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Computes the (weighted) mean of the given values.
tf.compat.v1.metrics.mean(
values, weights=None, metrics_collections=None, updates_collections=None,
name=None
)
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.
Args | |
---|---|
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. |
Returns | |
---|---|
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 .
|
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. |