reference/generated/torchrl.objectives.two_hot_encode

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torchrl.objectives.two_hot_encode

torchrl.objectives.two_hot_encode(x: Tensor, bins: Tensor) → Tensor

Encode raw scalar values on a sorted two-hot support.

Values between adjacent support points are represented by linear interpolation in raw value space. Values outside the support saturate at its endpoints.

Parameters:

• x (torch.Tensor) – Raw scalar targets.

• bins (torch.Tensor) – One-dimensional, ascending support.

Returns:

A tensor with shape (*x.shape, bins.numel()) on the dtype and device of x.

Examples

>>> import torch
>>> from torchrl.objectives import two_hot_encode
>>> bins = torch.tensor([-1.0, 0.0, 1.0])
>>> two_hot_encode(torch.tensor([0.25]), bins)
tensor([[0.0000, 0.7500, 0.2500]])