


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__)






from ...utils import is_transformers_available
from .pipeline_latent_diffusion_superresolution import LDMSuperResolutionPipeline


if is_transformers_available():
	from .pipeline_latent_diffusion import LDMBertModel, LDMTextToImagePipeline


