tf.cumprod(x, axis=0, exclusive=False, reverse=False, name=None)

tf.cumprod(x, axis=0, exclusive=False, reverse=False, name=None)

See the guide: Math > Scan

Compute the cumulative product of the tensor x along axis.

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.cumprod([a, b, c]) ==> [a, a * b, a * b * c]

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

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

Args:

• x: A Tensor. Must be one of the following types: float32, float64, int64, int32, uint8, uint16, int16, int8, complex64, complex128, qint8, quint8, qint32, half.
• axis: A Tensor of type int32 (default: 0).
• reverse: A bool (default: False).
• name: A name for the operation (optional).

Returns:

A Tensor. Has the same type as x.

Defined in tensorflow/python/ops/math_ops.py.