tf.keras.metrics.SparseTopKCategoricalAccuracy

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

Inherits From: MeanMetricWrapper, Mean, Metric

k (Optional) Number of top elements to look at for computing accuracy. Defaults to 5.
name (Optional) string name of the metric instance.
dtype (Optional) data type of the metric result.

Example:

m = keras.metrics.SparseTopKCategoricalAccuracy(k=1)
m.update_state([2, 1], [[0.1, 0.9, 0.8], [0.05, 0.95, 0]])
m.result()
0.5
m.reset_state()
m.update_state([2, 1], [[0.1, 0.9, 0.8], [0.05, 0.95, 0]],
               sample_weight=[0.7, 0.3])
m.result()
0.3

Usage with compile() API:

model.compile(optimizer='sgd',
              loss='sparse_categorical_crossentropy',
              metrics=[keras.metrics.SparseTopKCategoricalAccuracy()])

dtype

variables

Methods

add_variable

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add_weight

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from_config

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get_config

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Return the serializable config of the metric.

reset_state

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Reset 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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Compute the current metric value.

Returns
A scalar tensor, or a dictionary of scalar tensors.

stateless_reset_state

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stateless_result

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stateless_update_state

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update_state

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Accumulate statistics for the metric.

__call__

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Call self as a function.