AI/diffusers
1
0
Fork 0
mirror of https://github.com/huggingface/diffusers.git synced 2026-01-27 17:22:53 +03:00
Code Activity

allow custom height, width in StableDiffusionPipeline (#179)

Browse Source 
* 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
1 changed files with 6 additions and 1 deletions
Download Patch File Download Diff File Expand all files Collapse all files

7
src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py
View File

@@ -28,6 +28,8 @@ class StableDiffusionPipeline(DiffusionPipeline):
def __call__(
self,
prompt: Union[str, List[str]],
height: Optional[int] = 512,
width: Optional[int] = 512,
num_inference_steps: Optional[int] = 50,
guidance_scale: Optional[float] = 1.0,
eta: Optional[float] = 0.0,
@@ -45,6 +47,9 @@ class StableDiffusionPipeline(DiffusionPipeline):
else:
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.vae.to(torch_device)
self.text_encoder.to(torch_device)
@@ -72,7 +77,7 @@ class StableDiffusionPipeline(DiffusionPipeline):
# get the intial random noise
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,
)
latents = latents.to(torch_device)