CNN with Julia

CNNPrimer3

# Batching 
# See: https://github.com/FluxML/model-zoo/blob/master/vision/mnist/conv.jl
# Bundle images together with labels and group into minibatchess
function make_minibatch(X, Y, idxs)
    X_batch = Array{Float32}(undef, size(X[1])..., 1, length(idxs))
    for i in 1:length(idxs)
        X_batch[:, :, :, i] = Float32.(X[idxs[i]])
    end
    Y_batch = onehotbatch(Y[idxs], 0:9)
    return (X_batch, Y_batch)
end
# The CNN only "sees" 128 images at each training cycle:
batch_size = 128
mb_idxs = partition(1:length(train_imgs), batch_size)
# train set in the form of batches
train_set = [make_minibatch(train_imgs, train_labels, i) for i in mb_idxs];
# train set in one-go: used to calculate accuracy with the train set
train_set_full = make_minibatch(train_imgs, train_labels, 1:length(train_imgs));
# test set: to check we do not overfit the train data:
test_set = make_minibatch(test_imgs, test_labels, 1:length(test_imgs));