tf.metrics.percentage_below(
values,
threshold,
weights=None,
metrics_collections=None,
updates_collections=None,
name=None
)
Defined in tensorflow/python/ops/metrics_impl.py
.
Computes the percentage of values less than the given threshold.
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 numericTensor
of arbitrary size.threshold
: A scalar threshold.weights
: OptionalTensor
whose rank is either 0, or the same rank asvalues
, and must be broadcastable tovalues
(i.e., all dimensions must be either1
, or the same as the correspondingvalues
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
: ATensor
representing the current mean, the value oftotal
divided bycount
.update_op
: An operation that increments thetotal
andcount
variables appropriately.
Raises:
ValueError
: Ifweights
is notNone
and its shape doesn't matchvalues
, or if eithermetrics_collections
orupdates_collections
are not a list or tuple.RuntimeError
: If eager execution is enabled.