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[Fix] Set create_graph=False before eval in bubble example #776

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Merged
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Feb 2, 2024
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[Fix] Set create_graph=False before eval in bubble example #776

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4 changes: 2 additions & 2 deletions docs/zh/examples/bubble.md
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Expand Up @@ -301,9 +301,9 @@ examples/bubble/bubble.py:189:206

最后在给定的可视化区域上进行预测并可视化，可视化数据是区域内的二维点集，每个时刻 $t$ 的坐标是 $(x^t_i, y^t_i)$，对应值是 $(u^t_i, v^t_i, p^t_i,\phi^t_i)$，在此我们对预测得到的 $(u^t_i, v^t_i, p^t_i,\phi^t_i)$ 进行反归一化，我们将反归一化后的数据按时刻保存成 126 个 **vtu格式** 文件，最后用可视化软件打开查看即可。代码如下：

``` py linenums="212"
``` py linenums="222"
--8<--
examples/bubble/bubble.py:212:238
examples/bubble/bubble.py:222:248
--8<--
```

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10 changes: 10 additions & 0 deletions examples/bubble/bubble.py
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Expand Up @@ -208,6 +208,16 @@ def transform_out(in_, out):
visu_mat = geom["time_rect_visu"].sample_interior(
NPOINT_PDE * NTIME_PDE, evenly=True
)
# transform
def transform_out(in_, out):
psi_y = out["psi"]
y = in_["y"]
x = in_["x"]
u = jacobian(psi_y, y, create_graph=False)
v = -jacobian(psi_y, x, create_graph=False)
return {"u": u, "v": v}

model_psi.register_output_transform(transform_out)

pred_norm = solver.predict(visu_mat, None, 4096, no_grad=False, return_numpy=True)
# inverse normalization
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