

import importlib
import os

import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry

from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem

from .utils import require_lza, require_zstandard
def 						_snake_case(   SCREAMING_SNAKE_CASE__      :     Union[str, Any]				)							->				Optional[int]:





    '''simple docstring'''






    assert "mock" in _fsspec_registry
    assert "bz2" in _fsspec_registry
def 						_snake_case(   )							->				Dict:





    '''simple docstring'''






    assert "mock" not in _fsspec_registry
    assert "bz2" in _fsspec_registry
def 						_snake_case(   )							->				List[Any]:





    '''simple docstring'''






    A__   				=       'mock-s3-bucket'
    A__   				=       f's3://{mock_bucket}'
    A__   				=       extract_path_from_uri(SCREAMING_SNAKE_CASE__				)
    assert dataset_path.startswith('s3://'				) is False

    A__   				=       './local/path'
    A__   				=       extract_path_from_uri(SCREAMING_SNAKE_CASE__				)
    assert dataset_path == new_dataset_path
def 						_snake_case(   SCREAMING_SNAKE_CASE__      :     Tuple				)							->				Optional[Any]:





    '''simple docstring'''






    A__   				=       is_remote_filesystem(SCREAMING_SNAKE_CASE__				)
    assert is_remote is True

    A__   				=       fsspec.filesystem('file'				)

    A__   				=       is_remote_filesystem(SCREAMING_SNAKE_CASE__				)
    assert is_remote is False
@pytest.mark.parametrize('compression_fs_class'   ,      SCREAMING_SNAKE_CASE__				)
def 						_snake_case(   SCREAMING_SNAKE_CASE__      :     str   ,      SCREAMING_SNAKE_CASE__      :     Optional[Any]   ,      SCREAMING_SNAKE_CASE__      :     Optional[Any]   ,      SCREAMING_SNAKE_CASE__      :     Optional[Any]   ,      SCREAMING_SNAKE_CASE__      :     List[str]   ,      SCREAMING_SNAKE_CASE__      :     Dict   ,      SCREAMING_SNAKE_CASE__      :     Tuple				)							->				Optional[Any]:





    '''simple docstring'''






    A__   				=       {'gzip': gz_file, 'xz': xz_file, 'zstd': zstd_file, 'bz2': bza_file, 'lz4': lza_file}
    A__   				=       input_paths[compression_fs_class.protocol]
    if input_path is None:
        A__   				=       f'for \'{compression_fs_class.protocol}\' compression protocol, '
        if compression_fs_class.protocol == "lz4":
            reason += require_lza.kwargs["reason"]
        elif compression_fs_class.protocol == "zstd":
            reason += require_zstandard.kwargs["reason"]
        pytest.skip(SCREAMING_SNAKE_CASE__				)
    A__   				=       fsspec.filesystem(compression_fs_class.protocol   ,      fo=SCREAMING_SNAKE_CASE__				)
    assert isinstance(SCREAMING_SNAKE_CASE__   ,      SCREAMING_SNAKE_CASE__				)
    A__   				=       os.path.basename(SCREAMING_SNAKE_CASE__				)
    A__   				=       expected_filename[: expected_filename.rindex('.'				)]
    assert fs.glob('*'				) == [expected_filename]
    with fs.open(SCREAMING_SNAKE_CASE__   ,      'r'   ,      encoding='utf-8'				) as f, open(SCREAMING_SNAKE_CASE__   ,      encoding='utf-8'				) as expected_file:
        assert f.read() == expected_file.read()
@pytest.mark.parametrize('protocol'   ,      ['zip', 'gzip']				)
def 						_snake_case(   SCREAMING_SNAKE_CASE__      :     Optional[int]   ,      SCREAMING_SNAKE_CASE__      :     Dict   ,      SCREAMING_SNAKE_CASE__      :     Dict				)							->				List[Any]:





    '''simple docstring'''






    A__   				=       {'zip': zip_jsonl_path, 'gzip': jsonl_gz_path}
    A__   				=       compressed_file_paths[protocol]
    A__   				=       'dataset.jsonl'
    A__   				=       f'{protocol}://{member_file_path}::{compressed_file_path}'
    A__				,						*A__   				=       fsspec.get_fs_token_paths(SCREAMING_SNAKE_CASE__				)
    assert fs.isfile(SCREAMING_SNAKE_CASE__				)
    assert not fs.isfile('non_existing_' + member_file_path				)
@pytest.mark.integration
def 						_snake_case(   SCREAMING_SNAKE_CASE__      :     str   ,      SCREAMING_SNAKE_CASE__      :     str   ,      SCREAMING_SNAKE_CASE__      :     Optional[int]   ,      SCREAMING_SNAKE_CASE__      :     List[str]				)							->				Dict:





    '''simple docstring'''






    A__   				=       hf_api.dataset_info(SCREAMING_SNAKE_CASE__   ,      token=SCREAMING_SNAKE_CASE__				)
    A__   				=       HfFileSystem(repo_info=SCREAMING_SNAKE_CASE__   ,      token=SCREAMING_SNAKE_CASE__				)
    assert sorted(hffs.glob('*'				)				) == [".gitattributes", "data"]
    assert hffs.isdir('data'				)
    assert hffs.isfile('.gitattributes'				) and hffs.isfile('data/text_data.txt'				)
    with open(SCREAMING_SNAKE_CASE__				) as f:
        assert hffs.open('data/text_data.txt'   ,      'r'				).read() == f.read()

def 						_snake_case(   )							->				str:





    '''simple docstring'''






    A__   				=       'bz2'

    # Import module
    import datasets.filesystems

    # Overwrite protocol and reload
    register_implementation(SCREAMING_SNAKE_CASE__   ,      SCREAMING_SNAKE_CASE__   ,      clobber=SCREAMING_SNAKE_CASE__				)
    with pytest.warns(SCREAMING_SNAKE_CASE__				) as warning_info:
        importlib.reload(datasets.filesystems				)

    assert len(SCREAMING_SNAKE_CASE__				) == 1
    assert (
        str(warning_info[0].message				)
        == f'A filesystem protocol was already set for {protocol} and will be overwritten.'
    )




import numpy as np

from transformers import Pipeline
def 						_snake_case(   SCREAMING_SNAKE_CASE__      :     int				)							->				int:





    '''simple docstring'''






    A__   				=       np.max(SCREAMING_SNAKE_CASE__   ,      axis=-1   ,      keepdims=SCREAMING_SNAKE_CASE__				)
    A__   				=       np.exp(outputs - maxes				)
    return shifted_exp / shifted_exp.sum(axis=-1   ,      keepdims=SCREAMING_SNAKE_CASE__				)


class 			A						(							_UpperCAmelCase			):







    """simple docstring"""





    def 						snake_case__					(				self			:	Dict,**lowercase_			:	Tuple		)->   Tuple:





        '''simple docstring'''







        A__   				=       {}
        if "second_text" in kwargs:
            A__   				=       kwargs['second_text']
        return preprocess_kwargs, {}, {}


    def 						snake_case__					(				self			:	List[Any],lowercase_			:	int,lowercase_			:	Optional[int]=None		)->   List[str]:





        '''simple docstring'''







        return self.tokenizer(lowercase_,text_pair=lowercase_,return_tensors=self.framework		)


    def 						snake_case__					(				self			:	str,lowercase_			:	Dict		)->   List[str]:





        '''simple docstring'''







        return self.model(**lowercase_		)


    def 						snake_case__					(				self			:	Dict,lowercase_			:	Optional[int]		)->   Dict:





        '''simple docstring'''







        A__   				=       model_outputs.logits[0].numpy()
        A__   				=       softmax(lowercase_		)

        A__   				=       np.argmax(lowercase_		)
        A__   				=       self.model.config.idalabel[best_class]
        A__   				=       probabilities[best_class].item()
        A__   				=       logits.tolist()
        return {"label": label, "score": score, "logits": logits}

