
'''simple docstring'''

from typing import TYPE_CHECKING

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


__UpperCAmelCase												=   {
    '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:
   __UpperCAmelCase												=   ['DebertaV2TokenizerFast']

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __UpperCAmelCase												=   [
       '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:
   __UpperCAmelCase												=   [
       '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

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




'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__UpperCAmelCase												=   {'configuration_sew_d': ['SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SEWDConfig']}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __UpperCAmelCase												=   [
       'SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST',
       'SEWDForCTC',
       'SEWDForSequenceClassification',
       'SEWDModel',
       'SEWDPreTrainedModel',
   ]

if TYPE_CHECKING:
   from .configuration_sew_d import SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWDConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_sew_d import (
          SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST,
          SEWDForCTC,
          SEWDForSequenceClassification,
          SEWDModel,
          SEWDPreTrainedModel,
      )


else:
   import sys

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


