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RuntimeError: CUDNN_STATUS_EXECUTION_FAILED

See original GitHub issue

I’ve installed the correct requirements. But after running this: python main.py --dataset cifar10 --arch vgg --depth 16

I’m getting the following error:

Traceback (most recent call last):
  File "main.py", line 166, in <module>
    train(epoch)
  File "main.py", line 125, in train
    output = model(data)
  File "/home/jeferson/repo/rethinking-network-pruning/repense/lib/python3.6/site-packages/torch/nn/modules/module.py", line 357, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/jeferson/repo/rethinking-network-pruning/cifar/l1-norm-pruning/models/vgg.py", line 56, in forward
    x = self.feature(x)
  File "/home/jeferson/repo/rethinking-network-pruning/repense/lib/python3.6/site-packages/torch/nn/modules/module.py", line 357, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/jeferson/repo/rethinking-network-pruning/repense/lib/python3.6/site-packages/torch/nn/modules/container.py", line 67, in forward
    input = module(input)
  File "/home/jeferson/repo/rethinking-network-pruning/repense/lib/python3.6/site-packages/torch/nn/modules/module.py", line 357, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/jeferson/repo/rethinking-network-pruning/repense/lib/python3.6/site-packages/torch/nn/modules/conv.py", line 282, in forward
    self.padding, self.dilation, self.groups)
  File "/home/jeferson/repo/rethinking-network-pruning/repense/lib/python3.6/site-packages/torch/nn/functional.py", line 90, in conv2d
    return f(input, weight, bias)
RuntimeError: CUDNN_STATUS_EXECUTION_FAILED

Am I doing something wrong?

Issue Analytics

State:
Created 4 years ago
Comments:9 (4 by maintainers)

Top GitHub Comments

1reaction

songheonycommented, Oct 14, 2019

If you want to use CUDA >= 9.2, The code should be changed for Pytorch 0.4.1. Here is the source code I converted https://github.com/songheony/rethinking-network-pruning. I’ve tested it with Pytorch 1.2, CUDA 10

0reactions

jefersonfcommented, Oct 11, 2019

If you want to use CUDA >= 0.92, The code should be changed for Pytorch 0.4.1. Here is the source code I converted https://github.com/songheony/rethinking-network-pruning. I’ve tested it with Pytorch 1.2, CUDA 10

I’ll check it out!