
from typing import TYPE_CHECKING

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


_lowerCamelCase        ={
    """configuration_deberta_v2""": ["""DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DebertaV2Config""", """DebertaV2OnnxConfig"""],
    """tokenization_deberta_v2""": ["""DebertaV2Tokenizer"""],
}

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _lowerCamelCase        =["""DebertaV2TokenizerFast"""]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _lowerCamelCase        =[
          """TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """TFDebertaV2ForMaskedLM""",
          """TFDebertaV2ForQuestionAnswering""",
          """TFDebertaV2ForSequenceClassification""",
          """TFDebertaV2ForTokenClassification""",
          """TFDebertaV2Model""",
          """TFDebertaV2PreTrainedModel""",
      ]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _lowerCamelCase        =[
          """DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """DebertaV2ForMaskedLM""",
          """DebertaV2ForMultipleChoice""",
          """DebertaV2ForQuestionAnswering""",
          """DebertaV2ForSequenceClassification""",
          """DebertaV2ForTokenClassification""",
          """DebertaV2Model""",
          """DebertaV2PreTrainedModel""",
      ]


if TYPE_CHECKING:
      from .configuration_deberta_va import (
          DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP,
          DebertaVaConfig,
          DebertaVaOnnxConfig,
      )
      from .tokenization_deberta_va import DebertaVaTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_deberta_va_fast import DebertaVaTokenizerFast

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_deberta_va import (
                TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFDebertaVaForMaskedLM,
                TFDebertaVaForQuestionAnswering,
                TFDebertaVaForSequenceClassification,
                TFDebertaVaForTokenClassification,
                TFDebertaVaModel,
                TFDebertaVaPreTrainedModel,
            )

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_deberta_va import (
                DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
                DebertaVaForMaskedLM,
                DebertaVaForMultipleChoice,
                DebertaVaForQuestionAnswering,
                DebertaVaForSequenceClassification,
                DebertaVaForTokenClassification,
                DebertaVaModel,
                DebertaVaPreTrainedModel,
            )

else:
      import sys

      _lowerCamelCase        =_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






import sys





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

 lowerCamelCase		:     str          =				0
 lowerCamelCase		:     List[str]          =				sys.maxsize

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

 return 0 if min_len == sys.maxsize else min_len




