'''simple docstring'''

from typing import TYPE_CHECKING

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


__snake_case       :   List[Any]  		=    {
    '''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:
      __snake_case       :   int  		=    ['''DebertaV2TokenizerFast''']

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __snake_case       :   int  		=    [
          '''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:
      __snake_case       :   List[Any]  		=    [
          '''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

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

'''simple docstring'''

from typing import TYPE_CHECKING

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


__snake_case       :   Optional[int]  		=    {
    '''configuration_gptsan_japanese''': ['''GPTSAN_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTSanJapaneseConfig'''],
    '''tokenization_gptsan_japanese''': ['''GPTSanJapaneseTokenizer'''],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __snake_case       :   List[Any]  		=    [
          '''GPTSAN_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''GPTSanJapaneseForConditionalGeneration''',
          '''GPTSanJapaneseModel''',
          '''GPTSanJapanesePreTrainedModel''',
      ]
      __snake_case       :   Optional[int]  		=    [
          '''GPTSanJapaneseTokenizer''',
      ]


if TYPE_CHECKING:
      from .configuration_gptsan_japanese import GPTSAN_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTSanJapaneseConfig
      from .tokenization_gptsan_japanese import GPTSanJapaneseTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_gptsan_japanese import (
                GPTSAN_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST,
                GPTSanJapaneseForConditionalGeneration,
                GPTSanJapaneseModel,
                GPTSanJapanesePreTrainedModel,
            )
            from .tokenization_gptsan_japanese import GPTSanJapaneseTokenizer


else:
      import sys

      __snake_case       :   Tuple  		=    _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
