color: #808000; text-decoration-color: #808000\">f\"{</span>location<span style=\"color: #808000; text-decoration-color: #808000\">}/{</span>files[<span style=\"color: #0000ff; text-decoration-color: #0000ff\">0</span>]<span style=\"color: #808000; text-decoration-color: #808000\">}\"</span>)                                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">130 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">131 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># Construct a store per column</span>                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">132 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> prob_only:                                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">__init__.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">244</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">open</span>  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">241 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>)                                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">242 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>ds = vaex.dataset.open(path_output, fs_options=fs_options, fs=fs)          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">243 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">else</span>:                                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>244 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>ds = vaex.dataset.open(path, fs_options=fs_options, fs=fs, **kwargs)       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">245 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>df = vaex.from_dataset(ds)                                                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">246 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> df <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">is</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>:                                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">247 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> os.path.exists(path):                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">dataset.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">81</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">open</span>    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">  78 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">for</span> opener <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">in</span> opener_classes:                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">  79 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> opener.quick_test(path, fs_options=fs_options, fs=fs):                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">  80 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> opener.can_open(path, fs_options=fs_options, fs=fs, *args, **kwargs):      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>  81 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> opener.open(path, fs_options=fs_options, fs=fs, *args, **kwargs)   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">  82 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">  83 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># otherwise try all openers</span>                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">  84 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">for</span> opener <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">in</span> opener_classes:                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">dataset.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">1457</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">open</span>  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1454 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1455 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff; font-weight: bold\">@classmethod</span>                                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1456 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">open</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">cls</span>, path, *args, **kwargs):                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>1457 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">cls</span>(path, *args, **kwargs)                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1458 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1459 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">chunk_iterator</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>, columns, chunk_size=<span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>, reverse=<span style=\"color: #0000ff; text-decoration-color: #0000ff\">False</span>):                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1460 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">yield from</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._default_chunk_iterator(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._columns, columns, chunk_size, reve  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/hdf5/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">dataset.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">73</span> in    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">__init__</span>                                                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 70 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._version = <span style=\"color: #0000ff; text-decoration-color: #0000ff\">1</span>                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 71 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._load()                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 72 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">not</span> write:  <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># in write mode, call freeze yourself, so the hashes are computed</span>   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span> 73 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._freeze()                                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 74 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">else</span>:                                                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 75 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># make sure we set the row count, which otherwise freeze would do</span>              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 76 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._set_row_count()                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">dataset.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">1501</span> in       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">_freeze</span>                                                                                          <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1498 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">_freeze</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>):                                                                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1499 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._ids = frozendict(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._ids)                                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1500 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._columns = frozendict(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._columns)                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>1501 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._set_row_count()                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1502 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._frozen = <span style=\"color: #0000ff; text-decoration-color: #0000ff\">True</span>                                                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1503 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._hash_cache_needs_write:                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1504 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._write_hash_info()                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">dataset.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">423</span> in        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">_set_row_count</span>                                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 420 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._row_count = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">len</span>(values[<span style=\"color: #0000ff; text-decoration-color: #0000ff\">0</span>])                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 421 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">for</span> name, value <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">in</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">list</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._columns.items())[<span style=\"color: #0000ff; text-decoration-color: #0000ff\">1</span>:]:                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 422 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">len</span>(value) != <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._row_count:                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span> 423 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">raise</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">ValueError</span>(<span style=\"color: #808000; text-decoration-color: #808000\">f'First columns has length {</span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._row_count<span style=\"color: #808000; text-decoration-color: #808000\">}, while col</span>  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 424 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 425 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff; font-weight: bold\">@property</span>                                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"> 426 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">row_count</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>):                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">╰──────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
-       "<span style=\"color: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ValueError: </span>First columns has length <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>, while column epoch has length <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span>\n",
-       "\n",
-       "<span style=\"font-style: italic\">During handling of the above exception, another exception occurred:</span>\n",
-       "\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">╭─────────────────────────────── </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">Traceback </span><span style=\"color: #bf7f7f; text-decoration-color: #bf7f7f; font-weight: bold\">(most recent call last)</span><span style=\"color: #800000; text-decoration-color: #800000\"> ────────────────────────────────╮</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">interactiveshell</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">1975</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">wrapped</span>                                                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1972 </span><span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">│   │   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">handlers to crash IPython.</span>                                                <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1973 </span><span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">│   │   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">\"\"\"</span>                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1974 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">try</span>:                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>1975 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span>stb = handler(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>,etype,value,tb,tb_offset=tb_offset)                <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1976 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> validate_stb(stb)                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1977 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">except</span>:                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1978 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># clear custom handler immediately</span>                                    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">analytics.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">149</span>  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">ipython_exception_handler</span>                                                                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">146 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># TODO: create internal logging endpoint</span>                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">147 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">pass</span>                                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">148 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># We need to call the default ipython exception handler to raise the error</span>         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>149 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>shell.showtraceback((etype, evalue, tb), tb_offset=tb_offset)                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">150 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span>                                                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">151 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">track_exception_ipython</span>(                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">152 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>,                                                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/rich/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">traceback.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">130</span> in      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">ipy_show_traceback</span>                                                                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">127 </span><span style=\"color: #bfbfbf; text-decoration-color: #bfbfbf\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">\"\"\"wrap the default ip.showtraceback to store info for ip._showtraceback\"\"\"</span>    <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">128 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">nonlocal</span> tb_data                                                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">129 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>tb_data = kwargs                                                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>130 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>default_showtraceback(*args, **kwargs)                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">131 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span>                                                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">132 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">def</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">ipy_display_traceback</span>(                                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">133 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>*args: Any, is_syntax: <span style=\"color: #00ffff; text-decoration-color: #00ffff\">bool</span> = <span style=\"color: #0000ff; text-decoration-color: #0000ff\">False</span>, **kwargs: Any                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">interactiveshell</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">2116</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">showtraceback</span>                                                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">2113 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   │   </span>traceback.print_exc()                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">2114 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>                                                       <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">2115 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span>                                                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>2116 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>._showtraceback(etype, value, stb)                                <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">2117 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.call_pdb:                                                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">2118 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># drop into debugger</span>                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">2119 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.debugger(force=<span style=\"color: #0000ff; text-decoration-color: #0000ff\">True</span>)                                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/rich/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">traceback.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">146</span> in      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #00ff00; text-decoration-color: #00ff00\">ipy_display_traceback</span>                                                                            <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">143 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>compiled = tb_data.get(<span style=\"color: #808000; text-decoration-color: #808000\">\"running_compiled_code\"</span>, <span style=\"color: #0000ff; text-decoration-color: #0000ff\">False</span>)                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">144 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>tb_offset = tb_data.get(<span style=\"color: #808000; text-decoration-color: #808000\">\"tb_offset\"</span>, <span style=\"color: #0000ff; text-decoration-color: #0000ff\">1</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> compiled <span style=\"color: #0000ff; text-decoration-color: #0000ff\">else</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">0</span>)                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">145 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># remove ipython internal frames from trace with tb_offset</span>                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>146 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">for</span> _ <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">in</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">range</span>(tb_offset):                                                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">147 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> tb <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">is</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>:                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">148 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">break</span>                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">149 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>tb = tb.tb_next                                                            <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">╰──────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
-       "<span style=\"color: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">TypeError: </span><span style=\"color: #008000; text-decoration-color: #008000\">'NoneType'</span> object cannot be interpreted as an integer\n",
-       "\n",
-       "<span style=\"font-style: italic\">During handling of the above exception, another exception occurred:</span>\n",
-       "\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">╭─────────────────────────────── </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\">Traceback </span><span style=\"color: #bf7f7f; text-decoration-color: #bf7f7f; font-weight: bold\">(most recent call last)</span><span style=\"color: #800000; text-decoration-color: #800000\"> ────────────────────────────────╮</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">interactiveshell</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">3448</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">run_ast_nodes</span>                                                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3445 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>):                                                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3446 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span>code = compiler(mod, cell_name, mode)                                 <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3447 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span>asy = compare(code)                                                   <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>3448 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">await</span> <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.run_code(code, result, async_=asy):                         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3449 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">True</span>                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3450 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>                                                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3451 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\"># Flush softspace</span>                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">interactiveshell</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">3526</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">run_code</span>                                                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3523 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span>etype, value, tb = sys.exc_info()                                             <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3524 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> result <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">is</span> <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">not</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>:                                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3525 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>result.error_in_exec = value                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>3526 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.CustomTB(etype, value, tb)                                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3527 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">except</span>:                                                                           <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3528 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">if</span> result <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">is</span> <span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">not</span> <span style=\"color: #0000ff; text-decoration-color: #0000ff\">None</span>:                                                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">3529 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span>result.error_in_exec = sys.exc_info()[<span style=\"color: #0000ff; text-decoration-color: #0000ff\">1</span>]                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #bfbf7f; text-decoration-color: #bfbf7f\">/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/</span><span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">interactiveshell</span> <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #808000; text-decoration-color: #808000; font-weight: bold\">.py</span>:<span style=\"color: #0000ff; text-decoration-color: #0000ff\">1985</span> in <span style=\"color: #00ff00; text-decoration-color: #00ff00\">wrapped</span>                                                                              <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>                                                                                                  <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1982 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span>stb = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.InteractiveTB.structured_traceback(*sys.exc_info())        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1983 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">print</span>(<span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.InteractiveTB.stb2text(stb))                               <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1984 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span><span style=\"color: #00ffff; text-decoration-color: #00ffff\">print</span>(<span style=\"color: #808000; text-decoration-color: #808000\">\"The original exception:\"</span>)                                      <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span> <span style=\"color: #800000; text-decoration-color: #800000\">❱ </span>1985 <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span>stb = <span style=\"color: #00ffff; text-decoration-color: #00ffff\">self</span>.InteractiveTB.structured_traceback(                        <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1986 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   │   │   │   │   │   │   </span>(etype,value,tb), tb_offset=tb_offset         <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1987 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   │   </span>)                                                                     <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">│</span>   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1988 </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">│   │   │   │   </span><span style=\"color: #0000ff; text-decoration-color: #0000ff\">return</span> stb                                                                <span style=\"color: #800000; text-decoration-color: #800000\">│</span>\n",
-       "<span style=\"color: #800000; text-decoration-color: #800000\">╰──────────────────────────────────────────────────────────────────────────────────────────────────╯</span>\n",
-       "<span style=\"color: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">TypeError: </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">structured_traceback</span><span style=\"font-weight: bold\">()</span> missing <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span> required positional argument: <span style=\"color: #008000; text-decoration-color: #008000\">'evalue'</span>\n",
-       "</pre>\n"
-      ],
       "text/plain": [
-       "\u001b[31m╭─\u001b[0m\u001b[31m──────────────────────────────\u001b[0m\u001b[31m \u001b[0m\u001b[1;31mTraceback \u001b[0m\u001b[1;2;31m(most recent call last)\u001b[0m\u001b[31m \u001b[0m\u001b[31m───────────────────────────────\u001b[0m\u001b[31m─╮\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/\u001b[0m\u001b[1;33minteractiveshell\u001b[0m \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[1;33m.py\u001b[0m:\u001b[94m3508\u001b[0m in \u001b[92mrun_code\u001b[0m                                                                             \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m3505 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mif\u001b[0m async_:                                                                \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m3506 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[94mawait\u001b[0m \u001b[96meval\u001b[0m(code_obj, \u001b[96mself\u001b[0m.user_global_ns, \u001b[96mself\u001b[0m.user_ns)               \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m3507 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94melse\u001b[0m:                                                                     \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m3508 \u001b[2m│   │   │   │   │   \u001b[0mexec(code_obj, \u001b[96mself\u001b[0m.user_global_ns, \u001b[96mself\u001b[0m.user_ns)                     \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m3509 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mfinally\u001b[0m:                                                                      \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m3510 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[2m# Reset our crash handler in place\u001b[0m                                        \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m3511 \u001b[0m\u001b[2m│   │   │   │   \u001b[0msys.excepthook = old_excepthook                                           \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m in \u001b[92m<module>\u001b[0m:\u001b[94m1\u001b[0m                                                                                    \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m1 dq.finish()                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m2 \u001b[0m                                                                                             \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/utils/\u001b[0m\u001b[1;33mhelpers.py\u001b[0m: \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[94m25\u001b[0m in \u001b[92mdecorator\u001b[0m                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 22 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92mdecorator\u001b[0m(*args: P.args, **kwargs: P.kwargs) -> Optional[T]:                       \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 23 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mif\u001b[0m galileo_disabled():                                                             \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 24 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mreturn\u001b[0m \u001b[94mNone\u001b[0m                                                                    \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m 25 \u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m func(*args, **kwargs)                                                       \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 26 \u001b[0m\u001b[2m│   \u001b[0m                                                                                       \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 27 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mreturn\u001b[0m decorator                                                                       \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 28 \u001b[0m                                                                                           \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/core/\u001b[0m\u001b[1;33mfinish.py\u001b[0m:\u001b[94m61\u001b[0m \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m in \u001b[92mfinish\u001b[0m                                                                                        \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 58 \u001b[0m\u001b[2m│   \u001b[0m\u001b[2m# Certain tasks require extra finish logic\u001b[0m                                             \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 59 \u001b[0m\u001b[2m│   \u001b[0mdata_logger.logger_config.finish()                                                     \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 60 \u001b[0m\u001b[2m│   \u001b[0m                                                                                       \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m 61 \u001b[2m│   \u001b[0mdata_logger.upload(last_epoch, create_data_embs=create_data_embs)                      \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 62 \u001b[0m\u001b[2m│   \u001b[0mupload_dq_log_file()                                                                   \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 63 \u001b[0m\u001b[2m│   \u001b[0mbody = \u001b[96mdict\u001b[0m(                                                                           \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 64 \u001b[0m\u001b[2m│   │   \u001b[0mproject_id=\u001b[96mstr\u001b[0m(config.current_project_id),                                         \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/data_logg\u001b[0m \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33mer/\u001b[0m\u001b[1;33mbase_data_logger.py\u001b[0m:\u001b[94m267\u001b[0m in \u001b[92mupload\u001b[0m                                                             \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m264 \u001b[0m\u001b[2m│   │   │   \u001b[0mcreate_data_embs = \u001b[94mFalse\u001b[0m                                                       \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m265 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                   \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m266 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mfor\u001b[0m split \u001b[95min\u001b[0m Split.get_valid_attributes():                                         \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m267 \u001b[2m│   │   │   \u001b[0m\u001b[96mself\u001b[0m.upload_split(                                                             \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m268 \u001b[0m\u001b[2m│   │   │   │   \u001b[0mlocation, split, object_store, last_epoch, create_data_embs                \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m269 \u001b[0m\u001b[2m│   │   │   \u001b[0m)                                                                              \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m270 \u001b[0m                                                                                           \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/data_logg\u001b[0m \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33mer/\u001b[0m\u001b[1;33mbase_data_logger.py\u001b[0m:\u001b[94m295\u001b[0m in \u001b[92mupload_split\u001b[0m                                                       \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m292 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mreturn\u001b[0m                                                                         \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m293 \u001b[0m\u001b[2m│   │   \u001b[0min_frame_split = vaex.open(\u001b[33mf\u001b[0m\u001b[33m\"\u001b[0m\u001b[33m{\u001b[0min_frame_path\u001b[33m}\u001b[0m\u001b[33m/*.\u001b[0m\u001b[33m{\u001b[0m\u001b[96mself\u001b[0m.INPUT_DATA_FILE_EXT\u001b[33m}\u001b[0m\u001b[33m\"\u001b[0m)        \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m294 \u001b[0m\u001b[2m│   │   \u001b[0min_frame_split = \u001b[96mself\u001b[0m.convert_large_string(in_frame_split)                         \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m295 \u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m.upload_split_from_in_frame(                                                   \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m296 \u001b[0m\u001b[2m│   │   │   \u001b[0mobject_store,                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m297 \u001b[0m\u001b[2m│   │   │   \u001b[0min_frame_split,                                                                \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m298 \u001b[0m\u001b[2m│   │   │   \u001b[0msplit,                                                                         \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/loggers/data_logg\u001b[0m \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33mer/\u001b[0m\u001b[1;33msemantic_segmentation.py\u001b[0m:\u001b[94m166\u001b[0m in \u001b[92mupload_split_from_in_frame\u001b[0m                                    \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m163 \u001b[0m\u001b[2m│   │   \u001b[0m)                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m164 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                   \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m165 \u001b[0m\u001b[2m│   │   \u001b[0mdir_name = \u001b[33mf\u001b[0m\u001b[33m\"\u001b[0m\u001b[33m{\u001b[0msplit_loc\u001b[33m}\u001b[0m\u001b[33m/0\u001b[0m\u001b[33m\"\u001b[0m                                                        \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m166 \u001b[2m│   │   \u001b[0mout_frame = get_output_df(                                                         \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m167 \u001b[0m\u001b[2m│   │   │   \u001b[0mdir_name,                                                                      \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m168 \u001b[0m\u001b[2m│   │   │   \u001b[0mprob_only=\u001b[94mFalse\u001b[0m,                                                               \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m169 \u001b[0m\u001b[2m│   │   │   \u001b[0msplit=split,                                                                   \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/utils/\u001b[0m\u001b[1;33mvaex.py\u001b[0m:\u001b[94m192\u001b[0m \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m in \u001b[92mget_output_df\u001b[0m                                                                                 \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m189 \u001b[0m\u001b[2m│   \u001b[0m\u001b[2m# just open the processed file\u001b[0m                                                         \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m190 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mif\u001b[0m os.path.isfile(out_frame_path):                                                     \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m191 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m vaex.open(out_frame_path)                                                   \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m192 \u001b[2m│   \u001b[0mstr_cols = concat_hdf5_files(dir_name, prob_only)                                      \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m193 \u001b[0m\u001b[2m│   \u001b[0mout_frame = vaex.open(out_frame_path)                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m194 \u001b[0m\u001b[2m│   \u001b[0m                                                                                       \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m195 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mif\u001b[0m split == Split.inference:                                                           \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/utils/\u001b[0m\u001b[1;33mhdf5_store.\u001b[0m \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[1;33mpy\u001b[0m:\u001b[94m129\u001b[0m in \u001b[92mconcat_hdf5_files\u001b[0m                                                                      \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m126 \u001b[0m\u001b[2m│   \u001b[0mstr_cols = []                                                                          \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m127 \u001b[0m\u001b[2m│   \u001b[0mstores = {}                                                                            \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m128 \u001b[0m\u001b[2m│   \u001b[0mfiles = os.listdir(location)                                                           \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m129 \u001b[2m│   \u001b[0mdf = vaex.open(\u001b[33mf\u001b[0m\u001b[33m\"\u001b[0m\u001b[33m{\u001b[0mlocation\u001b[33m}\u001b[0m\u001b[33m/\u001b[0m\u001b[33m{\u001b[0mfiles[\u001b[94m0\u001b[0m]\u001b[33m}\u001b[0m\u001b[33m\"\u001b[0m)                                               \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m130 \u001b[0m\u001b[2m│   \u001b[0m                                                                                       \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m131 \u001b[0m\u001b[2m│   \u001b[0m\u001b[2m# Construct a store per column\u001b[0m                                                         \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m132 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mif\u001b[0m prob_only:                                                                          \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/\u001b[0m\u001b[1;33m__init__.py\u001b[0m:\u001b[94m244\u001b[0m in \u001b[92mopen\u001b[0m  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m241 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m)                                                                          \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m242 \u001b[0m\u001b[2m│   │   │   │   \u001b[0mds = vaex.dataset.open(path_output, fs_options=fs_options, fs=fs)          \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m243 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94melse\u001b[0m:                                                                          \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m244 \u001b[2m│   │   │   │   \u001b[0mds = vaex.dataset.open(path, fs_options=fs_options, fs=fs, **kwargs)       \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m245 \u001b[0m\u001b[2m│   │   │   \u001b[0mdf = vaex.from_dataset(ds)                                                     \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m246 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mif\u001b[0m df \u001b[95mis\u001b[0m \u001b[94mNone\u001b[0m:                                                                 \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m247 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mif\u001b[0m os.path.exists(path):                                                   \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/\u001b[0m\u001b[1;33mdataset.py\u001b[0m:\u001b[94m81\u001b[0m in \u001b[92mopen\u001b[0m    \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m  78 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mfor\u001b[0m opener \u001b[95min\u001b[0m opener_classes:                                                         \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m  79 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mif\u001b[0m opener.quick_test(path, fs_options=fs_options, fs=fs):                         \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m  80 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mif\u001b[0m opener.can_open(path, fs_options=fs_options, fs=fs, *args, **kwargs):      \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m  81 \u001b[2m│   │   │   │   \u001b[0m\u001b[94mreturn\u001b[0m opener.open(path, fs_options=fs_options, fs=fs, *args, **kwargs)   \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m  82 \u001b[0m\u001b[2m│   \u001b[0m                                                                                      \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m  83 \u001b[0m\u001b[2m│   \u001b[0m\u001b[2m# otherwise try all openers\u001b[0m                                                           \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m  84 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mfor\u001b[0m opener \u001b[95min\u001b[0m opener_classes:                                                         \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/\u001b[0m\u001b[1;33mdataset.py\u001b[0m:\u001b[94m1457\u001b[0m in \u001b[92mopen\u001b[0m  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1454 \u001b[0m\u001b[2m│   \u001b[0m                                                                                      \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1455 \u001b[0m\u001b[2m│   \u001b[0m\u001b[1;95m@classmethod\u001b[0m                                                                          \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1456 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92mopen\u001b[0m(\u001b[96mcls\u001b[0m, path, *args, **kwargs):                                                 \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m1457 \u001b[2m│   │   \u001b[0m\u001b[94mreturn\u001b[0m \u001b[96mcls\u001b[0m(path, *args, **kwargs)                                                 \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1458 \u001b[0m\u001b[2m│   \u001b[0m                                                                                      \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1459 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92mchunk_iterator\u001b[0m(\u001b[96mself\u001b[0m, columns, chunk_size=\u001b[94mNone\u001b[0m, reverse=\u001b[94mFalse\u001b[0m):                    \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1460 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94myield from\u001b[0m \u001b[96mself\u001b[0m._default_chunk_iterator(\u001b[96mself\u001b[0m._columns, columns, chunk_size, reve  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/hdf5/\u001b[0m\u001b[1;33mdataset.py\u001b[0m:\u001b[94m73\u001b[0m in    \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[92m__init__\u001b[0m                                                                                         \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 70 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m._version = \u001b[94m1\u001b[0m                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 71 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m._load()                                                                       \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 72 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mif\u001b[0m \u001b[95mnot\u001b[0m write:  \u001b[2m# in write mode, call freeze yourself, so the hashes are computed\u001b[0m   \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m 73 \u001b[2m│   │   │   \u001b[0m\u001b[96mself\u001b[0m._freeze()                                                                 \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 74 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94melse\u001b[0m:                                                                              \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 75 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[2m# make sure we set the row count, which otherwise freeze would do\u001b[0m              \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 76 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[96mself\u001b[0m._set_row_count()                                                          \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/\u001b[0m\u001b[1;33mdataset.py\u001b[0m:\u001b[94m1501\u001b[0m in       \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[92m_freeze\u001b[0m                                                                                          \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1498 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92m_freeze\u001b[0m(\u001b[96mself\u001b[0m):                                                                    \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1499 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m._ids = frozendict(\u001b[96mself\u001b[0m._ids)                                                 \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1500 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m._columns = frozendict(\u001b[96mself\u001b[0m._columns)                                         \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m1501 \u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m._set_row_count()                                                             \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1502 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m._frozen = \u001b[94mTrue\u001b[0m                                                               \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1503 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mif\u001b[0m \u001b[96mself\u001b[0m._hash_cache_needs_write:                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1504 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[96mself\u001b[0m._write_hash_info()                                                       \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/vaex/\u001b[0m\u001b[1;33mdataset.py\u001b[0m:\u001b[94m423\u001b[0m in        \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[92m_set_row_count\u001b[0m                                                                                   \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 420 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m._row_count = \u001b[96mlen\u001b[0m(values[\u001b[94m0\u001b[0m])                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 421 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mfor\u001b[0m name, value \u001b[95min\u001b[0m \u001b[96mlist\u001b[0m(\u001b[96mself\u001b[0m._columns.items())[\u001b[94m1\u001b[0m:]:                               \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 422 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mif\u001b[0m \u001b[96mlen\u001b[0m(value) != \u001b[96mself\u001b[0m._row_count:                                             \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m 423 \u001b[2m│   │   │   │   \u001b[0m\u001b[94mraise\u001b[0m \u001b[96mValueError\u001b[0m(\u001b[33mf\u001b[0m\u001b[33m'\u001b[0m\u001b[33mFirst columns has length \u001b[0m\u001b[33m{\u001b[0m\u001b[96mself\u001b[0m._row_count\u001b[33m}\u001b[0m\u001b[33m, while col\u001b[0m  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 424 \u001b[0m\u001b[2m│   \u001b[0m                                                                                      \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 425 \u001b[0m\u001b[2m│   \u001b[0m\u001b[1;95m@property\u001b[0m                                                                             \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m 426 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92mrow_count\u001b[0m(\u001b[96mself\u001b[0m):                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n",
-       "\u001b[1;91mValueError: \u001b[0mFirst columns has length \u001b[1;36m3\u001b[0m, while column epoch has length \u001b[1;36m2\u001b[0m\n",
-       "\n",
-       "\u001b[3mDuring handling of the above exception, another exception occurred:\u001b[0m\n",
-       "\n",
-       "\u001b[31m╭─\u001b[0m\u001b[31m──────────────────────────────\u001b[0m\u001b[31m \u001b[0m\u001b[1;31mTraceback \u001b[0m\u001b[1;2;31m(most recent call last)\u001b[0m\u001b[31m \u001b[0m\u001b[31m───────────────────────────────\u001b[0m\u001b[31m─╮\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/\u001b[0m\u001b[1;33minteractiveshell\u001b[0m \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[1;33m.py\u001b[0m:\u001b[94m1975\u001b[0m in \u001b[92mwrapped\u001b[0m                                                                              \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1972 \u001b[0m\u001b[2;33m│   │   │   │   \u001b[0m\u001b[33mhandlers to crash IPython.\u001b[0m                                                \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1973 \u001b[0m\u001b[2;33m│   │   │   │   \u001b[0m\u001b[33m\"\"\"\u001b[0m                                                                       \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1974 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mtry\u001b[0m:                                                                      \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m1975 \u001b[2m│   │   │   │   │   \u001b[0mstb = handler(\u001b[96mself\u001b[0m,etype,value,tb,tb_offset=tb_offset)                \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1976 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[94mreturn\u001b[0m validate_stb(stb)                                              \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1977 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mexcept\u001b[0m:                                                                   \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1978 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[2m# clear custom handler immediately\u001b[0m                                    \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/\u001b[0m\u001b[1;33manalytics.py\u001b[0m:\u001b[94m149\u001b[0m  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m in \u001b[92mipython_exception_handler\u001b[0m                                                                     \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m146 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[2m# TODO: create internal logging endpoint\u001b[0m                                       \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m147 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mpass\u001b[0m                                                                           \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m148 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[2m# We need to call the default ipython exception handler to raise the error\u001b[0m         \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m149 \u001b[2m│   │   \u001b[0mshell.showtraceback((etype, evalue, tb), tb_offset=tb_offset)                      \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m150 \u001b[0m\u001b[2m│   \u001b[0m                                                                                       \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m151 \u001b[0m\u001b[2m│   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92mtrack_exception_ipython\u001b[0m(                                                           \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m152 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[96mself\u001b[0m,                                                                              \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/rich/\u001b[0m\u001b[1;33mtraceback.py\u001b[0m:\u001b[94m130\u001b[0m in      \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[92mipy_show_traceback\u001b[0m                                                                               \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m127 \u001b[0m\u001b[2;90m│   │   │   \u001b[0m\u001b[33m\"\"\"wrap the default ip.showtraceback to store info for ip._showtraceback\"\"\"\u001b[0m    \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m128 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mnonlocal\u001b[0m tb_data                                                               \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m129 \u001b[0m\u001b[2m│   │   │   \u001b[0mtb_data = kwargs                                                               \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m130 \u001b[2m│   │   │   \u001b[0mdefault_showtraceback(*args, **kwargs)                                         \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m131 \u001b[0m\u001b[2m│   │   \u001b[0m                                                                                   \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m132 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mdef\u001b[0m \u001b[92mipy_display_traceback\u001b[0m(                                                         \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m133 \u001b[0m\u001b[2m│   │   │   \u001b[0m*args: Any, is_syntax: \u001b[96mbool\u001b[0m = \u001b[94mFalse\u001b[0m, **kwargs: Any                             \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/\u001b[0m\u001b[1;33minteractiveshell\u001b[0m \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[1;33m.py\u001b[0m:\u001b[94m2116\u001b[0m in \u001b[92mshowtraceback\u001b[0m                                                                        \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m2113 \u001b[0m\u001b[2m│   │   │   │   │   │   \u001b[0mtraceback.print_exc()                                             \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m2114 \u001b[0m\u001b[2m│   │   │   │   │   │   \u001b[0m\u001b[94mreturn\u001b[0m \u001b[94mNone\u001b[0m                                                       \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m2115 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m                                                                      \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m2116 \u001b[2m│   │   │   │   │   \u001b[0m\u001b[96mself\u001b[0m._showtraceback(etype, value, stb)                                \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m2117 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[94mif\u001b[0m \u001b[96mself\u001b[0m.call_pdb:                                                     \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m2118 \u001b[0m\u001b[2m│   │   │   │   │   │   \u001b[0m\u001b[2m# drop into debugger\u001b[0m                                              \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m2119 \u001b[0m\u001b[2m│   │   │   │   │   │   \u001b[0m\u001b[96mself\u001b[0m.debugger(force=\u001b[94mTrue\u001b[0m)                                         \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/rich/\u001b[0m\u001b[1;33mtraceback.py\u001b[0m:\u001b[94m146\u001b[0m in      \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[92mipy_display_traceback\u001b[0m                                                                            \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m143 \u001b[0m\u001b[2m│   │   │   \u001b[0mcompiled = tb_data.get(\u001b[33m\"\u001b[0m\u001b[33mrunning_compiled_code\u001b[0m\u001b[33m\"\u001b[0m, \u001b[94mFalse\u001b[0m)                         \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m144 \u001b[0m\u001b[2m│   │   │   \u001b[0mtb_offset = tb_data.get(\u001b[33m\"\u001b[0m\u001b[33mtb_offset\u001b[0m\u001b[33m\"\u001b[0m, \u001b[94m1\u001b[0m \u001b[94mif\u001b[0m compiled \u001b[94melse\u001b[0m \u001b[94m0\u001b[0m)                     \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m145 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[2m# remove ipython internal frames from trace with tb_offset\u001b[0m                     \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m146 \u001b[2m│   │   │   \u001b[0m\u001b[94mfor\u001b[0m _ \u001b[95min\u001b[0m \u001b[96mrange\u001b[0m(tb_offset):                                                     \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m147 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mif\u001b[0m tb \u001b[95mis\u001b[0m \u001b[94mNone\u001b[0m:                                                             \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m148 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[94mbreak\u001b[0m                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m149 \u001b[0m\u001b[2m│   │   │   │   \u001b[0mtb = tb.tb_next                                                            \u001b[31m│\u001b[0m\n",
-       "\u001b[31m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n",
-       "\u001b[1;91mTypeError: \u001b[0m\u001b[32m'NoneType'\u001b[0m object cannot be interpreted as an integer\n",
-       "\n",
-       "\u001b[3mDuring handling of the above exception, another exception occurred:\u001b[0m\n",
-       "\n",
-       "\u001b[31m╭─\u001b[0m\u001b[31m──────────────────────────────\u001b[0m\u001b[31m \u001b[0m\u001b[1;31mTraceback \u001b[0m\u001b[1;2;31m(most recent call last)\u001b[0m\u001b[31m \u001b[0m\u001b[31m───────────────────────────────\u001b[0m\u001b[31m─╮\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/\u001b[0m\u001b[1;33minteractiveshell\u001b[0m \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[1;33m.py\u001b[0m:\u001b[94m3448\u001b[0m in \u001b[92mrun_ast_nodes\u001b[0m                                                                        \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m3445 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m):                                                                        \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m3446 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0mcode = compiler(mod, cell_name, mode)                                 \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m3447 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0masy = compare(code)                                                   \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m3448 \u001b[2m│   │   │   │   \u001b[0m\u001b[94mif\u001b[0m \u001b[94mawait\u001b[0m \u001b[96mself\u001b[0m.run_code(code, result, async_=asy):                         \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m3449 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[94mreturn\u001b[0m \u001b[94mTrue\u001b[0m                                                           \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m3450 \u001b[0m\u001b[2m│   │   │   \u001b[0m                                                                              \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m3451 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[2m# Flush softspace\u001b[0m                                                             \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/\u001b[0m\u001b[1;33minteractiveshell\u001b[0m \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[1;33m.py\u001b[0m:\u001b[94m3526\u001b[0m in \u001b[92mrun_code\u001b[0m                                                                             \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m3523 \u001b[0m\u001b[2m│   │   │   \u001b[0metype, value, tb = sys.exc_info()                                             \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m3524 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mif\u001b[0m result \u001b[95mis\u001b[0m \u001b[95mnot\u001b[0m \u001b[94mNone\u001b[0m:                                                        \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m3525 \u001b[0m\u001b[2m│   │   │   │   \u001b[0mresult.error_in_exec = value                                              \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m3526 \u001b[2m│   │   │   \u001b[0m\u001b[96mself\u001b[0m.CustomTB(etype, value, tb)                                               \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m3527 \u001b[0m\u001b[2m│   │   \u001b[0m\u001b[94mexcept\u001b[0m:                                                                           \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m3528 \u001b[0m\u001b[2m│   │   │   \u001b[0m\u001b[94mif\u001b[0m result \u001b[95mis\u001b[0m \u001b[95mnot\u001b[0m \u001b[94mNone\u001b[0m:                                                        \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m3529 \u001b[0m\u001b[2m│   │   │   │   \u001b[0mresult.error_in_exec = sys.exc_info()[\u001b[94m1\u001b[0m]                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[2;33m/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/IPython/core/\u001b[0m\u001b[1;33minteractiveshell\u001b[0m \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[1;33m.py\u001b[0m:\u001b[94m1985\u001b[0m in \u001b[92mwrapped\u001b[0m                                                                              \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m                                                                                                  \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1982 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0mstb = \u001b[96mself\u001b[0m.InteractiveTB.structured_traceback(*sys.exc_info())        \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1983 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[96mprint\u001b[0m(\u001b[96mself\u001b[0m.InteractiveTB.stb2text(stb))                               \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1984 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m\u001b[96mprint\u001b[0m(\u001b[33m\"\u001b[0m\u001b[33mThe original exception:\u001b[0m\u001b[33m\"\u001b[0m)                                      \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m \u001b[31m❱ \u001b[0m1985 \u001b[2m│   │   │   │   │   \u001b[0mstb = \u001b[96mself\u001b[0m.InteractiveTB.structured_traceback(                        \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1986 \u001b[0m\u001b[2m│   │   │   │   │   │   │   │   │   │   │   \u001b[0m(etype,value,tb), tb_offset=tb_offset         \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1987 \u001b[0m\u001b[2m│   │   │   │   │   \u001b[0m)                                                                     \u001b[31m│\u001b[0m\n",
-       "\u001b[31m│\u001b[0m   \u001b[2m1988 \u001b[0m\u001b[2m│   │   │   │   \u001b[0m\u001b[94mreturn\u001b[0m stb                                                                \u001b[31m│\u001b[0m\n",
-       "\u001b[31m╰──────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n",
-       "\u001b[1;91mTypeError: \u001b[0m\u001b[1;35mstructured_traceback\u001b[0m\u001b[1m(\u001b[0m\u001b[1m)\u001b[0m missing \u001b[1;36m1\u001b[0m required positional argument: \u001b[32m'evalue'\u001b[0m\n"
+       "'https://console.dev.rungalileo.io/insights?projectId=7e78e642-cc40-4f5c-8f45-b2cadd8d674a&runId=617746f8-14a0-4e45-b27a-903492fe7343&split=training&metric=f1&depHigh=1&depLow=0&taskType=6'"
       ]
      },
+     "execution_count": 6,
      "metadata": {},
-     "output_type": "display_data"
+     "output_type": "execute_result"
     }
    ],
    "source": [

From 27c9e533af493ac63156a60abce2fc6d4fdbd1bc Mon Sep 17 00:00:00 2001
From: Derek <dcaustin33@gmail.com>
Date: Thu, 11 May 2023 13:56:45 -0700
Subject: [PATCH 05/16] Correction

---
 dataquality/loggers/model_logger/base_model_logger.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/dataquality/loggers/model_logger/base_model_logger.py b/dataquality/loggers/model_logger/base_model_logger.py
index 7dbd6ba6b..b82001f03 100644
--- a/dataquality/loggers/model_logger/base_model_logger.py
+++ b/dataquality/loggers/model_logger/base_model_logger.py
@@ -17,6 +17,7 @@
 from dataquality.utils.ampli import AmpliMetric
 from dataquality.utils.dq_logger import get_dq_logger
 from dataquality.utils.hdf5_store import _save_hdf5_file
+from dataquality.utils.thread_pool import ThreadPoolManager
 
 analytics = Analytics(ApiClient, config)  # type: ignore
 
@@ -98,8 +99,7 @@ def log(self) -> None:
         # global variables (cur_split and cur_epoch) that are subject to change
         # between subsequent threads
         self.set_split_epoch()
-        # ThreadPoolManager.add_thread(target=self._add_threaded_log)
-        self._add_threaded_log()
+        ThreadPoolManager.add_thread(target=self._add_threaded_log)
 
     def write_model_output(self, data: Dict) -> None:
         """Creates an hdf5 file from the data dict"""

From efe4d3995e4438a72ec8b4dda047a7caec080e12 Mon Sep 17 00:00:00 2001
From: Derek <dcaustin33@gmail.com>
Date: Thu, 11 May 2023 14:10:22 -0700
Subject: [PATCH 06/16] dep defaulted to none

---
 .gitignore                                    |   3 +-
 .../model_logger/semantic_segmentation.py     |   4 +-
 dataquality/schemas/semantic_segmentation.py  |   2 +-
 docs/cv/coco_deeplab_hooks.ipynb              | 257 +-----------------
 4 files changed, 17 insertions(+), 249 deletions(-)

diff --git a/.gitignore b/.gitignore
index 8bd0bf295..7030924a4 100644
--- a/.gitignore
+++ b/.gitignore
@@ -179,4 +179,5 @@ coco.ipynb
 
 # SemSeg
 CV_datasets/
-coco_hf_dataset.py
\ No newline at end of file
+coco_hf_dataset.py
+coco_deeplab_hooks.ipynb
\ No newline at end of file
diff --git a/dataquality/loggers/model_logger/semantic_segmentation.py b/dataquality/loggers/model_logger/semantic_segmentation.py
index f8b411ab6..c665bf8a1 100644
--- a/dataquality/loggers/model_logger/semantic_segmentation.py
+++ b/dataquality/loggers/model_logger/semantic_segmentation.py
@@ -135,7 +135,7 @@ def get_polygon_data(
                 image_ids.append(image_id)
                 preds.append(polygon.label_idx)
                 golds.append(-1)
-                data_error_potentials.append(0.0)
+                data_error_potentials.append(polygon.data_error_potential)
                 errors.append(polygon.error_type.value)
                 upload_polygon_contours(
                     polygon, self.logger_config.polygon_idx, self.contours_path
@@ -147,7 +147,7 @@ def get_polygon_data(
                 image_ids.append(image_id)
                 preds.append(-1)
                 golds.append(polygon.label_idx)
-                data_error_potentials.append(0.0)
+                data_error_potentials.append(polygon.data_error_potential)
                 errors.append(polygon.error_type.value)
                 upload_polygon_contours(
                     polygon, self.logger_config.polygon_idx, self.contours_path
diff --git a/dataquality/schemas/semantic_segmentation.py b/dataquality/schemas/semantic_segmentation.py
index 064d7de7c..56b5936cd 100644
--- a/dataquality/schemas/semantic_segmentation.py
+++ b/dataquality/schemas/semantic_segmentation.py
@@ -52,7 +52,7 @@ class Polygon(BaseModel):
     misclassified_class_label: Optional[int] = None
     error_type: ErrorType = ErrorType.none
     contours: List[Contour]
-    data_error_potential: float = 0.0
+    data_error_potential: Optional[float] = None
 
     @property
     def contours_opencv(self) -> List[np.ndarray]:
diff --git a/docs/cv/coco_deeplab_hooks.ipynb b/docs/cv/coco_deeplab_hooks.ipynb
index 74188ee25..c51512882 100644
--- a/docs/cv/coco_deeplab_hooks.ipynb
+++ b/docs/cv/coco_deeplab_hooks.ipynb
@@ -2,20 +2,9 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'ds = load_dataset(\\n    \"CVdatasets/CocoSegmentationOnlyVal5000\",\\n    use_auth_token=\"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\"\\n)'"
-      ]
-     },
-     "execution_count": 1,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# !pip install datasets evaluate torch torchvision \n",
     "import os\n",
@@ -40,17 +29,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Found dataset, there are 4030 images and 4030 masks\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# download the data from our public gcs bucket and save it to disk\n",
     "# dataset_path, img_path, mask_path = download_gcs_data()\n",
@@ -84,7 +65,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/"
@@ -93,19 +74,7 @@
     "outputId": "85d91dc9-405e-4f02-a6bf-6a88f9502412",
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Using cache found in /Users/derek/.cache/torch/hub/pytorch_vision_v0.10.0\n",
-      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.\n",
-      "  warnings.warn(\n",
-      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=DeepLabV3_ResNet50_Weights.COCO_WITH_VOC_LABELS_V1`. You can also use `weights=DeepLabV3_ResNet50_Weights.DEFAULT` to get the most up-to-date weights.\n",
-      "  warnings.warn(msg)\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "\n",
     "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
@@ -119,46 +88,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/core/__init__.py:27: GalileoWarning: configure is deprecated, use dq.set_console_url and dq.login\n",
-      "  warnings.warn(\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "📡 https://console.dev.rungalileo.io\n",
-      "🔭 Logging you into Galileo\n",
-      "\n",
-      "🚀 You're logged in to Galileo as galileo@rungalileo.io!\n",
-      "✨ Initializing existing public project 'Derek-Elliott-Proj'\n",
-      "🏃‍♂️ Fetching existing run 'test-polygon-df'\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/core/init.py:171: GalileoWarning: Run: Derek-Elliott-Proj/test-polygon-df already exists! The existing run will get overwritten on call to finish()!\n",
-      "  warnings.warn(\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "🛰 Connected to existing project 'Derek-Elliott-Proj', and existing run 'test-polygon-df'.\n",
-      "🚀 Found existing run labels. Setting labels for run to ['background', 'airplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car', 'cat', 'chair', 'cow', 'dining table', 'dog', 'horse', 'motorcycle', 'person', 'potted plant', 'sheep', 'couch', 'train', 'tv']. You do not need to set labels for this run.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "try:\n",
     "    import dataquality as dq\n",
@@ -205,43 +137,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "2023-05-11 13:49:23.693790: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
-      "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "We assume the dataloaders passed only have transforms that Tensor, Resize,         and Normalize the image and mask\n",
-      "‼ Any cropping or shearing transforms passed will lead to unexpected         results\n",
-      "See docs at https://dq.readthedocs.io/en/latest/ (placeholder) for more info         \n",
-      " \n",
-      "\n",
-      "Found layer classifier in model layers: backbone, classifier\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).\n",
-      "  warnings.warn(\n",
-      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torch/cuda/amp/grad_scaler.py:120: UserWarning: torch.cuda.amp.GradScaler is enabled, but CUDA is not available.  Disabling.\n",
-      "  warnings.warn(\"torch.cuda.amp.GradScaler is enabled, but CUDA is not available.  Disabling.\")\n",
-      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torch/amp/autocast_mode.py:204: UserWarning: User provided device_type of 'cuda', but CUDA is not available. Disabling\n",
-      "  warnings.warn('User provided device_type of \\'cuda\\', but CUDA is not available. Disabling')\n",
-      " 50%|█████     | 1/2 [00:03<00:03,  3.26s/it]\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from dataquality.integrations.cv.torch.semantic_segmentation import watch\n",
     "watch(\n",
@@ -278,140 +176,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/derek/.cache/huggingface/modules/evaluate_modules/metrics/evaluate-metric--mean_iou/08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9/mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
-      "  iou = total_area_intersect / total_area_union\n",
-      "/Users/derek/.cache/huggingface/modules/evaluate_modules/metrics/evaluate-metric--mean_iou/08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9/mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
-      "  acc = total_area_intersect / total_area_label\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.29s =  0.0m =  0.0h\n",
-      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.16s =  0.0m =  0.0h\n",
-      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.34s =  0.0m =  0.0h  \n",
-      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.24s =  0.0m =  0.0h\n",
-      " ☁️ Uploading Data\n",
-      "CuML libraries not found, running standard process. For faster Galileo processing, consider installing\n",
-      "`pip install 'dataquality[cuda]' --extra-index-url=https://pypi.nvidia.com/`\n"
-     ]
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "20400cf290fb49ac999011f681c1d08a",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Uploading data to Galileo:   0%|          | 0.00/25.8k [00:00<?, ?B/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "296d767ead8b41e99c30c6a9485aec73",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Processing data for upload:   0%|          | 0/2 [00:00<?, ?it/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "2180f3a91509488c96df48b96554616f",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Uploading data to Galileo:   0%|          | 0.00/20.1k [00:00<?, ?B/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "604fe792fcd74222b5eb2cf8b1ff695f",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Uploading data to Galileo:   0%|          | 0.00/25.8k [00:00<?, ?B/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "a761f4731e834ba8bc14beeafd4f3743",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Processing data for upload:   0%|          | 0/2 [00:00<?, ?it/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "1aec32edc98c4b32a40da5aa172403ed",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Uploading data to Galileo:   0%|          | 0.00/20.1k [00:00<?, ?B/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Job default successfully submitted. Results will be available soon at https://console.dev.rungalileo.io/insights?projectId=7e78e642-cc40-4f5c-8f45-b2cadd8d674a&runId=617746f8-14a0-4e45-b27a-903492fe7343&split=training&metric=f1&depHigh=1&depLow=0&taskType=6\n",
-      "Waiting for job (you can safely close this window)...\n",
-      "\tUploading processed validation data\n",
-      "Done! Job finished with status completed\n",
-      "Click here to see your run! https://console.dev.rungalileo.io/insights?projectId=7e78e642-cc40-4f5c-8f45-b2cadd8d674a&runId=617746f8-14a0-4e45-b27a-903492fe7343&split=training&metric=f1&depHigh=1&depLow=0&taskType=6\n",
-      "🧹 Cleaning up\n",
-      "🧹 Cleaning up\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "'https://console.dev.rungalileo.io/insights?projectId=7e78e642-cc40-4f5c-8f45-b2cadd8d674a&runId=617746f8-14a0-4e45-b27a-903492fe7343&split=training&metric=f1&depHigh=1&depLow=0&taskType=6'"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "dq.finish()"
    ]

From d236610cf474c3016a45eeadb9e167f9569bf82b Mon Sep 17 00:00:00 2001
From: dcaustin33 <dcaustin33@gmail.com>
Date: Thu, 11 May 2023 14:34:53 -0700
Subject: [PATCH 07/16] Update
 dataquality/loggers/model_logger/semantic_segmentation.py

Co-authored-by: Elliott <elliott@rungalileo.io>
---
 dataquality/loggers/model_logger/semantic_segmentation.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/dataquality/loggers/model_logger/semantic_segmentation.py b/dataquality/loggers/model_logger/semantic_segmentation.py
index c665bf8a1..0498d6dd1 100644
--- a/dataquality/loggers/model_logger/semantic_segmentation.py
+++ b/dataquality/loggers/model_logger/semantic_segmentation.py
@@ -227,6 +227,7 @@ def _get_data_dict(self) -> Dict:
         )
 
         polygon_data = self.get_polygon_data(pred_polygons_batch, gold_polygons_batch)
+        n_polygons = polygon_data["image_id"]
         if self.split == Split.inference:
             polygon_data["inference_name"] = [self.inference_name] * len(
                 polygon_data["image_id"]

From 464d719809dfcbdec822f44f4a4917b225eba5ac Mon Sep 17 00:00:00 2001
From: Derek <dcaustin33@gmail.com>
Date: Thu, 11 May 2023 14:36:13 -0700
Subject: [PATCH 08/16] Revised on comments

---
 .../model_logger/semantic_segmentation.py      | 18 ++++++++++--------
 1 file changed, 10 insertions(+), 8 deletions(-)

diff --git a/dataquality/loggers/model_logger/semantic_segmentation.py b/dataquality/loggers/model_logger/semantic_segmentation.py
index 0498d6dd1..c9cbff099 100644
--- a/dataquality/loggers/model_logger/semantic_segmentation.py
+++ b/dataquality/loggers/model_logger/semantic_segmentation.py
@@ -194,21 +194,25 @@ def _get_data_dict(self) -> Dict:
         # Errors
         calculate_misclassified_polygons_batch(self.pred_masks, gold_polygons_batch)
         calculate_undetected_polygons_batch(self.pred_masks, gold_polygons_batch)
+        heights = [img.shape[-1] for img in self.gold_masks]
+        widths = [img.shape[-2] for img in self.gold_masks]
 
         calculate_dep_polygons_batch(
             gold_polygons_batch,
             dep_heatmaps.numpy(),
-            height=[img.shape[-1] for img in self.gold_masks],
-            width=[img.shape[-2] for img in self.gold_masks],
+            height=heights,
+            width=widths,
         )
+        
+        
 
         image_data = {
             "image": [
                 f"{self.bucket_name}/{pth}" for pth in self.image_paths
             ],  # E.g. https://storage.googleapis.com/bucket_name/.../image_id.png
             "id": self.image_ids,
-            "height": [img.shape[-1] for img in self.gold_masks],
-            "width": [img.shape[-2] for img in self.gold_masks],
+            "height": heights,
+            "width": widths,
             "image_data_error_potential": image_dep,
             "mean_lm_score": [i for i in mean_mislabeled],
             "mean_iou": iou,
@@ -229,10 +233,8 @@ def _get_data_dict(self) -> Dict:
         polygon_data = self.get_polygon_data(pred_polygons_batch, gold_polygons_batch)
         n_polygons = polygon_data["image_id"]
         if self.split == Split.inference:
-            polygon_data["inference_name"] = [self.inference_name] * len(
-                polygon_data["image_id"]
-            )
+            polygon_data["inference_name"] = [self.inference_name] * n_polygons
         else:
-            polygon_data["epoch"] = [self.epoch] * len(polygon_data["image_id"])
+            polygon_data["epoch"] = [self.epoch] * n_polygons
 
         return polygon_data

From ee92eb2995f1152604478fb2f536786af373f474 Mon Sep 17 00:00:00 2001
From: Derek <dcaustin33@gmail.com>
Date: Fri, 12 May 2023 07:18:16 -0700
Subject: [PATCH 09/16] Linting

---
 dataquality/loggers/model_logger/semantic_segmentation.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/dataquality/loggers/model_logger/semantic_segmentation.py b/dataquality/loggers/model_logger/semantic_segmentation.py
index c9cbff099..f98adf517 100644
--- a/dataquality/loggers/model_logger/semantic_segmentation.py
+++ b/dataquality/loggers/model_logger/semantic_segmentation.py
@@ -203,8 +203,6 @@ def _get_data_dict(self) -> Dict:
             height=heights,
             width=widths,
         )
-        
-        
 
         image_data = {
             "image": [

From 936d1c791d6532fa02f37b9fc33d2de4f4ac0676 Mon Sep 17 00:00:00 2001
From: Derek <dcaustin33@gmail.com>
Date: Fri, 12 May 2023 08:52:12 -0700
Subject: [PATCH 10/16] Pyproject change

---
 pyproject.toml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/pyproject.toml b/pyproject.toml
index e834ca2d9..620e974c8 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -104,6 +104,7 @@ py37 = [
     "cachetools>=5.2.0",
     "types-cachetools>=5.3.0.0",
     "importlib-metadata<5.0.0",
+    "typing-extension>=4.5.0"
 ]
 
 evaluate = [

From 24234948257ca11b971eba5145dcb74041e70123 Mon Sep 17 00:00:00 2001
From: Derek <dcaustin33@gmail.com>
Date: Fri, 12 May 2023 08:59:09 -0700
Subject: [PATCH 11/16] Typo

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 620e974c8..4916b64bb 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -104,7 +104,7 @@ py37 = [
     "cachetools>=5.2.0",
     "types-cachetools>=5.3.0.0",
     "importlib-metadata<5.0.0",
-    "typing-extension>=4.5.0"
+    "typing-extensions>=4.5.0"
 ]
 
 evaluate = [

From 631be75514bc5037df24c709d29216d2ddf773c2 Mon Sep 17 00:00:00 2001
From: Derek <dcaustin33@gmail.com>
Date: Fri, 12 May 2023 09:07:25 -0700
Subject: [PATCH 12/16] Typing version change

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 4916b64bb..62e047958 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -104,7 +104,7 @@ py37 = [
     "cachetools>=5.2.0",
     "types-cachetools>=5.3.0.0",
     "importlib-metadata<5.0.0",
-    "typing-extensions>=4.5.0"
+    "typing-extensions>=4.0.0.0"
 ]
 
 evaluate = [

From 5ca3336d01bb9778ec05f6f5963ae68bb38af61f Mon Sep 17 00:00:00 2001
From: Derek <dcaustin33@gmail.com>
Date: Fri, 12 May 2023 09:07:57 -0700
Subject: [PATCH 13/16] Typing version change

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 62e047958..b9976b9d5 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -104,7 +104,7 @@ py37 = [
     "cachetools>=5.2.0",
     "types-cachetools>=5.3.0.0",
     "importlib-metadata<5.0.0",
-    "typing-extensions>=4.0.0.0"
+    "typing-extensions<=4.0.0.0"
 ]
 
 evaluate = [

From a12eb748b7bc05f81cca9d4b4b40b9ec7d265bdb Mon Sep 17 00:00:00 2001
From: Derek <dcaustin33@gmail.com>
Date: Fri, 12 May 2023 10:14:53 -0700
Subject: [PATCH 14/16] intermediate

---
 .../cv/torch/semantic_segmentation.py         |   1 +
 .../model_logger/semantic_segmentation.py     |   4 +-
 docs/cv/coco_deeplab_hooks.ipynb              | 135 ++++++++++++++++--
 3 files changed, 125 insertions(+), 15 deletions(-)

diff --git a/dataquality/integrations/cv/torch/semantic_segmentation.py b/dataquality/integrations/cv/torch/semantic_segmentation.py
index 925b5c671..4cd497c0e 100644
--- a/dataquality/integrations/cv/torch/semantic_segmentation.py
+++ b/dataquality/integrations/cv/torch/semantic_segmentation.py
@@ -322,6 +322,7 @@ def _on_step_end(self) -> None:
             # do not log if we are not in the final inference loop
             if not self.called_finish:
                 return
+            print('logging')
             logger = SemanticSegmentationModelLogger(
                 bucket_name=self.bucket_name,
                 image_paths=image_paths,
diff --git a/dataquality/loggers/model_logger/semantic_segmentation.py b/dataquality/loggers/model_logger/semantic_segmentation.py
index f98adf517..a4df54ae8 100644
--- a/dataquality/loggers/model_logger/semantic_segmentation.py
+++ b/dataquality/loggers/model_logger/semantic_segmentation.py
@@ -231,8 +231,8 @@ def _get_data_dict(self) -> Dict:
         polygon_data = self.get_polygon_data(pred_polygons_batch, gold_polygons_batch)
         n_polygons = polygon_data["image_id"]
         if self.split == Split.inference:
-            polygon_data["inference_name"] = [self.inference_name] * n_polygons
+            polygon_data["inference_name"] = [self.inference_name] * len(n_polygons)
         else:
-            polygon_data["epoch"] = [self.epoch] * n_polygons
+            polygon_data["epoch"] = [self.epoch] * len(n_polygons)
 
         return polygon_data
diff --git a/docs/cv/coco_deeplab_hooks.ipynb b/docs/cv/coco_deeplab_hooks.ipynb
index c51512882..1e7300697 100644
--- a/docs/cv/coco_deeplab_hooks.ipynb
+++ b/docs/cv/coco_deeplab_hooks.ipynb
@@ -2,9 +2,20 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'ds = load_dataset(\\n    \"CVdatasets/CocoSegmentationOnlyVal5000\",\\n    use_auth_token=\"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\"\\n)'"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# !pip install datasets evaluate torch torchvision \n",
     "import os\n",
@@ -29,9 +40,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Found dataset, there are 4030 images and 4030 masks\n"
+     ]
+    }
+   ],
    "source": [
     "# download the data from our public gcs bucket and save it to disk\n",
     "# dataset_path, img_path, mask_path = download_gcs_data()\n",
@@ -65,7 +84,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/"
@@ -74,7 +93,19 @@
     "outputId": "85d91dc9-405e-4f02-a6bf-6a88f9502412",
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Using cache found in /Users/derek/.cache/torch/hub/pytorch_vision_v0.10.0\n",
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.\n",
+      "  warnings.warn(\n",
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=DeepLabV3_ResNet50_Weights.COCO_WITH_VOC_LABELS_V1`. You can also use `weights=DeepLabV3_ResNet50_Weights.DEFAULT` to get the most up-to-date weights.\n",
+      "  warnings.warn(msg)\n"
+     ]
+    }
+   ],
    "source": [
     "\n",
     "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
@@ -88,9 +119,45 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/core/__init__.py:27: GalileoWarning: configure is deprecated, use dq.set_console_url and dq.login\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "📡 https://console.dev.rungalileo.io\n",
+      "🔭 Logging you into Galileo\n",
+      "\n",
+      "🚀 You're logged in to Galileo as galileo@rungalileo.io!\n",
+      "✨ Initializing existing public project 'Derek-Elliott-Proj'\n",
+      "🏃‍♂️ Fetching existing run 'polygon_dep'\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/dataquality/core/init.py:171: GalileoWarning: Run: Derek-Elliott-Proj/polygon_dep already exists! The existing run will get overwritten on call to finish()!\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "🛰 Connected to existing project 'Derek-Elliott-Proj', and existing run 'polygon_dep'.\n"
+     ]
+    }
+   ],
    "source": [
     "try:\n",
     "    import dataquality as dq\n",
@@ -109,7 +176,7 @@
     "import dataquality as dq\n",
     "dq.configure()\n",
     "\n",
-    "dq.init(\"semantic_segmentation\", \"Derek-Elliott-Proj\", 'test-polygon-df')\n",
+    "dq.init(\"semantic_segmentation\", \"Derek-Elliott-Proj\", 'polygon_dep')\n",
     "class_dict = { 'background': 0,\n",
     "                            'airplane': 1,\n",
     "                            'bicycle': 2,\n",
@@ -137,9 +204,43 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2023-05-12 10:06:21.051891: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
+      "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "We assume the dataloaders passed only have transforms that Tensor, Resize,         and Normalize the image and mask\n",
+      "‼ Any cropping or shearing transforms passed will lead to unexpected         results\n",
+      "See docs at https://dq.readthedocs.io/en/latest/ (placeholder) for more info         \n",
+      " \n",
+      "\n",
+      "Found layer classifier in model layers: backbone, classifier\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).\n",
+      "  warnings.warn(\n",
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torch/cuda/amp/grad_scaler.py:120: UserWarning: torch.cuda.amp.GradScaler is enabled, but CUDA is not available.  Disabling.\n",
+      "  warnings.warn(\"torch.cuda.amp.GradScaler is enabled, but CUDA is not available.  Disabling.\")\n",
+      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torch/amp/autocast_mode.py:204: UserWarning: User provided device_type of 'cuda', but CUDA is not available. Disabling\n",
+      "  warnings.warn('User provided device_type of \\'cuda\\', but CUDA is not available. Disabling')\n",
+      " 50%|█████     | 1/2 [00:03<00:03,  3.28s/it]\n"
+     ]
+    }
+   ],
    "source": [
     "from dataquality.integrations.cv.torch.semantic_segmentation import watch\n",
     "watch(\n",
@@ -176,9 +277,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "logging\n"
+     ]
+    }
+   ],
    "source": [
     "dq.finish()"
    ]

From f6ddd41e8579f43e205cd1a5518cdd62c74ff959 Mon Sep 17 00:00:00 2001
From: Derek <dcaustin33@gmail.com>
Date: Fri, 12 May 2023 11:20:14 -0700
Subject: [PATCH 15/16] Final commit

---
 docs/cv/coco_deeplab_hooks.ipynb | 145 ++++++++++++++++++++++++++-----
 1 file changed, 122 insertions(+), 23 deletions(-)

diff --git a/docs/cv/coco_deeplab_hooks.ipynb b/docs/cv/coco_deeplab_hooks.ipynb
index 1e7300697..3a2a278ce 100644
--- a/docs/cv/coco_deeplab_hooks.ipynb
+++ b/docs/cv/coco_deeplab_hooks.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -11,7 +11,7 @@
        "'ds = load_dataset(\\n    \"CVdatasets/CocoSegmentationOnlyVal5000\",\\n    use_auth_token=\"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\"\\n)'"
       ]
      },
-     "execution_count": 1,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -40,7 +40,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -84,7 +84,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 9,
    "metadata": {
     "colab": {
      "base_uri": "https://localhost:8080/"
@@ -119,7 +119,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -204,17 +204,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "2023-05-12 10:06:21.051891: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
-      "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
-     ]
-    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -231,13 +223,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).\n",
-      "  warnings.warn(\n",
-      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torch/cuda/amp/grad_scaler.py:120: UserWarning: torch.cuda.amp.GradScaler is enabled, but CUDA is not available.  Disabling.\n",
-      "  warnings.warn(\"torch.cuda.amp.GradScaler is enabled, but CUDA is not available.  Disabling.\")\n",
-      "/Users/derek/Desktop/dataquality/.venv/lib/python3.9/site-packages/torch/amp/autocast_mode.py:204: UserWarning: User provided device_type of 'cuda', but CUDA is not available. Disabling\n",
-      "  warnings.warn('User provided device_type of \\'cuda\\', but CUDA is not available. Disabling')\n",
-      " 50%|█████     | 1/2 [00:03<00:03,  3.28s/it]\n"
+      " 50%|█████     | 1/2 [00:02<00:02,  2.93s/it]\n"
      ]
     }
    ],
@@ -277,15 +263,128 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "logging\n"
+      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.22s =  0.0m =  0.0h\n",
+      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.14s =  0.0m =  0.0h\n",
+      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.19s =  0.0m =  0.0h\n",
+      "Logging 2 samples [########################################] 100.00% elapsed time  :     0.14s =  0.0m =  0.0h    \n",
+      " ☁️ Uploading Data\n",
+      "CuML libraries not found, running standard process. For faster Galileo processing, consider installing\n",
+      "`pip install 'dataquality[cuda]' --extra-index-url=https://pypi.nvidia.com/`\n"
      ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "5a4f12b6d15045ccb5aeed25e33d9c88",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Uploading data to Galileo:   0%|          | 0.00/25.8k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "00eb14bd666848f19abafccd97b4d13f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Processing data for upload:   0%|          | 0/2 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "71c52ffbb2cc4f35ad464b98c1e115b0",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Uploading data to Galileo:   0%|          | 0.00/20.1k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "828617f3273f4ee89ceda3b654b7bfe9",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Uploading data to Galileo:   0%|          | 0.00/25.8k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a6551f8b6def4d098cadeaa6542987f7",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Processing data for upload:   0%|          | 0/2 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "b3b793fea5ca4ed6b538b22025c689cc",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Uploading data to Galileo:   0%|          | 0.00/20.1k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Job default successfully submitted. Results will be available soon at https://console.dev.rungalileo.io/insights?projectId=7e78e642-cc40-4f5c-8f45-b2cadd8d674a&runId=4bc175ca-60c3-4cf4-b6ef-91013db1d7fa&split=training&metric=f1&depHigh=1&depLow=0&taskType=6\n",
+      "Waiting for job (you can safely close this window)...\n",
+      "\tUploading processed validation data\n",
+      "Done! Job finished with status completed\n",
+      "Click here to see your run! https://console.dev.rungalileo.io/insights?projectId=7e78e642-cc40-4f5c-8f45-b2cadd8d674a&runId=4bc175ca-60c3-4cf4-b6ef-91013db1d7fa&split=training&metric=f1&depHigh=1&depLow=0&taskType=6\n",
+      "🧹 Cleaning up\n",
+      "🧹 Cleaning up\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "'https://console.dev.rungalileo.io/insights?projectId=7e78e642-cc40-4f5c-8f45-b2cadd8d674a&runId=4bc175ca-60c3-4cf4-b6ef-91013db1d7fa&split=training&metric=f1&depHigh=1&depLow=0&taskType=6'"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [

From 6bfb3fef60a012d828ff733cd30449021ca6cc27 Mon Sep 17 00:00:00 2001
From: Derek <dcaustin33@gmail.com>
Date: Fri, 12 May 2023 11:57:06 -0700
Subject: [PATCH 16/16] Linting

---
 dataquality/integrations/cv/torch/semantic_segmentation.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/dataquality/integrations/cv/torch/semantic_segmentation.py b/dataquality/integrations/cv/torch/semantic_segmentation.py
index 4cd497c0e..70b705097 100644
--- a/dataquality/integrations/cv/torch/semantic_segmentation.py
+++ b/dataquality/integrations/cv/torch/semantic_segmentation.py
@@ -322,7 +322,7 @@ def _on_step_end(self) -> None:
             # do not log if we are not in the final inference loop
             if not self.called_finish:
                 return
-            print('logging')
+            print("logging")
             logger = SemanticSegmentationModelLogger(
                 bucket_name=self.bucket_name,
                 image_paths=image_paths,