



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
__snake_case						:Optional[Any]      		=     '''src/transformers'''
__snake_case						:List[Any]      		=     '''docs/source/en/tasks'''





def      __snake_case	(			_UpperCAmelCase   , _UpperCAmelCase   , _UpperCAmelCase				):
    with open(_UpperCAmelCase   , '''r'''   , encoding='''utf-8'''   , newline='''\n'''				) as f:
        __a						       =				f.readlines()
    # Find the start prompt.
    __a						       =				0
    while not lines[start_index].startswith(_UpperCAmelCase				):
        start_index += 1
    start_index += 1

    __a						       =				start_index
    while not lines[end_index].startswith(_UpperCAmelCase				):
        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.
__snake_case						:Dict      		=     direct_transformers_import(TRANSFORMERS_PATH)

__snake_case						:List[str]      		=     {
    '''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`).
__snake_case						:Optional[int]      		=     {
    '''summarization.md''': ('''nllb''',),
    '''translation.md''': ('''nllb''',),
}





def      __snake_case	(			_UpperCAmelCase				):
    __a						       =				TASK_GUIDE_TO_MODELS[task_guide]
    __a						       =				SPECIAL_TASK_GUIDE_TO_MODEL_TYPES.get(_UpperCAmelCase   , set()				)
    __a						       =				{
        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      __snake_case	(			_UpperCAmelCase   , _UpperCAmelCase=False				):
    __a       ,   __a       ,   __a       ,   __a						       =				_find_text_in_file(
        filename=os.path.join(_UpperCAmelCase   , _UpperCAmelCase				)   , start_prompt='''<!--This tip is automatically generated by `make fix-copies`, do not fill manually!-->'''   , end_prompt='''<!--End of the generated tip-->'''   , )

    __a						       =				get_model_list_for_task(_UpperCAmelCase				)

    if current_list != new_list:
        if overwrite:
            with open(os.path.join(_UpperCAmelCase   , _UpperCAmelCase				)   , '''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__":
 __snake_case						:Optional[Any]      		=     argparse.ArgumentParser()
 parser.add_argument('''--fix_and_overwrite''', action='''store_true''', help='''Whether to fix inconsistencies.''')
 __snake_case						:List[Any]      		=     parser.parse_args()

 for task_guide in TASK_GUIDE_TO_MODELS.keys():
  check_model_list_for_task(task_guide, args.fix_and_overwrite)










import os
from pathlib import Path
from unittest.mock import patch

import pytest
import zstandard as zstd

from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
    OfflineModeIsEnabled,
    cached_path,
    fsspec_get,
    fsspec_head,
    ftp_get,
    ftp_head,
    get_from_cache,
    http_get,
    http_head,
)


__snake_case						:List[str]      		=     '''\
    Text data.
    Second line of data.'''

__snake_case						:Optional[Any]      		=     '''file'''





@pytest.fixture(scope='''session'''				)
def      __snake_case	(			_UpperCAmelCase				):
    __a						       =				tmp_path_factory.mktemp('''data'''				) / (FILE_PATH + '''.zstd''')
    __a						       =				bytes(_UpperCAmelCase   , '''utf-8'''				)
    with zstd.open(_UpperCAmelCase   , '''wb'''				) as f:
        f.write(_UpperCAmelCase				)
    return path





@pytest.fixture
def      __snake_case	(			_UpperCAmelCase				):
    with open(os.path.join(tmpfs.local_root_dir   , _UpperCAmelCase				)   , '''w'''				) as f:
        f.write(_UpperCAmelCase				)
    return FILE_PATH





@pytest.mark.parametrize('''compression_format'''   , ['''gzip''', '''xz''', '''zstd''']				)
def      __snake_case	(			_UpperCAmelCase   , _UpperCAmelCase   , _UpperCAmelCase   , _UpperCAmelCase   , _UpperCAmelCase   , _UpperCAmelCase				):
    __a						       =				{'''gzip''': gz_file, '''xz''': xz_file, '''zstd''': zstd_path}
    __a						       =				input_paths[compression_format]
    __a						       =				tmp_path / '''cache'''
    __a						       =				DownloadConfig(cache_dir=_UpperCAmelCase   , extract_compressed_file=_UpperCAmelCase				)
    __a						       =				cached_path(_UpperCAmelCase   , download_config=_UpperCAmelCase				)
    with open(_UpperCAmelCase				) as f:
        __a						       =				f.read()
    with open(_UpperCAmelCase				) as f:
        __a						       =				f.read()
    assert extracted_file_content == expected_file_content





@pytest.mark.parametrize('''default_extracted'''   , [True, False]				)
@pytest.mark.parametrize('''default_cache_dir'''   , [True, False]				)
def      __snake_case	(			_UpperCAmelCase   , _UpperCAmelCase   , _UpperCAmelCase   , _UpperCAmelCase   , _UpperCAmelCase				):
    __a						       =				'''custom_cache'''
    __a						       =				'''custom_extracted_dir'''
    __a						       =				tmp_path / '''custom_extracted_path'''
    if default_extracted:
        __a						       =				('''downloads''' if default_cache_dir else custom_cache_dir, '''extracted''')
    else:
        monkeypatch.setattr('''datasets.config.EXTRACTED_DATASETS_DIR'''   , _UpperCAmelCase				)
        monkeypatch.setattr('''datasets.config.EXTRACTED_DATASETS_PATH'''   , str(_UpperCAmelCase				)				)
        __a						       =				custom_extracted_path.parts[-2:] if default_cache_dir else (custom_cache_dir, custom_extracted_dir)

    __a						       =				xz_file
    __a						       =				(
        DownloadConfig(extract_compressed_file=_UpperCAmelCase				)
        if default_cache_dir
        else DownloadConfig(cache_dir=tmp_path / custom_cache_dir   , extract_compressed_file=_UpperCAmelCase				)
    )
    __a						       =				cached_path(_UpperCAmelCase   , download_config=_UpperCAmelCase				)
    assert Path(_UpperCAmelCase				).parent.parts[-2:] == expected





def      __snake_case	(			_UpperCAmelCase				):
    # absolute path
    __a						       =				str(Path(_UpperCAmelCase				).resolve()				)
    assert cached_path(_UpperCAmelCase				) == text_file
    # relative path
    __a						       =				str(Path(_UpperCAmelCase				).resolve().relative_to(Path(os.getcwd()				)				)				)
    assert cached_path(_UpperCAmelCase				) == text_file





def      __snake_case	(			_UpperCAmelCase				):
    # absolute path
    __a						       =				str(tmp_path.resolve() / '''__missing_file__.txt'''				)
    with pytest.raises(_UpperCAmelCase				):
        cached_path(_UpperCAmelCase				)
    # relative path
    __a						       =				'''./__missing_file__.txt'''
    with pytest.raises(_UpperCAmelCase				):
        cached_path(_UpperCAmelCase				)





def      __snake_case	(			_UpperCAmelCase				):
    __a						       =				get_from_cache(f'tmp://{tmpfs_file}'				)
    with open(_UpperCAmelCase				) as f:
        __a						       =				f.read()
    assert output_file_content == FILE_CONTENT





@patch('''datasets.config.HF_DATASETS_OFFLINE'''   , _UpperCAmelCase				)
def      __snake_case	(			):
    with pytest.raises(_UpperCAmelCase				):
        cached_path('''https://huggingface.co'''				)





@patch('''datasets.config.HF_DATASETS_OFFLINE'''   , _UpperCAmelCase				)
def      __snake_case	(			_UpperCAmelCase				):
    __a						       =				tmp_path_factory.mktemp('''data'''				) / '''file.html'''
    with pytest.raises(_UpperCAmelCase				):
        http_get('''https://huggingface.co'''   , temp_file=_UpperCAmelCase				)
    with pytest.raises(_UpperCAmelCase				):
        http_head('''https://huggingface.co'''				)





@patch('''datasets.config.HF_DATASETS_OFFLINE'''   , _UpperCAmelCase				)
def      __snake_case	(			_UpperCAmelCase				):
    __a						       =				tmp_path_factory.mktemp('''data'''				) / '''file.html'''
    with pytest.raises(_UpperCAmelCase				):
        ftp_get('''ftp://huggingface.co'''   , temp_file=_UpperCAmelCase				)
    with pytest.raises(_UpperCAmelCase				):
        ftp_head('''ftp://huggingface.co'''				)





@patch('''datasets.config.HF_DATASETS_OFFLINE'''   , _UpperCAmelCase				)
def      __snake_case	(			_UpperCAmelCase				):
    __a						       =				tmp_path_factory.mktemp('''data'''				) / '''file.html'''
    with pytest.raises(_UpperCAmelCase				):
        fsspec_get('''s3://huggingface.co'''   , temp_file=_UpperCAmelCase				)
    with pytest.raises(_UpperCAmelCase				):
        fsspec_head('''s3://huggingface.co'''				)





