# tensorflow::ops::Cumsum

#include <math_ops.h>

Compute the cumulative sum of the tensor x along axis.

## Summary

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

```python tf.cumsum([a, b, c]) # => [a, a + b, a + b + c] ```

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

```python tf.cumsum([a, b, c], exclusive=True) # => [0, a, a + b] ```

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

```python tf.cumsum([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.cumsum([a, b, c], exclusive=True, reverse=True) # => [b + c, c, 0] ```

Arguments:

Returns:

### Constructors and Destructors

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

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::Cumsum::Attrs

Optional attribute setters for Cumsum.

## Public attributes

### out

::tensorflow::Output out

## Public functions

### Cumsum

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

### Cumsum

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

### node

::tensorflow::Node * node() const

### operator::tensorflow::Input

operator::tensorflow::Input() const

### operator::tensorflow::Output

operator::tensorflow::Output() const

Attrs Exclusive(
bool x
)

Attrs Reverse(
bool x
)