metrics.py 文件源码

def precision_recall_values(xvals, precision, recall, name=None):
    """Compute values on the precision/recall curve.

    Args:
      x: Python list of floats;
      precision: 1D Tensor decreasing.
      recall: 1D Tensor increasing.
    Return:
      list of precision values.
    """
    with ops.name_scope(name, "precision_recall_values",
                        [precision, recall]) as name:
        # Add bounds values to precision and recall.
        precision = tf.concat([[0.], precision, [0.]], axis=0)
        recall = tf.concat([[0.], recall, [1.]], axis=0)
        precision = tfe_math.cummax(precision, reverse=True)

        prec_values = []
        for x in xvals:
            mask = tf.less_equal(recall, x)
            val = tf.reduce_min(tf.boolean_mask(precision, mask))
            prec_values.append(val)
        return tf.tuple(prec_values)


# =========================================================================== #
# TF Extended metrics: old stuff!
# =========================================================================== #