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.