tf.cumsum(x, axis=0, exclusive=False, reverse=False, name=None)
Compute the cumulative sum of the tensor x
along axis
.
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: prettyprint
tf.cumsum([a, b, c]) ==> [a, a + b, a + b + c]
By setting the exclusive
kwarg to True
, an exclusive cumsum is performed instead: prettyprint
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: prettyprint
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: prettyprint
tf.cumsum([a, b, c], exclusive=True, reverse=True) ==> [b + c, c, 0]
Args:
-
x
: ATensor
. Must be one of the following types:float32
,float64
,int64
,int32
,uint8
,uint16
,int16
,int8
,complex64
,complex128
,qint8
,quint8
,qint32
,half
. -
axis
: ATensor
of typeint32
(default: 0). -
reverse
: Abool
(default: False). -
name
: A name for the operation (optional).
Returns:
A Tensor
. Has the same type as x
.
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