from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


SCREAMING_SNAKE_CASE__		:       List[Any]       						=       {
    "configuration_wav2vec2": ["WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Wav2Vec2Config"],
    "feature_extraction_wav2vec2": ["Wav2Vec2FeatureExtractor"],
    "processing_wav2vec2": ["Wav2Vec2Processor"],
    "tokenization_wav2vec2": ["Wav2Vec2CTCTokenizer", "Wav2Vec2Tokenizer"],
}


try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE__		:       Union[str, Any]       						=       [
          "WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST",
          "Wav2Vec2ForAudioFrameClassification",
          "Wav2Vec2ForCTC",
          "Wav2Vec2ForMaskedLM",
          "Wav2Vec2ForPreTraining",
          "Wav2Vec2ForSequenceClassification",
          "Wav2Vec2ForXVector",
          "Wav2Vec2Model",
          "Wav2Vec2PreTrainedModel",
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE__		:       str       						=       [
          "TF_WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST",
          "TFWav2Vec2ForCTC",
          "TFWav2Vec2Model",
          "TFWav2Vec2PreTrainedModel",
          "TFWav2Vec2ForSequenceClassification",
      ]

try:
      if not is_flax_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE__		:       Any       						=       [
          "FlaxWav2Vec2ForCTC",
          "FlaxWav2Vec2ForPreTraining",
          "FlaxWav2Vec2Model",
          "FlaxWav2Vec2PreTrainedModel",
      ]


if TYPE_CHECKING:
      from .configuration_wavaveca import WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP, WavaVecaConfig
      from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
      from .processing_wavaveca import WavaVecaProcessor
      from .tokenization_wavaveca import WavaVecaCTCTokenizer, WavaVecaTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_wavaveca import (
                WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST,
                WavaVecaForAudioFrameClassification,
                WavaVecaForCTC,
                WavaVecaForMaskedLM,
                WavaVecaForPreTraining,
                WavaVecaForSequenceClassification,
                WavaVecaForXVector,
                WavaVecaModel,
                WavaVecaPreTrainedModel,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_wavaveca import (
                TF_WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFWavaVecaForCTC,
                TFWavaVecaForSequenceClassification,
                TFWavaVecaModel,
                TFWavaVecaPreTrainedModel,
            )

      try:
            if not is_flax_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_wavaveca import (
                FlaxWavaVecaForCTC,
                FlaxWavaVecaForPreTraining,
                FlaxWavaVecaModel,
                FlaxWavaVecaPreTrainedModel,
            )


else:
      import sys

      SCREAMING_SNAKE_CASE__		:       Dict       						=       _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





from __future__ import annotations


def    a      ( a	)     ->float:




			'''simple docstring'''


			SCREAMING_SNAKE_CASE     						= 0.00
			SCREAMING_SNAKE_CASE     						= 0
			for resistor in resistors:
						if resistor <= 0:
									SCREAMING_SNAKE_CASE     						= F"""Resistor at index {index} has a negative or zero value!"""
									raise ValueError(a	)
						first_sum += 1 / float(a	)
						index += 1
			return 1 / first_sum


def    a      ( a	)     ->float:




			'''simple docstring'''


			SCREAMING_SNAKE_CASE     						= 0.00
			SCREAMING_SNAKE_CASE     						= 0
			for resistor in resistors:
						sum_r += resistor
						if resistor < 0:
									SCREAMING_SNAKE_CASE     						= F"""Resistor at index {index} has a negative value!"""
									raise ValueError(a	)
						index += 1
			return sum_r


if __name__ == "__main__":
							import doctest

							doctest.testmod()