tf.compat.v1.metrics.false_positives

Sum the weights of false positives.

tf.compat.v1.metrics.false_positives(
    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.

labelsThe ground truth values, a Tensor whose dimensions must match predictions. Will be cast to bool.
predictionsThe predicted values, a Tensor of arbitrary dimensions. Will be cast to bool.
weightsOptional 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_collectionsAn optional list of collections that the metric value variable should be added to.
updates_collectionsAn optional list of collections that the metric update ops should be added to.
nameAn optional variable_scope name.

value_tensorA Tensor representing the current value of the metric.
update_opAn operation that accumulates the error from a batch of data.

ValueErrorIf 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.
RuntimeErrorIf eager execution is enabled.