Computes the Top-k accuracy (`targ` is in the top `k` predictions of `inp`)

top_k_accuracy(inp, targ, k = 5, axis = -1)

Arguments

inp

predictions

targ

targets

k

k

axis

axis

Value

None

Examples


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)

}