






def 					SCREAMING_SNAKE_CASE    (			snake_case_ :							list					,  snake_case_ :							list       ):
	_validate_point(snake_case_       )
	_validate_point(snake_case_       )
	if len(snake_case_       ) != len(snake_case_       ):
		raise ValueError("Both points must be in the same n-dimensional space"       )

	return float(sum(abs(a - b       ) for a, b in zip(snake_case_					,  snake_case_       )       )       )







def 					SCREAMING_SNAKE_CASE    (			snake_case_ :							list[float]       ):
	if point:
		if isinstance(snake_case_					,  snake_case_       ):
			for item in point:
				if not isinstance(snake_case_					,  (int, float)       ):
					snake_case__			:				Optional[int]       =  (
					    "Expected a list of numbers as input, found "
					    F'''{type(snake_case_       ).__name__}'''
					)
					raise TypeError(snake_case_       )
		else:
			snake_case__			:				str       =  F'''Expected a list of numbers as input, found {type(snake_case_       ).__name__}'''
			raise TypeError(snake_case_       )
	else:
		raise ValueError("Missing an input"       )







def 					SCREAMING_SNAKE_CASE    (			snake_case_ :							list					,  snake_case_ :							list       ):
	_validate_point(snake_case_       )
	_validate_point(snake_case_       )
	if len(snake_case_       ) != len(snake_case_       ):
		raise ValueError("Both points must be in the same n-dimensional space"       )

	return float(sum(abs(x - y       ) for x, y in zip(snake_case_					,  snake_case_       )       )       )


if __name__ == "__main__":
	import doctest

	doctest.testmod()











from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__lowerCamelCase :      Union[str, 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:
	__lowerCamelCase :      Tuple										=				[
	    """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

	__lowerCamelCase :      Tuple										=				_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



