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Configuration error
| #!/usr/bin/env python | |
| # -*- coding: utf-8 -*- | |
| # | |
| # Copyright (c) 2023 Intel Corporation | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| # | |
| # SPDX-License-Identifier: Apache-2.0 | |
| # | |
| from enum import Enum, auto | |
| class DatasetType(Enum): | |
| TENSORFLOW_DATASETS = auto() | |
| TORCHVISION = auto() | |
| HUGGING_FACE = auto() | |
| GENERIC = auto() | |
| def __str__(self): | |
| return self.name.lower() | |
| def from_str(dataset_str): | |
| if dataset_str is None: | |
| return DatasetType.GENERIC | |
| dataset_str = dataset_str.lower() | |
| if dataset_str in ["tfds", "tensorflow", "tensorflow_datasets", "tensorflow datasets", "tensorflow_dataset", | |
| "tensorflow dataset"]: | |
| return DatasetType.TENSORFLOW_DATASETS | |
| elif dataset_str in ["torchvision"]: | |
| return DatasetType.TORCHVISION | |
| elif dataset_str in ["huggingface", "hugging_face", "hugging face"]: | |
| return DatasetType.HUGGING_FACE | |
| elif dataset_str in ["generic"]: | |
| return DatasetType.GENERIC | |
| else: | |
| options = [e.name for e in DatasetType] | |
| raise ValueError("Unsupported dataset type: {} (Select from: {})".format( | |
| dataset_str, options)) | |
| class ModelType(Enum): | |
| TF_HUB = auto() | |
| TORCHVISION = auto() | |
| PYTORCH_HUB = auto() | |
| HUGGING_FACE = auto() | |
| KERAS_APPLICATIONS = auto() | |
| TF_BERT_HUGGINGFACE = auto() | |
| GENERIC = auto() | |
| def __str__(self): | |
| return self.name.lower() | |
| def from_str(model_str): | |
| if model_str is None: | |
| return ModelType.GENERIC | |
| model_str = model_str.lower() | |
| if model_str in ["tfhub", "tf_hub", "tf hub", "tensorflow_hub", "tensorflow hub"]: | |
| return ModelType.TF_HUB | |
| elif model_str in ["torchvision"]: | |
| return ModelType.TORCHVISION | |
| elif model_str in ["pytorch_hub", "pyt_hub", "torch_hub", "torch hub", "pytorch hub"]: | |
| return ModelType.PYTORCH_HUB | |
| elif model_str in ["huggingface", "hugging_face", "hugging face"]: | |
| return ModelType.HUGGING_FACE | |
| elif model_str in ["keras", "keras_applications", "keras applications"]: | |
| return ModelType.KERAS_APPLICATIONS | |
| elif model_str in ["tf_bert_huggingface", "tf bert huggingface", "tf_bert_hugging_face", | |
| "tf bert hugging face"]: | |
| return ModelType.TF_BERT_HUGGINGFACE | |
| elif model_str in ["generic"]: | |
| return ModelType.GENERIC | |
| else: | |
| options = [e.name for e in ModelType] | |
| raise ValueError("Unsupported model type: {} (Select from: {})".format(model_str, options)) | |