While trying to implement Improved WGANs I bumped into another error. I wanted to replace MaxPool layers with strided convolutions, but it seems there is a problem with CUDNN when computing the gradient penalty. On CPU strides work fine.
/home/hartmank/anaconda2/lib/python2.7/site-packages/torch/autograd/variable.pyc in backward(self, gradient, retain_graph, create_graph, retain_variables)
150                 Defaults to False, unless ``gradient`` is a volatile Variable.
151         """
--> 152         torch.autograd.backward(self, gradient, retain_graph, create_graph, retain_variables)
153 
154     def register_hook(self, hook):

/home/hartmank/anaconda2/lib/python2.7/site-packages/torch/autograd/__init__.pyc in backward(variables, grad_variables, retain_graph, create_graph, retain_variables)
 96 
 97     Variable._execution_engine.run_backward(
---> 98         variables, grad_variables, retain_graph)
 99 
100 

RuntimeError: CUDNN_STATUS_NOT_SUPPORTED. This error may appear if you passed in a non-contiguous input.

GPU:

  
      gist.github.com
  
  
    https://gist.github.com/kahartma/0739a98e42e7bb0987120b156665ef61 3
GAN_Error_CUDA.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
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CPU:

  
      gist.github.com
  
  
    https://gist.github.com/kahartma/37b97c096a3dd141d19257ad6e2d73b8 1
GAN_Error_CPU.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
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compiled pytorch from source with CUDA 8.0.61 and CUDNN 6.0.21