






from typing import TYPE_CHECKING

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


__magic_name__:  Any  	=			{
    "configuration_dpr": ["DPR_PRETRAINED_CONFIG_ARCHIVE_MAP", "DPRConfig"],
    "tokenization_dpr": [
        "DPRContextEncoderTokenizer",
        "DPRQuestionEncoderTokenizer",
        "DPRReaderOutput",
        "DPRReaderTokenizer",
    ],
}


try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__magic_name__:  str  	=			[
		    "DPRContextEncoderTokenizerFast",
		    "DPRQuestionEncoderTokenizerFast",
		    "DPRReaderTokenizerFast",
		]

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__magic_name__:  List[str]  	=			[
		    "DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "DPRContextEncoder",
		    "DPRPretrainedContextEncoder",
		    "DPRPreTrainedModel",
		    "DPRPretrainedQuestionEncoder",
		    "DPRPretrainedReader",
		    "DPRQuestionEncoder",
		    "DPRReader",
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__magic_name__:  str  	=			[
		    "TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "TFDPRContextEncoder",
		    "TFDPRPretrainedContextEncoder",
		    "TFDPRPretrainedQuestionEncoder",
		    "TFDPRPretrainedReader",
		    "TFDPRQuestionEncoder",
		    "TFDPRReader",
		]


if TYPE_CHECKING:
		from .configuration_dpr import DPR_PRETRAINED_CONFIG_ARCHIVE_MAP, DPRConfig
		from .tokenization_dpr import (
		    DPRContextEncoderTokenizer,
		    DPRQuestionEncoderTokenizer,
		    DPRReaderOutput,
		    DPRReaderTokenizer,
		)

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_dpr_fast import (
				    DPRContextEncoderTokenizerFast,
				    DPRQuestionEncoderTokenizerFast,
				    DPRReaderTokenizerFast,
				)

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_dpr import (
				    DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    DPRContextEncoder,
				    DPRPretrainedContextEncoder,
				    DPRPreTrainedModel,
				    DPRPretrainedQuestionEncoder,
				    DPRPretrainedReader,
				    DPRQuestionEncoder,
				    DPRReader,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_dpr import (
				    TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TFDPRContextEncoder,
				    TFDPRPretrainedContextEncoder,
				    TFDPRPretrainedQuestionEncoder,
				    TFDPRPretrainedReader,
				    TFDPRQuestionEncoder,
				    TFDPRReader,
				)

else:
		import sys

		__magic_name__:  Optional[Any]  	=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)








def 					UpperCamelCase		( _A				):






						"""simple docstring"""







						return 1 if input_a == 0 else 0

def 					UpperCamelCase		( ):






						"""simple docstring"""







						assert not_gate(0				) == 1
						assert not_gate(1				) == 0


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