I am extracting the feature maps from every activation layer after convolutions, and I am struggling to visualise the output:
def get_fmaps(input, model):
    fmaps = []
    for i in [0, 3, 6, 8, 10]:  ##conv2d index
        out = []
        out.append(model.features[0].forward(input))
        out.append(model.features[1].forward(out[0]))
        for x in range(2,i+1):
            out.append(model.features[x].forward(out[x-1]))
        fmaps.append(model.features[i+1].forward(out[i])) ##output after activation function
    return fmaps

I’m not sure if this is the correct way to do it, but once I have returned fmaps, how do I visualise the feature maps?