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TensorFlow 1 version
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View source on GitHub
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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
reset_states
reset_states()
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 metric value tensor.
Result computation is an idempotent operation that simply calculates the metric value using the state variables.
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. |