tf.keras.metrics.categorical_accuracy

Calculates how often predictions matches one-hot labels.

Standalone usage:

y_true = [[0, 0, 1], [0, 1, 0]] y_pred = [[0.1, 0.9, 0.8], [0.05, 0.95, 0]] m = tf.keras.metrics.categorical_accuracy(y_true, y_pred) assert m.shape == (2,) m.numpy() array([0., 1.], dtype=float32)

You can provide logits of classes as y_pred, since argmax of logits and probabilities are same.

y_true One-hot ground truth values.
y_pred The prediction values.

Categorical accuracy values.