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)
