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# 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+⋯+x i y_i = x_1 + x_2 + x_3 + \dots + x_i y i​=x 1​+x 2​+x 3​+⋯+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])

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