



"""simple docstring"""




from typing import TYPE_CHECKING

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


_lowerCAmelCase    : int							=							{
    "configuration_electra": ["ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP", "ElectraConfig", "ElectraOnnxConfig"],
    "tokenization_electra": ["ElectraTokenizer"],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase    : int							=							["ElectraTokenizerFast"]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase    : Dict							=							[
     "ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST",
     "ElectraForCausalLM",
     "ElectraForMaskedLM",
     "ElectraForMultipleChoice",
     "ElectraForPreTraining",
     "ElectraForQuestionAnswering",
     "ElectraForSequenceClassification",
     "ElectraForTokenClassification",
     "ElectraModel",
     "ElectraPreTrainedModel",
     "load_tf_weights_in_electra",
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase    : Dict							=							[
     "TF_ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST",
     "TFElectraForMaskedLM",
     "TFElectraForMultipleChoice",
     "TFElectraForPreTraining",
     "TFElectraForQuestionAnswering",
     "TFElectraForSequenceClassification",
     "TFElectraForTokenClassification",
     "TFElectraModel",
     "TFElectraPreTrainedModel",
 ]

try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase    : List[str]							=							[
     "FlaxElectraForCausalLM",
     "FlaxElectraForMaskedLM",
     "FlaxElectraForMultipleChoice",
     "FlaxElectraForPreTraining",
     "FlaxElectraForQuestionAnswering",
     "FlaxElectraForSequenceClassification",
     "FlaxElectraForTokenClassification",
     "FlaxElectraModel",
     "FlaxElectraPreTrainedModel",
 ]


if TYPE_CHECKING:
 from .configuration_electra import ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP, ElectraConfig, ElectraOnnxConfig
 from .tokenization_electra import ElectraTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_electra_fast import ElectraTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_electra import (
      ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST,
      ElectraForCausalLM,
      ElectraForMaskedLM,
      ElectraForMultipleChoice,
      ElectraForPreTraining,
      ElectraForQuestionAnswering,
      ElectraForSequenceClassification,
      ElectraForTokenClassification,
      ElectraModel,
      ElectraPreTrainedModel,
      load_tf_weights_in_electra,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_electra import (
      TF_ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFElectraForMaskedLM,
      TFElectraForMultipleChoice,
      TFElectraForPreTraining,
      TFElectraForQuestionAnswering,
      TFElectraForSequenceClassification,
      TFElectraForTokenClassification,
      TFElectraModel,
      TFElectraPreTrainedModel,
  )

 try:
  if not is_flax_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_flax_electra import (
      FlaxElectraForCausalLM,
      FlaxElectraForMaskedLM,
      FlaxElectraForMultipleChoice,
      FlaxElectraForPreTraining,
      FlaxElectraForQuestionAnswering,
      FlaxElectraForSequenceClassification,
      FlaxElectraForTokenClassification,
      FlaxElectraModel,
      FlaxElectraPreTrainedModel,
  )

else:
 import sys

 _lowerCAmelCase    : Tuple							=							_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





"""simple docstring"""




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


_lowerCAmelCase    : Union[str, Any]							=							{}

try:
 if not is_sentencepiece_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase    : Optional[Any]							=							["GPTSw3Tokenizer"]


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

else:
 import sys

 _lowerCAmelCase    : List[Any]							=							_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
