



'''simple docstring'''




from collections import deque

from .hash_table import HashTable






class 		_UpperCamelCase						(							lowerCamelCase__					):


			'''simple docstring'''

			def __init__(							self  :				Union[str, Any]							,  *lowerCAmelCase__  :				Union[str, Any]							,  **lowerCAmelCase__  :				Optional[Any]		):





					"""simple docstring"""






					super().__init__(*lowerCAmelCase__							,  **lowerCAmelCase__		)

			def UpperCamelCase__      (							self  :				Tuple							,  lowerCAmelCase__  :				Optional[Any]							,  lowerCAmelCase__  :				Optional[Any]		):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE :	Tuple					 =	deque([]		) if self.values[key] is None else self.values[key]
					self.values[key].appendleft(lowerCAmelCase__		)
					__SCREAMING_SNAKE_CASE :	int					 =	self.values[key]

			def UpperCamelCase__      (							self  :				Tuple		):





					"""simple docstring"""






					return (
					    sum(self.charge_factor - len(lowerCAmelCase__		) for slot in self.values		)
					    / self.size_table
					    * self.charge_factor
					)



			def UpperCamelCase__      (							self  :				Optional[int]							,  lowerCAmelCase__  :				Optional[Any]							,  lowerCAmelCase__  :				str=None		):





					"""simple docstring"""






					if not (
					    len(self.values[key]		) == self.charge_factor and self.values.count(lowerCAmelCase__		) == 0
					):
							return key
					return super()._collision_resolution(lowerCAmelCase__							,  lowerCAmelCase__		)




'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase__ :			List[Any]												=				{
    '''configuration_time_series_transformer''': [
        '''TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''TimeSeriesTransformerConfig''',
    ],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase__ :			List[Any]												=				[
						    '''TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''TimeSeriesTransformerForPrediction''',
						    '''TimeSeriesTransformerModel''',
						    '''TimeSeriesTransformerPreTrainedModel''',
						]


if TYPE_CHECKING:
						from .configuration_time_series_transformer import (
						    TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    TimeSeriesTransformerConfig,
						)

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_time_series_transformer import (
												    TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TimeSeriesTransformerForPrediction,
												    TimeSeriesTransformerModel,
												    TimeSeriesTransformerPreTrainedModel,
												)

else:
						import sys

						UpperCamelCase__ :			Dict												=				_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)