



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


_lowerCamelCase      			=						'http://www.mocksite.com/file1.txt'
_lowerCamelCase      			=						'"text": ["foo", "foo"]'
_lowerCamelCase      			=						'6d8ce9aa78a471c7477201efbeabd3bb01ac2e7d100a6dc024ba1608361f90a8'



class       a					:

     '''simple docstring'''





     lowerCAmelCase    :	str       		=  200
     lowerCAmelCase    :	List[str]       		=  {'Content-Length': '100'}
     lowerCAmelCase    :	Union[str, Any]       		=  {}
     def   lowerCamelCase_       (     self       :      List[str] ,   **__snake_case       :      int    ):
         return [bytes(__snake_case ,   '''utf-8'''    )]




def  SCREAMING_SNAKE_CASE     (	*__UpperCamelCase      :						Optional[int]	,					**__UpperCamelCase      :						Dict				)  ->							List[str]:
    return MockResponse()




@pytest.mark.parametrize('''urls_type'''	,					[str, list, dict]				)
def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						int	,					__UpperCamelCase      :						Dict	,					__UpperCamelCase      :						Optional[int]				)  ->							List[Any]:
    import requests

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

    UpperCAmelCase_										=					URL
    if issubclass(__UpperCamelCase	,					__UpperCamelCase				):
        UpperCAmelCase_										=					url
    elif issubclass(__UpperCamelCase	,					__UpperCamelCase				):
        UpperCAmelCase_										=					[url]
    elif issubclass(__UpperCamelCase	,					__UpperCamelCase				):
        UpperCAmelCase_										=					{'''train''': url}
    UpperCAmelCase_										=					'''dummy'''
    UpperCAmelCase_										=					'''downloads'''
    UpperCAmelCase_										=					tmp_path
    UpperCAmelCase_										=					DownloadConfig(
        cache_dir=os.path.join(__UpperCamelCase	,					__UpperCamelCase				)	,					use_etag=__UpperCamelCase	,					)
    UpperCAmelCase_										=					DownloadManager(dataset_name=__UpperCamelCase	,					download_config=__UpperCamelCase				)
    UpperCAmelCase_										=					dl_manager.download(__UpperCamelCase				)
    UpperCAmelCase_										=					urls
    for downloaded_paths in [downloaded_paths]:
        if isinstance(__UpperCamelCase	,					__UpperCamelCase				):
            UpperCAmelCase_										=					[downloaded_paths]
            UpperCAmelCase_										=					[urls]
        elif isinstance(__UpperCamelCase	,					__UpperCamelCase				):
            assert "train" in downloaded_paths.keys()
            UpperCAmelCase_										=					downloaded_paths.values()
            UpperCAmelCase_										=					urls.values()
        assert downloaded_paths
        for downloaded_path, input_url in zip(__UpperCamelCase	,					__UpperCamelCase				):
            assert downloaded_path == dl_manager.downloaded_paths[input_url]
            UpperCAmelCase_										=					Path(__UpperCamelCase				)
            UpperCAmelCase_										=					downloaded_path.parts
            assert parts[-1] == HASH
            assert parts[-2] == cache_subdir
            assert downloaded_path.exists()
            UpperCAmelCase_										=					downloaded_path.read_text()
            assert content == CONTENT
            UpperCAmelCase_										=					downloaded_path.with_suffix('''.json'''				)
            assert metadata_downloaded_path.exists()
            UpperCAmelCase_										=					json.loads(metadata_downloaded_path.read_text()				)
            assert metadata_content == {"url": URL, "etag": None}




@pytest.mark.parametrize('''paths_type'''	,					[str, list, dict]				)
def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						int	,					__UpperCamelCase      :						List[Any]	,					__UpperCamelCase      :						List[str]				)  ->							int:
    UpperCAmelCase_										=					str(__UpperCamelCase				)
    if issubclass(__UpperCamelCase	,					__UpperCamelCase				):
        UpperCAmelCase_										=					filename
    elif issubclass(__UpperCamelCase	,					__UpperCamelCase				):
        UpperCAmelCase_										=					[filename]
    elif issubclass(__UpperCamelCase	,					__UpperCamelCase				):
        UpperCAmelCase_										=					{'''train''': filename}
    UpperCAmelCase_										=					'''dummy'''
    UpperCAmelCase_										=					xz_file.parent
    UpperCAmelCase_										=					'''extracted'''
    UpperCAmelCase_										=					DownloadConfig(
        cache_dir=__UpperCamelCase	,					use_etag=__UpperCamelCase	,					)
    UpperCAmelCase_										=					DownloadManager(dataset_name=__UpperCamelCase	,					download_config=__UpperCamelCase				)
    UpperCAmelCase_										=					dl_manager.extract(__UpperCamelCase				)
    UpperCAmelCase_										=					paths
    for extracted_paths in [extracted_paths]:
        if isinstance(__UpperCamelCase	,					__UpperCamelCase				):
            UpperCAmelCase_										=					[extracted_paths]
            UpperCAmelCase_										=					[paths]
        elif isinstance(__UpperCamelCase	,					__UpperCamelCase				):
            assert "train" in extracted_paths.keys()
            UpperCAmelCase_										=					extracted_paths.values()
            UpperCAmelCase_										=					paths.values()
        assert extracted_paths
        for extracted_path, input_path in zip(__UpperCamelCase	,					__UpperCamelCase				):
            assert extracted_path == dl_manager.extracted_paths[input_path]
            UpperCAmelCase_										=					Path(__UpperCamelCase				)
            UpperCAmelCase_										=					extracted_path.parts
            assert parts[-1] == hash_url_to_filename(__UpperCamelCase	,					etag=__UpperCamelCase				)
            assert parts[-2] == extracted_subdir
            assert extracted_path.exists()
            UpperCAmelCase_										=					extracted_path.read_text()
            UpperCAmelCase_										=					text_file.read_text()
            assert extracted_file_content == expected_file_content




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						List[str]	,					__UpperCamelCase      :						List[Any]				)  ->							Optional[Any]:
    assert path.endswith('''.jsonl'''				)
    for num_items, line in enumerate(__UpperCamelCase	,					start=1				):
        UpperCAmelCase_										=					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  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Tuple	,					__UpperCamelCase      :						Union[str, Any]				)  ->							Union[str, Any]:
    UpperCAmelCase_										=					request.getfixturevalue(__UpperCamelCase				)
    UpperCAmelCase_										=					DownloadManager()
    for num_jsonl, (path, file) in enumerate(dl_manager.iter_archive(__UpperCamelCase				)	,					start=1				):
        _test_jsonl(__UpperCamelCase	,					__UpperCamelCase				)
    assert num_jsonl == 2




@pytest.mark.parametrize('''archive_nested_jsonl'''	,					['''tar_nested_jsonl_path''', '''zip_nested_jsonl_path''']				)
def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						int	,					__UpperCamelCase      :						str				)  ->							Optional[int]:
    UpperCAmelCase_										=					request.getfixturevalue(__UpperCamelCase				)
    UpperCAmelCase_										=					DownloadManager()
    for num_tar, (path, file) in enumerate(dl_manager.iter_archive(__UpperCamelCase				)	,					start=1				):
        for num_jsonl, (subpath, subfile) in enumerate(dl_manager.iter_archive(__UpperCamelCase				)	,					start=1				):
            _test_jsonl(__UpperCamelCase	,					__UpperCamelCase				)
    assert num_tar == 1
    assert num_jsonl == 2




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Optional[Any]				)  ->							Optional[Any]:
    UpperCAmelCase_										=					DownloadManager()
    for num_file, file in enumerate(dl_manager.iter_files(__UpperCamelCase				)	,					start=1				):
        assert os.path.basename(__UpperCamelCase				) == ("test.txt" if num_file == 1 else "train.txt")
    assert num_file == 2











from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_lowerCamelCase      			=						{
    'configuration_roberta': ['ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RobertaConfig', 'RobertaOnnxConfig'],
    'tokenization_roberta': ['RobertaTokenizer'],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCamelCase      			=						['RobertaTokenizerFast']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCamelCase      			=						[
     'ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST',
     'RobertaForCausalLM',
     'RobertaForMaskedLM',
     'RobertaForMultipleChoice',
     'RobertaForQuestionAnswering',
     'RobertaForSequenceClassification',
     'RobertaForTokenClassification',
     'RobertaModel',
     'RobertaPreTrainedModel',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCamelCase      			=						[
     'TF_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST',
     'TFRobertaForCausalLM',
     'TFRobertaForMaskedLM',
     'TFRobertaForMultipleChoice',
     'TFRobertaForQuestionAnswering',
     'TFRobertaForSequenceClassification',
     'TFRobertaForTokenClassification',
     'TFRobertaMainLayer',
     'TFRobertaModel',
     'TFRobertaPreTrainedModel',
 ]

try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCamelCase      			=						[
     'FlaxRobertaForCausalLM',
     'FlaxRobertaForMaskedLM',
     'FlaxRobertaForMultipleChoice',
     'FlaxRobertaForQuestionAnswering',
     'FlaxRobertaForSequenceClassification',
     'FlaxRobertaForTokenClassification',
     'FlaxRobertaModel',
     'FlaxRobertaPreTrainedModel',
 ]


if TYPE_CHECKING:
 from .configuration_roberta import ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP, RobertaConfig, RobertaOnnxConfig
 from .tokenization_roberta import RobertaTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_roberta_fast import RobertaTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_roberta import (
      ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
      RobertaForCausalLM,
      RobertaForMaskedLM,
      RobertaForMultipleChoice,
      RobertaForQuestionAnswering,
      RobertaForSequenceClassification,
      RobertaForTokenClassification,
      RobertaModel,
      RobertaPreTrainedModel,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_roberta import (
      TF_ROBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFRobertaForCausalLM,
      TFRobertaForMaskedLM,
      TFRobertaForMultipleChoice,
      TFRobertaForQuestionAnswering,
      TFRobertaForSequenceClassification,
      TFRobertaForTokenClassification,
      TFRobertaMainLayer,
      TFRobertaModel,
      TFRobertaPreTrainedModel,
  )

 try:
  if not is_flax_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_flax_roberta import (
      FlaxRobertaForCausalLM,
      FlaxRobertaForMaskedLM,
      FlaxRobertaForMultipleChoice,
      FlaxRobertaForQuestionAnswering,
      FlaxRobertaForSequenceClassification,
      FlaxRobertaForTokenClassification,
      FlaxRobertaModel,
      FlaxRobertaPreTrainedModel,
  )

else:
 import sys

 _lowerCamelCase      			=						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





