View source on GitHub |
Computes the (weighted) sum of the given values.
Inherits From: Metric
, Layer
, Module
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. |
Standalone usage:
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
merge_state
merge_state(
metrics
)
Merges the state from one or more metrics.
This method can be used by distributed systems to merge the state computed by different metric instances. Typically the state will be stored in the form of the metric's weights. For example, a tf.keras.metrics.Mean metric contains a list of two weight values: a total and a count. If there were two instances of a tf.keras.metrics.Accuracy that each independently aggregated partial state for an overall accuracy calculation, these two metric's states could be combined as follows:
m1 = tf.keras.metrics.Accuracy()
_ = m1.update_state([[1], [2]], [[0], [2]])
m2 = tf.keras.metrics.Accuracy()
_ = m2.update_state([[3], [4]], [[3], [4]])
m2.merge_state([m1])
m2.result().numpy()
0.75
Args | |
---|---|
metrics
|
an iterable of metrics. The metrics must have compatible state. |
Raises | |
---|---|
ValueError
|
If the provided iterable does not contain metrics matching the metric's required specifications. |
reset_state
reset_state()
Resets all of the metric state variables.
This function is called between epochs/steps, when a metric is evaluated during training.
result
result()
Computes and returns the scalar metric value tensor or a dict of scalars.
Result computation is an idempotent operation that simply calculates the metric value using the state variables.
Returns | |
---|---|
A scalar tensor, or a dictionary of scalar tensors. |
update_state
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. |