| import torch |
|
|
| import node_helpers |
| from comfy_extras.nodes_wan import get_audio_embed_bucket_fps, linear_interpolation |
|
|
|
|
| def apply_wan_s2v_audio_conditioning(positive, negative, length, audio_encoder_output=None, frame_offset=0): |
| if audio_encoder_output is None: |
| return positive, negative, frame_offset |
|
|
| latent_t = ((length - 1) // 4) + 1 |
| feat = torch.cat(audio_encoder_output["encoded_audio_all_layers"]) |
| video_rate = 30 |
| fps = 16 |
| feat = linear_interpolation(feat, input_fps=50, output_fps=video_rate) |
| batch_frames = latent_t * 4 |
| audio_embed_bucket, _ = get_audio_embed_bucket_fps(feat, fps=fps, batch_frames=batch_frames, m=0, video_rate=video_rate) |
| audio_embed_bucket = audio_embed_bucket.unsqueeze(0) |
| if len(audio_embed_bucket.shape) == 3: |
| audio_embed_bucket = audio_embed_bucket.permute(0, 2, 1) |
| elif len(audio_embed_bucket.shape) == 4: |
| audio_embed_bucket = audio_embed_bucket.permute(0, 2, 3, 1) |
|
|
| audio_embed_bucket = audio_embed_bucket[:, :, :, frame_offset:frame_offset + batch_frames] |
| if audio_embed_bucket.shape[3] > 0: |
| positive = node_helpers.conditioning_set_values(positive, {"audio_embed": audio_embed_bucket}) |
| negative = node_helpers.conditioning_set_values(negative, {"audio_embed": audio_embed_bucket * 0.0}) |
| frame_offset += batch_frames |
| return positive, negative, frame_offset |
