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Computes how often integer targets are in the top K predictions.

Standalone usage:

y_true = [2, 1]
y_pred = [[0.1, 0.9, 0.8], [0.05, 0.95, 0]]
m = tf.keras.metrics.sparse_top_k_categorical_accuracy(
    y_true, y_pred, k=3)
assert m.shape == (2,)
array([1., 1.], dtype=float32)

y_true tensor of true targets.
y_pred tensor of predicted targets.
k (Optional) Number of top elements to look at for computing accuracy. Defaults to 5.

Sparse top K categorical accuracy value.