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Update class name and assign back to vars

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DepFA 2022-11-02 00:38:17 +00:00 committed by GitHub
parent cd88e21dc5
commit 5b6bedf6f2
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1 changed files with 6 additions and 2 deletions
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8
modules/sd_samplers.py
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@ -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])