


from typing import TYPE_CHECKING

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


snake_case__				:	str					       =					{
    'configuration_mobilebert': [
        'MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'MobileBertConfig',
        'MobileBertOnnxConfig',
    ],
    'tokenization_mobilebert': ['MobileBertTokenizer'],
}

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      snake_case__				:	Dict					       =					['MobileBertTokenizerFast']

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      snake_case__				:	Union[str, Any]					       =					[
          'MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
          'MobileBertForMaskedLM',
          'MobileBertForMultipleChoice',
          'MobileBertForNextSentencePrediction',
          'MobileBertForPreTraining',
          'MobileBertForQuestionAnswering',
          'MobileBertForSequenceClassification',
          'MobileBertForTokenClassification',
          'MobileBertLayer',
          'MobileBertModel',
          'MobileBertPreTrainedModel',
          'load_tf_weights_in_mobilebert',
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      snake_case__				:	Union[str, Any]					       =					[
          'TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
          'TFMobileBertForMaskedLM',
          'TFMobileBertForMultipleChoice',
          'TFMobileBertForNextSentencePrediction',
          'TFMobileBertForPreTraining',
          'TFMobileBertForQuestionAnswering',
          'TFMobileBertForSequenceClassification',
          'TFMobileBertForTokenClassification',
          'TFMobileBertMainLayer',
          'TFMobileBertModel',
          'TFMobileBertPreTrainedModel',
      ]


if TYPE_CHECKING:
      from .configuration_mobilebert import (
          MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
          MobileBertConfig,
          MobileBertOnnxConfig,
      )
      from .tokenization_mobilebert import MobileBertTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_mobilebert_fast import MobileBertTokenizerFast

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_mobilebert import (
                MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                MobileBertForMaskedLM,
                MobileBertForMultipleChoice,
                MobileBertForNextSentencePrediction,
                MobileBertForPreTraining,
                MobileBertForQuestionAnswering,
                MobileBertForSequenceClassification,
                MobileBertForTokenClassification,
                MobileBertLayer,
                MobileBertModel,
                MobileBertPreTrainedModel,
                load_tf_weights_in_mobilebert,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_mobilebert import (
                TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFMobileBertForMaskedLM,
                TFMobileBertForMultipleChoice,
                TFMobileBertForNextSentencePrediction,
                TFMobileBertForPreTraining,
                TFMobileBertForQuestionAnswering,
                TFMobileBertForSequenceClassification,
                TFMobileBertForTokenClassification,
                TFMobileBertMainLayer,
                TFMobileBertModel,
                TFMobileBertPreTrainedModel,
            )

else:
      import sys

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









import os

import pytest

from transformers.dynamic_module_utils import get_imports


snake_case__				:	List[Any]					       =					'\nimport os\n'

snake_case__				:	List[str]					       =					'\ndef foo():\n    import os\n    return False\n'

snake_case__				:	List[Any]					       =					'\ndef foo():\n    def bar():\n        if True:\n            import os\n        return False\n    return bar()\n'

snake_case__				:	List[str]					       =					'\nimport os\n\ntry:\n    import bar\nexcept ImportError:\n    raise ValueError()\n'

snake_case__				:	Optional[Any]					       =					'\nimport os\n\ndef foo():\n    try:\n        import bar\n    except ImportError:\n        raise ValueError()\n'

snake_case__				:	Tuple					       =					'\nimport os\n\ntry:\n    import bar\nexcept (ImportError, AttributeError):\n    raise ValueError()\n'

snake_case__				:	str					       =					'\nimport os\n\ntry:\n    import bar\nexcept ImportError as e:\n    raise ValueError()\n'

snake_case__				:	Optional[Any]					       =					'\nimport os\n\ntry:\n    import bar\nexcept:\n    raise ValueError()\n'

snake_case__				:	Any					       =					'\nimport os\n\ntry:\n    import bar\n    import baz\nexcept ImportError:\n    raise ValueError()\n'

snake_case__				:	Union[str, Any]					       =					'\nimport os\n\ntry:\n    import bar\n    import baz\nexcept ImportError:\n    x = 1\n    raise ValueError()\n'

snake_case__				:	Any					       =					[
    TOP_LEVEL_IMPORT,
    IMPORT_IN_FUNCTION,
    DEEPLY_NESTED_IMPORT,
    TOP_LEVEL_TRY_IMPORT,
    GENERIC_EXCEPT_IMPORT,
    MULTILINE_TRY_IMPORT,
    MULTILINE_BOTH_IMPORT,
    MULTIPLE_EXCEPTS_IMPORT,
    EXCEPT_AS_IMPORT,
    TRY_IMPORT_IN_FUNCTION,
]


@pytest.mark.parametrize("""case"""						,						A__					)
def    __lowerCamelCase   (      A__						: Dict						,						A__						: int					)     ->    List[Any]:
   lowerCamelCase_						:   List[str]		= os.path.join(A__						,						"""test_file.py"""					)
   with open(A__						,						"""w"""					) as _tmp_file:
      _tmp_file.write(A__					)

   lowerCamelCase_						:   str		= get_imports(A__					)
   assert parsed_imports == ["os"]





