delete irrelevant code

apg_guidance.py

@@ -34,30 +34,19 @@ def apg_forward(
     dims=[-1, -2],
 ):
     diff = pred_cond - pred_uncond
-    # orig_cfg_guided = pred_uncond + guidance_scale * (pred_cond - pred_uncond)
-    # print("======== 新的一轮 =========")
-    # print("原来的diff", "min:", diff.min(), "max:", diff.max(), "mean:", diff.mean(), "std:", diff.std(), f"cfg会乘上{guidance_scale=}")
-    # print("如果跑cfg orig_cfg_guided", "min:", orig_cfg_guided.min(), "max:", orig_cfg_guided.max(), "mean:", orig_cfg_guided.mean(), "std:", orig_cfg_guided.std())
     if momentum_buffer is not None:
         momentum_buffer.update(diff)
         diff = momentum_buffer.running_average
-        # print("跑完momentum_buffer后", "min:", diff.min(), "max:", diff.max(), "mean:", diff.mean(), "std:", diff.std(), f"cfg会乘上{guidance_scale=}")
 
     if norm_threshold > 0:
         ones = torch.ones_like(diff)
         diff_norm = diff.norm(p=2, dim=dims, keepdim=True)
-        # print("diff_norm", diff_norm)
-        # 只有比1大的时候（爆音）才会进行缩放
         scale_factor = torch.minimum(ones, norm_threshold / diff_norm)
         diff = diff * scale_factor
-        # print("跑完norm_threshold scale factor后", "min:", diff.min(), "max:", diff.max(), "mean:", diff.mean(), "std:", diff.std())
 
     diff_parallel, diff_orthogonal = project(diff, pred_cond, dims)
-    # print("跑完project后, diff_parallel", "min:", diff_parallel.min(), "max:", diff_parallel.max(), "mean:", diff_parallel.mean(), "std:", diff_parallel.std())
     normalized_update = diff_orthogonal + eta * diff_parallel
-    # print("跑完normalized_update后", "min:", normalized_update.min(), "max:", normalized_update.max(), "mean:", normalized_update.mean(), "std:", normalized_update.std())
     pred_guided = pred_cond + (guidance_scale - 1) * normalized_update
-    # print("最终pred_guided", "min:", pred_guided.min(), "max:", pred_guided.max(), "mean:", pred_guided.mean(), "std:", pred_guided.std())
     return pred_guided