tf.compat.v1.metrics.percentage_below
Computes the percentage of values less than the given threshold.
tf.compat.v1.metrics.percentage_below( values, threshold, weights=None, metrics_collections=None, updates_collections=None, name=None )
The percentage_below
function creates two local variables, total
and count
that are used to compute the percentage of values
that fall below threshold
. This rate is weighted by weights
, and it is ultimately returned as percentage
which is an idempotent operation that simply divides total
by count
.
For estimation of the metric over a stream of data, the function creates an update_op
operation that updates these variables and returns the percentage
.
If weights
is None
, weights default to 1. Use weights of 0 to mask values.
Args | |
---|---|
values | A numeric Tensor of arbitrary size. |
threshold | A scalar threshold. |
weights | Optional Tensor whose rank is either 0, or the same rank as values , and must be broadcastable to values (i.e., all dimensions must be either 1 , or the same as the corresponding values dimension). |
metrics_collections | An optional list of collections that the metric value variable should be added to. |
updates_collections | An optional list of collections that the metric update ops should be added to. |
name | An optional variable_scope name. |
Returns | |
---|---|
percentage | A Tensor representing the current mean, the value of total divided by count . |
update_op | An operation that increments the total and count variables appropriately. |
Raises | |
---|---|
ValueError | If weights is not None and its shape doesn't match values , or if either metrics_collections or updates_collections are not a list or tuple. |
RuntimeError | If eager execution is enabled. |
© 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/compat/v1/metrics/percentage_below