tf.contrib.metrics.count

Computes the number of examples, or sum of weights.

tf.contrib.metrics.count(
    values, weights=None, metrics_collections=None, updates_collections=None,
    name=None
)

This metric keeps track of the denominator in tf.compat.v1.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	A Tensor of arbitrary dimensions. Only it's shape is used.
weights	Optional Tensor whose 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 labels 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	A Tensor representing the current value of the metric.
update_op	An operation that accumulates the metric from a batch of data.

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.