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# torch.linalg.cross¶

torch.linalg.cross(input, other, *, dim=- 1, out=None)Tensor

Computes the cross product of two 3-dimensional vectors.

Supports input of float, double, cfloat and cdouble dtypes. Also supports batches of vectors, for which it computes the product along the dimension dim. In this case, the output has the same batch dimensions as the inputs broadcast to a common shape.

Parameters
• input (Tensor) – the first input tensor.

• other (Tensor) – the second input tensor.

• dim (int, optional) – the dimension along which to take the cross-product. Default: -1.

Keyword Arguments

out (Tensor, optional) – the output tensor. Ignored if None. Default: None.

Raises

RuntimeError – If after broadcasting input.size(dim) != 3 or other.size(dim) != 3.

Example

>>> a = torch.randn(4, 3)
>>> a
tensor([[-0.3956,  1.1455,  1.6895],
[-0.5849,  1.3672,  0.3599],
[-1.1626,  0.7180, -0.0521],
[-0.1339,  0.9902, -2.0225]])
>>> b = torch.randn(4, 3)
>>> b
tensor([[-0.0257, -1.4725, -1.2251],
[-1.1479, -0.7005, -1.9757],
[-1.3904,  0.3726, -1.1836],
[-0.9688, -0.7153,  0.2159]])
>>> torch.linalg.cross(a, b)
tensor([[ 1.0844, -0.5281,  0.6120],
[-2.4490, -1.5687,  1.9792],
[-0.8304, -1.3037,  0.5650],
[-1.2329,  1.9883,  1.0551]])
>>> a = torch.randn(1, 3)  # a is broadcast to match shape of b
>>> a
tensor([[-0.9941, -0.5132,  0.5681]])
>>> torch.linalg.cross(a, b)
tensor([[ 1.4653, -1.2325,  1.4507],
[ 1.4119, -2.6163,  0.1073],
[ 0.3957, -1.9666, -1.0840],
[ 0.2956, -0.3357,  0.2139]])


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