Compute the cumulative sum of the tensor x along axis.
tf.raw_ops.Cumsum(
    x, axis, 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, int32, uint8, int16, int8, complex64, int64, qint8, quint8, qint32, bfloat16, uint16, complex128, half, uint32, uint64.
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. Must be one of the following types: int32, int64.
A Tensor of type int32 (default: 0). Must be in the range
[-rank(x), rank(x)).
 | 
exclusive
 | 
An optional bool. Defaults to False.
If True, perform exclusive cumsum.
 | 
reverse
 | 
An optional bool. Defaults to False.
A bool (default: False).
 | 
name
 | 
A name for the operation (optional). | 
Returns | |
|---|---|
A Tensor. Has the same type as x.
 |