support_shape=[0]_tensor

docs/source/cls/custom_dataset.md

@@ -108,7 +108,7 @@ for epoch in range(1, epochs + 1):
         optimizer.clear_grad()
 
         # Calculate loss
-        avg_loss = loss.numpy()[0]
+        avg_loss = float(loss)
 
         # Calculate metrics
         preds = paddle.argmax(logits, axis=1)

docs/tutorial/cls/cls_tutorial.ipynb

@@ -509,7 +509,7 @@
     "        optimizer.clear_grad()\n",
     "\n",
     "        # Calculate loss\n",
-    "        avg_loss += loss.numpy()[0]\n",
+    "        avg_loss += float(loss)\n",
     "\n",
     "        # Calculate metrics\n",
     "        preds = paddle.argmax(logits, axis=1)\n",

paddlespeech/cls/exps/panns/train.py

@@ -101,7 +101,7 @@ if __name__ == "__main__":
             optimizer.clear_grad()
 
             # Calculate loss
-            avg_loss += loss.numpy()[0]
+            avg_loss += float(loss)
 
             # Calculate metrics
             preds = paddle.argmax(logits, axis=1)

paddlespeech/kws/exps/mdtc/train.py

@@ -110,7 +110,7 @@ if __name__ == '__main__':
             optimizer.clear_grad()
 
             # Calculate loss
-            avg_loss += loss.numpy()[0]
+            avg_loss += float(loss)
 
             # Calculate metrics
             num_corrects += corrects

tests/unit/tts/test_pwg.py

@@ -24,7 +24,7 @@ from paddlespeech.t2s.models.parallel_wavegan import PWGGenerator
 from paddlespeech.t2s.models.parallel_wavegan import ResidualBlock
 from paddlespeech.t2s.models.parallel_wavegan import ResidualPWGDiscriminator
 from paddlespeech.t2s.utils.layer_tools import summary
-from paddlespeech.t2s.utils.profile import synchronize
+from paddle.device.cuda import synchronize
 
 paddle.set_device("gpu:0")
 device = torch.device("cuda:0")