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tf.keras.metrics.Mean

Computes the (weighted) mean of the given values.

Inherits From: Metric, Layer, Module

Used in the notebooks

Used in the guide Used in the tutorials

For example, if values is [1, 3, 5, 7] then the mean is 4. If the weights were specified as [1, 1, 0, 0] then the mean would be 2.

This metric creates two variables, total and count that are used to compute the average of values. This average is ultimately returned as mean which is an idempotent operation that simply divides total by count.

If sample_weight is None, weights default to 1. Use sample_weight of 0 to mask values.

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

Standalone usage:

m = tf.keras.metrics.Mean()
m.update_state([1, 3, 5, 7])
m.result().numpy()
4.0
m.reset_state()
m.update_state([1, 3, 5, 7], sample_weight=[1, 1, 0, 0])
m.result().numpy()
2.0

Usage with compile() API:

model.add_metric(tf.keras.metrics.Mean(name='mean_1')(outputs))
model.compile(optimizer='sgd', loss='mse')

Methods

reset_state

View source

Resets all of the metric state variables.

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

result