# Copyright 2023 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from typing import TYPE_CHECKING from ..utils import ( DIFFUSERS_SLOW_IMPORT, _LazyModule, is_flax_available, is_torch_available, ) _import_structure = {} if is_torch_available(): _import_structure["adapter"] = ["MultiAdapter", "T2IAdapter"] _import_structure["autoencoders.autoencoder_asym_kl"] = ["AsymmetricAutoencoderKL"] _import_structure["autoencoders.autoencoder_kl"] = ["AutoencoderKL"] _import_structure["autoencoders.autoencoder_kl_temporal_decoder"] = ["AutoencoderKLTemporalDecoder"] _import_structure["autoencoders.autoencoder_tiny"] = ["AutoencoderTiny"] _import_structure["autoencoders.consistency_decoder_vae"] = ["ConsistencyDecoderVAE"] _import_structure["controlnet"] = ["ControlNetModel"] _import_structure["dual_transformer_2d"] = ["DualTransformer2DModel"] _import_structure["embeddings"] = ["ImageProjection"] _import_structure["modeling_utils"] = ["ModelMixin"] _import_structure["prior_transformer"] = ["PriorTransformer"] _import_structure["t5_film_transformer"] = ["T5FilmDecoder"] _import_structure["transformer_2d"] = ["Transformer2DModel"] _import_structure["transformer_temporal"] = ["TransformerTemporalModel"] _import_structure["unet_1d"] = ["UNet1DModel"] _import_structure["unet_2d"] = ["UNet2DModel"] _import_structure["unet_2d_condition"] = ["UNet2DConditionModel"] _import_structure["unet_3d_condition"] = ["UNet3DConditionModel"] _import_structure["unet_kandinsky3"] = ["Kandinsky3UNet"] _import_structure["unet_motion_model"] = ["MotionAdapter", "UNetMotionModel"] _import_structure["unet_spatio_temporal_condition"] = ["UNetSpatioTemporalConditionModel"] _import_structure["uvit_2d"] = ["UVit2DModel"] _import_structure["vq_model"] = ["VQModel"] if is_flax_available(): _import_structure["controlnet_flax"] = ["FlaxControlNetModel"] _import_structure["unet_2d_condition_flax"] = ["FlaxUNet2DConditionModel"] _import_structure["vae_flax"] = ["FlaxAutoencoderKL"] if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT: if is_torch_available(): from .adapter import MultiAdapter, T2IAdapter from .autoencoders import ( AsymmetricAutoencoderKL, AutoencoderKL, AutoencoderKLTemporalDecoder, AutoencoderTiny, ConsistencyDecoderVAE, ) from .controlnet import ControlNetModel from .dual_transformer_2d import DualTransformer2DModel from .embeddings import ImageProjection from .modeling_utils import ModelMixin from .prior_transformer import PriorTransformer from .t5_film_transformer import T5FilmDecoder from .transformer_2d import Transformer2DModel from .transformer_temporal import TransformerTemporalModel from .unet_1d import UNet1DModel from .unet_2d import UNet2DModel from .unet_2d_condition import UNet2DConditionModel from .unet_3d_condition import UNet3DConditionModel from .unet_kandinsky3 import Kandinsky3UNet from .unet_motion_model import MotionAdapter, UNetMotionModel from .unet_spatio_temporal_condition import UNetSpatioTemporalConditionModel from .uvit_2d import UVit2DModel from .vq_model import VQModel if is_flax_available(): from .controlnet_flax import FlaxControlNetModel from .unet_2d_condition_flax import FlaxUNet2DConditionModel from .vae_flax import FlaxAutoencoderKL else: import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)