pytorch從python2遷移到python3時遇到torch.FloatTensor constructor received an invalid combination of argumen
在執行 AI_Challenger_2018閱讀理解程式基準程式碼時出現以下錯誤:
raceback (most recent call last): File "train.py", line 39, in <module> model = MwAN(vocab_size=vocab_size, embedding_size=args.emsize, encoder_size=args.nhid, drop_out=args.dropout) File "/root/qa_lwh/AI_Challenger_2018/Baselines/opinion_questions_machine_reading_comprehension2018_baseline/model.py", line 17, in __init__ bidirectional=True) File "/root/anaconda3/envs/python36/lib/python3.6/site-packages/torch/nn/modules/rnn.py", line 482, in __init__ super(GRU, self).__init__('GRU', *args, **kwargs) File "/root/anaconda3/envs/python36/lib/python3.6/site-packages/torch/nn/modules/rnn.py", line 39, in __init__ w_ih = Parameter(torch.Tensor(gate_size, layer_input_size)) TypeError: torch.FloatTensor constructor received an invalid combination of arguments - got (float, int), but expected one of: * no arguments * (int ...) didn't match because some of the arguments have invalid types: (float, int) * (torch.FloatTensor viewed_tensor) * (torch.Size size) * (torch.FloatStorage data) * (Sequence data)
經過除錯發現model.py 語句出錯
self.a_encoder = nn.GRU(input_size=embedding_size, hidden_size=embedding_size / 2, batch_first=True, bidirectional=True)
python3中遇到除操作時都將結果轉換為float型別,強制轉換為int後,錯誤消失,訓練程式可以正確執行。
self.a_encoder = nn.GRU(input_size=embedding_size, hidden_size=int(embedding_size / 2), batch_first=True, bidirectional=True)