If I have a Conv1d
layers:
self.conv1 = torch.nn.Conv1d(
in_channels=feature_dim,
out_channels=feature_dim,
kernel_size=kernel_sizes[0],
stride=1
)
# padding=kernel_sizes[0] // 2)
self.conv2 = torch.nn.Conv1d(
in_channels=feature_dim,
out_channels=feature_dim,
kernel_size=kernel_sizes[1],
stride=1
)
# padding=kernel_sizes[1] // 2)
self.conv3 = torch.nn.Conv1d(
in_channels=feature_dim,
out_channels=feature_dim,
kernel_size=kernel_sizes[2],
stride=1
)
# padding=kernel_sizes[2] // 2)
self.conv4 = torch.nn.Conv1d(
in_channels=feature_dim,
out_channels=feature_dim,
kernel_size=kernel_sizes[3],
stride=1,
padding=2)
My sizes look like:
inp torch.Size([8, 161, 196])
out1 torch.Size([8, 161, 186])
out2 torch.Size([8, 161, 178])
out3 torch.Size([8, 161, 172])
out4 torch.Size([8, 161, 188])
But I want conv4
to increase the from 172 back to 196. I assume I can control that with padding, but I’m not sure how.