



"""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     ):
  lowerCAmelCase_       :	Union[List[PIL.Image.Image], np.ndarray]
  lowerCAmelCase_       :	Optional[List[bool]]


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     ):
         lowerCAmelCase_       :	np.ndarray
         lowerCAmelCase_       :	List[bool]



       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"""







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


A    =			{'configuration_plbart': ['PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PLBartConfig']}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A    =			['PLBartTokenizer']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A    =			[
							    'PLBART_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'PLBartForCausalLM',
							    'PLBartForConditionalGeneration',
							    'PLBartForSequenceClassification',
							    'PLBartModel',
							    'PLBartPreTrainedModel',
							]


if TYPE_CHECKING:
							from .configuration_plbart import PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP, PLBartConfig

							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_plbart import PLBartTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_plbart import (
														    PLBART_PRETRAINED_MODEL_ARCHIVE_LIST,
														    PLBartForCausalLM,
														    PLBartForConditionalGeneration,
														    PLBartForSequenceClassification,
														    PLBartModel,
														    PLBartPreTrainedModel,
														)


else:
							import sys

							A    =			_LazyModule(__name__, globals()['__file__'], _import_structure)



