


'''simple docstring'''







from __future__ import annotations




def        __lowercase						(      __SCREAMING_SNAKE_CASE		)				->					float:
     __a       =   0.00
     __a       =   0
     for resistor in resistors:
          if resistor <= 0:
               __a       =   F'''Resistor at index {index} has a negative or zero value!'''
               raise ValueError(__SCREAMING_SNAKE_CASE		)
          first_sum += 1 / float(__SCREAMING_SNAKE_CASE		)
          index += 1
     return 1 / first_sum




def        __lowercase						(      __SCREAMING_SNAKE_CASE		)				->					float:
     __a       =   0.00
     __a       =   0
     for resistor in resistors:
          sum_r += resistor
          if resistor < 0:
               __a       =   F'''Resistor at index {index} has a negative value!'''
               raise ValueError(__SCREAMING_SNAKE_CASE		)
          index += 1
     return sum_r


if __name__ == "__main__":
 import doctest

 doctest.testmod()










'''simple docstring'''







from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE_      =			{
    'configuration_rag': ['RagConfig'],
    'retrieval_rag': ['RagRetriever'],
    'tokenization_rag': ['RagTokenizer'],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE_      =			[
     'RagModel',
     'RagPreTrainedModel',
     'RagSequenceForGeneration',
     'RagTokenForGeneration',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE_      =			[
     'TFRagModel',
     'TFRagPreTrainedModel',
     'TFRagSequenceForGeneration',
     'TFRagTokenForGeneration',
 ]


if TYPE_CHECKING:
 from .configuration_rag import RagConfig
 from .retrieval_rag import RagRetriever
 from .tokenization_rag import RagTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_rag import RagModel, RagPreTrainedModel, RagSequenceForGeneration, RagTokenForGeneration

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_rag import (
      TFRagModel,
      TFRagPreTrainedModel,
      TFRagSequenceForGeneration,
      TFRagTokenForGeneration,
  )

else:
 import sys

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






