From 5fbfe8c9fdaa0040301155e2993ce61a26d4a9af Mon Sep 17 00:00:00 2001
From: li-lizhe <147392333@qq.com>
Date: Mon, 14 Sep 2026 09:15:19 +0800
Subject: [PATCH] fix(wan): use device-agnostic default for get_i2v_mask

The `get_i2v_mask` method had a hardcoded `device="cuda"` default,
which crashes on non-CUDA accelerators (Ascend NPU, etc.) with
"Torch not compiled with CUDA enabled" when called without an
explicit device argument.

Change the default to None and resolve via `self._execution_device`,
matching the pattern used across other pipeline methods.

Verified on Ascend 910B NPU: torch.zeros(device="cuda") crashes,
fix with device-agnostic resolution creates tensors on the correct
device.
---
 src/diffusers/pipelines/wan/pipeline_wan_animate.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/src/diffusers/pipelines/wan/pipeline_wan_animate.py b/src/diffusers/pipelines/wan/pipeline_wan_animate.py
index a923219a7550..c2416243f111 100644
--- a/src/diffusers/pipelines/wan/pipeline_wan_animate.py
+++ b/src/diffusers/pipelines/wan/pipeline_wan_animate.py
@@ -465,8 +465,10 @@ def get_i2v_mask(
         mask_len: int = 1,
         mask_pixel_values: torch.Tensor | None = None,
         dtype: torch.dtype | None = None,
-        device: str | torch.device = "cuda",
+        device: str | torch.device | None = None,
     ) -> torch.Tensor:
+        device = device or self._execution_device
+
         # mask_pixel_values shape (if supplied): [B, C = 1, T, latent_h, latent_w]
         if mask_pixel_values is None:
             mask_lat_size = torch.zeros(