


'''simple docstring'''







from typing import TYPE_CHECKING

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


lowerCAmelCase    :     Union[str, Any]					=						{
    """configuration_albert""": ["""ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """AlbertConfig""", """AlbertOnnxConfig"""],
}

try:
       if not is_sentencepiece_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase    :     Tuple					=						["""AlbertTokenizer"""]

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase    :     Optional[int]					=						["""AlbertTokenizerFast"""]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase    :     int					=						[
           """ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """AlbertForMaskedLM""",
           """AlbertForMultipleChoice""",
           """AlbertForPreTraining""",
           """AlbertForQuestionAnswering""",
           """AlbertForSequenceClassification""",
           """AlbertForTokenClassification""",
           """AlbertModel""",
           """AlbertPreTrainedModel""",
           """load_tf_weights_in_albert""",
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase    :     str					=						[
           """TF_ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """TFAlbertForMaskedLM""",
           """TFAlbertForMultipleChoice""",
           """TFAlbertForPreTraining""",
           """TFAlbertForQuestionAnswering""",
           """TFAlbertForSequenceClassification""",
           """TFAlbertForTokenClassification""",
           """TFAlbertMainLayer""",
           """TFAlbertModel""",
           """TFAlbertPreTrainedModel""",
       ]

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase    :     int					=						[
           """FlaxAlbertForMaskedLM""",
           """FlaxAlbertForMultipleChoice""",
           """FlaxAlbertForPreTraining""",
           """FlaxAlbertForQuestionAnswering""",
           """FlaxAlbertForSequenceClassification""",
           """FlaxAlbertForTokenClassification""",
           """FlaxAlbertModel""",
           """FlaxAlbertPreTrainedModel""",
       ]

if TYPE_CHECKING:
       from .configuration_albert import ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, AlbertConfig, AlbertOnnxConfig

       try:
              if not is_sentencepiece_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_albert import AlbertTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_albert_fast import AlbertTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_albert import (
                  ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  AlbertForMaskedLM,
                  AlbertForMultipleChoice,
                  AlbertForPreTraining,
                  AlbertForQuestionAnswering,
                  AlbertForSequenceClassification,
                  AlbertForTokenClassification,
                  AlbertModel,
                  AlbertPreTrainedModel,
                  load_tf_weights_in_albert,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_albert import (
                  TF_ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFAlbertForMaskedLM,
                  TFAlbertForMultipleChoice,
                  TFAlbertForPreTraining,
                  TFAlbertForQuestionAnswering,
                  TFAlbertForSequenceClassification,
                  TFAlbertForTokenClassification,
                  TFAlbertMainLayer,
                  TFAlbertModel,
                  TFAlbertPreTrainedModel,
              )

       try:
              if not is_flax_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_flax_albert import (
                  FlaxAlbertForMaskedLM,
                  FlaxAlbertForMultipleChoice,
                  FlaxAlbertForPreTraining,
                  FlaxAlbertForQuestionAnswering,
                  FlaxAlbertForSequenceClassification,
                  FlaxAlbertForTokenClassification,
                  FlaxAlbertModel,
                  FlaxAlbertPreTrainedModel,
              )
else:
       import sys

       lowerCAmelCase    :     Dict					=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





'''simple docstring'''







import pytest

import datasets


# Import fixture modules as plugins
lowerCAmelCase    :     List[str]					=						["""tests.fixtures.files""", """tests.fixtures.hub""", """tests.fixtures.fsspec"""]






def 			lowercase				(_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 			lowercase				(_A					):







       """simple docstring"""







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






@pytest.fixture(autouse=_A					)
def 			lowercase				(_A   ,						_A					):







       """simple docstring"""







       _lowerCAmelCase    :							str   			=       tmp_path_factory.getbasetemp() / 'cache'
       _lowerCAmelCase    :							Dict   			=       test_hf_cache_home / 'datasets'
       _lowerCAmelCase    :							List[Any]   			=       test_hf_cache_home / 'metrics'
       _lowerCAmelCase    :							List[Any]   			=       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					)					)
       _lowerCAmelCase    :							Dict   			=       test_hf_datasets_cache / 'downloads'
       monkeypatch.setattr('datasets.config.DOWNLOADED_DATASETS_PATH'   ,						str(_A					)					)
       _lowerCAmelCase    :							Union[str, Any]   			=       test_hf_datasets_cache / 'downloads' / 'extracted'
       monkeypatch.setattr('datasets.config.EXTRACTED_DATASETS_PATH'   ,						str(_A					)					)






@pytest.fixture(autouse=_A   ,						scope='session'					)
def 			lowercase				():







       """simple docstring"""







       datasets.disable_progress_bar()






@pytest.fixture(autouse=_A					)
def 			lowercase				(_A					):







       """simple docstring"""







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






@pytest.fixture
def 			lowercase				(_A					):







       """simple docstring"""







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

