I would like to know the difference between kernel_size and stride in conv1d class in torch.nn and how does they both work.
As i understand my input of size in_channels gets converted to out_channels but I can not get how out_channels, kernel_size and stride works out.
If out_channels is the output size then shouldn’t it be dependent on kernel_size and stride
Can someone please help to clarify this…as I am trying in code examples I am getting the input and output channels is fixed as we provide in object init…but the third parameter is changing with kernel_Size and stride.
My problem is to apply a 1D convolution over a 50 step time series data.
Can someone please help to clarify these parameters.