tf.contrib.metrics.streaming_mean_absolute_error(
predictions,
labels,
weights=None,
metrics_collections=None,
updates_collections=None,
name=None
)
Defined in tensorflow/contrib/metrics/python/ops/metric_ops.py
.
Computes the mean absolute error between the labels and predictions. (deprecated)
The streaming_mean_absolute_error
function creates two local variables,
total
and count
that are used to compute the mean absolute error. This
average is weighted by weights
, and it is ultimately returned as
mean_absolute_error
: 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_absolute_error
. Internally, an absolute_errors
operation computes the
absolute value of the differences between predictions
and labels
. Then
update_op
increments total
with the reduced sum of the product of
weights
and absolute_errors
, 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:
predictions
: ATensor
of arbitrary shape.labels
: ATensor
of the same shape aspredictions
.weights
: OptionalTensor
indicating the frequency with which an example is sampled. Rank must be 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 thatmean_absolute_error
should be added to.updates_collections
: An optional list of collections thatupdate_op
should be added to.name
: An optional variable_scope name.
Returns:
mean_absolute_error
: ATensor
representing the current mean, the value oftotal
divided bycount
.update_op
: An operation that increments thetotal
andcount
variables appropriately and whose value matchesmean_absolute_error
.
Raises:
ValueError
: Ifpredictions
andlabels
have mismatched shapes, or ifweights
is notNone
and its shape doesn't matchpredictions
, or if eithermetrics_collections
orupdates_collections
are not a list or tuple.