Computes the Top-k accuracy (`targ` is in the top `k` predictions of `inp`)
top_k_accuracy(inp, targ, k = 5, axis = -1)
predictions
targets
k
axis
None
if (FALSE) {
loaders = loaders()
data = Data_Loaders(loaders['train'], loaders['valid'])$cuda()
model = nn$Sequential() +
nn$Flatten() +
nn$Linear(28L * 28L, 10L)
metrics = list(accuracy,top_k_accuracy)
learn = Learner(data, model, loss_func = F$cross_entropy, opt_func = Adam,
metrics = metrics)
}