# What does 'channel' mean in the case of an 1D convolution?

While reading about 1D-convolution in PyTorch, I encountered the concept of channels

in_channels (int) – Number of channels in the input image

out_channels (int) – Number of channels produced by the convolution


Although I encountered this concept of channels early, I am confused about channels and might understand in a wrong manner.

Since the operation we are discussing is 1D convolution, then there will be two lists of numbers, one is input list and other is filter list. Last one is feature map (output list).

They look like below

The left one is the input list, the middle one is the filter list and the rightmost is the output list.

Each cell in the input list contains a whole number. Each cell may take value in the fixed range $$[a,b]$$ of numbers.

What is the concept of channels used here? From where the channels are coming? Is the number of channels stand for the number of elements in the corresponding list?

• – redhqs Jul 23 at 6:08

To map from N input channels to M output channels requires $$N \times M$$ filters. Each of the M outputs is connected by a filter to each of the N inputs, and the results of running those N convolutions is summed and passed through a nonlinear activation function to generate an output channel.