| 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. |
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')
reset_statesreset_states()
Resets all of the metric state variables.
This function is called between epochs/steps, when a metric is evaluated during training.
resultresult()
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. |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/keras/metrics/Sum