





"""simple docstring"""


from typing import TYPE_CHECKING

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


a__       :  Optional[int]       		=					{"""configuration_regnet""": ["""REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """RegNetConfig"""]}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   a__       :  Any       		=					[
       """REGNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """RegNetForImageClassification""",
       """RegNetModel""",
       """RegNetPreTrainedModel""",
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   a__       :  str       		=					[
       """TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """TFRegNetForImageClassification""",
       """TFRegNetModel""",
       """TFRegNetPreTrainedModel""",
   ]

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   a__       :  Dict       		=					[
       """FlaxRegNetForImageClassification""",
       """FlaxRegNetModel""",
       """FlaxRegNetPreTrainedModel""",
   ]


if TYPE_CHECKING:
   from .configuration_regnet import REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP, RegNetConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_regnet import (
          REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
          RegNetForImageClassification,
          RegNetModel,
          RegNetPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_regnet import (
          TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFRegNetForImageClassification,
          TFRegNetModel,
          TFRegNetPreTrainedModel,
      )

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_regnet import (
          FlaxRegNetForImageClassification,
          FlaxRegNetModel,
          FlaxRegNetPreTrainedModel,
      )


else:
   import sys

   a__       :  int       		=					_LazyModule(__name__, globals()["""__file__"""], _import_structure)








"""simple docstring"""


from typing import TYPE_CHECKING

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


a__       :  List[Any]       		=					{
    """configuration_realm""": ["""REALM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """RealmConfig"""],
    """tokenization_realm""": ["""RealmTokenizer"""],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   a__       :  Union[str, Any]       		=					["""RealmTokenizerFast"""]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   a__       :  Dict       		=					[
       """REALM_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """RealmEmbedder""",
       """RealmForOpenQA""",
       """RealmKnowledgeAugEncoder""",
       """RealmPreTrainedModel""",
       """RealmReader""",
       """RealmScorer""",
       """load_tf_weights_in_realm""",
   ]
   a__       :  Any       		=					["""RealmRetriever"""]


if TYPE_CHECKING:
   from .configuration_realm import REALM_PRETRAINED_CONFIG_ARCHIVE_MAP, RealmConfig
   from .tokenization_realm import RealmTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_realm import RealmTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_realm import (
          REALM_PRETRAINED_MODEL_ARCHIVE_LIST,
          RealmEmbedder,
          RealmForOpenQA,
          RealmKnowledgeAugEncoder,
          RealmPreTrainedModel,
          RealmReader,
          RealmScorer,
          load_tf_weights_in_realm,
      )
      from .retrieval_realm import RealmRetriever


else:
   import sys

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

