

from typing import TYPE_CHECKING

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


__lowercase     : Any       =						{
    '''configuration_roformer''': ['''ROFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RoFormerConfig''', '''RoFormerOnnxConfig'''],
    '''tokenization_roformer''': ['''RoFormerTokenizer'''],
}

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __lowercase     : Optional[Any]       =						['''RoFormerTokenizerFast''']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __lowercase     : Optional[Any]       =						[
         '''ROFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''RoFormerForCausalLM''',
         '''RoFormerForMaskedLM''',
         '''RoFormerForMultipleChoice''',
         '''RoFormerForQuestionAnswering''',
         '''RoFormerForSequenceClassification''',
         '''RoFormerForTokenClassification''',
         '''RoFormerLayer''',
         '''RoFormerModel''',
         '''RoFormerPreTrainedModel''',
         '''load_tf_weights_in_roformer''',
     ]


try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __lowercase     : int       =						[
         '''TF_ROFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''TFRoFormerForCausalLM''',
         '''TFRoFormerForMaskedLM''',
         '''TFRoFormerForMultipleChoice''',
         '''TFRoFormerForQuestionAnswering''',
         '''TFRoFormerForSequenceClassification''',
         '''TFRoFormerForTokenClassification''',
         '''TFRoFormerLayer''',
         '''TFRoFormerModel''',
         '''TFRoFormerPreTrainedModel''',
     ]


try:
     if not is_flax_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __lowercase     : List[str]       =						[
         '''FLAX_ROFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''FlaxRoFormerForMaskedLM''',
         '''FlaxRoFormerForMultipleChoice''',
         '''FlaxRoFormerForQuestionAnswering''',
         '''FlaxRoFormerForSequenceClassification''',
         '''FlaxRoFormerForTokenClassification''',
         '''FlaxRoFormerModel''',
         '''FlaxRoFormerPreTrainedModel''',
     ]


if TYPE_CHECKING:
     from .configuration_roformer import ROFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, RoFormerConfig, RoFormerOnnxConfig
     from .tokenization_roformer import RoFormerTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_roformer_fast import RoFormerTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_roformer import (
              ROFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
              RoFormerForCausalLM,
              RoFormerForMaskedLM,
              RoFormerForMultipleChoice,
              RoFormerForQuestionAnswering,
              RoFormerForSequenceClassification,
              RoFormerForTokenClassification,
              RoFormerLayer,
              RoFormerModel,
              RoFormerPreTrainedModel,
              load_tf_weights_in_roformer,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_roformer import (
              TF_ROFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFRoFormerForCausalLM,
              TFRoFormerForMaskedLM,
              TFRoFormerForMultipleChoice,
              TFRoFormerForQuestionAnswering,
              TFRoFormerForSequenceClassification,
              TFRoFormerForTokenClassification,
              TFRoFormerLayer,
              TFRoFormerModel,
              TFRoFormerPreTrainedModel,
          )

     try:
          if not is_flax_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_flax_roformer import (
              FLAX_ROFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
              FlaxRoFormerForMaskedLM,
              FlaxRoFormerForMultipleChoice,
              FlaxRoFormerForQuestionAnswering,
              FlaxRoFormerForSequenceClassification,
              FlaxRoFormerForTokenClassification,
              FlaxRoFormerModel,
              FlaxRoFormerPreTrainedModel,
          )


else:
     import sys

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





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


lowercase   =	{}


try:
		if not is_sentencepiece_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase   =	['''MLukeTokenizer''']

if TYPE_CHECKING:
		try:
				if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_mluke import MLukeTokenizer


else:
		import sys

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





