mygrad.cumsum#

mygrad.cumsum(a: ArrayLike, axis: Union[None, int, Tuple[int, ...]] = None, *, constant: Optional[bool] = None) → Tensor[source]#

Return the cumulative sum of the elements along a given axis.

This docstring was adapted from the official numpy documentation

Parameters

aArrayLike

Input array.

axisint, optional

Axis along which the cumulative sum is computed. The default (None) is to compute the cumsum over the flattened array.

constantOptional[bool]

If True, this tensor is treated as a constant, and thus does not facilitate back propagation (i.e. constant.grad will always return None).

Defaults to False for float-type data. Defaults to True for integer-type data.

Integer-type tensors must be constant.

Returns

mygrad.Tensor

Examples

>>> from mygrad import cumsum, Tensor
>>> a = Tensor([[1, 2, 3],
...             [4, 5, 6]])
>>> cumsum(a)
Tensor([ 1,  3,  6, 10, 15, 21])

>>> cumsum(a, axis=0)      # sum over rows for each of the 3 columns
Tensor([[1, 2, 3],
        [5, 7, 9]])
>>> cumsum(a, axis=1)      # sum over columns for each of the 2 rows
Tensor([[ 1,  3,  6],
        [ 4,  9, 15]])