slydg / gru_to_predict_timeseries Goto Github PK

python 1_train_predictor.py --data ecg --filename chfdb_chf13_45590.pkl

=> Start training from scratch
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Namespace(augment=True, batch_size=64, bptt=50, clip=10, data='ecg', device='cuda', dropout=0.2, emsize=32, epochs=400, eval_batch_size=64, filename='chfdb_chf13_45590.pkl', log_interval=10, lr=0.0002, model='LSTM', nhid=32, nlayers=2, prediction_window_size=10, pretrained=False, res_connection=False, resume=False, save_fig=False, save_interval=10, seed=1111, teacher_forcing_ratio=0.7, tied=False, weight_decay=0.0001)
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Traceback (most recent call last):
File "1_train_predictor.py", line 320, in
train(args,model,train_dataset,epoch)
File "1_train_predictor.py", line 228, in train
loss1 = criterion(outSeq1.view(args.batch_size,-1), targetSeq.view(args.batch_size,-1))
RuntimeError: view size is not compatible with input tensor's size and stride (at least one dimension spans across two contiguous subspaces). Use .reshape(...) instead.