tf.cumprod( x, axis=0, exclusive=False, reverse=False, name=None )
Defined in tensorflow/python/ops/math_ops.py
.
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]
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). Must be in the range [-rank(x), rank(x))
.exclusive
: If True
, perform exclusive cumprod.reverse
: A bool
(default: False).name
: A name for the operation (optional).A Tensor
. Has the same type as x
.
© 2018 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/cumprod