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 | |
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A Tensor. Has the same type as x. |