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deepbeepmeep
2025-07-15 22:26:56 +02:00
parent 37f41804a6
commit 64c59c15d9
21 changed files with 734 additions and 392 deletions
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4
wan/multitalk/attention.py
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@@ -333,7 +333,7 @@ class SingleStreamMutiAttention(SingleStreamAttention):
human1 = normalize_and_scale(x_ref_attn_map[0], (human1_min_value, human1_max_value), (self.rope_h1[0], self.rope_h1[1]))
human2 = normalize_and_scale(x_ref_attn_map[1], (human2_min_value, human2_max_value), (self.rope_h2[0], self.rope_h2[1]))
back = torch.full((x_ref_attn_map.size(1),), self.rope_bak, dtype=human1.dtype).to(human1.device)
back = torch.full((x_ref_attn_map.size(1),), self.rope_bak, dtype=human1.dtype, device=human1.device)
max_indices = x_ref_attn_map.argmax(dim=0)
normalized_map = torch.stack([human1, human2, back], dim=1)
normalized_pos = normalized_map[range(x_ref_attn_map.size(1)), max_indices] # N
@@ -351,7 +351,7 @@ class SingleStreamMutiAttention(SingleStreamAttention):
if self.qk_norm:
encoder_k = self.add_k_norm(encoder_k)
per_frame = torch.zeros(N_a, dtype=encoder_k.dtype).to(encoder_k.device)
per_frame = torch.zeros(N_a, dtype=encoder_k.dtype, device=encoder_k.device)
per_frame[:per_frame.size(0)//2] = (self.rope_h1[0] + self.rope_h1[1]) / 2
per_frame[per_frame.size(0)//2:] = (self.rope_h2[0] + self.rope_h2[1]) / 2
encoder_pos = torch.concat([per_frame]*N_t, dim=0)