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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`. It broadcasts over the batch dimensions.

  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.

  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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