Merge pull request #291 from HydrogenSulfate/fix_ZeroDim_in_tests

reshape norm output to 0-D tensor manually

Author: plusNew001

paddlescience/network/grad_norm.py

@@ -84,8 +84,8 @@ def get_grad_norm_loss(self, losses):
         norms = []
         for i in range(losses.shape[0]):
             grad = paddle.autograd.grad(losses[i], W, retain_graph=True)
-            norms.append(paddle.norm(self.loss_weights[i] * grad[0], p=2))
-        norms = paddle.concat(norms)
+            norms.append(paddle.norm(self.loss_weights[i] * grad[0], p=2).reshape([]))
+        norms = paddle.stack(norms)
 
         # calculate the inverse train rate
         loss_ratio = losses.numpy() / self.initial_losses