Python版本python 3.7
框架版本PaddlePaddle 2.1.2

/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/nn/layer/norm.py:641: UserWarning: When training, we now always track global mean and variance.
"When training, we now always track global mean and variance.")
[130644, 100]
[130644, 100]
---------------------------------------------------------------------------OSError Traceback (most recent call last) in
19 writer.add_scalar(tag="train/loss", step=epoch, value=train_loss)
20 writer.add_scalar(tag="train/acc", step=epoch, value=train_acc)
---> 21 val_loss, val_acc = eval(train_index, train_label, gnn_model, graph,criterion,val_index, val_label)
22 writer.add_scalar(tag="eval/loss", step=epoch, value=val_loss)
23 writer.add_scalar(tag="eval/acc", step=epoch, value=val_acc)
in eval(node_index, node_label, gnn_model, graph, criterion, eval_index, eval_label)
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dygraph/base.py in _decorate_function(func, *args,**kwargs)
329 def _decorate_function(func, *args,*kwargs):
330 with self:
--> 331 return func(args,kwargs)
332
333 @decorator.decorator
in eval(node_index, node_label, gnn_model, graph, criterion, eval_index, eval_label)
14 def eval(node_index, node_label, gnn_model, graph, criterion,eval_index,eval_label):
15 gnn_model.eval()
---> 16 pred = gnn_model(graph, graph.node_feat["words"],paddle.reshape(node_index,[-1]),paddle.reshape(node_label,[-1]))
17 pred = paddle.gather(pred, eval_index)
18 loss = criterion(pred, eval_label)
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py incall(self, *inputs,*kwargs)
900 self._built = True
901
--> 902 outputs = self.forward(inputs,kwargs)
903
904 for forward_post_hook in self._forward_post_hooks.values():
in forward(self, graph, feature, label_idx, label_y)
90 feature = paddle.scatter(feature, label_idx, label_embed, overwrite=True)
91 print(feature.shape)
---> 92 res_feature = self.trans(feature)
93 for idx,m in enumerate(self.gats):
94 feature = m(graph, feature)
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py incall(self, *inputs,*kwargs)
900 self._built = True
901
--> 902 outputs = self.forward(inputs,kwargs)
903
904 for forward_post_hook in self._forward_post_hooks.values():
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dygraph/container.py in forward(self, input)
96 def forward(self, input):
97 for layer in self._sub_layers.values():
---> 98 input = layer(input)
99 return input
100
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py incall(self, *inputs,**kwargs)
900 self._built = True
901
--> 902 outputs = self.forward(*inputs,**kwargs)
903
904 for forward_post_hook in self._forward_post_hooks.values():
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/nn/layer/norm.py in forward(self, input)
651 epsilon=self._epsilon,
652 data_format=self._data_format,
--> 653 use_global_stats=self._use_global_stats)
654
655 def extra_repr(self):
/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/nn/functional/norm.py in batch_norm(x, running_mean, running_var, weight, bias, training, momentum, epsilon, data_format, use_global_stats, name)
188 batch_norm_out, _, _, _, _, _ = core.ops.batch_norm(
189 x, weight, bias, running_mean, running_var, mean_out, variance_out,
--> 190 *attrs)
191 return dygraph_utils._append_activation_in_dygraph(
192 batch_norm_out, act=None)
OSError: (External) Cudnn error, CUDNN_STATUS_NOT_SUPPORTED (at /paddle/paddle/fluid/operators/batch_norm_op.cu:372)
[operator < batch_norm > error]