



"""simple docstring"""

import json
import os
from pathlib import Path

import pytest

from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename


A_						:    Optional[Any]				=      'http://www.mocksite.com/file1.txt'
A_						:    Optional[Any]				=      '"text": ["foo", "foo"]'
A_						:    Tuple				=      '6d8ce9aa78a471c7477201efbeabd3bb01ac2e7d100a6dc024ba1608361f90a8'
class     lowerCAmelCase__						:


	'''simple docstring'''







	_SCREAMING_SNAKE_CASE	:		str  						= 2_00
	_SCREAMING_SNAKE_CASE	:		List[Any]  						= {'''Content-Length''': '''100'''}
	_SCREAMING_SNAKE_CASE	:		Optional[Any]  						= {}





	def 			_lowerCAmelCase     (      self				:       Optional[Any]     ,       **_SCREAMING_SNAKE_CASE				:       Any    )						->	str:





					"""simple docstring"""


					return [bytes(_SCREAMING_SNAKE_CASE     ,       'utf-8'    )]




def  __snake_case							(	*__A      :						List[Any]							,		**__A      :						Optional[Any]     )     ->       Any:






				'''simple docstring'''
				return MockResponse()
@pytest.mark.parametrize('urls_type'							,		[str, list, dict]     )
def  __snake_case							(	__A      :						Any							,		__A      :						Tuple							,		__A      :						str     )     ->       Optional[int]:






				'''simple docstring'''
				import requests

				monkeypatch.setattr(__A							,		'request'							,		__A     )

				SCREAMING_SNAKE_CASE						:							Dict							=     URL
				if issubclass(__A							,		__A     ):
								SCREAMING_SNAKE_CASE						:							str							=     url
				elif issubclass(__A							,		__A     ):
								SCREAMING_SNAKE_CASE						:							int							=     [url]
				elif issubclass(__A							,		__A     ):
								SCREAMING_SNAKE_CASE						:							Optional[int]							=     {'train': url}
				SCREAMING_SNAKE_CASE						:							List[Any]							=     'dummy'
				SCREAMING_SNAKE_CASE						:							Optional[int]							=     'downloads'
				SCREAMING_SNAKE_CASE						:							int							=     tmp_path
				SCREAMING_SNAKE_CASE						:							Tuple							=     DownloadConfig(
				    cache_dir=os.path.join(__A							,		__A     )							,		use_etag=__A							,		)
				SCREAMING_SNAKE_CASE						:							List[str]							=     DownloadManager(dataset_name=__A							,		download_config=__A     )
				SCREAMING_SNAKE_CASE						:							Tuple							=     dl_manager.download(__A     )
				SCREAMING_SNAKE_CASE						:							int							=     urls
				for downloaded_paths in [downloaded_paths]:
								if isinstance(__A							,		__A     ):
												SCREAMING_SNAKE_CASE						:							Optional[Any]							=     [downloaded_paths]
												SCREAMING_SNAKE_CASE						:							Dict							=     [urls]
								elif isinstance(__A							,		__A     ):
												assert "train" in downloaded_paths.keys()
												SCREAMING_SNAKE_CASE						:							Tuple							=     downloaded_paths.values()
												SCREAMING_SNAKE_CASE						:							int							=     urls.values()
								assert downloaded_paths
								for downloaded_path, input_url in zip(__A							,		__A     ):
												assert downloaded_path == dl_manager.downloaded_paths[input_url]
												SCREAMING_SNAKE_CASE						:							int							=     Path(__A     )
												SCREAMING_SNAKE_CASE						:							Union[str, Any]							=     downloaded_path.parts
												assert parts[-1] == HASH
												assert parts[-2] == cache_subdir
												assert downloaded_path.exists()
												SCREAMING_SNAKE_CASE						:							Any							=     downloaded_path.read_text()
												assert content == CONTENT
												SCREAMING_SNAKE_CASE						:							List[str]							=     downloaded_path.with_suffix('.json'     )
												assert metadata_downloaded_path.exists()
												SCREAMING_SNAKE_CASE						:							Union[str, Any]							=     json.loads(metadata_downloaded_path.read_text()     )
												assert metadata_content == {"url": URL, "etag": None}
@pytest.mark.parametrize('paths_type'							,		[str, list, dict]     )
def  __snake_case							(	__A      :						int							,		__A      :						Dict							,		__A      :						str     )     ->       Optional[int]:






				'''simple docstring'''
				SCREAMING_SNAKE_CASE						:							str							=     str(__A     )
				if issubclass(__A							,		__A     ):
								SCREAMING_SNAKE_CASE						:							Any							=     filename
				elif issubclass(__A							,		__A     ):
								SCREAMING_SNAKE_CASE						:							Optional[int]							=     [filename]
				elif issubclass(__A							,		__A     ):
								SCREAMING_SNAKE_CASE						:							List[str]							=     {'train': filename}
				SCREAMING_SNAKE_CASE						:							Any							=     'dummy'
				SCREAMING_SNAKE_CASE						:							Union[str, Any]							=     xz_file.parent
				SCREAMING_SNAKE_CASE						:							Union[str, Any]							=     'extracted'
				SCREAMING_SNAKE_CASE						:							Tuple							=     DownloadConfig(
				    cache_dir=__A							,		use_etag=__A							,		)
				SCREAMING_SNAKE_CASE						:							int							=     DownloadManager(dataset_name=__A							,		download_config=__A     )
				SCREAMING_SNAKE_CASE						:							Union[str, Any]							=     dl_manager.extract(__A     )
				SCREAMING_SNAKE_CASE						:							Tuple							=     paths
				for extracted_paths in [extracted_paths]:
								if isinstance(__A							,		__A     ):
												SCREAMING_SNAKE_CASE						:							List[Any]							=     [extracted_paths]
												SCREAMING_SNAKE_CASE						:							List[Any]							=     [paths]
								elif isinstance(__A							,		__A     ):
												assert "train" in extracted_paths.keys()
												SCREAMING_SNAKE_CASE						:							Optional[int]							=     extracted_paths.values()
												SCREAMING_SNAKE_CASE						:							List[str]							=     paths.values()
								assert extracted_paths
								for extracted_path, input_path in zip(__A							,		__A     ):
												assert extracted_path == dl_manager.extracted_paths[input_path]
												SCREAMING_SNAKE_CASE						:							Any							=     Path(__A     )
												SCREAMING_SNAKE_CASE						:							Any							=     extracted_path.parts
												assert parts[-1] == hash_url_to_filename(__A							,		etag=__A     )
												assert parts[-2] == extracted_subdir
												assert extracted_path.exists()
												SCREAMING_SNAKE_CASE						:							List[Any]							=     extracted_path.read_text()
												SCREAMING_SNAKE_CASE						:							Union[str, Any]							=     text_file.read_text()
												assert extracted_file_content == expected_file_content
def  __snake_case							(	__A      :						Union[str, Any]							,		__A      :						Optional[Any]     )     ->       Optional[int]:






				'''simple docstring'''
				assert path.endswith('.jsonl'     )
				for num_items, line in enumerate(__A							,		start=1     ):
								SCREAMING_SNAKE_CASE						:							int							=     json.loads(line.decode('utf-8'     )     )
								assert item.keys() == {"col_1", "col_2", "col_3"}
				assert num_items == 4
@pytest.mark.parametrize('archive_jsonl'							,		['tar_jsonl_path', 'zip_jsonl_path']     )
def  __snake_case							(	__A      :						Tuple							,		__A      :						str     )     ->       List[Any]:






				'''simple docstring'''
				SCREAMING_SNAKE_CASE						:							Union[str, Any]							=     request.getfixturevalue(__A     )
				SCREAMING_SNAKE_CASE						:							Tuple							=     DownloadManager()
				for num_jsonl, (path, file) in enumerate(dl_manager.iter_archive(__A     )							,		start=1     ):
								_test_jsonl(__A							,		__A     )
				assert num_jsonl == 2
@pytest.mark.parametrize('archive_nested_jsonl'							,		['tar_nested_jsonl_path', 'zip_nested_jsonl_path']     )
def  __snake_case							(	__A      :						List[Any]							,		__A      :						Optional[int]     )     ->       Union[str, Any]:






				'''simple docstring'''
				SCREAMING_SNAKE_CASE						:							List[Any]							=     request.getfixturevalue(__A     )
				SCREAMING_SNAKE_CASE						:							Dict							=     DownloadManager()
				for num_tar, (path, file) in enumerate(dl_manager.iter_archive(__A     )							,		start=1     ):
								for num_jsonl, (subpath, subfile) in enumerate(dl_manager.iter_archive(__A     )							,		start=1     ):
												_test_jsonl(__A							,		__A     )
				assert num_tar == 1
				assert num_jsonl == 2







def  __snake_case							(	__A      :						Optional[Any]     )     ->       Dict:






				'''simple docstring'''
				SCREAMING_SNAKE_CASE						:							Any							=     DownloadManager()
				for num_file, file in enumerate(dl_manager.iter_files(__A     )							,		start=1     ):
								assert os.path.basename(__A     ) == ("test.txt" if num_file == 1 else "train.txt")
				assert num_file == 2










"""simple docstring"""

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


A_						:    Optional[Any]				=      {
    'configuration_squeezebert': [
        'SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'SqueezeBertConfig',
        'SqueezeBertOnnxConfig',
    ],
    'tokenization_squeezebert': ['SqueezeBertTokenizer'],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A_						:    Tuple				=      ['SqueezeBertTokenizerFast']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A_						:    int				=      [
							    'SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'SqueezeBertForMaskedLM',
							    'SqueezeBertForMultipleChoice',
							    'SqueezeBertForQuestionAnswering',
							    'SqueezeBertForSequenceClassification',
							    'SqueezeBertForTokenClassification',
							    'SqueezeBertModel',
							    'SqueezeBertModule',
							    'SqueezeBertPreTrainedModel',
							]


if TYPE_CHECKING:
							from .configuration_squeezebert import (
							    SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    SqueezeBertConfig,
							    SqueezeBertOnnxConfig,
							)
							from .tokenization_squeezebert import SqueezeBertTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_squeezebert import (
														    SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    SqueezeBertForMaskedLM,
														    SqueezeBertForMultipleChoice,
														    SqueezeBertForQuestionAnswering,
														    SqueezeBertForSequenceClassification,
														    SqueezeBertForTokenClassification,
														    SqueezeBertModel,
														    SqueezeBertModule,
														    SqueezeBertPreTrainedModel,
														)

else:
							import sys

							A_						:    Optional[Any]				=      _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





