tensorflow::ops::Cumprod

#include <math_ops.h>

Compute the cumulative product of the tensor x along axis.

Summary

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: ```prettyprint tf.cumprod([a, b, c]) ==> [a, a * b, a * b * c] ```

By setting the exclusive kwarg to True, an exclusive cumprod is performed instead: ```prettyprint tf.cumprod([a, b, c], exclusive=True) ==> [0, a, a * b] ```

By setting the reverse kwarg to True, the cumprod is performed in the opposite direction: ```prettyprint tf.cumprod([a, b, c], reverse=True) ==> [a * b * c, b * c, c] `` This is more efficient than using separatetf.reverse` ops.

The reverse and exclusive kwargs can also be combined: ```prettyprint tf.cumprod([a, b, c], exclusive=True, reverse=True) ==> [b * c, c, 0] ```

Arguments:

• scope: A Scope object

Returns:

• Output: The out tensor.

Public attributes

::tensorflow::Output out

Public functions

 Cumprod(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input x,
  ::tensorflow::Input axis
)

 Cumprod(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input x,
  ::tensorflow::Input axis,
  const Cumprod::Attrs & attrs
)

::tensorflow::Node * node() const 

operator::tensorflow::Input() const 

operator::tensorflow::Output() const 

Public static functions

Attrs Exclusive(
  bool x
)

Attrs Reverse(
  bool x
)