From 9a1435946ce7cc7f2cdaa0a312e1c0d296b8c276 Mon Sep 17 00:00:00 2001 From: laksjdjf Date: Fri, 24 Feb 2023 14:04:23 +0900 Subject: [PATCH] Update sd_samplers_kdiffusion.py --- modules/sd_samplers_kdiffusion.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index 528f513fe..ea974be04 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -101,11 +101,13 @@ class CFGDenoiser(torch.nn.Module): sigma_in = torch.cat([torch.stack([sigma[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [sigma] + [sigma]) image_cond_in = torch.cat([torch.stack([image_cond[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [image_cond] + [torch.zeros_like(self.init_latent)]) - denoiser_params = CFGDenoiserParams(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, tensor, uncond) cfg_denoiser_callback(denoiser_params) x_in = denoiser_params.x image_cond_in = denoiser_params.image_cond sigma_in = denoiser_params.sigma + tensor = denoiser_params.tensor + uncond = denoiser_params.uncond if tensor.shape[1] == uncond.shape[1]: if not is_edit_model: