From 8e9fb0e11c6cfeb67270f9435ffd6974f6537f37 Mon Sep 17 00:00:00 2001 From: kijai <40791699+kijai@users.noreply.github.com> Date: Wed, 2 Jul 2025 16:47:19 +0300 Subject: [PATCH] Update nodes.py --- nodes.py | 20 ++++++++++++++++---- 1 file changed, 16 insertions(+), 4 deletions(-) diff --git a/nodes.py b/nodes.py index 2e9c709..09a5c4d 100644 --- a/nodes.py +++ b/nodes.py @@ -3837,6 +3837,10 @@ class WanVideoSampler: indices = (torch.arange(4 + 1) - 2) * 1 # start video generation iteratively + estimated_iterations = max(1, min(max_frames_num, len(multitalk_audio_embedding)) // (frame_num - motion_frame) + 1) + loop_pbar = tqdm(total=estimated_iterations, desc="Generating video clips") + iteration_count = 0 + audio_embedding = [multitalk_audio_embedding] while True: audio_embs = [] @@ -3949,7 +3953,6 @@ class WanVideoSampler: for i in tqdm(range(len(timesteps)-1)): timestep = timesteps[i] latent_model_input = latent.to(device) - print("latent_model_input shape: ", latent_model_input.shape) noise_pred, self.cache_state = predict_with_cfg( latent_model_input, @@ -4022,7 +4025,10 @@ class WanVideoSampler: gen_video_list.append(videos[:, :, cur_motion_frames_num:]) # decide whether is done - if arrive_last_frame: break + if arrive_last_frame: + loop_pbar.update(estimated_iterations - iteration_count) + loop_pbar.close() + break # update next condition frames is_first_clip = False @@ -4032,6 +4038,10 @@ class WanVideoSampler: audio_start_idx += (frame_num - cur_motion_frames_num) audio_end_idx = audio_start_idx + clip_length + # Update progress bar + iteration_count += 1 + loop_pbar.update(1) + # Repeat audio emb if audio_end_idx >= min(max_frames_num, len(audio_embedding[0])): arrive_last_frame = True @@ -4048,8 +4058,10 @@ class WanVideoSampler: else: miss_lengths.append(0) - if max_frames_num <= frame_num: break - + if max_frames_num <= frame_num: + loop_pbar.update(estimated_iterations - iteration_count) + loop_pbar.close() + break gen_video_samples = torch.cat(gen_video_list, dim=2)[:, :, :int(max_frames_num)] gen_video_samples = gen_video_samples.to(torch.float32)