Reduces all values from the src tensor to the indices specified in the index tensor in the self tensor using the applied reduction defined via the reduce argument ("sum", "prod", "mean", "amax", "amin"). For each value in src, it is reduced to an index in self which is specified by its index in src for dimension != dim and by the corresponding value in index for dimension = dim. If include_self="True", the values in the self tensor are included in the reduction.
self, index and src should all have the same number of dimensions. It is also required that index.size(d) <= src.size(d) for all dimensions d, and that index.size(d) <= self.size(d) for all dimensions d != dim. Note that index and src do not broadcast.
self[index[i][j][k]][j][k] += src[i][j][k] # if dim == 0 self[i][index[i][j][k]][k] += src[i][j][k] # if dim == 1 self[i][j][index[i][j][k]] += src[i][j][k] # if dim == 2
>>> src = torch.tensor([1., 2., 3., 4., 5., 6.]) >>> index = torch.tensor([0, 1, 0, 1, 2, 1]) >>> input = torch.tensor([1., 2., 3., 4.]) >>> input.scatter_reduce(0, index, src, reduce="sum") tensor([5., 14., 8., 4.]) >>> input.scatter_reduce(0, index, src, reduce="sum", include_self=False) tensor([4., 12., 5., 4.]) >>> input2 = torch.tensor([5., 4., 3., 2.]) >>> input2.scatter_reduce(0, index, src, reduce="amax") tensor([5., 6., 5., 2.]) >>> input2.scatter_reduce(0, index, src, reduce="amax", include_self=False) tensor([3., 6., 5., 2.])
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4