chin-gyou / improving-variational-encoder-decoders-in-dialogue-generation Goto Github PK

I am new about pytorch, what's wrong about this problem?
Traceback (most recent call last): File "/home/yangjingying/PycharmProjects/VariationalSeq2Seq-master/main.py", line 269, in <module> save_every=save_every, sample_every=sample_every, print_every=print_every, learning_rate=learning_rate) File "/home/yangjingying/PycharmProjects/VariationalSeq2Seq-master/main.py", line 142, in train criterion, kl_anneal_weight, p_teach_force) File "/home/yangjingying/PycharmProjects/VariationalSeq2Seq-master/main.py", line 100, in _train_step loss.backward() File "/home/yangjingying/anaconda2/lib/python2.7/site-packages/torch/tensor.py", line 102, in backward torch.autograd.backward(self, gradient, retain_graph, create_graph) File "/home/yangjingying/anaconda2/lib/python2.7/site-packages/torch/autograd/__init__.py", line 90, in backward allow_unreachable=True) # allow_unreachable flag RuntimeError: select(): index 19 out of range for tensor of size [19, 32, 30000] at dimension 0 Closing remaining open files:./data/train.h5...done

Hi,

I want to train my dataset with dataproducer.py limit set to 500. It seems like https://github.com/snakeztc/NeuralDialog-CVAE can easily handle that and even bigger (limit=1000) with batch size 128. I'm using NVIDIA Volta GPU.

There'es some inefficiency going on here that I can't seem to solve.
Do you have any idea how can I go about solving this?

Thanks.