torch.cross#

torch.cross(input,other,dim=None,*,out=None)→Tensor#

Returns the cross product of vectors in dimensiondim ofinputandother.

Supports input of float, double, cfloat and cdouble dtypes. Also supports batchesof vectors, for which it computes the product along the dimensiondim.In this case, the output has the same batch dimensions as the inputs.

Warning

Ifdim is not given, it defaults to the first dimension foundwith the size 3. Note that this might be unexpected.

This behavior is deprecated and will be changed to match that oftorch.linalg.cross()in a future release.

See also

torch.linalg.cross() which has dim=-1 as default.

Parameters

• input (Tensor) – the input tensor.

• other (Tensor) – the second input tensor

• dim (int,optional) – the dimension to take the cross-product in.

Keyword Arguments

out (Tensor,optional) – the output tensor.

Example:

>>>a=torch.randn(4,3)>>>atensor([[-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)>>>btensor([[-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.cross(a,b,dim=1)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]])>>>torch.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]])