'''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 		SCREAMING_SNAKE_CASE     (					a__	):







				'''simple docstring'''
				UpperCAmelCase__							=							42
				UpperCAmelCase__							=							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 		SCREAMING_SNAKE_CASE     (					a__	):







							'''simple docstring'''
							UpperCAmelCase__							=							42
							UpperCAmelCase__							=							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'''





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowerCAmelCase_	:		Union[str, Any]			=     {"""configuration_opt""": ["""OPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """OPTConfig"""]}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowerCAmelCase_	:		Tuple			=     [
			    """OPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
			    """OPTForCausalLM""",
			    """OPTModel""",
			    """OPTPreTrainedModel""",
			    """OPTForSequenceClassification""",
			    """OPTForQuestionAnswering""",
			]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowerCAmelCase_	:		str			=     ["""TFOPTForCausalLM""", """TFOPTModel""", """TFOPTPreTrainedModel"""]

try:
			if not is_flax_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowerCAmelCase_	:		List[Any]			=     [
			    """FlaxOPTForCausalLM""",
			    """FlaxOPTModel""",
			    """FlaxOPTPreTrainedModel""",
			]


if TYPE_CHECKING:
			from .configuration_opt import OPT_PRETRAINED_CONFIG_ARCHIVE_MAP, OPTConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_opt import (
						    OPT_PRETRAINED_MODEL_ARCHIVE_LIST,
						    OPTForCausalLM,
						    OPTForQuestionAnswering,
						    OPTForSequenceClassification,
						    OPTModel,
						    OPTPreTrainedModel,
						)

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_opt import TFOPTForCausalLM, TFOPTModel, TFOPTPreTrainedModel

			try:
						if not is_flax_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_flax_opt import FlaxOPTForCausalLM, FlaxOPTModel, FlaxOPTPreTrainedModel

else:
			import sys

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


