tf.metrics.mean( values, weights=None, metrics_collections=None, updates_collections=None, name=None )
Defined in tensorflow/python/ops/metrics_impl.py
.
Computes the (weighted) mean of the given values.
The mean
function creates two local variables, total
and count
that are used to compute the average of values
. This average is ultimately returned as mean
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 mean
. update_op
increments total
with the reduced sum of the product of values
and weights
, and it increments count
with the reduced sum of weights
.
If weights
is None
, weights default to 1. Use weights of 0 to mask values.
values
: A Tensor
of arbitrary dimensions.weights
: Optional Tensor
whose 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 values
dimension).metrics_collections
: An optional list of collections that mean
should be added to.updates_collections
: An optional list of collections that update_op
should be added to.name
: An optional variable_scope name.mean
: A Tensor
representing the current mean, the value of total
divided by count
.update_op
: An operation that increments the total
and count
variables appropriately and whose value matches mean_value
.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.
© 2018 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/metrics/mean