kernel_size=3?

[a897456]

in models.py
self.resblocks = nn.ModuleList()
for i in range(len(self.ups)):
ch = h.upsample_initial_channel//(2**(i+1))
for j, (k, d) in enumerate(zip(h.resblock_kernel_sizes, h.resblock_dilation_sizes)):
self.resblocks.append(resblock(h, ch, k, d))

class ResBlock1(torch.nn.Module):
def init(self, h, channels, kernel_size=3, dilation=(1, 3, 5)):

The k in the first paragraph is [3 7 11],Why is k fixed to 3 in the second paragraph?