optimizers.py 文件源码

def piecewise_constant(x, boundaries, values):
    """ Piecewise constant function.

    Arguments:
        x: A 0-D Tensor.
        boundaries: A 1-D NumPy array with strictly increasing entries.
        values: A 1-D NumPy array that specifies the values for the intervals
            defined by `boundaries`. (It should therefore have one more entry
            than `boundaries`.)

    Returns: A 0-D Tensor. Its value is `values[0]` when `x <= boundaries[0]`,
        `values[1]` when `x > boundaries[0]` and `x <= boundaries[1]`, ..., and
        values[-1] when `x > boundaries[-1]`.
    """

    pred_fn_pairs = {}
    pred_fn_pairs[x <= boundaries[0]] = lambda: tf.constant(values[0])
    pred_fn_pairs[x > boundaries[-1]] = lambda: tf.constant(values[-1])
    for lower, upper, value in zip(boundaries[:-1],
                                   boundaries[1:],
                                   values[1:-1]):
        # We need to bind value here; can do this with lambda value=value: ...
        pred = (x > lower) & (x <= upper)
        pred_fn_pairs[pred] = lambda value=value: tf.constant(value)

    return tf.case(pred_fn_pairs, lambda: tf.constant(values[0]),
                   exclusive=True)