tfp.experimental.distributions.marginal_fns.ps.cumprod

Compute the cumulative product of the tensor x along axis.

tfp.experimental.distributions.marginal_fns.ps.cumprod(
    x, axis=0, exclusive=False, reverse=False, name=None
)

By default, this op performs an inclusive cumprod, which means that the first element of the input is identical to the first element of the output:

tf.math.cumprod([a, b, c])  # [a, a * b, a * b * c]

By setting the exclusive kwarg to True, an exclusive cumprod is performed instead:

tf.math.cumprod([a, b, c], exclusive=True)  # [1, a, a * b]

By setting the reverse kwarg to True, the cumprod is performed in the opposite direction:

tf.math.cumprod([a, b, c], reverse=True)  # [a * b * c, b * c, c]

This is more efficient than using separate tf.reverse ops. The reverse and exclusive kwargs can also be combined:

tf.math.cumprod([a, b, c], exclusive=True, reverse=True)  # [b * c, c, 1]