



"""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__			(   A__      ):

			"""simple docstring"""


			A__	:					List[str]							  =     4_2
			A__	:					Dict							  =     4_2


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__			(   A__      ):

						"""simple docstring"""


						A__	:					Union[str, Any]							  =     4_2
						A__	:					Optional[Any]							  =     4_2



			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"""
import operator as op


SCREAMING_SNAKE_CASE_					     =	'''scaler.pt'''
SCREAMING_SNAKE_CASE_					     =	'''pytorch_model'''
SCREAMING_SNAKE_CASE_					     =	'''random_states'''
SCREAMING_SNAKE_CASE_					     =	'''optimizer'''
SCREAMING_SNAKE_CASE_					     =	'''scheduler'''
SCREAMING_SNAKE_CASE_					     =	'''pytorch_model.bin'''
SCREAMING_SNAKE_CASE_					     =	'''pytorch_model.bin.index.json'''
SCREAMING_SNAKE_CASE_					     =	'''model.safetensors'''
SCREAMING_SNAKE_CASE_					     =	'''model.safetensors.index.json'''
SCREAMING_SNAKE_CASE_					     =	'''1.10.2'''
SCREAMING_SNAKE_CASE_					     =	'''py38'''
SCREAMING_SNAKE_CASE_					     =	'''4.17.0'''
SCREAMING_SNAKE_CASE_					     =	['''ml.p3.16xlarge''', '''ml.p3dn.24xlarge''', '''ml.p4dn.24xlarge''']
SCREAMING_SNAKE_CASE_					     =	['''FULL_SHARD''', '''SHARD_GRAD_OP''', '''NO_SHARD''', '''HYBRID_SHARD''', '''HYBRID_SHARD_ZERO2''']
SCREAMING_SNAKE_CASE_					     =	['''TRANSFORMER_BASED_WRAP''', '''SIZE_BASED_WRAP''', '''NO_WRAP''']
SCREAMING_SNAKE_CASE_					     =	['''BACKWARD_PRE''', '''BACKWARD_POST''', '''NO_PREFETCH''']
SCREAMING_SNAKE_CASE_					     =	['''FULL_STATE_DICT''', '''LOCAL_STATE_DICT''', '''SHARDED_STATE_DICT''']
SCREAMING_SNAKE_CASE_					     =	'''2.0.1'''
SCREAMING_SNAKE_CASE_					     =	['''pdsh''', '''standard''', '''openmpi''', '''mvapich''']
SCREAMING_SNAKE_CASE_					     =	['''default''', '''reduce-overhead''', '''max-autotune''']

SCREAMING_SNAKE_CASE_					     =	{'''>''': op.gt, '''>=''': op.ge, '''==''': op.eq, '''!=''': op.ne, '''<=''': op.le, '''<''': op.lt}

# These are the args for `torch.distributed.launch` for pytorch < 1.9
SCREAMING_SNAKE_CASE_					     =	[
    '''nnodes''',
    '''nproc_per_node''',
    '''rdzv_backend''',
    '''rdzv_endpoint''',
    '''rdzv_id''',
    '''rdzv_conf''',
    '''standalone''',
    '''max_restarts''',
    '''monitor_interval''',
    '''start_method''',
    '''role''',
    '''module''',
    '''m''',
    '''no_python''',
    '''run_path''',
    '''log_dir''',
    '''r''',
    '''redirects''',
    '''t''',
    '''tee''',
    '''node_rank''',
    '''master_addr''',
    '''master_port''',
]

SCREAMING_SNAKE_CASE_					     =	['''DEEPSPEED''', '''MULTI_GPU''', '''FSDP''', '''MEGATRON_LM''']
SCREAMING_SNAKE_CASE_					     =	['''DEEPSPEED''', '''MULTI_XPU''', '''FSDP''']
