From 34fecc3063f65ba2bc25612e561f440d651d328b Mon Sep 17 00:00:00 2001 From: kijai <40791699+kijai@users.noreply.github.com> Date: Thu, 12 Jun 2025 18:19:52 +0300 Subject: [PATCH] Update nodes.py --- nodes.py | 10 +--------- 1 file changed, 1 insertion(+), 9 deletions(-) diff --git a/nodes.py b/nodes.py index bdd8209..0e55828 100644 --- a/nodes.py +++ b/nodes.py @@ -2399,8 +2399,6 @@ class WanVideoExperimentalArgs: "fresca_scale_low": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01}), "fresca_scale_high": ("FLOAT", {"default": 1.25, "min": 0.0, "max": 10.0, "step": 0.01}), "fresca_freq_cutoff": ("INT", {"default": 20, "min": 0, "max": 10000, "step": 1}), - "use_nag": ("BOOLEAN", {"default": False}), - "nag_scale": ("FLOAT", {"default": 11.0, "min": 1.0, "max": 20.0, "step": 1.0}), }, } @@ -3004,14 +3002,8 @@ class WanVideoSampler: drift_timesteps = torch.cat([drift_timesteps, torch.tensor([0]).to(drift_timesteps.device)]).to(drift_timesteps.device) timesteps[-drift_steps:] = drift_timesteps[-drift_steps:] - use_cfg_zero_star = use_fresca = nag_scale = False - nag_negative_context = None + use_cfg_zero_star = use_fresca = False if experimental_args is not None: - use_nag = experimental_args.get("use_nag", False) - if use_nag: - nag_negative_context = text_embeds["negative_prompt_embeds"] - nag_scale = experimental_args.get("nag_scale", 11) - video_attention_split_steps = experimental_args.get("video_attention_split_steps", []) if video_attention_split_steps: transformer.video_attention_split_steps = [int(x.strip()) for x in video_attention_split_steps.split(",")]