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]
Returns | |
---|---|
A Tensor . Has the same type as x .
|