I have input data (images) that come with obscene number of channels (700+). To address this, I intend to have conv filter with (1x1) size so that it acts on a single pixel. what I want is: this filter acts only on this pixel (no spatial scanning!).
PS: I read about the “groups trick”, I think it is useful too and I used it in the first layer. But I completely forgot that I still have the problem of 1x1 filter acting on all pixels.

    self.torso = nn.Sequential(OrderedDict([
        ('nn_in_nn', nn.Conv2d(in_channels=ch_in, out_channels=64 * ch_out_multip, kernel_size=(1, 1), stride=1, padding=(0, 0),
                               groups=8 )),