hoelee/stable-diffusion-webui
1
0
Fork 0
mirror of https://github.com/AUTOMATIC1111/stable-diffusion-webui.git synced 2025-08-04 11:12:35 +00:00
Code Issues Actions Packages Projects Releases Wiki Activity

--no-half-vae

Browse Source
This commit is contained in:
AUTOMATIC
2022-10-10 16:11:14 +03:00
parent a357823339
commit 7349088d32
5 changed files with 20 additions and 5 deletions
Download Patch File Download Diff File Expand all files Collapse all files

11
modules/processing.py
View File

@@ -259,6 +259,13 @@ def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, see
return x
def decode_first_stage(model, x):
with devices.autocast(disable=x.dtype == devices.dtype_vae):
x = model.decode_first_stage(x)
return x
def get_fixed_seed(seed):
if seed is None or seed == '' or seed == -1:
return int(random.randrange(4294967294))
@@ -400,7 +407,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
samples_ddim = samples_ddim.to(devices.dtype)
x_samples_ddim = p.sd_model.decode_first_stage(samples_ddim)
x_samples_ddim = decode_first_stage(p.sd_model, samples_ddim)
x_samples_ddim = torch.clamp((x_samples_ddim + 1.0) / 2.0, min=0.0, max=1.0)
del samples_ddim
@@ -533,7 +540,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
if self.scale_latent:
samples = torch.nn.functional.interpolate(samples, size=(self.height // opt_f, self.width // opt_f), mode="bilinear")
else:
decoded_samples = self.sd_model.decode_first_stage(samples)
decoded_samples = decode_first_stage(self.sd_model, samples)
if opts.upscaler_for_img2img is None or opts.upscaler_for_img2img == "None":
decoded_samples = torch.nn.functional.interpolate(decoded_samples, size=(self.height, self.width), mode="bilinear")