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author | DepFA <35278260+dfaker@users.noreply.github.com> | 2022-11-02 00:38:17 +0000 |
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committer | GitHub <noreply@github.com> | 2022-11-02 00:38:17 +0000 |
commit | 5b6bedf6f2ebacb7f1f5809af8e26a6a1af16e2a (patch) | |
tree | 1da50e0faaa78ece2254ebbc507d533ee9527807 /modules/sd_samplers.py | |
parent | cd88e21dc5d5cfdfbd408454acd259b7db9d0ec8 (diff) | |
download | stable-diffusion-webui-gfx803-5b6bedf6f2ebacb7f1f5809af8e26a6a1af16e2a.tar.gz stable-diffusion-webui-gfx803-5b6bedf6f2ebacb7f1f5809af8e26a6a1af16e2a.tar.bz2 stable-diffusion-webui-gfx803-5b6bedf6f2ebacb7f1f5809af8e26a6a1af16e2a.zip |
Update class name and assign back to vars
Diffstat (limited to 'modules/sd_samplers.py')
-rw-r--r-- | modules/sd_samplers.py | 8 |
1 files changed, 6 insertions, 2 deletions
diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py index 30cb5c4b..ebc0d896 100644 --- a/modules/sd_samplers.py +++ b/modules/sd_samplers.py @@ -11,7 +11,7 @@ from modules import prompt_parser, devices, processing, images from modules.shared import opts, cmd_opts, state
import modules.shared as shared
-from modules.script_callbacks import CGFDenoiserParams, cfg_denoiser_callback
+from modules.script_callbacks import CFGDenoiserParams, cfg_denoiser_callback
SamplerData = namedtuple('SamplerData', ['name', 'constructor', 'aliases', 'options'])
@@ -279,7 +279,11 @@ class CFGDenoiser(torch.nn.Module): image_cond_in = torch.cat([torch.stack([image_cond[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [image_cond])
sigma_in = torch.cat([torch.stack([sigma[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [sigma])
- cfg_denoiser_callback(CGFDenoiserParams(x_in, image_cond_in, sigma_in, state.sampling_step, state.sampling_steps))
+ denoiser_params = CFGDenoiserParams(x_in, image_cond_in, sigma_in, state.sampling_step, state.sampling_steps)
+ cfg_denoiser_callback(denoiser_params)
+ x_in = denoiser_params.x
+ image_cond_in = denoiser_params.image_cond
+ sigma_in = denoiser_params.sigma
if tensor.shape[1] == uncond.shape[1]:
cond_in = torch.cat([tensor, uncond])
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