from .utils import gen_output def scatter_add_(output, index, input, dim=0): """ -> Tensor Sums up all values from the tensor :attr:`input` into :attr:`output` at the indices specified in the :attr:`index` tensor along an given axis :attr:`dim`. For each value in :attr:`input`, its output index is specified by its index in :attr:`input` for dimension != :attr:`dim` and by the corresponding value in :attr:`index` for dimension = :attr:`dim`. If multiple indices reference the same location, their contributions add. If :attr:`input` and :attr:`index` are n-dimensional tensors with size :math:`(x_0, ..., x_{i-1}, x_i, x_{i+1}, ..., x_{n-1})` and :attr:`dim` = i, then :attr:`output` must be an n-dimensional tensor with size :math:`(x_0, ..., x_{i-1}, y, x_{i+1}, ..., x_{n-1})`. Moreover, the values of :attr:`index` must be between `0` and `output.size(dim) - 1`. For one-dimensional tensors, the operation computes :math:`output_i = output_i + \sum_j input_j`, where sum is over :math:`j` such that :math:`index_j = i`. Args: output (Tensor): The destination tensor index (LongTensor): The indices of elements to scatter input (Tensor): The source tensor dim (int, optional): The axis along which to index Example:: >> input = torch.Tensor([[2, 0, 1, 4, 3], [0,2, 1, 3, 4]]) >> index = torch.LongTensor([[4, 5, 2, 3], [0, 0, 2, 2, 1]]) >> output = torch.zeros(2, 6) >> scatter_add_(output, index, input, dim=1) 0 0 4 3 3 0 2 4 4 0 0 0 [torch.FloatTensor of size 2x6] """ return output.scatter_add_(dim, index, input) def scatter_add(index, input, dim=0, size=None, fill_value=0): """ -> Tensor Sums ap all values from the tensor :attr:`input` at the indices specified in the :attr:`index` tensor along an given axis :attr:`dim`. The output size at dimension :attr:`dim` is given by :attr:`size` and must be at least size `index.max(dim) - 1`. If :attr:`size` is not given, a minimal sized output tensor is returned. The output tensor is initially filled with the specified value at :attr:`fill_value`. For one-dimensional tensors, the operation computes :math:`output_i = fill_value + \sum_j input_j`, where sum is over :math:`j` such that :math:`index_j = i`. A more detailed explanation is described in :meth:`~scatter_add_`. Args: index (LongTensor): The indices of elements to scatter input (Tensor): The source tensor dim (int, optional): The axis along which to index size (int, optional): Output size at dimension :attr:`dim` fill_value (int, optional): Initial filling of output tensor """ output = gen_output(index, input, dim, size, fill_value) return scatter_add_(output, index, input, dim)