TensorFlow 1 version | View source on GitHub |
Compute the cumulative sum of the tensor x
along axis
.
tf.math.cumsum(
x, axis=0, exclusive=False, reverse=False, name=None
)
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 | |
---|---|
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 cumsum.
|
reverse
|
A bool (default: False).
|
name
|
A name for the operation (optional). |
Returns | |
---|---|
A Tensor . Has the same type as x .
|