tensorflow:: ops:: Cumsum

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:

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

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

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:

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:

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

Args:

• scope: A Scope object
• 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)) .

Optional attributes (see Attrs ):

• exclusive: If True , perform exclusive cumsum.
• reverse: A bool (default: False).

Returns:

• Output : The out tensor.

Public attributes

Operation operation

::tensorflow::Output out

Public functions

 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
)

::tensorflow::Node * node() const 

 operator::tensorflow::Input() const 

 operator::tensorflow::Output() const 

Public static functions

Attrs Exclusive(
  bool x
)

Attrs Reverse(
  bool x
)