tf.keras.metrics.Sum

Compute the (weighted) sum of the given values.

Inherits From: Metric

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

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

This metric creates one variable, total. This is ultimately returned as the sum value.

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

Example:

m = metrics.Sum()
m.update_state([1, 3, 5, 7])
m.result()
16.0
 
m = metrics.Sum()
m.update_state([1, 3, 5, 7], sample_weight=[1, 1, 0, 0])
m.result()
4.0

dtype

variables

Methods

add_variable

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add_variable(
    shape, initializer, dtype=None, aggregation='sum', name=None
)

add_weight

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add_weight(
    shape=(), initializer=None, dtype=None, name=None
)

from_config

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@classmethod
from_config(
    config
)

get_config

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get_config()

Return the serializable config of the metric.

reset_state

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reset_state()

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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result()

Compute the current metric value.

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

stateless_reset_state

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stateless_reset_state()

stateless_result

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stateless_result(
    metric_variables
)

stateless_update_state

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stateless_update_state(
    metric_variables, *args, **kwargs
)

update_state

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update_state(
    values, sample_weight=None
)

Accumulate statistics for the metric.

__call__

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__call__(
    *args, **kwargs
)

Call self as a function.