broadcast.
Note:
 This operation may behave nondeterministically when given tensors
 on a CUDA device. See Reproducibility for more information.

Note:
 The backward pass is implemented only for "src.shape ==
 index.shape".

Parameters:
      * dim (int) -- the axis along which to index
  * **index** (*LongTensor*) -- the indices of elements to scatter
    and add, can be either empty or of the same dimensionality as
    "src". When empty, the operation returns "self" unchanged.

  * **src** (*Tensor*) -- the source elements to scatter and add

Example:
  >>> src = torch.ones((2, 5))
  >>> index = torch.tensor([[0, 1, 2, 0, 0]])
  >>> torch.zeros(3, 5, dtype=src.dtype).scatter_add_(0, index, src)
  tensor([[1., 0., 0., 1., 1.],
          [0., 1., 0., 0., 0.],
          [0., 0., 1., 0., 0.]])
  >>> index = torch.tensor([[0, 1, 2, 0, 0], [0, 1, 2, 2, 2]])
  >>> torch.zeros(3, 5, dtype=src.dtype).scatter_add_(0, index, src)
