mindspore.ops.lerp

mindspore.ops.lerp(input, end, weight)[source]

Does a linear interpolation of two tensors input and end based on a float or tensor weight.

o u t p u t_{i} = i n p u t_{i} + w e i g h t_{i} * (e n d_{i} - i n p u t_{i})

Note

The shapes of input and end must be broadcastable.
If weight is a tensor, then the shapes of weight , start , and end must be broadcastable.
On the Ascend platform, if weight dtype is float, the type of input and end need to be float32.

Parameters

input (Tensor) – The tensor with the starting points.
end (Tensor) – The tensor with the ending points.
weight (Union[float, Tensor]) – The weight for the interpolation formula.

Returns

Tensor

Supported Platforms:: Ascend GPU CPU

Examples

>>> import mindspore
>>> start = mindspore.tensor([1., 2., 3., 4.], mindspore.float32)
>>> end = mindspore.tensor([10., 10., 10., 10.], mindspore.float32)
>>> output = mindspore.ops.lerp(start, end, 0.5)
>>> print(output)
[5.5 6.  6.5 7. ]
>>> output = mindspore.ops.lerp(start, end, mindspore.tensor([0.5, 0.5, 0.5, 0.5], mindspore.float32))
>>> print(output)
[5.5 6.  6.5 7. ]