# 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 ..utils import _LazyModule, is_flax_available, is_torch_available _import_structure = {} if is_torch_available(): _import_structure["adapter"] = ["MultiAdapter", "T2IAdapter"] _import_structure["autoencoder_asym_kl"] = ["AsymmetricAutoencoderKL"] _import_structure["autoencoder_kl"] = ["AutoencoderKL"] _import_structure["autoencoder_tiny"] = ["AutoencoderTiny"] _import_structure["controlnet"] = ["ControlNetModel"] _import_structure["dual_transformer_2d"] = ["DualTransformer2DModel"] _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["vq_model"] = ["VQModel"] if is_flax_available(): _import_structure["controlnet_flax"] = ["FlaxControlNetModel"] _import_structure["unet_2d_condition_flax"] = ["FlaxUNet2DConditionModel"] _import_structure["vae_flax"] = ["FlaxAutoencoderKL"] import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)