torch.meshgrid

torch.meshgrid(*tensors)

Take $N$ tensors, each of which can be either scalar or 1-dimensional vector, and create $N$ N-dimensional grids, where the $i$ ^th grid is defined by expanding the $i$ ^th input over dimensions defined by other inputs.

Args:

tensors (list of Tensor): list of scalars or 1 dimensional tensors. Scalars will be treated as tensors of size $(1,)$ automatically

Returns:

seq (sequence of Tensors): If the input has $k$ tensors of size $(N_1,), (N_2,), \ldots , (N_k,)$ , then the output would also have $k$ tensors, where all tensors are of size $(N_1, N_2, \ldots , N_k)$ .

Example:

>>> x = torch.tensor([1, 2, 3])
>>> y = torch.tensor([4, 5, 6])
>>> grid_x, grid_y = torch.meshgrid(x, y)
>>> grid_x
tensor([[1, 1, 1],
        [2, 2, 2],
        [3, 3, 3]])
>>> grid_y
tensor([[4, 5, 6],
        [4, 5, 6],
        [4, 5, 6]])