tf.contrib.metrics.streaming_root_mean_squared_error( predictions, labels, weights=None, metrics_collections=None, updates_collections=None, name=None )
Defined in tensorflow/contrib/metrics/python/ops/metric_ops.py
.
See the guide: Metrics (contrib) > Metric Ops
Computes the root mean squared error between the labels and predictions.
The streaming_root_mean_squared_error
function creates two local variables, total
and count
that are used to compute the root mean squared error. This average is weighted by weights
, and it is ultimately returned as root_mean_squared_error
: an idempotent operation that takes the square root of the division of 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 root_mean_squared_error
. Internally, a squared_error
operation computes the element-wise square of the difference between predictions
and labels
. Then update_op
increments total
with the reduced sum of the product of weights
and squared_error
, 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.
predictions
: A Tensor
of arbitrary shape.labels
: A Tensor
of the same shape as predictions
.weights
: Optional Tensor
indicating the frequency with which an example is sampled. Rank must be 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 root_mean_squared_error
should be added to.updates_collections
: An optional list of collections that update_op
should be added to.name
: An optional variable_scope name.root_mean_squared_error
: 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 root_mean_squared_error
.ValueError
: If predictions
and labels
have mismatched shapes, or if weights
is not None
and its shape doesn't match predictions
, or if either metrics_collections
or updates_collections
are not a list or tuple.
© 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/contrib/metrics/streaming_root_mean_squared_error