
"""simple docstring"""




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,
)


_A			:       Union[str, Any]   		=       '\\n    Text data.\n    Second line of data.'

_A			:       Optional[int]   		=       'file'


@pytest.fixture(scope="session"  )
def   __magic_name__	(      __snake_case				:       Dict  ) ->				List[Any]:
       lowercase    :				Optional[int]       		=							tmp_path_factory.mktemp("data"  ) / (FILE_PATH + '.zstd')
       lowercase    :				Optional[int]       		=							bytes(_SCREAMING_SNAKE_CASE     , "utf-8"  )
       with zstd.open(_SCREAMING_SNAKE_CASE     , "wb"  ) as f:
              f.write(_SCREAMING_SNAKE_CASE  )
       return path


@pytest.fixture
def   __magic_name__	(      __snake_case				:       int  ) ->				Tuple:
       with open(os.path.join(tmpfs.local_root_dir     , _SCREAMING_SNAKE_CASE  )     , "w"  ) as f:
              f.write(_SCREAMING_SNAKE_CASE  )
       return FILE_PATH


@pytest.mark.parametrize("compression_format"     , ["gzip", "xz", "zstd"]  )
def   __magic_name__	(      __snake_case				:       int     , __snake_case				:       Optional[int]     , __snake_case				:       List[Any]     , __snake_case				:       str     , __snake_case				:       Optional[int]     , __snake_case				:       Optional[Any]  ) ->				Optional[int]:
       lowercase    :				Optional[int]       		=							{'gzip': gz_file, 'xz': xz_file, 'zstd': zstd_path}
       lowercase    :				Optional[int]       		=							input_paths[compression_format]
       lowercase    :				Any       		=							tmp_path / 'cache'
       lowercase    :				int       		=							DownloadConfig(cache_dir=_SCREAMING_SNAKE_CASE     , extract_compressed_file=_SCREAMING_SNAKE_CASE  )
       lowercase    :				str       		=							cached_path(_SCREAMING_SNAKE_CASE     , download_config=_SCREAMING_SNAKE_CASE  )
       with open(_SCREAMING_SNAKE_CASE  ) as f:
              lowercase    :				int       		=							f.read()
       with open(_SCREAMING_SNAKE_CASE  ) as f:
              lowercase    :				Union[str, Any]       		=							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   __magic_name__	(      __snake_case				:       int     , __snake_case				:       Union[str, Any]     , __snake_case				:       int     , __snake_case				:       str     , __snake_case				:       List[Any]  ) ->				int:
       lowercase    :				Optional[int]       		=							'custom_cache'
       lowercase    :				str       		=							'custom_extracted_dir'
       lowercase    :				Optional[int]       		=							tmp_path / 'custom_extracted_path'
       if default_extracted:
              lowercase    :				str       		=							('downloads' if default_cache_dir else custom_cache_dir, 'extracted')
       else:
              monkeypatch.setattr("datasets.config.EXTRACTED_DATASETS_DIR"     , _SCREAMING_SNAKE_CASE  )
              monkeypatch.setattr("datasets.config.EXTRACTED_DATASETS_PATH"     , str(_SCREAMING_SNAKE_CASE  )  )
              lowercase    :				Union[str, Any]       		=							custom_extracted_path.parts[-2:] if default_cache_dir else (custom_cache_dir, custom_extracted_dir)

       lowercase    :				Optional[int]       		=							xz_file
       lowercase    :				Dict       		=							(
           DownloadConfig(extract_compressed_file=_SCREAMING_SNAKE_CASE  )
           if default_cache_dir
           else DownloadConfig(cache_dir=tmp_path / custom_cache_dir     , extract_compressed_file=_SCREAMING_SNAKE_CASE  )
       )
       lowercase    :				int       		=							cached_path(_SCREAMING_SNAKE_CASE     , download_config=_SCREAMING_SNAKE_CASE  )
       assert Path(_SCREAMING_SNAKE_CASE  ).parent.parts[-2:] == expected


def   __magic_name__	(      __snake_case				:       List[str]  ) ->				Optional[int]:
       # absolute path
       lowercase    :				List[str]       		=							str(Path(_SCREAMING_SNAKE_CASE  ).resolve()  )
       assert cached_path(_SCREAMING_SNAKE_CASE  ) == text_file
       # relative path
       lowercase    :				List[Any]       		=							str(Path(_SCREAMING_SNAKE_CASE  ).resolve().relative_to(Path(os.getcwd()  )  )  )
       assert cached_path(_SCREAMING_SNAKE_CASE  ) == text_file


def   __magic_name__	(      __snake_case				:       Optional[int]  ) ->				Any:
       # absolute path
       lowercase    :				Any       		=							str(tmp_path.resolve() / "__missing_file__.txt"  )
       with pytest.raises(_SCREAMING_SNAKE_CASE  ):
              cached_path(_SCREAMING_SNAKE_CASE  )
       # relative path
       lowercase    :				Tuple       		=							'./__missing_file__.txt'
       with pytest.raises(_SCREAMING_SNAKE_CASE  ):
              cached_path(_SCREAMING_SNAKE_CASE  )


def   __magic_name__	(      __snake_case				:       List[Any]  ) ->				int:
       lowercase    :				Tuple       		=							get_from_cache(f"""tmp://{tmpfs_file}"""  )
       with open(_SCREAMING_SNAKE_CASE  ) as f:
              lowercase    :				str       		=							f.read()
       assert output_file_content == FILE_CONTENT


@patch("datasets.config.HF_DATASETS_OFFLINE"     , _SCREAMING_SNAKE_CASE  )
def   __magic_name__	(      ) ->				Optional[int]:
       with pytest.raises(_SCREAMING_SNAKE_CASE  ):
              cached_path("https://huggingface.co"  )


@patch("datasets.config.HF_DATASETS_OFFLINE"     , _SCREAMING_SNAKE_CASE  )
def   __magic_name__	(      __snake_case				:       Any  ) ->				int:
       lowercase    :				Tuple       		=							tmp_path_factory.mktemp("data"  ) / 'file.html'
       with pytest.raises(_SCREAMING_SNAKE_CASE  ):
              http_get("https://huggingface.co"     , temp_file=_SCREAMING_SNAKE_CASE  )
       with pytest.raises(_SCREAMING_SNAKE_CASE  ):
              http_head("https://huggingface.co"  )


@patch("datasets.config.HF_DATASETS_OFFLINE"     , _SCREAMING_SNAKE_CASE  )
def   __magic_name__	(      __snake_case				:       Optional[Any]  ) ->				int:
       lowercase    :				Optional[Any]       		=							tmp_path_factory.mktemp("data"  ) / 'file.html'
       with pytest.raises(_SCREAMING_SNAKE_CASE  ):
              ftp_get("ftp://huggingface.co"     , temp_file=_SCREAMING_SNAKE_CASE  )
       with pytest.raises(_SCREAMING_SNAKE_CASE  ):
              ftp_head("ftp://huggingface.co"  )


@patch("datasets.config.HF_DATASETS_OFFLINE"     , _SCREAMING_SNAKE_CASE  )
def   __magic_name__	(      __snake_case				:       Dict  ) ->				Optional[int]:
       lowercase    :				Union[str, Any]       		=							tmp_path_factory.mktemp("data"  ) / 'file.html'
       with pytest.raises(_SCREAMING_SNAKE_CASE  ):
              fsspec_get("s3://huggingface.co"     , temp_file=_SCREAMING_SNAKE_CASE  )
       with pytest.raises(_SCREAMING_SNAKE_CASE  ):
              fsspec_head("s3://huggingface.co"  )






'''simple docstring'''



import os
import sys

__lowercase	:						List[Any]       =	os.path.join(os.path.dirname(__file__), 'src')
sys.path.append(SRC_DIR)


from transformers import (
    AutoConfig,
    AutoModel,
    AutoModelForCausalLM,
    AutoModelForMaskedLM,
    AutoModelForQuestionAnswering,
    AutoModelForSequenceClassification,
    AutoTokenizer,
    add_start_docstrings,
)


__lowercase	:						int       =	[
    'torch',
    'numpy',
    'tokenizers',
    'filelock',
    'requests',
    'tqdm',
    'regex',
    'sentencepiece',
    'sacremoses',
    'importlib_metadata',
    'huggingface_hub',
]






@add_start_docstrings(AutoConfig.__doc__   )
def   lowerCamelCase							(*_SCREAMING_SNAKE_CASE      :   List[str]						,      **_SCREAMING_SNAKE_CASE      :   List[Any]   ):
					return AutoConfig.from_pretrained(*_SCREAMING_SNAKE_CASE						,      **_SCREAMING_SNAKE_CASE   )






@add_start_docstrings(AutoTokenizer.__doc__   )
def   lowerCamelCase							(*_SCREAMING_SNAKE_CASE      :   str						,      **_SCREAMING_SNAKE_CASE      :   Any   ):
					return AutoTokenizer.from_pretrained(*_SCREAMING_SNAKE_CASE						,      **_SCREAMING_SNAKE_CASE   )






@add_start_docstrings(AutoModel.__doc__   )
def   lowerCamelCase							(*_SCREAMING_SNAKE_CASE      :   int						,      **_SCREAMING_SNAKE_CASE      :   Union[str, Any]   ):
					return AutoModel.from_pretrained(*_SCREAMING_SNAKE_CASE						,      **_SCREAMING_SNAKE_CASE   )






@add_start_docstrings(AutoModelForCausalLM.__doc__   )
def   lowerCamelCase							(*_SCREAMING_SNAKE_CASE      :   List[Any]						,      **_SCREAMING_SNAKE_CASE      :   Optional[int]   ):
					return AutoModelForCausalLM.from_pretrained(*_SCREAMING_SNAKE_CASE						,      **_SCREAMING_SNAKE_CASE   )






@add_start_docstrings(AutoModelForMaskedLM.__doc__   )
def   lowerCamelCase							(*_SCREAMING_SNAKE_CASE      :   Union[str, Any]						,      **_SCREAMING_SNAKE_CASE      :   List[Any]   ):
					return AutoModelForMaskedLM.from_pretrained(*_SCREAMING_SNAKE_CASE						,      **_SCREAMING_SNAKE_CASE   )






@add_start_docstrings(AutoModelForSequenceClassification.__doc__   )
def   lowerCamelCase							(*_SCREAMING_SNAKE_CASE      :   Optional[Any]						,      **_SCREAMING_SNAKE_CASE      :   Any   ):
					return AutoModelForSequenceClassification.from_pretrained(*_SCREAMING_SNAKE_CASE						,      **_SCREAMING_SNAKE_CASE   )






@add_start_docstrings(AutoModelForQuestionAnswering.__doc__   )
def   lowerCamelCase							(*_SCREAMING_SNAKE_CASE      :   Any						,      **_SCREAMING_SNAKE_CASE      :   List[str]   ):
					return AutoModelForQuestionAnswering.from_pretrained(*_SCREAMING_SNAKE_CASE						,      **_SCREAMING_SNAKE_CASE   )



