Merge pull request #47 from nodefluxio/refactor-vortex-runtime

Refactor vortex runtime and namespace package

CHANGELOG.md

@@ -54,8 +54,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   - change `scheduler` to `lr_scheduler` in `config.trainer`.
   - change field `validation` to `validator` and move it from `config.trainer` to main `config`.
 - Refactor `DatasetWrapper` into `BasicDatasetWrapper` and `DefaultDatasetWrapper`
+- Change output type of BaseRuntime `__call__` method to list of orderedDict
 - It is now possible to override image auto padding in dataset object by adding and set `self.disable_image_auto_pad = True` attribute on the `collate_fn` object provided by the `model_components`
-
+- Refactor package into 2 namespace packages : `vortex.runtime` and `vortex.development`. In which case `vortex.development` is depend on `vortex.runtime`, but `vortex.runtime` can be installed as a standalone package for minimal requirement inferencing library
 
 ## v0.1.0
 

dockerfiles/vortex.dockerfile

@@ -0,0 +1,19 @@
+FROM nvidia/cuda:10.0-cudnn7-devel-ubuntu18.04
+
+ARG DEBIAN_FRONTEND=noninteractive
+
+RUN apt update && apt install -y git
+
+WORKDIR /app/vortex
+
+COPY ./src /app/vortex/src
+
+## install system requirements
+RUN apt update && xargs apt install -y < src/development/requirements.sys
+
+## install python requirements
+RUN pip3 install -U pip setuptools
+
+RUN pip3 install 'src/runtime[all]' 'src/development[optuna_vis]'
+
+WORKDIR /app

docs/api/vortex.core.factory.md → docs/api/vortex.development.core.factory.md

@@ -1,4 +1,4 @@
-# vortex.core.factory
+# vortex.development.core.factory
 
 ---
 
@@ -60,7 +60,7 @@ The dictionary returned will contain several keys :
 - `collate_fn` : if provided, module to be embedded to dataloader's `collate_fn` function to modify dataset label's format into desirable format that can be accepted by `loss` components
 
 ```python
-from vortex.core.factory import create_model
+from vortex.development.core.factory import create_model
 from easydict import EasyDict
 
 model_config = EasyDict({
@@ -91,91 +91,6 @@ print(model_components.keys())
 
 
 
----
-
----
-
-### create_runtime_model
-
-
-
-Functions to create runtime model, currently the usage of this created object must be used together
-
-
-
-```python
-def create_runtime_model(
-      model_path : typing.Union[str, pathlib.Path],
-      runtime : str,
-      output_name = ['output'],
-      *args,
-      **kwargs,
-)
-```
-
-
-
-**Arguments**:
-
-- `model_path` _Union[str, Path]_ - Path to Intermediate Representation (IR) model file
-- `runtime` _str_ - Backend runtime to be used, e.g. : 'cpu' or 'cuda' (Depends on available runtime options)
-- `output_name` _list, optional_ - Runtime output(s) variable name. Defaults to ["output"].
-
-
-**Returns**:
-
-- `Type[BaseRuntime]` - Runtime model objects based on IR file model's type and selected `runtime`
-
-
-**Raises**:
-
-- `RuntimeError` - Raises if selected `runtime` is not available
-
-
-**Examples**:
-
-
-
-```python
-from vortex.core.factory import create_runtime_model
-import numpy as np
-import cv2
-
-model_path = 'tests/output_test/test_classification_pipelines/test_classification_pipelines.onnx'
-
-runtime_model = create_runtime_model(
-    model_path = model_path,
-    runtime = 'cpu'
-)
-
-print(type(runtime_model))
-
-## Get model's input specifications and additional inferencing parameters
-
-print(runtime_model.input_specs)
-
-# Inferencing example
-
-input_shape = runtime_model.input_specs['input']['shape']
-batch_imgs = np.array([cv2.resize(cv2.imread('tests/images/cat.jpg'),(input_shape[2],input_shape[1]))])
-
-## Make sure the shape of input data is equal to input specifications
-assert batch_imgs.shape == tuple(input_shape)
-
-from vortex.core.pipelines import IRPredictionPipeline
-
-## Additional parameters can be inspected from input_specs,
-## E.g. `score_threshold` or `iou_threshold` for object detection
-additional_input_parameters = {}
-
-prediction_results = IRPredictionPipeline._runtime_predict(model=runtime_model,
-                                                        image=batch_imgs,
-                                                        **additional_input_parameters)
-print(prediction_results)
-```
-
-
-
 ---
 
 ---
@@ -225,7 +140,7 @@ def create_dataloader(
 
 
 ```python
-from vortex.core.factory import create_dataloader
+from vortex.development.core.factory import create_dataloader
 from easydict import EasyDict
 
 dataloader_config = EasyDict({

docs/api/vortex.core.pipelines.md → docs/api/vortex.development.core.pipelines.md

@@ -1,4 +1,4 @@
-# vortex.core.pipelines
+# vortex.development.core.pipelines
 
 ---
 
@@ -42,8 +42,8 @@ def __init__(
 
 
 ```python
-from vortex.utils.parser import load_config
-from vortex.core.pipelines import GraphExportPipeline
+from vortex.development.utils.parser import load_config
+from vortex.development.core.pipelines import GraphExportPipeline
 
 # Parse config
 config = load_config('experiments/config/example.yml')
@@ -131,8 +131,8 @@ def __init__(
 
 
 ```python
-from vortex.core.pipelines import HypOptPipeline
-from vortex.utils.parser.loader import Loader
+from vortex.development.core.pipelines import HypOptPipeline
+from vortex.development.utils.parser.loader import Loader
 import yaml
 
 # Parse config
@@ -224,8 +224,8 @@ def __init__(
 
 
 ```python
-from vortex.core.pipelines import PytorchPredictionPipeline
-from vortex.utils.parser import load_config
+from vortex.development.core.pipelines import PytorchPredictionPipeline
+from vortex.development.utils.parser import load_config
 
 # Parse config
 config_path = 'experiments/config/example.yml'
@@ -368,8 +368,8 @@ def __init__(
 
 
 ```python
-from vortex.core.pipelines import IRPredictionPipeline
-from vortex.utils.parser import load_config
+from vortex.development.core.pipelines import IRPredictionPipeline
+from vortex.development.utils.parser import load_config
 
 # Parse config
 model_file = 'experiments/outputs/example/example.pt' # Model file with extension '.onnx' or '.pt'
@@ -522,8 +522,8 @@ Defaults to False.
 
 
 ```python
-from vortex.utils.parser import load_config
-from vortex.core.pipelines import TrainingPipeline
+from vortex.development.utils.parser import load_config
+from vortex.development.core.pipelines import TrainingPipeline
 
 # Parse config
 config_path = 'experiments/config/example.yml'
@@ -615,8 +615,8 @@ def __init__(
 
 
 ```python
-from vortex.utils.parser import load_config
-from vortex.core.pipelines import PytorchValidationPipeline
+from vortex.development.utils.parser import load_config
+from vortex.development.core.pipelines import PytorchValidationPipeline
 
 # Parse config
 config_path = 'experiments/config/example.yml'
@@ -732,8 +732,8 @@ def __init__(
 
 
 ```python
-from vortex.utils.parser import load_config
-from vortex.core.pipelines import IRValidationPipeline
+from vortex.development.utils.parser import load_config
+from vortex.development.core.pipelines import IRValidationPipeline
 
 # Parse config
 config_path = 'experiments/config/example.yml'

docs/api/vortex.runtime.md

@@ -0,0 +1,135 @@
+# vortex.runtime
+
+---
+
+---
+
+
+
+## Functions
+
+---
+
+---
+
+### create_runtime_model
+
+
+
+Functions to create runtime model
+
+
+
+```python
+def create_runtime_model(
+      model_path : typing.Union[str, pathlib.Path],
+      runtime : str,
+      output_name = ['output'],
+      *args,
+      **kwargs,
+)
+```
+
+
+
+**Arguments**:
+
+- `model_path` _Union[str, Path]_ - Path to Intermediate Representation (IR) model file
+- `runtime` _str_ - Backend runtime to be used, e.g. : 'cpu' or 'cuda' (Depends on available runtime options)
+- `output_name` _list, optional_ - Runtime output(s) variable name. Defaults to ["output"].
+
+
+**Returns**:
+
+- `Type[BaseRuntime]` - Runtime model objects based on IR file model's type and selected `runtime`
+
+
+**Raises**:
+
+- `RuntimeError` - Raises if selected `runtime` is not available
+
+
+**Examples**:
+
+
+
+```python
+from vortex.runtime import create_runtime_model
+import numpy as np
+import cv2
+
+model_path = 'tests/output_test/test_classification_pipelines/test_classification_pipelines.onnx'
+
+runtime_model = create_runtime_model(
+    model_path = model_path,
+    runtime = 'cpu'
+)
+
+print(type(runtime_model))
+
+## Get model's input specifications and additional inferencing parameters
+
+print(runtime_model.input_specs)
+
+# Inferencing example
+
+input_shape = runtime_model.input_specs['input']['shape']
+batch_imgs = np.array([cv2.resize(cv2.imread('tests/images/cat.jpg'),(input_shape[2],input_shape[1]))])
+
+## Make sure the shape of input data is equal to input specifications
+assert batch_imgs.shape == tuple(input_shape)
+
+## Additional parameters can be inspected from input_specs,
+## E.g. `score_threshold` or `iou_threshold` for object detection
+additional_input_parameters = {}
+
+## Inference is done by utilizing __call__ method
+prediction_results = runtime_model(batch_imgs,
+                                    **additional_input_parameters)
+
+print(prediction_results)
+```
+
+
+
+---
+
+---
+
+### check_available_runtime
+
+
+
+Function to check current environment's available runtime
+
+
+
+```python
+def check_available_runtime(
+)
+```
+
+
+
+**Returns**:
+
+- `dict` - Dictionary containing status of available runtime
+
+
+**Examples**:
+
+
+
+```python
+from vortex.runtime import check_available_runtime
+
+available_runtime = check_available_runtime()
+print(available_runtime)
+```
+
+
+
+---
+
+
+