Fix HunyuanVideo produces NaN on PyTorch<2.5 (#10482)

Co-authored-by: Sayak Paul <[email protected]>

Author: 2 people

src/diffusers/models/transformers/transformer_hunyuan_video.py

@@ -713,15 +713,15 @@ def forward(
         condition_sequence_length = encoder_hidden_states.shape[1]
         sequence_length = latent_sequence_length + condition_sequence_length
         attention_mask = torch.zeros(
-            batch_size, sequence_length, sequence_length, device=hidden_states.device, dtype=torch.bool
-        )  # [B, N, N]
+            batch_size, sequence_length, device=hidden_states.device, dtype=torch.bool
+        )  # [B, N]
 
         effective_condition_sequence_length = encoder_attention_mask.sum(dim=1, dtype=torch.int)  # [B,]
         effective_sequence_length = latent_sequence_length + effective_condition_sequence_length
 
         for i in range(batch_size):
-            attention_mask[i, : effective_sequence_length[i], : effective_sequence_length[i]] = True
-        attention_mask = attention_mask.unsqueeze(1)  # [B, 1, N, N], for broadcasting across attention heads
+            attention_mask[i, : effective_sequence_length[i]] = True
+        attention_mask = attention_mask.unsqueeze(1)  # [B, 1, N], for broadcasting across attention heads
 
         # 4. Transformer blocks
         if torch.is_grad_enabled() and self.gradient_checkpointing: