



from typing import TYPE_CHECKING

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


lowerCamelCase__			= {
    """configuration_transfo_xl""": ["""TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TransfoXLConfig"""],
    """tokenization_transfo_xl""": ["""TransfoXLCorpus""", """TransfoXLTokenizer"""],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__			= [
						    """TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """AdaptiveEmbedding""",
						    """TransfoXLForSequenceClassification""",
						    """TransfoXLLMHeadModel""",
						    """TransfoXLModel""",
						    """TransfoXLPreTrainedModel""",
						    """load_tf_weights_in_transfo_xl""",
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__			= [
						    """TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """TFAdaptiveEmbedding""",
						    """TFTransfoXLForSequenceClassification""",
						    """TFTransfoXLLMHeadModel""",
						    """TFTransfoXLMainLayer""",
						    """TFTransfoXLModel""",
						    """TFTransfoXLPreTrainedModel""",
						]


if TYPE_CHECKING:
						from .configuration_transfo_xl import TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP, TransfoXLConfig
						from .tokenization_transfo_xl import TransfoXLCorpus, TransfoXLTokenizer

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_transfo_xl import (
												    TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
												    AdaptiveEmbedding,
												    TransfoXLForSequenceClassification,
												    TransfoXLLMHeadModel,
												    TransfoXLModel,
												    TransfoXLPreTrainedModel,
												    load_tf_weights_in_transfo_xl,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_transfo_xl import (
												    TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFAdaptiveEmbedding,
												    TFTransfoXLForSequenceClassification,
												    TFTransfoXLLMHeadModel,
												    TFTransfoXLMainLayer,
												    TFTransfoXLModel,
												    TFTransfoXLPreTrainedModel,
												)

else:
						import sys

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





def   lowerCAmelCase__						(							_SCREAMING_SNAKE_CASE       :			list				,     _SCREAMING_SNAKE_CASE       :			list				,     _SCREAMING_SNAKE_CASE       :			int				,     _SCREAMING_SNAKE_CASE       :			int				,     _SCREAMING_SNAKE_CASE       :			int    ):
				"""simple docstring"""







				if index == number_of_items:
								return 0
				__a       =		0
				__a       =		0
				__a       =		knapsack(_SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     index + 1    )
				if weights[index] <= max_weight:
								__a       =		values[index] + knapsack(
								    _SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     max_weight - weights[index]				,     index + 1    )
				return max(_SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE    )


if __name__ == "__main__":
						import doctest

						doctest.testmod()
