tf.contrib.metrics.streaming_recall_at_k( predictions, labels, k, 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 [email protected] of the predictions with respect to dense labels. (deprecated)
THIS FUNCTION IS DEPRECATED. It will be removed after 2016-11-08. Instructions for updating: Please use streaming_sparse_recall_at_k
, and reshape labels from [batch_size] to [batch_size, 1].
The streaming_recall_at_k
function creates two local variables, total
and count
, that are used to compute the [email protected] frequency. This frequency is ultimately returned as recall_at_<k>
: 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 recall_at_<k>
. Internally, an in_top_k
operation computes a Tensor
with shape [batch_size] whose elements indicate whether or not the corresponding label is in the top k
predictions
. Then update_op
increments total
with the reduced sum of weights
where in_top_k
is True
, 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 float Tensor
of dimension [batch_size, num_classes].labels
: A Tensor
of dimension [batch_size] whose type is in int32
, int64
.k
: The number of top elements to look at for computing recall.weights
: 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 recall_at_k
should be added to.updates_collections
: An optional list of collections update_op
should be added to.name
: An optional variable_scope name.recall_at_k
: A Tensor
representing the [email protected], the fraction of labels which fall into the top k
predictions.update_op
: An operation that increments the total
and count
variables appropriately and whose value matches recall_at_k
.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_recall_at_k