9d1ff2c8a536945885daecbd98dd2ecb387d9276,skorch/net.py,,valid_loss_score,#Any#Any#Any#,39

Before Change

// pylint: disable=unused-argument
def valid_loss_score(net, X=None, y=None):
    losses = net.history[-1, "batches", :, "valid_loss"]
    batch_sizes = net.history[-1, "batches", :, "valid_batch_size"]
    return np.average(losses, weights=batch_sizes)


// pylint: disable=too-many-instance-attributes
class NeuralNet(object):

After Change

// pylint: disable=unused-argument
def valid_loss_score(net, X=None, y=None):
    return net.history[-1, "batches", -1, "valid_loss"]


// pylint: disable=too-many-instance-attributes
class NeuralNet(object):

Instances