





'''simple docstring'''






def   UpperCamelCase__ (						lowerCAmelCase    ):





      """simple docstring"""


      _lowerCAmelCase					=				len(lowerCAmelCase    )
      _lowerCAmelCase					=				sum(lowerCAmelCase    )

      _lowerCAmelCase					=				[[False for x in range(s + 1    )] for y in range(n + 1    )]

      for i in range(1				,      n + 1    ):
            _lowerCAmelCase					=				True

      for i in range(1				,      s + 1    ):
            _lowerCAmelCase					=				False

      for i in range(1				,      n + 1    ):
            for j in range(1				,      s + 1    ):
                  _lowerCAmelCase					=				dp[i][j - 1]

                  if arr[i - 1] <= j:
                        _lowerCAmelCase					=				dp[i][j] or dp[i - 1][j - arr[i - 1]]

      for j in range(int(s / 2    )				,      -1				,      -1    ):
            if dp[n][j] is True:
                  _lowerCAmelCase					=				s - 2 * j
                  break

      return diff













'''simple docstring'''






from typing import TYPE_CHECKING

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


A__							:  int    ={
    '''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:
      A__							:  str    =[
          '''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:
      A__							:  Union[str, Any]    =[
          '''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:
      A__							:  List[str]    =[
          '''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

      A__							:  Any    =_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






