tf.contrib.metrics.count(
values,
weights=None,
metrics_collections=None,
updates_collections=None,
name=None
)
Defined in tensorflow/contrib/metrics/python/ops/metric_ops.py
.
Computes the number of examples, or sum of weights
.
This metric keeps track of the denominator in tf.metrics.mean
.
When evaluating some metric (e.g. mean) on one or more subsets of the data,
this auxiliary metric is useful for keeping track of how many examples there
are in each subset.
If weights
is None
, weights default to 1. Use weights of 0 to mask values.
Args:
values
: ATensor
of arbitrary dimensions. Only it's shape is used.weights
: OptionalTensor
whose rank is either 0, or the same rank aslabels
, and must be broadcastable tolabels
(i.e., all dimensions must be either1
, or the same as the correspondinglabels
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:
count
: ATensor
representing the current value of the metric.update_op
: An operation that accumulates the metric from a batch of data.
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.