Spaces:
Paused
Paused
| # coding=utf-8 | |
| # Copyright 2023 The HuggingFace Inc. team. | |
| # | |
| # 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. | |
| """ | |
| Utility that checks the list of models in the tips in the task-specific pages of the doc is up to date and potentially | |
| fixes it. | |
| Use from the root of the repo with: | |
| ```bash | |
| python utils/check_task_guides.py | |
| ``` | |
| for a check that will error in case of inconsistencies (used by `make repo-consistency`). | |
| To auto-fix issues run: | |
| ```bash | |
| python utils/check_task_guides.py --fix_and_overwrite | |
| ``` | |
| which is used by `make fix-copies`. | |
| """ | |
| import argparse | |
| import os | |
| from transformers.utils import direct_transformers_import | |
| # All paths are set with the intent you should run this script from the root of the repo with the command | |
| # python utils/check_task_guides.py | |
| TRANSFORMERS_PATH = "src/transformers" | |
| PATH_TO_TASK_GUIDES = "docs/source/en/tasks" | |
| def _find_text_in_file(filename: str, start_prompt: str, end_prompt: str) -> str: | |
| """ | |
| Find the text in filename between two prompts. | |
| Args: | |
| filename (`str`): The file to search into. | |
| start_prompt (`str`): A string to look for at the start of the content searched. | |
| end_prompt (`str`): A string that will mark the end of the content to look for. | |
| Returns: | |
| `str`: The content between the prompts. | |
| """ | |
| with open(filename, "r", encoding="utf-8", newline="\n") as f: | |
| lines = f.readlines() | |
| # Find the start prompt. | |
| start_index = 0 | |
| while not lines[start_index].startswith(start_prompt): | |
| start_index += 1 | |
| start_index += 1 | |
| # Now go until the end prompt. | |
| end_index = start_index | |
| while not lines[end_index].startswith(end_prompt): | |
| end_index += 1 | |
| end_index -= 1 | |
| while len(lines[start_index]) <= 1: | |
| start_index += 1 | |
| while len(lines[end_index]) <= 1: | |
| end_index -= 1 | |
| end_index += 1 | |
| return "".join(lines[start_index:end_index]), start_index, end_index, lines | |
| # This is to make sure the transformers module imported is the one in the repo. | |
| transformers_module = direct_transformers_import(TRANSFORMERS_PATH) | |
| # Map between a task guide and the corresponding auto class. | |
| TASK_GUIDE_TO_MODELS = { | |
| "asr.md": transformers_module.models.auto.modeling_auto.MODEL_FOR_CTC_MAPPING_NAMES, | |
| "audio_classification.md": transformers_module.models.auto.modeling_auto.MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES, | |
| "language_modeling.md": transformers_module.models.auto.modeling_auto.MODEL_FOR_CAUSAL_LM_MAPPING_NAMES, | |
| "image_classification.md": transformers_module.models.auto.modeling_auto.MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES, | |
| "masked_language_modeling.md": transformers_module.models.auto.modeling_auto.MODEL_FOR_MASKED_LM_MAPPING_NAMES, | |
| "multiple_choice.md": transformers_module.models.auto.modeling_auto.MODEL_FOR_MULTIPLE_CHOICE_MAPPING_NAMES, | |
| "object_detection.md": transformers_module.models.auto.modeling_auto.MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES, | |
| "question_answering.md": transformers_module.models.auto.modeling_auto.MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES, | |
| "semantic_segmentation.md": transformers_module.models.auto.modeling_auto.MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES, | |
| "sequence_classification.md": transformers_module.models.auto.modeling_auto.MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES, | |
| "summarization.md": transformers_module.models.auto.modeling_auto.MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES, | |
| "token_classification.md": transformers_module.models.auto.modeling_auto.MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES, | |
| "translation.md": transformers_module.models.auto.modeling_auto.MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES, | |
| "video_classification.md": transformers_module.models.auto.modeling_auto.MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING_NAMES, | |
| "document_question_answering.md": transformers_module.models.auto.modeling_auto.MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING_NAMES, | |
| "monocular_depth_estimation.md": transformers_module.models.auto.modeling_auto.MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES, | |
| } | |
| # This list contains model types used in some task guides that are not in `CONFIG_MAPPING_NAMES` (therefore not in any | |
| # `MODEL_MAPPING_NAMES` or any `MODEL_FOR_XXX_MAPPING_NAMES`). | |
| SPECIAL_TASK_GUIDE_TO_MODEL_TYPES = { | |
| "summarization.md": ("nllb",), | |
| "translation.md": ("nllb",), | |
| } | |
| def get_model_list_for_task(task_guide: str) -> str: | |
| """ | |
| Return the list of models supporting a given task. | |
| Args: | |
| task_guide (`str`): The name of the task guide to check. | |
| Returns: | |
| `str`: The list of models supporting this task, as links to their respective doc pages separated by commas. | |
| """ | |
| model_maping_names = TASK_GUIDE_TO_MODELS[task_guide] | |
| special_model_types = SPECIAL_TASK_GUIDE_TO_MODEL_TYPES.get(task_guide, set()) | |
| model_names = { | |
| code: name | |
| for code, name in transformers_module.MODEL_NAMES_MAPPING.items() | |
| if (code in model_maping_names or code in special_model_types) | |
| } | |
| return ", ".join([f"[{name}](../model_doc/{code})" for code, name in model_names.items()]) + "\n" | |
| def check_model_list_for_task(task_guide: str, overwrite: bool = False): | |
| """ | |
| For a given task guide, checks the model list in the generated tip for consistency with the state of the lib and | |
| updates it if needed. | |
| Args: | |
| task_guide (`str`): | |
| The name of the task guide to check. | |
| overwrite (`bool`, *optional*, defaults to `False`): | |
| Whether or not to overwrite the table when it's not up to date. | |
| """ | |
| current_list, start_index, end_index, lines = _find_text_in_file( | |
| filename=os.path.join(PATH_TO_TASK_GUIDES, task_guide), | |
| start_prompt="<!--This tip is automatically generated by `make fix-copies`, do not fill manually!-->", | |
| end_prompt="<!--End of the generated tip-->", | |
| ) | |
| new_list = get_model_list_for_task(task_guide) | |
| if current_list != new_list: | |
| if overwrite: | |
| with open(os.path.join(PATH_TO_TASK_GUIDES, task_guide), "w", encoding="utf-8", newline="\n") as f: | |
| f.writelines(lines[:start_index] + [new_list] + lines[end_index:]) | |
| else: | |
| raise ValueError( | |
| f"The list of models that can be used in the {task_guide} guide needs an update. Run `make fix-copies`" | |
| " to fix this." | |
| ) | |
| if __name__ == "__main__": | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.") | |
| args = parser.parse_args() | |
| for task_guide in TASK_GUIDE_TO_MODELS.keys(): | |
| check_model_list_for_task(task_guide, args.fix_and_overwrite) | |