oneflow.lerp¶
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oneflow.
lerp
(start, end, weight) → Tensor¶ The documentation is referenced from: https://pytorch.org/docs/stable/generated/torch.lerp.html.
Does a linear interpolation of two tensors start and end based on a scalar or tensor weight and returns the result.
The shapes of start` and end must be broadcastable. If weight is a tensor, then the shapes of weight, start, and end must be broadcastable.
\[out_{i} = start_{i} + weight_{i} * (end_{i} - start_{i})\]- Parameters
start (oneflow.Tensor) – the tensor with the starting points.
end (oneflow.Tensor) – the tensor with the ending points.
weight (float or oneflow.Tensor) – the weight for the interpolation formula.
For example:
>>> import oneflow as flow >>> start = flow.arange(1., 5.) >>> end = flow.empty(4).fill_(10) >>> flow.lerp(start, end, 0.5) tensor([5.5000, 6.0000, 6.5000, 7.0000], dtype=oneflow.float32) >>> flow.lerp(start, end, flow.full_like(start, 0.5)) tensor([5.5000, 6.0000, 6.5000, 7.0000], dtype=oneflow.float32)