





from typing import TYPE_CHECKING

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


__UpperCAmelCase       :   Optional[int]				       =							{
    "configuration_whisper": ["WHISPER_PRETRAINED_CONFIG_ARCHIVE_MAP", "WhisperConfig", "WhisperOnnxConfig"],
    "feature_extraction_whisper": ["WhisperFeatureExtractor"],
    "processing_whisper": ["WhisperProcessor"],
    "tokenization_whisper": ["WhisperTokenizer"],
}

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase       :   Any				       =							["WhisperTokenizerFast"]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase       :   int				       =							[
          "WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST",
          "WhisperForConditionalGeneration",
          "WhisperModel",
          "WhisperPreTrainedModel",
          "WhisperForAudioClassification",
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase       :   Dict				       =							[
          "TF_WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST",
          "TFWhisperForConditionalGeneration",
          "TFWhisperModel",
          "TFWhisperPreTrainedModel",
      ]

try:
      if not is_flax_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase       :   Optional[int]				       =							[
          "FlaxWhisperForConditionalGeneration",
          "FlaxWhisperModel",
          "FlaxWhisperPreTrainedModel",
          "FlaxWhisperForAudioClassification",
      ]


if TYPE_CHECKING:
      from .configuration_whisper import WHISPER_PRETRAINED_CONFIG_ARCHIVE_MAP, WhisperConfig, WhisperOnnxConfig
      from .feature_extraction_whisper import WhisperFeatureExtractor
      from .processing_whisper import WhisperProcessor
      from .tokenization_whisper import WhisperTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_whisper_fast import WhisperTokenizerFast

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_whisper import (
                WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST,
                WhisperForAudioClassification,
                WhisperForConditionalGeneration,
                WhisperModel,
                WhisperPreTrainedModel,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_whisper import (
                TF_WHISPER_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFWhisperForConditionalGeneration,
                TFWhisperModel,
                TFWhisperPreTrainedModel,
            )

      try:
            if not is_flax_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_flax_whisper import (
                FlaxWhisperForAudioClassification,
                FlaxWhisperForConditionalGeneration,
                FlaxWhisperModel,
                FlaxWhisperPreTrainedModel,
            )

else:
      import sys

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













def 			A__							(    SCREAMING_SNAKE_CASE__ = 200)   ->    int:
  __snake_case:						Optional[int]   =						[1, 2, 5, 10, 20, 50, 100, 200]
  __snake_case:						List[Any]   =						[0] * (pence + 1)
  __snake_case:						int   =						1  # base case: 1 way to make 0 pence

  for coin in coins:
    for i in range(SCREAMING_SNAKE_CASE__					,					pence + 1					,					1):
      number_of_ways[i] += number_of_ways[i - coin]
  return number_of_ways[pence]


if __name__ == "__main__":
      assert solution(200) == 73_682






