oneflow.bincount¶
-
oneflow.
bincount
()¶ oneflow.bincount(input, weights=None, minlength=0) → Tensor
The interface is consistent with PyTorch.
The documentation is referenced from: https://pytorch.org/docs/1.10/generated/torch.bincount.html.
Count the frequency of each value in an array of non-negative ints.
The number of bins (size 1) is one larger than the largest value in
input
unlessinput
is empty, in which case the result is a tensor of size 0. Ifminlength
is specified, the number of bins is at leastminlength
and ifinput
is empty, then the result is tensor of sizeminlength
filled with zeros. Ifn
is the value at positioni
,out[n] += weights[i]
ifweights
is specified elseout[n] += 1
.- Parameters
input (oneflow.Tensor) – 1-d int Tensor
weights (oneflow.Tensor) – optional, weight for each value in the input tensor. Should be of same size as input tensor.
minlength (int) – optional, minimum number of bins. Should be non-negative.
For example:
>>> import oneflow as flow >>> x = flow.tensor([1, 2, 4, 6]) >>> flow.bincount(x) tensor([0, 1, 1, 0, 1, 0, 1], dtype=oneflow.int64) >>> x = flow.tensor([1, 2, 1]) >>> weights = flow.tensor([0.1, 0.2, 0.15]) >>> flow.bincount(x, weights=weights) tensor([0.0000, 0.2500, 0.2000], dtype=oneflow.float32) >>> flow.bincount(x, weights=weights, minlength=4) tensor([0.0000, 0.2500, 0.2000, 0.0000], dtype=oneflow.float32)