"""simple docstring"""







from typing import TYPE_CHECKING

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


_SCREAMING_SNAKE_CASE	:		Optional[Any]   =   {
    '''configuration_big_bird''': ['''BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BigBirdConfig''', '''BigBirdOnnxConfig'''],
}

try:
     if not is_sentencepiece_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _SCREAMING_SNAKE_CASE	:		Dict   =   ['''BigBirdTokenizer''']

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _SCREAMING_SNAKE_CASE	:		List[str]   =   ['''BigBirdTokenizerFast''']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _SCREAMING_SNAKE_CASE	:		Union[str, Any]   =   [
         '''BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''BigBirdForCausalLM''',
         '''BigBirdForMaskedLM''',
         '''BigBirdForMultipleChoice''',
         '''BigBirdForPreTraining''',
         '''BigBirdForQuestionAnswering''',
         '''BigBirdForSequenceClassification''',
         '''BigBirdForTokenClassification''',
         '''BigBirdLayer''',
         '''BigBirdModel''',
         '''BigBirdPreTrainedModel''',
         '''load_tf_weights_in_big_bird''',
     ]

try:
     if not is_flax_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _SCREAMING_SNAKE_CASE	:		Any   =   [
         '''FlaxBigBirdForCausalLM''',
         '''FlaxBigBirdForMaskedLM''',
         '''FlaxBigBirdForMultipleChoice''',
         '''FlaxBigBirdForPreTraining''',
         '''FlaxBigBirdForQuestionAnswering''',
         '''FlaxBigBirdForSequenceClassification''',
         '''FlaxBigBirdForTokenClassification''',
         '''FlaxBigBirdModel''',
         '''FlaxBigBirdPreTrainedModel''',
     ]

if TYPE_CHECKING:
     from .configuration_big_bird import BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP, BigBirdConfig, BigBirdOnnxConfig

     try:
          if not is_sentencepiece_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_big_bird import BigBirdTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_big_bird_fast import BigBirdTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_big_bird import (
              BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST,
              BigBirdForCausalLM,
              BigBirdForMaskedLM,
              BigBirdForMultipleChoice,
              BigBirdForPreTraining,
              BigBirdForQuestionAnswering,
              BigBirdForSequenceClassification,
              BigBirdForTokenClassification,
              BigBirdLayer,
              BigBirdModel,
              BigBirdPreTrainedModel,
              load_tf_weights_in_big_bird,
          )

     try:
          if not is_flax_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_flax_big_bird import (
              FlaxBigBirdForCausalLM,
              FlaxBigBirdForMaskedLM,
              FlaxBigBirdForMultipleChoice,
              FlaxBigBirdForPreTraining,
              FlaxBigBirdForQuestionAnswering,
              FlaxBigBirdForSequenceClassification,
              FlaxBigBirdForTokenClassification,
              FlaxBigBirdModel,
              FlaxBigBirdPreTrainedModel,
          )

else:
     import sys

     _SCREAMING_SNAKE_CASE	:		str   =   _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)











from typing import TYPE_CHECKING

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


UpperCamelCase_      			=  {
    "configuration_mobilenet_v1": [
        "MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "MobileNetV1Config",
        "MobileNetV1OnnxConfig",
    ],
}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase_      			=  ["MobileNetV1FeatureExtractor"]
							UpperCamelCase_      			=  ["MobileNetV1ImageProcessor"]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase_      			=  [
							    "MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "MobileNetV1ForImageClassification",
							    "MobileNetV1Model",
							    "MobileNetV1PreTrainedModel",
							    "load_tf_weights_in_mobilenet_v1",
							]


if TYPE_CHECKING:
							from .configuration_mobilenet_va import (
							    MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    MobileNetVaConfig,
							    MobileNetVaOnnxConfig,
							)

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_mobilenet_va import MobileNetVaFeatureExtractor
														from .image_processing_mobilenet_va import MobileNetVaImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_mobilenet_va import (
														    MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MobileNetVaForImageClassification,
														    MobileNetVaModel,
														    MobileNetVaPreTrainedModel,
														    load_tf_weights_in_mobilenet_va,
														)


else:
							import sys

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





