odie2630463 / wavenet Goto Github PK

I've changed your CausalConv1d as below:
`class CausualConv1d(nn.Module):
def init(self,in_channels,out_channels,kernel_size=2,stride=1,dilation=1,bias=True):
super(CausalConv1d,self).init()

	self.pad = (kernel_size - 1) * dilation
	self.conv = nn.Conv1d(in_channels,out_channels,kernel_size,stride=stride,padding=self.pad,dilation=dilation,bias=bias)

def forward(self,inputs):
	
	outputs = self.conv(inputs)
	return outputs[:,:,:-self.pad]

`

And then I replace filter_conv and gate_conv in class ResidualBlock from DilatedConv1d to my CausalConv1d. I found this architecture from the original Tensorflow code. Theoretically, the receptive field of the networks remains unchanged. And things went well during training.
However, it caused a cuda runtime error(59):device-side assert triggered at /opt/conda/conda-bld/pytorch_1522182087074/work/torch/lib/THC/THCTensorCopy.cu:204 when I tried to use your generate_sample.ipynb. I tried to solve this for a day without any solutions. I wonder if there's any chance that you know why this happens.
Thank you for reading and if, for answering.

In execution Generate_sample error :

sample = torch.cat((sample,new),dim=1)
RuntimeError: zero-dimensional tensor (at position 1) cannot be concatenated

Can you tell me how to deal with it?
thanks！