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allow custom height, width in StableDiffusionPipeline (#179) 

* allow custom height width

* raise if height width are not mul of 8
This commit is contained in:
Suraj Patil 2022-08-15 10:28:03 +05:30 committed by GitHub
parent c25d8c905c
commit 5f25818a0f
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1 changed files with 6 additions and 1 deletions
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7
src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py
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@ -28,6 +28,8 @@ class StableDiffusionPipeline(DiffusionPipeline):
def __call__( def __call__(
self, self,
prompt: Union[str, List[str]], prompt: Union[str, List[str]],
height: Optional[int] = 512,
width: Optional[int] = 512,
num_inference_steps: Optional[int] = 50, num_inference_steps: Optional[int] = 50,
guidance_scale: Optional[float] = 1.0, guidance_scale: Optional[float] = 1.0,
eta: Optional[float] = 0.0, eta: Optional[float] = 0.0,
@ -45,6 +47,9 @@ class StableDiffusionPipeline(DiffusionPipeline):
else: else:
raise ValueError(f"`prompt` has to be of type `str` or `list` but is {type(prompt)}") raise ValueError(f"`prompt` has to be of type `str` or `list` but is {type(prompt)}")
if height % 8 != 0 or width % 8 != 0:
raise ValueError(f"`height` and `width` have to be divisible by 8 but are {height} and {width}.")
self.unet.to(torch_device) self.unet.to(torch_device)
self.vae.to(torch_device) self.vae.to(torch_device)
self.text_encoder.to(torch_device) self.text_encoder.to(torch_device)
@ -72,7 +77,7 @@ class StableDiffusionPipeline(DiffusionPipeline):
# get the intial random noise # get the intial random noise
latents = torch.randn( latents = torch.randn(
(batch_size, self.unet.in_channels, self.unet.sample_size, self.unet.sample_size), (batch_size, self.unet.in_channels, height // 8, width // 8),
generator=generator, generator=generator,
) )
latents = latents.to(torch_device) latents = latents.to(torch_device)