Thanks for your reponse. I’ve added os.environ['CUDA_LAUNCH_BLOCKING'] = "1" before running main() and here is the stack trace.
Traceback (most recent call last):
  File "C:/Users/Administrator/Desktop/mycode/deep-learning/graphsage-simple-master/graphsage/model.py", line 227, in <module>
    run_cora()
  File "C:/Users/Administrator/Desktop/mycode/deep-learning/graphsage-simple-master/graphsage/model.py", line 120, in run_cora
    loss = graphsage.loss(batch_nodes, torch.LongTensor(labels[np.array(batch_nodes)]).to(device))
  File "C:/Users/Administrator/Desktop/mycode/deep-learning/graphsage-simple-master/graphsage/model.py", line 40, in loss
    scores = self.forward(nodes)
  File "C:/Users/Administrator/Desktop/mycode/deep-learning/graphsage-simple-master/graphsage/model.py", line 34, in forward
    embeds = self.enc(nodes)  # (num_nodes, embed_dim)
  File "C:\Users\Administrator\Anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 722, in _call_impl
    result = self.forward(*input, **kwargs)
  File "C:\Users\Administrator\Desktop\mycode\deep-learning\graphsage-simple-master\graphsage\encoders.py", line 38, in forward
    neigh_feats = self.aggregator.forward(
  File "C:\Users\Administrator\Desktop\mycode\deep-learning\graphsage-simple-master\graphsage\aggregators.py", line 65, in forward
    embed_matrix = self.features(torch.LongTensor(unique_nodes_list).to(self.device))
  File "C:/Users/Administrator/Desktop/mycode/deep-learning/graphsage-simple-master/graphsage/model.py", line 98, in <lambda>
    agg2 = MeanAggregator(lambda nodes: enc1(nodes), device)
  File "C:\Users\Administrator\Anaconda3\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 722, in _call_impl
    result = self.forward(*input, **kwargs)
  File "C:\Users\Administrator\Desktop\mycode\deep-learning\graphsage-simple-master\graphsage\encoders.py", line 49, in forward
    combined = F.relu(combined.mm(self.weight))
RuntimeError: CUDA error: CUBLAS_STATUS_EXECUTION_FAILED when calling `cublasSgemm( handle, opa, opb, m, n, k, &alpha, a, lda, b, ldb, &beta, c, ldc)`

When i remove the statement of “base_model”, it runs without error. So I don’t think it’s running out of GPU memory.