
"""simple docstring"""




from typing import TYPE_CHECKING

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


snake_case					  =						{
    'configuration_videomae': ['VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'VideoMAEConfig'],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	snake_case					  =						[
	    'VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'VideoMAEForPreTraining',
	    'VideoMAEModel',
	    'VideoMAEPreTrainedModel',
	    'VideoMAEForVideoClassification',
	]

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	snake_case					  =						['VideoMAEFeatureExtractor']
	snake_case					  =						['VideoMAEImageProcessor']

if TYPE_CHECKING:
	from .configuration_videomae import VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP, VideoMAEConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_videomae import (
		    VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST,
		    VideoMAEForPreTraining,
		    VideoMAEForVideoClassification,
		    VideoMAEModel,
		    VideoMAEPreTrainedModel,
		)

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .feature_extraction_videomae import VideoMAEFeatureExtractor
		from .image_processing_videomae import VideoMAEImageProcessor

else:
	import sys

	snake_case					  =						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)








"""simple docstring"""





from typing import TYPE_CHECKING

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


UpperCamelCase					=     {
    """configuration_led""": ["""LED_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LEDConfig"""],
    """tokenization_led""": ["""LEDTokenizer"""],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase					=     ["""LEDTokenizerFast"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase					=     [
      """LED_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """LEDForConditionalGeneration""",
      """LEDForQuestionAnswering""",
      """LEDForSequenceClassification""",
      """LEDModel""",
      """LEDPreTrainedModel""",
  ]


try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase					=     ["""TFLEDForConditionalGeneration""", """TFLEDModel""", """TFLEDPreTrainedModel"""]


if TYPE_CHECKING:
  from .configuration_led import LED_PRETRAINED_CONFIG_ARCHIVE_MAP, LEDConfig
  from .tokenization_led import LEDTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_led_fast import LEDTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_led import (
        LED_PRETRAINED_MODEL_ARCHIVE_LIST,
        LEDForConditionalGeneration,
        LEDForQuestionAnswering,
        LEDForSequenceClassification,
        LEDModel,
        LEDPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_led import TFLEDForConditionalGeneration, TFLEDModel, TFLEDPreTrainedModel

else:
  import sys

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






