automatically generate op convenience overloads?

Should we extend the code generation for ops to automatically generate convenience overloads? This would help reduce the gap between Python notation and Java notation.

As an example of where we stand now, here's some Python code (keras/metrics.py, around line 2203):

    dp = p[:self.num_thresholds - 1] - p[1:]

And here's the corresponding Java code (AUC.java, around line 809):

    Operand<T> dP =
        tf.math.sub(
            tf.slice(
                p, tf.constant(new int[] {0}), tf.constant(new int[] {getNumThresholds() - 1})),
            tf.slice(p, tf.constant(new int[] {1}), tf.constant(new int[] {-1})));

先比較 keras/metrics.py 約第 2203 行的 Python 範例與 AUC.java 約第 809 行的 Java 實作。確定應產生哪些 convenience overloads，以及 Python 和 Java 形式應如何對應；確定一致的產生範圍和由此產生的 Java API 後，即可視為完成。