Update nodes.py
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@@ -3129,11 +3129,11 @@ class WanVideoSampler:
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controlnet["controlnet_stride"] = controlnet["control_stride"]
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#uni3c
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pcd_data = None
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pcd_data = pcd_data_input = None
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if uni3c_embeds is not None:
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transformer.controlnet = uni3c_embeds["controlnet"]
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pcd_data = {
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"render_latent": uni3c_embeds["render_latent"],
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"render_latent": uni3c_embeds["render_latent"].to(dtype),
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"render_mask": uni3c_embeds["render_mask"],
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"camera_embedding": uni3c_embeds["camera_embedding"],
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"controlnet_weight": uni3c_embeds["controlnet_weight"],
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@@ -3372,6 +3372,14 @@ class WanVideoSampler:
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audio_emb = audio_embedding[human_idx][center_indices].unsqueeze(0).to(device)
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audio_embs.append(audio_emb)
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audio_embs = torch.concat(audio_embs, dim=0).to(dtype)
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if context_window is not None and pcd_data is not None:
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pcd_data_input = {"render_latent": pcd_data["render_latent"][:, :, context_window]}
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for k in pcd_data:
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if k != "render_latent":
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pcd_data_input[k] = pcd_data[k]
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else:
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pcd_data_input = pcd_data
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base_params = {
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@@ -3388,7 +3396,7 @@ class WanVideoSampler:
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'audio_proj': audio_proj if fantasytalking_embeds is not None else None,
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'audio_context_lens': audio_context_lens if fantasytalking_embeds is not None else None,
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'audio_scale': audio_scale,
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"pcd_data": pcd_data,
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"pcd_data": pcd_data_input,
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"controlnet": controlnet,
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"add_cond": add_cond_input,
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"nag_params": text_embeds.get("nag_params", {}),
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