torch.cumsum

torch.cumsum(input, dim, *, dtype=None, out=None) → Tensor

Returns the cumulative sum of elements of input in the dimension dim.

For example, if input is a vector of size N, the result will also be a vector of size N, with elements.

$$y_i = x_1 + x_2 + x_3 + \dots + x_i$$

Parameters

• input (Tensor) – the input tensor.
• dim (int) – the dimension to do the operation over

Keyword Arguments

• dtype (torch.dtype, optional) – the desired data type of returned tensor. If specified, the input tensor is casted to dtype before the operation is performed. This is useful for preventing data type overflows. Default: None.
• out (Tensor, optional) – the output tensor.

Example:

>>> a = torch.randint(1, 20, (10,))
>>> a
tensor([13,  7,  3, 10, 13,  3, 15, 10,  9, 10])
>>> torch.cumsum(a, dim=0)
tensor([13, 20, 23, 33, 46, 49, 64, 74, 83, 93])