


'''simple docstring'''

from ..utils import (
    OptionalDependencyNotAvailable,
    is_flax_available,
    is_invisible_watermark_available,
    is_k_diffusion_available,
    is_librosa_available,
    is_note_seq_available,
    is_onnx_available,
    is_torch_available,
    is_transformers_available,
)


try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       from ..utils.dummy_pt_objects import *  # noqa F403
else:
       from .consistency_models import ConsistencyModelPipeline
       from .dance_diffusion import DanceDiffusionPipeline
       from .ddim import DDIMPipeline
       from .ddpm import DDPMPipeline
       from .dit import DiTPipeline
       from .latent_diffusion import LDMSuperResolutionPipeline
       from .latent_diffusion_uncond import LDMPipeline
       from .pipeline_utils import AudioPipelineOutput, DiffusionPipeline, ImagePipelineOutput
       from .pndm import PNDMPipeline
       from .repaint import RePaintPipeline
       from .score_sde_ve import ScoreSdeVePipeline
       from .stochastic_karras_ve import KarrasVePipeline

try:
       if not (is_torch_available() and is_librosa_available()):
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       from ..utils.dummy_torch_and_librosa_objects import *  # noqa F403
else:
       from .audio_diffusion import AudioDiffusionPipeline, Mel

try:
       if not (is_torch_available() and is_transformers_available()):
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       from ..utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
       from .alt_diffusion import AltDiffusionImgaImgPipeline, AltDiffusionPipeline
       from .audioldm import AudioLDMPipeline
       from .controlnet import (
           StableDiffusionControlNetImgaImgPipeline,
           StableDiffusionControlNetInpaintPipeline,
           StableDiffusionControlNetPipeline,
       )
       from .deepfloyd_if import (
           IFImgaImgPipeline,
           IFImgaImgSuperResolutionPipeline,
           IFInpaintingPipeline,
           IFInpaintingSuperResolutionPipeline,
           IFPipeline,
           IFSuperResolutionPipeline,
       )
       from .kandinsky import (
           KandinskyImgaImgPipeline,
           KandinskyInpaintPipeline,
           KandinskyPipeline,
           KandinskyPriorPipeline,
       )
       from .kandinskya_a import (
           KandinskyVaaControlnetImgaImgPipeline,
           KandinskyVaaControlnetPipeline,
           KandinskyVaaImgaImgPipeline,
           KandinskyVaaInpaintPipeline,
           KandinskyVaaPipeline,
           KandinskyVaaPriorEmbaEmbPipeline,
           KandinskyVaaPriorPipeline,
       )
       from .latent_diffusion import LDMTextToImagePipeline
       from .paint_by_example import PaintByExamplePipeline
       from .semantic_stable_diffusion import SemanticStableDiffusionPipeline
       from .shap_e import ShapEImgaImgPipeline, ShapEPipeline
       from .stable_diffusion import (
           CycleDiffusionPipeline,
           StableDiffusionAttendAndExcitePipeline,
           StableDiffusionDepthaImgPipeline,
           StableDiffusionDiffEditPipeline,
           StableDiffusionImageVariationPipeline,
           StableDiffusionImgaImgPipeline,
           StableDiffusionInpaintPipeline,
           StableDiffusionInpaintPipelineLegacy,
           StableDiffusionInstructPixaPixPipeline,
           StableDiffusionLatentUpscalePipeline,
           StableDiffusionLDMaDPipeline,
           StableDiffusionModelEditingPipeline,
           StableDiffusionPanoramaPipeline,
           StableDiffusionParadigmsPipeline,
           StableDiffusionPipeline,
           StableDiffusionPixaPixZeroPipeline,
           StableDiffusionSAGPipeline,
           StableDiffusionUpscalePipeline,
           StableUnCLIPImgaImgPipeline,
           StableUnCLIPPipeline,
       )
       from .stable_diffusion_safe import StableDiffusionPipelineSafe
       from .text_to_video_synthesis import TextToVideoSDPipeline, TextToVideoZeroPipeline, VideoToVideoSDPipeline
       from .unclip import UnCLIPImageVariationPipeline, UnCLIPPipeline
       from .unidiffuser import ImageTextPipelineOutput, UniDiffuserModel, UniDiffuserPipeline, UniDiffuserTextDecoder
       from .versatile_diffusion import (
           VersatileDiffusionDualGuidedPipeline,
           VersatileDiffusionImageVariationPipeline,
           VersatileDiffusionPipeline,
           VersatileDiffusionTextToImagePipeline,
       )
       from .vq_diffusion import VQDiffusionPipeline


try:
       if not (is_torch_available() and is_transformers_available() and is_invisible_watermark_available()):
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       from ..utils.dummy_torch_and_transformers_and_invisible_watermark_objects import *  # noqa F403
else:
       from .stable_diffusion_xl import StableDiffusionXLImgaImgPipeline, StableDiffusionXLPipeline

try:
       if not is_onnx_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       from ..utils.dummy_onnx_objects import *  # noqa F403
else:
       from .onnx_utils import OnnxRuntimeModel

try:
       if not (is_torch_available() and is_transformers_available() and is_onnx_available()):
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       from ..utils.dummy_torch_and_transformers_and_onnx_objects import *  # noqa F403
else:
       from .stable_diffusion import (
           OnnxStableDiffusionImgaImgPipeline,
           OnnxStableDiffusionInpaintPipeline,
           OnnxStableDiffusionInpaintPipelineLegacy,
           OnnxStableDiffusionPipeline,
           OnnxStableDiffusionUpscalePipeline,
           StableDiffusionOnnxPipeline,
       )

try:
       if not (is_torch_available() and is_transformers_available() and is_k_diffusion_available()):
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       from ..utils.dummy_torch_and_transformers_and_k_diffusion_objects import *  # noqa F403
else:
       from .stable_diffusion import StableDiffusionKDiffusionPipeline

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       from ..utils.dummy_flax_objects import *  # noqa F403
else:
       from .pipeline_flax_utils import FlaxDiffusionPipeline


try:
       if not (is_flax_available() and is_transformers_available()):
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       from ..utils.dummy_flax_and_transformers_objects import *  # noqa F403
else:
       from .controlnet import FlaxStableDiffusionControlNetPipeline
       from .stable_diffusion import (
           FlaxStableDiffusionImgaImgPipeline,
           FlaxStableDiffusionInpaintPipeline,
           FlaxStableDiffusionPipeline,
       )
try:
       if not (is_transformers_available() and is_torch_available() and is_note_seq_available()):
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       from ..utils.dummy_transformers_and_torch_and_note_seq_objects import *  # noqa F403
else:
       from .spectrogram_diffusion import MidiProcessor, SpectrogramDiffusionPipeline


import numpy as np
import PIL
import torch
import torchvision.transforms as T
import torchvision.transforms.functional as TF
from PIL import Image







def 						_snake_case		(     SCREAMING_SNAKE_CASE		,				SCREAMING_SNAKE_CASE=256					)							->   Optional[int]:

     """simple docstring"""







     _lowerCAmelCase :       Any	   =     min(img.size					)

     if s < target_image_size:
          raise ValueError(f'''min dim for image {s} < {target_image_size}'''					)

     _lowerCAmelCase :       Dict	   =     target_image_size / s
     _lowerCAmelCase :       Dict	   =     (round(r * img.size[1]					), round(r * img.size[0]					))
     _lowerCAmelCase :       Any	   =     TF.resize(SCREAMING_SNAKE_CASE		,				SCREAMING_SNAKE_CASE		,				interpolation=PIL.Image.LANCZOS					)
     _lowerCAmelCase :       str	   =     TF.center_crop(SCREAMING_SNAKE_CASE		,				output_size=2 * [target_image_size]					)
     _lowerCAmelCase :       int	   =     torch.unsqueeze(T.ToTensor()(SCREAMING_SNAKE_CASE					)		,				0					)
     return img







def 						_snake_case		(     SCREAMING_SNAKE_CASE					)							->   List[str]:

     """simple docstring"""







     _lowerCAmelCase :       List[Any]	   =     2.0 * x - 1.0
     return x







def 						_snake_case		(     SCREAMING_SNAKE_CASE		,				SCREAMING_SNAKE_CASE=True		,				SCREAMING_SNAKE_CASE="RGB"					)							->   int:

     """simple docstring"""







     _lowerCAmelCase :       Optional[int]	   =     x.detach().cpu()
     if process:
          _lowerCAmelCase :       List[Any]	   =     post_process_tensor(SCREAMING_SNAKE_CASE					)
     _lowerCAmelCase :       Optional[int]	   =     x.numpy()
     if process:
          _lowerCAmelCase :       List[Any]	   =     (255 * x).astype(np.uinta					)
     _lowerCAmelCase :       Optional[int]	   =     Image.fromarray(SCREAMING_SNAKE_CASE					)
     if not x.mode == mode:
          _lowerCAmelCase :       str	   =     x.convert(SCREAMING_SNAKE_CASE					)
     return x







def 						_snake_case		(     SCREAMING_SNAKE_CASE					)							->   Union[str, Any]:

     """simple docstring"""







     _lowerCAmelCase :       Any	   =     torch.clamp(SCREAMING_SNAKE_CASE		,				-1.0		,				1.0					)
     _lowerCAmelCase :       Any	   =     (x + 1.0) / 2.0
     _lowerCAmelCase :       List[Any]	   =     x.permute(1		,				2		,				0					)
     return x







def 						_snake_case		(     SCREAMING_SNAKE_CASE					)							->   Tuple:

     """simple docstring"""







     _lowerCAmelCase :       str	   =     post_process_tensor(x.squeeze()					)
     return x.permute(2		,				0		,				1					).unsqueeze(0					)






