





'''simple docstring'''

from typing import TYPE_CHECKING

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


lowercase__		:     List[str]			=							{
    'configuration_mvp': ['MVP_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MvpConfig', 'MvpOnnxConfig'],
    'tokenization_mvp': ['MvpTokenizer'],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowercase__		:     Union[str, Any]			=							['MvpTokenizerFast']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowercase__		:     Union[str, Any]			=							[
       '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

   lowercase__		:     int			=							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)










'''simple docstring'''

def    a__							(							lowercase   :	int,   lowercase   :	int,   lowercase   :	int )						->						float:





     """simple docstring"""

     _UpperCamelCase							       =			(num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
     # formula for sum of series
     return total







def    a__							(							)						->						Tuple:





     """simple docstring"""

     print(sum_of_series(1,   1,   10 ) )


if __name__ == "__main__":
   import doctest

   doctest.testmod()



