tf.contrib.metrics.count( values, weights=None, metrics_collections=None, updates_collections=None, name=None )
Computes the number of examples, or sum of
This metric keeps track of the denominator in
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.
None, weights default to 1. Use weights of 0 to mask values.
Tensorof arbitrary dimensions. Only it's shape is used.
Tensorwhose rank is either 0, or the same rank as
labels, and must be broadcastable to
labels(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 value of the metric.
update_op: An operation that accumulates the metric from a batch of data.
Noneand its shape doesn't match
values, or if either
updates_collectionsare not a list or tuple.
RuntimeError: If eager execution is enabled.