Hi I'm using this framework on my dataset, everything works fine on CPU, but when I moved them to gpu, it had the error as following:
File "/home/ibm_decoder/DecoderRNN.py", line 107, in forward_step predicted_softmax = function(self.out(output.contiguous().view(-1, self.hidden_size)), dim=1).view(batch_size, output_size, -1) File "/home/anaconda2/envs/lib/python3.6/site-packages/torch/nn/functional.py", line 1317, in log_softmax ret = input.log_softmax(dim) RuntimeError: CUDA out of memory. Tried to allocate 2.77 GiB (GPU 0; 10.76 GiB total capacity; 8.66 GiB already allocated; 943.56 MiB free; 9.06 GiB reserved in total by PyTorch)
The batch size is only 32, so I don't know what was wrong and what caused such big memory allocation.
Hi I'm using this framework on my dataset, everything works fine on CPU, but when I moved them to gpu, it had the error as following:
File "/home/ibm_decoder/DecoderRNN.py", line 107, in forward_step predicted_softmax = function(self.out(output.contiguous().view(-1, self.hidden_size)), dim=1).view(batch_size, output_size, -1) File "/home/anaconda2/envs/lib/python3.6/site-packages/torch/nn/functional.py", line 1317, in log_softmax ret = input.log_softmax(dim) RuntimeError: CUDA out of memory. Tried to allocate 2.77 GiB (GPU 0; 10.76 GiB total capacity; 8.66 GiB already allocated; 943.56 MiB free; 9.06 GiB reserved in total by PyTorch)The batch size is only 32, so I don't know what was wrong and what caused such big memory allocation.