tf.keras.metrics.Sum

Computes the (weighted) sum of the given values.

Main aliases

tf.metrics.Sum

Compat aliases for migration

See Migration guide for more details.

tf.keras.metrics.Sum(
    name='sum', dtype=None
)

For example, if values is [1, 3, 5, 7] then the sum is 16. If the weights were specified as [1, 1, 0, 0] then the sum would be 4.

This metric creates one variable, total, that is used to compute the sum of values. This is ultimately returned as sum.

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

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

m = tf.keras.metrics.Sum()
m.update_state([1, 3, 5, 7])
m.result().numpy()
16.0

Usage with compile() API:

model.add_metric(tf.keras.metrics.Sum(name='sum_1')(outputs))
model.compile(optimizer='sgd', loss='mse')

Methods

reset_state()

Resets all of the metric state variables.

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

result()

Computes and returns the metric value tensor.

Result computation is an idempotent operation that simply calculates the metric value using the state variables.

update_state(
    values, sample_weight=None
)

Accumulates statistics for computing the metric.

Args
`values`	Per-example value.
`sample_weight`	Optional weighting of each example. Defaults to 1.

Returns
Update op.