tf.metrics.percentage_below( values, threshold, weights=None, metrics_collections=None, updates_collections=None, name=None )
Computes the percentage of values less than the given threshold.
percentage_below function creates two local variables,
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
For estimation of the metric over a stream of data, the function creates an
update_op operation that updates these variables and returns the
None, weights default to 1. Use weights of 0 to mask values.
values: A numeric
Tensorof arbitrary size.
threshold: A scalar threshold.
Tensorwhose 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
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.
Tensorrepresenting the current mean, the value of
update_op: An operation that increments the
Noneand its shape doesn't match
values, or if either
updates_collectionsare not a list or tuple.
RuntimeError: If eager execution is enabled.
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Code samples licensed under the Apache 2.0 License.