From 6e30631c35c2549fcf779644314a78621ee04d6a Mon Sep 17 00:00:00 2001 From: Li Wan Date: Tue, 26 Mar 2024 09:51:30 +1100 Subject: [PATCH] Change to NO_MODEL --- src/marqo/s2_inference/models/model_type.py | 2 +- src/marqo/s2_inference/no_model_utils.py | 2 +- src/marqo/s2_inference/s2_inference.py | 31 +++++++++++---------- 3 files changed, 18 insertions(+), 17 deletions(-) diff --git a/src/marqo/s2_inference/models/model_type.py b/src/marqo/s2_inference/models/model_type.py index 94deb64a0..96117e1a1 100644 --- a/src/marqo/s2_inference/models/model_type.py +++ b/src/marqo/s2_inference/models/model_type.py @@ -13,4 +13,4 @@ class ModelType(str, Enum): FP16_CLIP = "fp16_clip" Random = 'random' HF_MODEL = 'hf' - No_Model = "no_model" \ No newline at end of file + NO_MODEL= "no_model" \ No newline at end of file diff --git a/src/marqo/s2_inference/no_model_utils.py b/src/marqo/s2_inference/no_model_utils.py index b7eef56e9..741bf861e 100644 --- a/src/marqo/s2_inference/no_model_utils.py +++ b/src/marqo/s2_inference/no_model_utils.py @@ -11,6 +11,6 @@ def load(self, *args, **kwargs) -> None: pass def encode(self, *args, **kwargs) -> None: - raise VectoriseError(f"Cannot vectorise anything with '{ModelType.No_Model}'. " + raise VectoriseError(f"Cannot vectorise anything with '{ModelType.NO_MODEL}'. " f"This model is intended for adding documents and searching with custom vectors only. " f"If vectorisation is needed, please use a different model ") \ No newline at end of file diff --git a/src/marqo/s2_inference/s2_inference.py b/src/marqo/s2_inference/s2_inference.py index 84ab2bd0f..176d51f6c 100644 --- a/src/marqo/s2_inference/s2_inference.py +++ b/src/marqo/s2_inference/s2_inference.py @@ -1,27 +1,28 @@ """This is the interface for interacting with S2 Inference The functions defined here would have endpoints, later on. """ +import datetime +import threading + import numpy as np -from marqo.api.exceptions import ModelCacheManagementError, InvalidArgError, ConfigurationError, InternalError +import torch +from PIL import UnidentifiedImageError + +from marqo import marqo_docs +from marqo.api.exceptions import ModelCacheManagementError, ConfigurationError, InternalError +from marqo.s2_inference import constants +from marqo.s2_inference.configs import get_default_normalization, get_default_seq_length from marqo.s2_inference.errors import ( VectoriseError, InvalidModelPropertiesError, ModelLoadError, - UnknownModelError, ModelNotInCacheError, ModelDownloadError, S2InferenceError) -from PIL import UnidentifiedImageError + UnknownModelError, ModelNotInCacheError, ModelDownloadError) +from marqo.s2_inference.logger import get_logger from marqo.s2_inference.model_registry import load_model_properties -from marqo.s2_inference.configs import get_default_normalization, get_default_seq_length +from marqo.s2_inference.models.model_type import ModelType from marqo.s2_inference.types import * -from marqo.s2_inference.logger import get_logger -import torch -import datetime -from marqo.s2_inference import constants -from marqo.tensor_search.enums import AvailableModelsKey from marqo.tensor_search.configs import EnvVars +from marqo.tensor_search.enums import AvailableModelsKey from marqo.tensor_search.models.private_models import ModelAuth -import threading from marqo.tensor_search.utils import read_env_vars_and_defaults, generate_batches -from marqo.tensor_search.configs import EnvVars -from marqo.s2_inference.models.model_type import ModelType -from marqo import marqo_docs logger = get_logger(__name__) @@ -219,7 +220,7 @@ def validate_model_properties(model_name: str, model_properties: dict) -> dict: required_keys = ["name", "dimensions"] elif model_type in (ModelType.HF_MODEL, ): required_keys = ["dimensions"] - elif model_type in (ModelType.No_Model,): + elif model_type in (ModelType.NO_MODEL,): required_keys = ["dimensions"] if not model_name == "no_model": raise InvalidModelPropertiesError(f"To use the 'no_model' feature, you must provide 'model = no_model' " @@ -231,7 +232,7 @@ def validate_model_properties(model_name: str, model_properties: dict) -> dict: else: raise InvalidModelPropertiesError(f"Invalid model type. Please check the model type in model_properties. " f"Supported model types are '{ModelType.SBERT}', '{ModelType.OpenCLIP}', " - f"'{ModelType.CLIP}', '{ModelType.HF_MODEL}', '{ModelType.No_Model}', " + f"'{ModelType.CLIP}', '{ModelType.HF_MODEL}', '{ModelType.NO_MODEL}', " f"'{ModelType.Test}', '{ModelType.Random}', '{ModelType.MultilingualClip}', " f"'{ModelType.FP16_CLIP}', '{ModelType.SBERT_ONNX}', '{ModelType.CLIP_ONNX}' ")