See also:
 "torch.cartesian_prod()" has the same effect but it collects the
 data in a tensor of vectors.

Parameters:
      * tensors (list of Tensor) -- list of scalars or 1
        dimensional tensors. Scalars will be treated as tensors of
        size (1,) automatically
  * **indexing** (*Optional**[**str**]*) --

    (str, optional): the indexing mode, either "xy" or "ij",
    defaults to "ij". See warning for future changes.

    If "xy" is selected, the first dimension corresponds to the
    cardinality of the second input and the second dimension
    corresponds to the cardinality of the first input.

    If "ij" is selected, the dimensions are in the same order as
    the cardinality of the inputs.

Returns:
      If the input has N tensors of size S_0 \ldots S_{N-1}`, then the
      output will also have N tensors, where each tensor is of shape
      (S_0, ..., S_{N-1}).
Return type:
      seq (sequence of Tensors)
Example: