'''simple docstring'''


from typing import TYPE_CHECKING

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


__snake_case						  =		{
    """configuration_distilbert""": [
        """DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """DistilBertConfig""",
        """DistilBertOnnxConfig""",
    ],
    """tokenization_distilbert""": ["""DistilBertTokenizer"""],
}

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

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __snake_case						  =		[
           """DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """DistilBertForMaskedLM""",
           """DistilBertForMultipleChoice""",
           """DistilBertForQuestionAnswering""",
           """DistilBertForSequenceClassification""",
           """DistilBertForTokenClassification""",
           """DistilBertModel""",
           """DistilBertPreTrainedModel""",
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __snake_case						  =		[
           """TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """TFDistilBertForMaskedLM""",
           """TFDistilBertForMultipleChoice""",
           """TFDistilBertForQuestionAnswering""",
           """TFDistilBertForSequenceClassification""",
           """TFDistilBertForTokenClassification""",
           """TFDistilBertMainLayer""",
           """TFDistilBertModel""",
           """TFDistilBertPreTrainedModel""",
       ]

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __snake_case						  =		[
           """FlaxDistilBertForMaskedLM""",
           """FlaxDistilBertForMultipleChoice""",
           """FlaxDistilBertForQuestionAnswering""",
           """FlaxDistilBertForSequenceClassification""",
           """FlaxDistilBertForTokenClassification""",
           """FlaxDistilBertModel""",
           """FlaxDistilBertPreTrainedModel""",
       ]


if TYPE_CHECKING:
       from .configuration_distilbert import (
           DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
           DistilBertConfig,
           DistilBertOnnxConfig,
       )
       from .tokenization_distilbert import DistilBertTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_distilbert_fast import DistilBertTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_distilbert import (
                  DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  DistilBertForMaskedLM,
                  DistilBertForMultipleChoice,
                  DistilBertForQuestionAnswering,
                  DistilBertForSequenceClassification,
                  DistilBertForTokenClassification,
                  DistilBertModel,
                  DistilBertPreTrainedModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_distilbert import (
                  TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFDistilBertForMaskedLM,
                  TFDistilBertForMultipleChoice,
                  TFDistilBertForQuestionAnswering,
                  TFDistilBertForSequenceClassification,
                  TFDistilBertForTokenClassification,
                  TFDistilBertMainLayer,
                  TFDistilBertModel,
                  TFDistilBertPreTrainedModel,
              )

       try:
              if not is_flax_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_flax_distilbert import (
                  FlaxDistilBertForMaskedLM,
                  FlaxDistilBertForMultipleChoice,
                  FlaxDistilBertForQuestionAnswering,
                  FlaxDistilBertForSequenceClassification,
                  FlaxDistilBertForTokenClassification,
                  FlaxDistilBertModel,
                  FlaxDistilBertPreTrainedModel,
              )

else:
       import sys

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


'''simple docstring'''


from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__snake_case						  =		{"""configuration_focalnet""": ["""FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FocalNetConfig"""]}


try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __snake_case						  =		[
           """FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """FocalNetForImageClassification""",
           """FocalNetForMaskedImageModeling""",
           """FocalNetBackbone""",
           """FocalNetModel""",
           """FocalNetPreTrainedModel""",
       ]

if TYPE_CHECKING:
       from .configuration_focalnet import FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FocalNetConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_focalnet import (
                  FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST,
                  FocalNetBackbone,
                  FocalNetForImageClassification,
                  FocalNetForMaskedImageModeling,
                  FocalNetModel,
                  FocalNetPreTrainedModel,
              )

else:
       import sys

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

