






"""simple docstring"""

from typing import TYPE_CHECKING

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


lowercase    			=       {'''configuration_reformer''': ['''REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ReformerConfig''']}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase    			=       ['''ReformerTokenizer''']

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase    			=       ['''ReformerTokenizerFast''']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase    			=       [
					    '''REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''ReformerAttention''',
					    '''ReformerForMaskedLM''',
					    '''ReformerForQuestionAnswering''',
					    '''ReformerForSequenceClassification''',
					    '''ReformerLayer''',
					    '''ReformerModel''',
					    '''ReformerModelWithLMHead''',
					    '''ReformerPreTrainedModel''',
					]


if TYPE_CHECKING:
					from .configuration_reformer import REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, ReformerConfig

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_reformer import ReformerTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_reformer_fast import ReformerTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_reformer import (
										    REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    ReformerAttention,
										    ReformerForMaskedLM,
										    ReformerForQuestionAnswering,
										    ReformerForSequenceClassification,
										    ReformerLayer,
										    ReformerModel,
										    ReformerModelWithLMHead,
										    ReformerPreTrainedModel,
										)

else:
					import sys

					lowercase    			=       _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)











"""simple docstring"""

def _lowerCAmelCase	(  __lowerCamelCase:list ,						__lowerCamelCase:list   ):

						'''simple docstring'''






						_validate_point(__lowerCamelCase   )
						_validate_point(__lowerCamelCase   )
						if len(__lowerCamelCase   ) != len(__lowerCamelCase   ):
												raise ValueError("Both points must be in the same n-dimensional space"   )

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






def _lowerCAmelCase	(  __lowerCamelCase:list[float]   ):

						'''simple docstring'''






						if point:
												if isinstance(__lowerCamelCase ,						__lowerCamelCase   ):
																		for item in point:
																								if not isinstance(__lowerCamelCase ,						(int, float)   ):
																														__magic_name__            =     (
																														    "Expected a list of numbers as input, found "
																														    f'''{type(__lowerCamelCase   ).__name__}'''
																														)
																														raise TypeError(__lowerCamelCase   )
												else:
																		__magic_name__            =     f'''Expected a list of numbers as input, found {type(__lowerCamelCase   ).__name__}'''
																		raise TypeError(__lowerCamelCase   )
						else:
												raise ValueError("Missing an input"   )






def _lowerCAmelCase	(  __lowerCamelCase:list ,						__lowerCamelCase:list   ):

						'''simple docstring'''






						_validate_point(__lowerCamelCase   )
						_validate_point(__lowerCamelCase   )
						if len(__lowerCamelCase   ) != len(__lowerCamelCase   ):
												raise ValueError("Both points must be in the same n-dimensional space"   )

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


if __name__ == "__main__":
			import doctest

			doctest.testmod()



