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# torch.lerp¶

torch.lerp(input, end, weight, *, out=None)

Does a linear interpolation of two tensors start (given by input) and end based on a scalar or tensor weight and returns the resulting out tensor.

$\text{out}_i = \text{start}_i + \text{weight}_i \times (\text{end}_i - \text{start}_i)$

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.

Parameters
• input (Tensor) – the tensor with the starting points

• end (Tensor) – the tensor with the ending points

• weight (float or tensor) – the weight for the interpolation formula

Keyword Arguments

out (Tensor, optional) – the output tensor.

Example:

>>> start = torch.arange(1., 5.)
>>> end = torch.empty(4).fill_(10)
>>> start
tensor([ 1.,  2.,  3.,  4.])
>>> end
tensor([ 10.,  10.,  10.,  10.])
>>> torch.lerp(start, end, 0.5)
tensor([ 5.5000,  6.0000,  6.5000,  7.0000])
>>> torch.lerp(start, end, torch.full_like(start, 0.5))
tensor([ 5.5000,  6.0000,  6.5000,  7.0000])


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