code: 
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_torch_available,
  )
  
  
  SCREAMING_SNAKE_CASE : List[str]          =    {
      "configuration_bark": [
          "BARK_PRETRAINED_CONFIG_ARCHIVE_MAP",
          "BarkCoarseConfig",
          "BarkConfig",
          "BarkFineConfig",
          "BarkSemanticConfig",
      ],
      "processing_bark": ["BarkProcessor"],
  }
  
  try:
  	if not is_torch_available():
  		raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  	pass
  else:
  	SCREAMING_SNAKE_CASE : Optional[int]          =    [
  	    "BARK_PRETRAINED_MODEL_ARCHIVE_LIST",
  	    "BarkFineModel",
  	    "BarkSemanticModel",
  	    "BarkCoarseModel",
  	    "BarkModel",
  	    "BarkPreTrainedModel",
  	    "BarkCausalModel",
  	]
  
  if TYPE_CHECKING:
  	from .configuration_bark import (
  	    BARK_PRETRAINED_CONFIG_ARCHIVE_MAP,
  	    BarkCoarseConfig,
  	    BarkConfig,
  	    BarkFineConfig,
  	    BarkSemanticConfig,
  	)
  	from .processing_bark import BarkProcessor
  
  	try:
  		if not is_torch_available():
  			raise OptionalDependencyNotAvailable()
  	except OptionalDependencyNotAvailable:
  		pass
  	else:
  		from .modeling_bark import (
  		    BARK_PRETRAINED_MODEL_ARCHIVE_LIST,
  		    BarkCausalModel,
  		    BarkCoarseModel,
  		    BarkFineModel,
  		    BarkModel,
  		    BarkPreTrainedModel,
  		    BarkSemanticModel,
  		)
  
  else:
  	import sys
  
  	SCREAMING_SNAKE_CASE : Tuple          =    _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
  
  
  
style_context: 
  
  
  from ...utils import is_transformers_available
  from .pipeline_latent_diffusion_superresolution import LDMSuperResolutionPipeline
  
  
  if is_transformers_available():
  	from .pipeline_latent_diffusion import LDMBertModel, LDMTextToImagePipeline
  
  
  