from typing import TYPE_CHECKING from ...utils import ( DIFFUSERS_SLOW_IMPORT, OptionalDependencyNotAvailable, _LazyModule, get_objects_from_module, 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 import dummy_torch_and_transformers_objects # noqa F403 _dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects)) else: _import_structure["camera"] = ["create_pan_cameras"] _import_structure["pipeline_shap_e"] = ["ShapEPipeline"] _import_structure["pipeline_shap_e_img2img"] = ["ShapEImg2ImgPipeline"] _import_structure["renderer"] = [ "BoundingBoxVolume", "ImportanceRaySampler", "MLPNeRFModelOutput", "MLPNeRSTFModel", "ShapEParamsProjModel", "ShapERenderer", "StratifiedRaySampler", "VoidNeRFModel", ] 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 * else: from .camera import create_pan_cameras from .pipeline_shap_e import ShapEPipeline from .pipeline_shap_e_img2img import ShapEImg2ImgPipeline from .renderer import ( BoundingBoxVolume, ImportanceRaySampler, MLPNeRFModelOutput, MLPNeRSTFModel, ShapEParamsProjModel, ShapERenderer, StratifiedRaySampler, VoidNeRFModel, ) 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)