I have an input tensor of shape [8 , 500 , 502 ] where 8 is the batch size , 500 is the length of a bag ( i’m using multiple instance learning ) and 502 is my window size. One bag represents the concatenation of 2 histograms.
I want to use a feature extractor with Conv1d auto encoder-decoder.
Should i transpose my input to x = x.transpose(2,1).contiguous() or use something like  x = x.view(8*500, 1 , 502) . I am a bit confused with the concept of the channels to the 1D Convolution.
Thanks in advance