"""simple docstring"""


from typing import TYPE_CHECKING

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


__UpperCamelCase									=			{
    'configuration_bridgetower': [
        'BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'BridgeTowerConfig',
        'BridgeTowerTextConfig',
        'BridgeTowerVisionConfig',
    ],
    'processing_bridgetower': ['BridgeTowerProcessor'],
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __UpperCamelCase									=			['BridgeTowerImageProcessor']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __UpperCamelCase									=			[
        'BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST',
        'BridgeTowerForContrastiveLearning',
        'BridgeTowerForImageAndTextRetrieval',
        'BridgeTowerForMaskedLM',
        'BridgeTowerModel',
        'BridgeTowerPreTrainedModel',
    ]


if TYPE_CHECKING:
    from .configuration_bridgetower import (
        BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP,
        BridgeTowerConfig,
        BridgeTowerTextConfig,
        BridgeTowerVisionConfig,
    )
    from .processing_bridgetower import BridgeTowerProcessor

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .image_processing_bridgetower import BridgeTowerImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_bridgetower import (
            BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST,
            BridgeTowerForContrastiveLearning,
            BridgeTowerForImageAndTextRetrieval,
            BridgeTowerForMaskedLM,
            BridgeTowerModel,
            BridgeTowerPreTrainedModel,
        )


else:
    import sys

    __UpperCamelCase									=			_LazyModule(__name__, globals()['''__file__'''], _import_structure)






"""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    :List[Any]     =					{'configuration_opt': ['OPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'OPTConfig']}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCAmelCase    :Any     =					[
      'OPT_PRETRAINED_MODEL_ARCHIVE_LIST',
      'OPTForCausalLM',
      'OPTModel',
      'OPTPreTrainedModel',
      'OPTForSequenceClassification',
      'OPTForQuestionAnswering',
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCAmelCase    :Optional[int]     =					['TFOPTForCausalLM', 'TFOPTModel', 'TFOPTPreTrainedModel']

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCAmelCase    :Any     =					[
      'FlaxOPTForCausalLM',
      'FlaxOPTModel',
      'FlaxOPTPreTrainedModel',
  ]


if TYPE_CHECKING:
  from .configuration_opt import OPT_PRETRAINED_CONFIG_ARCHIVE_MAP, OPTConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_opt import (
        OPT_PRETRAINED_MODEL_ARCHIVE_LIST,
        OPTForCausalLM,
        OPTForQuestionAnswering,
        OPTForSequenceClassification,
        OPTModel,
        OPTPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_opt import TFOPTForCausalLM, TFOPTModel, TFOPTPreTrainedModel

  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flax_opt import FlaxOPTForCausalLM, FlaxOPTModel, FlaxOPTPreTrainedModel

else:
  import sys

  _lowerCAmelCase    :int     =					_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


