



'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


lowercase_	 =						{"configuration_fnet": ["FNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FNetConfig"]}

try:
  if not is_sentencepiece_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_	 =						["FNetTokenizer"]

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_	 =						["FNetTokenizerFast"]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_	 =						[
      "FNET_PRETRAINED_MODEL_ARCHIVE_LIST",
      "FNetForMaskedLM",
      "FNetForMultipleChoice",
      "FNetForNextSentencePrediction",
      "FNetForPreTraining",
      "FNetForQuestionAnswering",
      "FNetForSequenceClassification",
      "FNetForTokenClassification",
      "FNetLayer",
      "FNetModel",
      "FNetPreTrainedModel",
  ]


if TYPE_CHECKING:
  from .configuration_fnet import FNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FNetConfig

  try:
    if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_fnet import FNetTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_fnet_fast import FNetTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_fnet import (
        FNET_PRETRAINED_MODEL_ARCHIVE_LIST,
        FNetForMaskedLM,
        FNetForMultipleChoice,
        FNetForNextSentencePrediction,
        FNetForPreTraining,
        FNetForQuestionAnswering,
        FNetForSequenceClassification,
        FNetForTokenClassification,
        FNetLayer,
        FNetModel,
        FNetPreTrainedModel,
    )


else:
  import sys

  lowercase_	 =						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)








'''simple docstring'''





import pytest

import datasets


# Import fixture modules as plugins
lowercase_	 =						["tests.fixtures.files", "tests.fixtures.hub", "tests.fixtures.fsspec"]




def lowerCAmelCase						(__A						,			__A):



     """simple docstring"""



     for item in items:
          if any(marker in item.keywords for marker in ['''integration''', '''unit''']):
               continue
          item.add_marker(pytest.mark.unit)




def lowerCAmelCase						(__A):



     """simple docstring"""



     config.addinivalue_line('''markers'''						,			'''torchaudio_latest: mark test to run with torchaudio>=0.12''')




@pytest.fixture(autouse=__A)
def lowerCAmelCase						(__A						,			__A):



     """simple docstring"""



     _a											=						tmp_path_factory.getbasetemp() / '''cache'''
     _a											=						test_hf_cache_home / '''datasets'''
     _a											=						test_hf_cache_home / '''metrics'''
     _a											=						test_hf_cache_home / '''modules'''
     monkeypatch.setattr('''datasets.config.HF_DATASETS_CACHE'''						,			str(__A))
     monkeypatch.setattr('''datasets.config.HF_METRICS_CACHE'''						,			str(__A))
     monkeypatch.setattr('''datasets.config.HF_MODULES_CACHE'''						,			str(__A))
     _a											=						test_hf_datasets_cache / '''downloads'''
     monkeypatch.setattr('''datasets.config.DOWNLOADED_DATASETS_PATH'''						,			str(__A))
     _a											=						test_hf_datasets_cache / '''downloads''' / '''extracted'''
     monkeypatch.setattr('''datasets.config.EXTRACTED_DATASETS_PATH'''						,			str(__A))




@pytest.fixture(autouse=__A						,			scope='''session''')
def lowerCAmelCase						():



     """simple docstring"""



     datasets.disable_progress_bar()




@pytest.fixture(autouse=__A)
def lowerCAmelCase						(__A):



     """simple docstring"""



     monkeypatch.setattr('''datasets.config.HF_UPDATE_DOWNLOAD_COUNTS'''						,			__A)




@pytest.fixture
def lowerCAmelCase						(__A):



     """simple docstring"""



     monkeypatch.setattr('''sqlalchemy.util.deprecations.SILENCE_UBER_WARNING'''						,			__A)



