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tf.keras.metrics.sparse_categorical_accuracy

Calculates how often predictions matches integer labels.

Standalone usage:

y_true = [2, 1]
y_pred = [[0.1, 0.9, 0.8], [0.05, 0.95, 0]]
m = tf.keras.metrics.sparse_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.

Args
y_true Integer ground truth values.
y_pred The prediction values.
Returns
Sparse categorical accuracy values.

© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/keras/metrics/sparse_categorical_accuracy