






from typing import TYPE_CHECKING

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


lowerCamelCase__							=     {
    """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__							=     ["""ElectraTokenizerFast"""]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase__							=     [
         """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__							=     [
         """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__							=     [
         """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__							=     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)










from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable


lowerCamelCase__							=     {"""configuration_dpt""": ["""DPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DPTConfig"""]}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase__							=     ["""DPTFeatureExtractor"""]
     lowerCamelCase__							=     ["""DPTImageProcessor"""]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase__							=     [
         """DPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """DPTForDepthEstimation""",
         """DPTForSemanticSegmentation""",
         """DPTModel""",
         """DPTPreTrainedModel""",
     ]


if TYPE_CHECKING:
     from .configuration_dpt import DPT_PRETRAINED_CONFIG_ARCHIVE_MAP, DPTConfig

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .feature_extraction_dpt import DPTFeatureExtractor
          from .image_processing_dpt import DPTImageProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_dpt import (
              DPT_PRETRAINED_MODEL_ARCHIVE_LIST,
              DPTForDepthEstimation,
              DPTForSemanticSegmentation,
              DPTModel,
              DPTPreTrainedModel,
          )


else:
     import sys

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


