Scatter Div

torch_scatter.scatter_div(src, index, dim=-1, out=None, dim_size=None, fill_value=1)

Divides all values from the src tensor into out at the indices specified in the index tensor along a given axis dim.If multiple indices reference the same location, their contributions divide (cf. scatter_add()).

For one-dimensional tensors, the operation computes

\[\mathrm{out}_i = \mathrm{out}_i \cdot \prod_j \frac{1}{\mathrm{src}_j}\]

where \(\prod_j\) is over \(j\) such that \(\mathrm{index}_j = i\).

Parameters:

• src (Tensor) – The source tensor.
• index (LongTensor) – The indices of elements to scatter.
• dim (int, optional) – The axis along which to index. (default: -1)
• out (Tensor, optional) – The destination tensor. (default: None)
• dim_size (int, optional) – If out is not given, automatically create output with size dim_size at dimension dim. If dim_size is not given, a minimal sized output tensor is returned. (default: None)
• fill_value (int, optional) – If out is not given, automatically fill output tensor with fill_value. (default: 1)

Return type:

Tensor

from torch_scatter import scatter_div

src = torch.Tensor([[2, 1, 1, 4, 2], [1, 2, 1, 2, 4]]).float()
index = torch.tensor([[4, 5, 4, 2, 3], [0, 0, 2, 2, 1]])
out = src.new_ones((2, 6))

out = scatter_div(src, index, out=out)

print(out)

tensor([[1.0000, 1.0000, 0.2500, 0.5000, 0.5000, 1.0000],
        [0.5000, 0.2500, 0.5000, 1.0000, 1.0000, 1.0000]])