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.randn(10)
>>> a
tensor([-0.8286, -0.4890,  0.5155,  0.8443,  0.1865, -0.1752, -2.0595,
         0.1850, -1.1571, -0.4243])
>>> torch.cumsum(a, dim=0)
tensor([-0.8286, -1.3175, -0.8020,  0.0423,  0.2289,  0.0537, -2.0058,
        -1.8209, -2.9780, -3.4022])