






from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE__				     =			{
    '''configuration_mvp''': ['''MVP_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MvpConfig''', '''MvpOnnxConfig'''],
    '''tokenization_mvp''': ['''MvpTokenizer'''],
}

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

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							SCREAMING_SNAKE_CASE__				     =			[
							    '''MVP_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''MvpForCausalLM''',
							    '''MvpForConditionalGeneration''',
							    '''MvpForQuestionAnswering''',
							    '''MvpForSequenceClassification''',
							    '''MvpModel''',
							    '''MvpPreTrainedModel''',
							]

if TYPE_CHECKING:
							from .configuration_mvp import MVP_PRETRAINED_CONFIG_ARCHIVE_MAP, MvpConfig, MvpOnnxConfig
							from .tokenization_mvp import MvpTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_mvp_fast import MvpTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_mvp import (
														    MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MvpForCausalLM,
														    MvpForConditionalGeneration,
														    MvpForQuestionAnswering,
														    MvpForSequenceClassification,
														    MvpModel,
														    MvpPreTrainedModel,
														)

else:
							import sys

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







def 		UpperCamelCase						(   lowercase_ )		->						float:


  '''simple docstring'''






  if not nums:  # Makes sure that the list is not empty
    raise ValueError("""List is empty""" )

  lowercase__	: int     		=   sum(lowercase_ ) / len(lowercase_ )  # Calculate the average
  return sum(abs(x - average ) for x in nums ) / len(lowercase_ )


if __name__ == "__main__":
     import doctest

     doctest.testmod()






