Hi,
I’m new in PyTorch and trying to reimplement FC-DenseNet.
So, I defined the up sampling layer as:
class TransUpBlock(nn.Module): 
    def __init__(self, num_input_feat, num_output_feat):
        super(TransUpBlock, self).__init__()
        self.deconv = nn.ConvTranspose2d(num_input_feat,
         num_output_feat, kernel_size=3, stride=2, padding=0, bias=False) 
    def forward(self, input_, skip): 
        output_ = self.deconv(input_)
        output_ = center_crop(output_, skip.size(2), skip.size(3)) # From PyTorch Tiramiso
        output_ = torch.cat([output_, skip], 1) # From PyTorch Tiramiso
        return output_

where the training code contains:
model = model.cuda()
.
.
.
for i , (input, target) in enumerate(train_loader):
    target = target.cuda(async=True)
    input = input.cuda()
    input_var = torch.autograd.Variable(input) 
    target_var = torch.autograd.Variable(target)
    output = model(input_var)

When I feed the network, I got this error message:
  File "My_Train.py", line 271, in train
    output = model(input_var) #(A) performs forward pass
  File "/usr/lib64/python2.7/site-packages/torch/nn/modules/module.py", line 206, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/boroujerdi/Dokumente/CVPR_2017_Open_Access_Repository/DenseNet/My_IMP/My_Net.py", line 215, in forward
    output_ = self.transUpBlocks[i](output_, skip)
  File "/usr/lib64/python2.7/site-packages/torch/nn/modules/module.py", line 206, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/boroujerdi/Dokumente/CVPR_2017_Open_Access_Repository/DenseNet/My_IMP/My_Net.py", line 92, in forward
    output_ = self.deconv(input_)
  File "/usr/lib64/python2.7/site-packages/torch/nn/modules/module.py", line 206, in __call__
    result = self.forward(*input, **kwargs)
  File "/usr/lib64/python2.7/site-packages/torch/nn/modules/conv.py", line 524, in forward
    output_padding, self.groups, self.dilation)
  File "/usr/lib64/python2.7/site-packages/torch/nn/functional.py", line 137, in conv_transpose2d
    return f(input, weight, bias)
RuntimeError: CUDNN_STATUS_BAD_PARAM

Do you think there is something wrong with my cudnn?
Any kind of help will be appreciated.