





'''simple docstring'''

from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL
from PIL import Image

from ...utils import (
    BaseOutput,
    OptionalDependencyNotAvailable,
    is_flax_available,
    is_k_diffusion_available,
    is_k_diffusion_version,
    is_onnx_available,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)






@dataclass
class   UpperCAmelCase      (			UpperCamelCase__							):
 __lowercase  						=							42
 __lowercase  						=							42


try:
  if not (is_transformers_available() and is_torch_available()):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
  from .pipeline_cycle_diffusion import CycleDiffusionPipeline
  from .pipeline_stable_diffusion import StableDiffusionPipeline
  from .pipeline_stable_diffusion_attend_and_excite import StableDiffusionAttendAndExcitePipeline
  from .pipeline_stable_diffusion_imgaimg import StableDiffusionImgaImgPipeline
  from .pipeline_stable_diffusion_inpaint import StableDiffusionInpaintPipeline
  from .pipeline_stable_diffusion_inpaint_legacy import StableDiffusionInpaintPipelineLegacy
  from .pipeline_stable_diffusion_instruct_pixapix import StableDiffusionInstructPixaPixPipeline
  from .pipeline_stable_diffusion_latent_upscale import StableDiffusionLatentUpscalePipeline
  from .pipeline_stable_diffusion_ldmad import StableDiffusionLDMaDPipeline
  from .pipeline_stable_diffusion_model_editing import StableDiffusionModelEditingPipeline
  from .pipeline_stable_diffusion_panorama import StableDiffusionPanoramaPipeline
  from .pipeline_stable_diffusion_paradigms import StableDiffusionParadigmsPipeline
  from .pipeline_stable_diffusion_sag import StableDiffusionSAGPipeline
  from .pipeline_stable_diffusion_upscale import StableDiffusionUpscalePipeline
  from .pipeline_stable_unclip import StableUnCLIPPipeline
  from .pipeline_stable_unclip_imgaimg import StableUnCLIPImgaImgPipeline
  from .safety_checker import StableDiffusionSafetyChecker
  from .stable_unclip_image_normalizer import StableUnCLIPImageNormalizer

try:
  if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ...utils.dummy_torch_and_transformers_objects import StableDiffusionImageVariationPipeline
else:
  from .pipeline_stable_diffusion_image_variation import StableDiffusionImageVariationPipeline


try:
  if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.26.0")):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ...utils.dummy_torch_and_transformers_objects import (
      StableDiffusionDepthaImgPipeline,
      StableDiffusionDiffEditPipeline,
      StableDiffusionPixaPixZeroPipeline,
  )
else:
  from .pipeline_stable_diffusion_depthaimg import StableDiffusionDepthaImgPipeline
  from .pipeline_stable_diffusion_diffedit import StableDiffusionDiffEditPipeline
  from .pipeline_stable_diffusion_pixapix_zero import StableDiffusionPixaPixZeroPipeline


try:
  if not (
      is_torch_available()
      and is_transformers_available()
      and is_k_diffusion_available()
      and is_k_diffusion_version(">=", "0.0.12")
  ):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ...utils.dummy_torch_and_transformers_and_k_diffusion_objects import *  # noqa F403
else:
  from .pipeline_stable_diffusion_k_diffusion import StableDiffusionKDiffusionPipeline

try:
  if not (is_transformers_available() and is_onnx_available()):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ...utils.dummy_onnx_objects import *  # noqa F403
else:
  from .pipeline_onnx_stable_diffusion import OnnxStableDiffusionPipeline, StableDiffusionOnnxPipeline
  from .pipeline_onnx_stable_diffusion_imgaimg import OnnxStableDiffusionImgaImgPipeline
  from .pipeline_onnx_stable_diffusion_inpaint import OnnxStableDiffusionInpaintPipeline
  from .pipeline_onnx_stable_diffusion_inpaint_legacy import OnnxStableDiffusionInpaintPipelineLegacy
  from .pipeline_onnx_stable_diffusion_upscale import OnnxStableDiffusionUpscalePipeline

if is_transformers_available() and is_flax_available():
  import flax






  @flax.struct.dataclass
  class   UpperCAmelCase      (			UpperCamelCase__							):
   __lowercase  						=							42
   __lowercase  						=							42

  from ...schedulers.scheduling_pndm_flax import PNDMSchedulerState
  from .pipeline_flax_stable_diffusion import FlaxStableDiffusionPipeline
  from .pipeline_flax_stable_diffusion_imgaimg import FlaxStableDiffusionImgaImgPipeline
  from .pipeline_flax_stable_diffusion_inpaint import FlaxStableDiffusionInpaintPipeline
  from .safety_checker_flax import FlaxStableDiffusionSafetyChecker










'''simple docstring'''

# 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

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__lowerCAmelCase				:      Optional[int]						      ={
    "configuration_vivit": ["VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "VivitConfig"],
}
try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __lowerCAmelCase				:      int						      =["VivitImageProcessor"]


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __lowerCAmelCase				:      int						      =[
      "VIVIT_PRETRAINED_MODEL_ARCHIVE_LIST",
      "VivitModel",
      "VivitPreTrainedModel",
      "VivitForVideoClassification",
  ]


if TYPE_CHECKING:
  from .configuration_vivit import VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, VivitConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .image_processing_vivit import VivitImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_vivit import (
        VIVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
        VivitForVideoClassification,
        VivitModel,
        VivitPreTrainedModel,
    )


else:
  import sys

  __lowerCAmelCase				:      List[Any]						      =_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



