# 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["unets.unet_1d"] = ["UNet1DModel"]

_import_structure["unets.unet_2d"] = ["UNet2DModel"]

_import_structure["unets.unet_2d_condition"] = ["UNet2DConditionModel"]

_import_structure["unets.unet_3d_condition"] = ["UNet3DConditionModel"]

_import_structure["unets.unet_kandinsky3"] = ["Kandinsky3UNet"]

_import_structure["unets.unet_motion_model"] = ["MotionAdapter", "UNetMotionModel"]

_import_structure["unets.unet_spatio_temporal_condition"] = ["UNetSpatioTemporalConditionModel"]

_import_structure["unets.uvit_2d"] = ["UVit2DModel"]

_import_structure["vq_model"] = ["VQModel"]

if is_flax_available():

_import_structure["controlnet_flax"] = ["FlaxControlNetModel"]

_import_structure["unets.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 .unets import (

Kandinsky3UNet,

MotionAdapter,

UNet1DModel,

UNet2DConditionModel,

UNet2DModel,

UNet3DConditionModel,

UNetMotionModel,

UNetSpatioTemporalConditionModel,

UVit2DModel,

)

from .vq_model import VQModel

if is_flax_available():

from .controlnet_flax import FlaxControlNetModel

from .unets import FlaxUNet2DConditionModel

from .vae_flax import FlaxAutoencoderKL

else:

import sys

sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)