@@ -861,7 +861,7 @@ def __call__(
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mask_image : Union [torch .FloatTensor , PIL .Image .Image ] = None ,
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height : Optional [int ] = None ,
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width : Optional [int ] = None ,
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- strength : float = 1.0 ,
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+ strength : float = 0.9999 ,
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num_inference_steps : int = 50 ,
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denoising_start : Optional [float ] = None ,
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denoising_end : Optional [float ] = None ,
@@ -910,7 +910,7 @@ def __call__(
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The height in pixels of the generated image.
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width (`int`, *optional*, defaults to self.unet.config.sample_size * self.vae_scale_factor):
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The width in pixels of the generated image.
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- strength (`float`, *optional*, defaults to 1. ):
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+ strength (`float`, *optional*, defaults to 0.9999 ):
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Conceptually, indicates how much to transform the masked portion of the reference `image`. Must be
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between 0 and 1. `image` will be used as a starting point, adding more noise to it the larger the
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`strength`. The number of denoising steps depends on the amount of noise initially added. When
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