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


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



class 			SCREAMING_SNAKE_CASE_			:
  '''simple docstring'''


  lowercase		:  str							  =					200
  lowercase		:  List[Any]							  =					{'''Content-Length''': '''100'''}
  lowercase		:  Optional[Any]							  =					{}







  def 		SCREAMING_SNAKE_CASE_		(					self     :       Optional[Any]   ,						**SCREAMING_SNAKE_CASE__     :       Any  )     ->					str:
         return [bytes(_SCREAMING_SNAKE_CASE   ,						'utf-8'  )]







def A__	(      *lowercase:  List[Any],		**lowercase:  Optional[Any]       )					->		Any:
       return MockResponse()



@pytest.mark.parametrize('urls_type',		[str, list, dict]       )
def A__	(      lowercase:  Any,		lowercase:  Tuple,		lowercase:  str       )					->		Optional[int]:
       import requests

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

       A    :  Dict								=URL
       if issubclass(__A,		__A       ):
              A    :  str								=url
       elif issubclass(__A,		__A       ):
              A    :  int								=[url]
       elif issubclass(__A,		__A       ):
              A    :  Optional[int]								={'train': url}
       A    :  List[Any]								='dummy'
       A    :  Optional[int]								='downloads'
       A    :  int								=tmp_path
       A    :  Tuple								=DownloadConfig(
           cache_dir=os.path.join(__A,		__A       ),		use_etag=__A,		)
       A    :  List[str]								=DownloadManager(dataset_name=__A,		download_config=__A       )
       A    :  Tuple								=dl_manager.download(__A       )
       A    :  int								=urls
       for downloaded_paths in [downloaded_paths]:
              if isinstance(__A,		__A       ):
                     A    :  Optional[Any]								=[downloaded_paths]
                     A    :  Dict								=[urls]
              elif isinstance(__A,		__A       ):
                     assert "train" in downloaded_paths.keys()
                     A    :  Tuple								=downloaded_paths.values()
                     A    :  int								=urls.values()
              assert downloaded_paths
              for downloaded_path, input_url in zip(__A,		__A       ):
                     assert downloaded_path == dl_manager.downloaded_paths[input_url]
                     A    :  int								=Path(__A       )
                     A    :  Union[str, Any]								=downloaded_path.parts
                     assert parts[-1] == HASH
                     assert parts[-2] == cache_subdir
                     assert downloaded_path.exists()
                     A    :  Any								=downloaded_path.read_text()
                     assert content == CONTENT
                     A    :  List[str]								=downloaded_path.with_suffix('.json'       )
                     assert metadata_downloaded_path.exists()
                     A    :  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 A__	(      lowercase:  int,		lowercase:  Dict,		lowercase:  str       )					->		Optional[int]:
       A    :  str								=str(__A       )
       if issubclass(__A,		__A       ):
              A    :  Any								=filename
       elif issubclass(__A,		__A       ):
              A    :  Optional[int]								=[filename]
       elif issubclass(__A,		__A       ):
              A    :  List[str]								={'train': filename}
       A    :  Any								='dummy'
       A    :  Union[str, Any]								=xz_file.parent
       A    :  Union[str, Any]								='extracted'
       A    :  Tuple								=DownloadConfig(
           cache_dir=__A,		use_etag=__A,		)
       A    :  int								=DownloadManager(dataset_name=__A,		download_config=__A       )
       A    :  Union[str, Any]								=dl_manager.extract(__A       )
       A    :  Tuple								=paths
       for extracted_paths in [extracted_paths]:
              if isinstance(__A,		__A       ):
                     A    :  List[Any]								=[extracted_paths]
                     A    :  List[Any]								=[paths]
              elif isinstance(__A,		__A       ):
                     assert "train" in extracted_paths.keys()
                     A    :  Optional[int]								=extracted_paths.values()
                     A    :  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]
                     A    :  Any								=Path(__A       )
                     A    :  Any								=extracted_path.parts
                     assert parts[-1] == hash_url_to_filename(__A,		etag=__A       )
                     assert parts[-2] == extracted_subdir
                     assert extracted_path.exists()
                     A    :  List[Any]								=extracted_path.read_text()
                     A    :  Union[str, Any]								=text_file.read_text()
                     assert extracted_file_content == expected_file_content



def A__	(      lowercase:  Union[str, Any],		lowercase:  Optional[Any]       )					->		Optional[int]:
       assert path.endswith('.jsonl'       )
       for num_items, line in enumerate(__A,		start=1       ):
              A    :  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 A__	(      lowercase:  Tuple,		lowercase:  str       )					->		List[Any]:
       A    :  Union[str, Any]								=request.getfixturevalue(__A       )
       A    :  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 A__	(      lowercase:  List[Any],		lowercase:  Optional[int]       )					->		Union[str, Any]:
       A    :  List[Any]								=request.getfixturevalue(__A       )
       A    :  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 A__	(      lowercase:  Optional[Any]       )					->		Dict:
       A    :  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_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


A_						:    Optional[int]				=      {
    'configuration_llama': ['LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LlamaConfig'],
}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A_						:    int				=      ['LlamaTokenizer']

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A_						:    List[str]				=      ['LlamaTokenizerFast']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A_						:    List[str]				=      [
							    'LlamaForCausalLM',
							    'LlamaModel',
							    'LlamaPreTrainedModel',
							    'LlamaForSequenceClassification',
							]


if TYPE_CHECKING:
							from .configuration_llama import LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, LlamaConfig

							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_llama import LlamaTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_llama_fast import LlamaTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_llama import LlamaForCausalLM, LlamaForSequenceClassification, LlamaModel, LlamaPreTrainedModel


else:
							import sys

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





