from typing import TYPE_CHECKING

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


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

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

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowercase										= [
        '''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:
    __lowercase										= [
        '''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

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






import os

import pytest

from transformers.dynamic_module_utils import get_imports


__lowercase										= '''
import os
'''

__lowercase										= '''
def foo():
    import os
    return False
'''

__lowercase										= '''
def foo():
    def bar():
        if True:
            import os
        return False
    return bar()
'''

__lowercase										= '''
import os

try:
    import bar
except ImportError:
    raise ValueError()
'''

__lowercase										= '''
import os

def foo():
    try:
        import bar
    except ImportError:
        raise ValueError()
'''

__lowercase										= '''
import os

try:
    import bar
except (ImportError, AttributeError):
    raise ValueError()
'''

__lowercase										= '''
import os

try:
    import bar
except ImportError as e:
    raise ValueError()
'''

__lowercase										= '''
import os

try:
    import bar
except:
    raise ValueError()
'''

__lowercase										= '''
import os

try:
    import bar
    import baz
except ImportError:
    raise ValueError()
'''

__lowercase										= '''
import os

try:
    import bar
    import baz
except ImportError:
    x = 1
    raise ValueError()
'''

__lowercase										= [
    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'''  ,      SCREAMING_SNAKE_CASE     )
def lowerCamelCase  (       SCREAMING_SNAKE_CASE  ,      SCREAMING_SNAKE_CASE     ):
    '''simple docstring'''







    __UpperCamelCase					:List[Any]        =		os.path.join(SCREAMING_SNAKE_CASE  ,      '''test_file.py'''     )
    with open(SCREAMING_SNAKE_CASE  ,      '''w'''     ) as _tmp_file:
        _tmp_file.write(SCREAMING_SNAKE_CASE     )

    __UpperCamelCase					:Dict        =		get_imports(SCREAMING_SNAKE_CASE     )
    assert parsed_imports == ["os"]





