tf.metrics.true_negatives(
labels,
predictions,
weights=None,
metrics_collections=None,
updates_collections=None,
name=None
)
Defined in tensorflow/python/ops/metrics_impl.py
.
Sum the weights of true_negatives.
If weights
is None
, weights default to 1. Use weights of 0 to mask values.
Args:
labels
: The ground truth values, aTensor
whose dimensions must matchpredictions
. Will be cast tobool
.predictions
: The predicted values, aTensor
of arbitrary dimensions. Will be cast tobool
.weights
: OptionalTensor
whose rank is either 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 that the metric value variable should be added to.updates_collections
: An optional list of collections that the metric update ops should be added to.name
: An optional variable_scope name.
Returns:
value_tensor
: ATensor
representing the current value of the metric.update_op
: An operation that accumulates the error from a batch of data.
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.RuntimeError
: If eager execution is enabled.