

"""simple docstring"""

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


_UpperCamelCase		    =						{
    """configuration_flaubert""": ["""FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FlaubertConfig""", """FlaubertOnnxConfig"""],
    """tokenization_flaubert""": ["""FlaubertTokenizer"""],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _UpperCamelCase		    =						[
        """FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """FlaubertForMultipleChoice""",
        """FlaubertForQuestionAnswering""",
        """FlaubertForQuestionAnsweringSimple""",
        """FlaubertForSequenceClassification""",
        """FlaubertForTokenClassification""",
        """FlaubertModel""",
        """FlaubertWithLMHeadModel""",
        """FlaubertPreTrainedModel""",
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _UpperCamelCase		    =						[
        """TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """TFFlaubertForMultipleChoice""",
        """TFFlaubertForQuestionAnsweringSimple""",
        """TFFlaubertForSequenceClassification""",
        """TFFlaubertForTokenClassification""",
        """TFFlaubertModel""",
        """TFFlaubertPreTrainedModel""",
        """TFFlaubertWithLMHeadModel""",
    ]


if TYPE_CHECKING:
    from .configuration_flaubert import FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, FlaubertConfig, FlaubertOnnxConfig
    from .tokenization_flaubert import FlaubertTokenizer

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flaubert import (
            FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            FlaubertForMultipleChoice,
            FlaubertForQuestionAnswering,
            FlaubertForQuestionAnsweringSimple,
            FlaubertForSequenceClassification,
            FlaubertForTokenClassification,
            FlaubertModel,
            FlaubertPreTrainedModel,
            FlaubertWithLMHeadModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_flaubert import (
            TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFFlaubertForMultipleChoice,
            TFFlaubertForQuestionAnsweringSimple,
            TFFlaubertForSequenceClassification,
            TFFlaubertForTokenClassification,
            TFFlaubertModel,
            TFFlaubertPreTrainedModel,
            TFFlaubertWithLMHeadModel,
        )

else:
    import sys

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









"""simple docstring"""

def 			SCREAMING_SNAKE_CASE       (   lowercase__      ) ->	int:
 return 1 if input_a == 0 else 0



def 			SCREAMING_SNAKE_CASE       (   ) ->	None:
 assert not_gate(0      ) == 1
 assert not_gate(1      ) == 0


if __name__ == "__main__":
    print(not_gate(0))
    print(not_gate(1))






