

'''simple docstring'''


from typing import TYPE_CHECKING

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


lowerCAmelCase__						:       Any										=						{
    """configuration_longformer""": [
        """LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """LongformerConfig""",
        """LongformerOnnxConfig""",
    ],
    """tokenization_longformer""": ["""LongformerTokenizer"""],
}

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase__						:       Any										=						["""LongformerTokenizerFast"""]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase__						:       Dict										=						[
					    """LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """LongformerForMaskedLM""",
					    """LongformerForMultipleChoice""",
					    """LongformerForQuestionAnswering""",
					    """LongformerForSequenceClassification""",
					    """LongformerForTokenClassification""",
					    """LongformerModel""",
					    """LongformerPreTrainedModel""",
					    """LongformerSelfAttention""",
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase__						:       List[str]										=						[
					    """TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """TFLongformerForMaskedLM""",
					    """TFLongformerForMultipleChoice""",
					    """TFLongformerForQuestionAnswering""",
					    """TFLongformerForSequenceClassification""",
					    """TFLongformerForTokenClassification""",
					    """TFLongformerModel""",
					    """TFLongformerPreTrainedModel""",
					    """TFLongformerSelfAttention""",
					]


if TYPE_CHECKING:
					from .configuration_longformer import (
					    LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    LongformerConfig,
					    LongformerOnnxConfig,
					)
					from .tokenization_longformer import LongformerTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_longformer_fast import LongformerTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_longformer import (
										    LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    LongformerForMaskedLM,
										    LongformerForMultipleChoice,
										    LongformerForQuestionAnswering,
										    LongformerForSequenceClassification,
										    LongformerForTokenClassification,
										    LongformerModel,
										    LongformerPreTrainedModel,
										    LongformerSelfAttention,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_longformer import (
										    TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFLongformerForMaskedLM,
										    TFLongformerForMultipleChoice,
										    TFLongformerForQuestionAnswering,
										    TFLongformerForSequenceClassification,
										    TFLongformerForTokenClassification,
										    TFLongformerModel,
										    TFLongformerPreTrainedModel,
										    TFLongformerSelfAttention,
										)

else:
					import sys

					lowerCAmelCase__						:       str										=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






'''simple docstring'''


from bisect import bisect
from itertools import accumulate




def 	_a       (				__lowerCAmelCase		:      Optional[int]   ,							__lowerCAmelCase		:      Tuple   ,							__lowerCAmelCase		:      List[Any]   ,							__lowerCAmelCase		:      Optional[Any]     ):

		"""simple docstring"""

		snake_case__						:       Any       						=  sorted(zip(__lowerCAmelCase   ,							__lowerCAmelCase     )   ,							key=lambda __lowerCAmelCase     : x[0] / x[1]   ,							reverse=__lowerCAmelCase     )
		snake_case__						,       snake_case__						:       Union[str, Any]       						=  [i[0] for i in r], [i[1] for i in r]
		snake_case__						:       Dict       						=  list(accumulate(__lowerCAmelCase     )     )
		snake_case__						:       Optional[int]       						=  bisect(__lowerCAmelCase   ,							__lowerCAmelCase     )
		return (
		    0
		    if k == 0
		    else sum(vl[:k]     ) + (w - acc[k - 1]) * (vl[k]) / (wt[k])
		    if k != n
		    else sum(vl[:k]     )
		)


if __name__ == "__main__":
					import doctest

					doctest.testmod()



