

import sys






def        __lowercase   (  _A    ,     _A      )  ->    int:
      if not numbers:
            return 0
      if target == 0 and target in numbers:
            return 0
      if not isinstance(_A    ,     (list, tuple)      ) or not all(
          isinstance(_A    ,     _A      ) for number in numbers      ):
            raise ValueError("""numbers must be an iterable of integers"""      )

      SCREAMING_SNAKE_CASE			:   str	  = 0
      SCREAMING_SNAKE_CASE			:   List[Any]	  = sys.maxsize

      while right < len(_A      ):
            curr_sum += numbers[right]
            while curr_sum >= target and left <= right:
                  SCREAMING_SNAKE_CASE			:   Dict	  = min(_A    ,     right - left + 1      )
                  curr_sum -= numbers[left]
                  left += 1
            right += 1

      return 0 if min_len == sys.maxsize else min_len







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_speech_available,
    is_torch_available,
)


UpperCAmelCase__			:  Tuple					     =     {
    """configuration_speech_to_text_2""": ["""SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Speech2Text2Config"""],
    """processing_speech_to_text_2""": ["""Speech2Text2Processor"""],
    """tokenization_speech_to_text_2""": ["""Speech2Text2Tokenizer"""],
}


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase__			:  Tuple					     =     [
      """SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """Speech2Text2ForCausalLM""",
      """Speech2Text2PreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_speech_to_text_a import SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP, SpeechaTextaConfig
  from .processing_speech_to_text_a import SpeechaTextaProcessor
  from .tokenization_speech_to_text_a import SpeechaTextaTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_speech_to_text_a import (
        SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST,
        SpeechaTextaForCausalLM,
        SpeechaTextaPreTrainedModel,
    )

else:
  import sys

  UpperCAmelCase__			:  Optional[int]					     =     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




