tf.metrics.true_negatives

Sum the weights of true_negatives.

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tf.compat.v1.metrics.true_negatives

tf.metrics.true_negatives(
    labels, predictions, weights=None, metrics_collections=None,
    updates_collections=None, name=None
)

If weights is None, weights default to 1. Use weights of 0 to mask values.

Args
labels	The ground truth values, a Tensor whose dimensions must match predictions. Will be cast to bool.
predictions	The predicted values, a Tensor of arbitrary dimensions. Will be cast to bool.
weights	Optional 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 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	A Tensor representing the current value of the metric.
update_op	An operation that accumulates the error from a batch of data.

Raises
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.
RuntimeError	If eager execution is enabled.