torch / torch
torch.bucketize¶
-
torch.
bucketize
(input, boundaries, *, out_int32=False, right=False, out=None) → Tensor¶ Returns the indices of the buckets to which each value in the
input
belongs, where the boundaries of the buckets are set byboundaries
. Return a new tensor with the same size asinput
. Ifright
is False (default), then the left boundary is closed. More formally, the returned index satisfies the following rules:right
returned index satisfies
False
boundaries[i-1] <= input[m][n]...[l][x] < boundaries[i]
True
boundaries[i-1] < input[m][n]...[l][x] <= boundaries[i]
- Parameters
- Keyword Arguments
out_int32 (bool, optional) – indicate the output data type. torch.int32 if True, torch.int64 otherwise. Default value is False, i.e. default output data type is torch.int64.
right (bool, optional) – if False, return the first suitable location that is found. If True, return the last such index. If no suitable index found, return 0 for non-numerical value (eg. nan, inf) or the size of
boundaries
(one pass the last index). In other words, if False, gets the lower bound index for each value ininput
fromboundaries
. If True, gets the upper bound index instead. Default value is False.out (Tensor, optional) – the output tensor, must be the same size as
input
if provided.
Example:
>>> boundaries = torch.tensor([1, 3, 5, 7, 9]) >>> boundaries tensor([1, 3, 5, 7, 9]) >>> v = torch.tensor([[3, 6, 9], [3, 6, 9]]) >>> v tensor([[3, 6, 9], [3, 6, 9]]) >>> torch.bucketize(v, boundaries) tensor([[1, 3, 4], [1, 3, 4]]) >>> torch.bucketize(v, boundaries, right=True) tensor([[2, 3, 5], [2, 3, 5]])
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