

"""simple docstring"""





from typing import TYPE_CHECKING

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


_SCREAMING_SNAKE_CASE							:	Optional[Any]										=			{
    """configuration_bart""": ["""BART_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BartConfig""", """BartOnnxConfig"""],
    """tokenization_bart""": ["""BartTokenizer"""],
}

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_SCREAMING_SNAKE_CASE							:	Union[str, Any]										=			["""BartTokenizerFast"""]

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_SCREAMING_SNAKE_CASE							:	int										=			[
				    """BART_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """BartForCausalLM""",
				    """BartForConditionalGeneration""",
				    """BartForQuestionAnswering""",
				    """BartForSequenceClassification""",
				    """BartModel""",
				    """BartPretrainedModel""",
				    """PretrainedBartModel""",
				]

try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_SCREAMING_SNAKE_CASE							:	int										=			[
				    """TFBartForConditionalGeneration""",
				    """TFBartForSequenceClassification""",
				    """TFBartModel""",
				    """TFBartPretrainedModel""",
				]

try:
				if not is_flax_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_SCREAMING_SNAKE_CASE							:	List[Any]										=			[
				    """FlaxBartDecoderPreTrainedModel""",
				    """FlaxBartForCausalLM""",
				    """FlaxBartForConditionalGeneration""",
				    """FlaxBartForQuestionAnswering""",
				    """FlaxBartForSequenceClassification""",
				    """FlaxBartModel""",
				    """FlaxBartPreTrainedModel""",
				]

if TYPE_CHECKING:
				from .configuration_bart import BART_PRETRAINED_CONFIG_ARCHIVE_MAP, BartConfig, BartOnnxConfig
				from .tokenization_bart import BartTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_bart_fast import BartTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_bart import (
								    BART_PRETRAINED_MODEL_ARCHIVE_LIST,
								    BartForCausalLM,
								    BartForConditionalGeneration,
								    BartForQuestionAnswering,
								    BartForSequenceClassification,
								    BartModel,
								    BartPretrainedModel,
								    PretrainedBartModel,
								)

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tf_bart import (
								    TFBartForConditionalGeneration,
								    TFBartForSequenceClassification,
								    TFBartModel,
								    TFBartPretrainedModel,
								)

				try:
								if not is_flax_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_flax_bart import (
								    FlaxBartDecoderPreTrainedModel,
								    FlaxBartForCausalLM,
								    FlaxBartForConditionalGeneration,
								    FlaxBartForQuestionAnswering,
								    FlaxBartForSequenceClassification,
								    FlaxBartModel,
								    FlaxBartPreTrainedModel,
								)

else:
				import sys

				_SCREAMING_SNAKE_CASE							:	int										=			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





"""simple docstring"""





from __future__ import annotations



def 							_lowerCAmelCase   (    UpperCAmelCase  :				list[int]   ,				UpperCAmelCase  :				int					):


					'''simple docstring'''






					UpperCamelCase__		:     dict[int, int]								={}
					for index, val in enumerate(UpperCAmelCase					):
										UpperCamelCase__		:     List[Any]								=target - val
										if compl in chk_map:
															return [chk_map[compl], index]
										UpperCamelCase__		:     Any								=index
					return []


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				print(F'''{two_sum([2, 7, 1_1, 1_5], 9) = }''')


