| from typing import TYPE_CHECKING |
|
|
| from ....utils import ( |
| DIFFUSERS_SLOW_IMPORT, |
| OptionalDependencyNotAvailable, |
| _LazyModule, |
| is_torch_available, |
| is_transformers_available, |
| ) |
|
|
|
|
| _dummy_objects = {} |
| _import_structure = {} |
|
|
| try: |
| if not (is_transformers_available() and is_torch_available()): |
| raise OptionalDependencyNotAvailable() |
| except OptionalDependencyNotAvailable: |
| from ....utils.dummy_torch_and_transformers_objects import ( |
| LearnedClassifierFreeSamplingEmbeddings, |
| VQDiffusionPipeline, |
| ) |
|
|
| _dummy_objects.update( |
| { |
| "LearnedClassifierFreeSamplingEmbeddings": LearnedClassifierFreeSamplingEmbeddings, |
| "VQDiffusionPipeline": VQDiffusionPipeline, |
| } |
| ) |
| else: |
| _import_structure["pipeline_vq_diffusion"] = ["LearnedClassifierFreeSamplingEmbeddings", "VQDiffusionPipeline"] |
|
|
|
|
| if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT: |
| try: |
| if not (is_transformers_available() and is_torch_available()): |
| raise OptionalDependencyNotAvailable() |
| except OptionalDependencyNotAvailable: |
| from ....utils.dummy_torch_and_transformers_objects import ( |
| LearnedClassifierFreeSamplingEmbeddings, |
| VQDiffusionPipeline, |
| ) |
| else: |
| from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline |
|
|
| else: |
| import sys |
|
|
| sys.modules[__name__] = _LazyModule( |
| __name__, |
| globals()["__file__"], |
| _import_structure, |
| module_spec=__spec__, |
| ) |
|
|
| for name, value in _dummy_objects.items(): |
| setattr(sys.modules[__name__], name, value) |
|
|