




from typing import TYPE_CHECKING

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


UpperCamelCase__       				=	{
    '''configuration_imagegpt''': ['''IMAGEGPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ImageGPTConfig''', '''ImageGPTOnnxConfig''']
}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase__       				=	['''ImageGPTFeatureExtractor''']
  UpperCamelCase__       				=	['''ImageGPTImageProcessor''']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase__       				=	[
      '''IMAGEGPT_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''ImageGPTForCausalImageModeling''',
      '''ImageGPTForImageClassification''',
      '''ImageGPTModel''',
      '''ImageGPTPreTrainedModel''',
      '''load_tf_weights_in_imagegpt''',
  ]


if TYPE_CHECKING:
  from .configuration_imagegpt import IMAGEGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, ImageGPTConfig, ImageGPTOnnxConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_imagegpt import ImageGPTFeatureExtractor
    from .image_processing_imagegpt import ImageGPTImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_imagegpt import (
        IMAGEGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
        ImageGPTForCausalImageModeling,
        ImageGPTForImageClassification,
        ImageGPTModel,
        ImageGPTPreTrainedModel,
        load_tf_weights_in_imagegpt,
    )

else:
  import sys

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





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_speech_available,
    is_torch_available,
)


__A       ={
    "configuration_speech_to_text_2": ["SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Speech2Text2Config"],
    "processing_speech_to_text_2": ["Speech2Text2Processor"],
    "tokenization_speech_to_text_2": ["Speech2Text2Tokenizer"],
}


try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__A       =[
				    "SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST",
				    "Speech2Text2ForCausalLM",
				    "Speech2Text2PreTrainedModel",
				]


if TYPE_CHECKING:
				from .configuration_speech_to_text_a import SPEECH_TO_TEXT_2_PRETRAINED_CONFIG_ARCHIVE_MAP, SpeechaTextaConfig
				from .processing_speech_to_text_a import SpeechaTextaProcessor
				from .tokenization_speech_to_text_a import SpeechaTextaTokenizer

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_speech_to_text_a import (
								    SPEECH_TO_TEXT_2_PRETRAINED_MODEL_ARCHIVE_LIST,
								    SpeechaTextaForCausalLM,
								    SpeechaTextaPreTrainedModel,
								)

else:
				import sys

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





