mirror of
https://github.com/huggingface/transformers.git
synced 2025-07-04 21:30:07 +06:00
0f96c26de6
* refactor: Make direct_import util * edit direct import fn * add docstring * make import function specific to transformers only * edit doc string
116 lines
5.3 KiB
Python
116 lines
5.3 KiB
Python
# 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.
|
|
|
|
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, start_prompt, end_prompt):
|
|
"""
|
|
Find the text in `filename` between a line beginning with `start_prompt` and before `end_prompt`, removing empty
|
|
lines.
|
|
"""
|
|
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
|
|
|
|
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)
|
|
|
|
TASK_GUIDE_TO_MODELS = {
|
|
"asr.mdx": transformers_module.models.auto.modeling_auto.MODEL_FOR_CTC_MAPPING_NAMES,
|
|
"audio_classification.mdx": transformers_module.models.auto.modeling_auto.MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES,
|
|
"language_modeling.mdx": transformers_module.models.auto.modeling_auto.MODEL_FOR_CAUSAL_LM_MAPPING_NAMES,
|
|
"image_classification.mdx": transformers_module.models.auto.modeling_auto.MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES,
|
|
"masked_language_modeling.mdx": transformers_module.models.auto.modeling_auto.MODEL_FOR_MASKED_LM_MAPPING_NAMES,
|
|
"multiple_choice.mdx": transformers_module.models.auto.modeling_auto.MODEL_FOR_MULTIPLE_CHOICE_MAPPING_NAMES,
|
|
"object_detection.mdx": transformers_module.models.auto.modeling_auto.MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES,
|
|
"question_answering.mdx": transformers_module.models.auto.modeling_auto.MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES,
|
|
"semantic_segmentation.mdx": transformers_module.models.auto.modeling_auto.MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES,
|
|
"sequence_classification.mdx": transformers_module.models.auto.modeling_auto.MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES,
|
|
"summarization.mdx": transformers_module.models.auto.modeling_auto.MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES,
|
|
"token_classification.mdx": transformers_module.models.auto.modeling_auto.MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES,
|
|
"translation.mdx": transformers_module.models.auto.modeling_auto.MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES,
|
|
"video_classification.mdx": transformers_module.models.auto.modeling_auto.MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING_NAMES,
|
|
"document_question_answering.mdx": transformers_module.models.auto.modeling_auto.MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING_NAMES,
|
|
}
|
|
|
|
|
|
def get_model_list_for_task(task_guide):
|
|
"""
|
|
Return the list of models supporting given task.
|
|
"""
|
|
config_maping_names = TASK_GUIDE_TO_MODELS[task_guide]
|
|
model_names = {
|
|
code: name for code, name in transformers_module.MODEL_NAMES_MAPPING.items() if code in config_maping_names
|
|
}
|
|
return ", ".join([f"[{name}](../model_doc/{code})" for code, name in model_names.items()]) + "\n"
|
|
|
|
|
|
def check_model_list_for_task(task_guide, overwrite=False):
|
|
"""For a given task guide, checks the model list in the generated tip for consistency with the state of the lib and overwrites if needed."""
|
|
|
|
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)
|