tf.keras.metrics.CategoricalHinge

Computes the categorical hinge metric between y_true and y_pred.

Inherits From: Mean, Metric, Layer, Module

name (Optional) string name of the metric instance.
dtype (Optional) data type of the metric result.

Standalone usage:

m = tf.keras.metrics.CategoricalHinge()
m.update_state([[0, 1], [0, 0]], [[0.6, 0.4], [0.4, 0.6]])
m.result().numpy()
1.4000001
m.reset_state()
m.update_state([[0, 1], [0, 0]], [[0.6, 0.4], [0.4, 0.6]],
               sample_weight=[1, 0])
m.result().numpy()
1.2

Usage with compile() API:

model.compile(
    optimizer='sgd',
    loss='mse',
    metrics=[tf.keras.metrics.CategoricalHinge()])

Methods

reset_state

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Resets all of the metric state variables.

This function is called between epochs/steps, when a metric is evaluated during training.

result

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Computes and returns the metric value tensor.

Result computation is an idempotent operation that simply calculates the metric value using the state variables.

update_state

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Accumulates metric statistics.

y_true and y_pred should have the same shape.

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