


from typing import TYPE_CHECKING

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


__a   				=      {
    """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:
  __a   				=      ["""DebertaV2TokenizerFast"""]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __a   				=      [
      """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:
  __a   				=      [
      """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

  __a   				=      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__a   				=      {
    '''configuration_decision_transformer''': [
        '''DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''DecisionTransformerConfig''',
    ],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __a   				=      [
      '''DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''DecisionTransformerGPT2Model''',
      '''DecisionTransformerGPT2PreTrainedModel''',
      '''DecisionTransformerModel''',
      '''DecisionTransformerPreTrainedModel''',
  ]


if TYPE_CHECKING:
  from .configuration_decision_transformer import (
      DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
      DecisionTransformerConfig,
  )

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_decision_transformer import (
        DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        DecisionTransformerGPTaModel,
        DecisionTransformerGPTaPreTrainedModel,
        DecisionTransformerModel,
        DecisionTransformerPreTrainedModel,
    )


else:
  import sys

  __a   				=      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

