tf.compat.v1.metrics.true_negatives

Sum the weights of true_negatives.

tf.compat.v1.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.

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.

value_tensor A Tensor representing the current value of the metric.
update_op An operation that accumulates the error from a batch of data.

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.