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# 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__)
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