
"""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 			lowerCAmelCase_		(__lowerCamelCase						):


				"""simple docstring"""



				__UpperCamelCase   :		Union[List[PIL.Image.Image], np.ndarray]
				__UpperCamelCase   :		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 			lowerCAmelCase_		(__lowerCamelCase						):


									"""simple docstring"""



									__UpperCamelCase   :		np.ndarray
									__UpperCamelCase   :		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"""




import logging

from transformers import PretrainedConfig


UpperCAmelCase__   :					Union[str, Any]												=				logging.getLogger(__name__)


UpperCAmelCase__   :					Any												=				{
    'bertabs-finetuned-cnndm': 'https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/config.json',
}



class 			lowerCAmelCase_		(a__						):


				"""simple docstring"""



				__UpperCamelCase   :		List[Any]       =     '''bertabs'''



				def __init__(self     , SCREAMING_SNAKE_CASE__=3_05_22     , SCREAMING_SNAKE_CASE__=5_12     , SCREAMING_SNAKE_CASE__=6     , SCREAMING_SNAKE_CASE__=5_12     , SCREAMING_SNAKE_CASE__=8     , SCREAMING_SNAKE_CASE__=5_12     , SCREAMING_SNAKE_CASE__=0.2     , SCREAMING_SNAKE_CASE__=6     , SCREAMING_SNAKE_CASE__=7_68     , SCREAMING_SNAKE_CASE__=8     , SCREAMING_SNAKE_CASE__=20_48     , SCREAMING_SNAKE_CASE__=0.2     , **SCREAMING_SNAKE_CASE__     , )      ->	Union[str, Any]:



											"""simple docstring"""




											super().__init__(**SCREAMING_SNAKE_CASE__					)

											SCREAMING_SNAKE_CASE__		: Optional[Any]     =     vocab_size
											SCREAMING_SNAKE_CASE__		: Any     =     max_pos

											SCREAMING_SNAKE_CASE__		: List[Any]     =     enc_layers
											SCREAMING_SNAKE_CASE__		: Tuple     =     enc_hidden_size
											SCREAMING_SNAKE_CASE__		: Dict     =     enc_heads
											SCREAMING_SNAKE_CASE__		: Optional[Any]     =     enc_ff_size
											SCREAMING_SNAKE_CASE__		: Dict     =     enc_dropout

											SCREAMING_SNAKE_CASE__		: Any     =     dec_layers
											SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     dec_hidden_size
											SCREAMING_SNAKE_CASE__		: Any     =     dec_heads
											SCREAMING_SNAKE_CASE__		: List[Any]     =     dec_ff_size
											SCREAMING_SNAKE_CASE__		: str     =     dec_dropout




