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:

```python tf.cumprod([a, b, c]) # => [a, a * b, a * b * c] ```

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

```python 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:

```python 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:

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

Arguments:

Returns:

Constructors and Destructors

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)

Public attributes

out

Public functions

node() const
::tensorflow::Node *
operator::tensorflow::Input() const
operator::tensorflow::Output() const

Public static functions

Exclusive(bool x)
Reverse(bool x)

Structs

tensorflow::ops::Cumprod::Attrs

Optional attribute setters for Cumprod.

Public attributes

out

::tensorflow::Output out

Public functions

Cumprod

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

Cumprod

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

node

::tensorflow::Node * node() const 

operator::tensorflow::Input

 operator::tensorflow::Input() const 

operator::tensorflow::Output

 operator::tensorflow::Output() const 

Public static functions

Exclusive

Attrs Exclusive(
  bool x
)

Reverse

Attrs Reverse(
  bool x
)