hello, the technique I use does start learning representation of pixels, and it give me around 30-32% accuracy on cifar10 dataset, but the problem is how do I make it to learn combined representation of pixels, for example, it has learnt what
a white pixel is, what a black pixel is, but when shown a combination of these pixels, then it has no idea what to do. To do this, I increase my embedding layer size to 1000, like,
nn.Embedding(1000, 10)

but what more patterns do I make it learn, for example, if I want to make it have a learnt representation for a combination of a 2x2 patch like,
[BW
 BW] -> [10 learnt numbers]

or a 3x3 patch like,
[WBW
 BWB
 WBW] -> [10 learnt numbers]

But there could be so many of these patches.