def meshgrid(*x, indexing="xy"):
    """Creates grids of coordinates from coordinate vectors.

    Given `N` 1-D tensors `T0, T1, ..., TN-1` as inputs with corresponding
    lengths `S0, S1, ..., SN-1`, this creates an `N` N-dimensional tensors
    `G0, G1, ..., GN-1` each with shape `(S0, ..., SN-1)` where the output
    `Gi` is constructed by expanding `Ti` to the result shape.

    Args:
        x: 1-D tensors representing the coordinates of a grid.
        indexing: `"xy"` or `"ij"`. "xy" is cartesian; `"ij"` is matrix
            indexing of output. Defaults to `"xy"`.

    Returns:
        Sequence of N tensors.

    Example:
    >>> from keras.src import ops
    >>> x = ops.array([1, 2, 3])
    >>> y = ops.array([4, 5, 6])

    >>> grid_x, grid_y = ops.meshgrid(x, y, indexing="ij")
    >>> grid_x
    array([[1, 1, 1],
           [2, 2, 2],
           [3, 3, 3]])
    >>> grid_y
    array([[4, 5, 6],
           [4, 5, 6],
           [4, 5, 6]])
    """
    if any_symbolic_tensors(x):
        return Meshgrid(indexing=indexing).symbolic_call(*x)
    return backend.numpy.meshgrid(*x, indexing=indexing)
Creates grids of coordinates from coordinate vectors.

    Given `N` 1-D tensors `T0, T1, ..., TN-1` as inputs with corresponding
    lengths `S0, S1, ..., SN-1`, this creates an `N` N-dimensional tensors
    `G0, G1, ..., GN-1` each with shape `(S0, ..., SN-1)` where the output
    `Gi` is constructed by expanding `Ti` to the result shape.

    Args:
        x: 1-D tensors representing the coordinates of a grid.
        indexing: `"xy"` or `"ij"`. "xy" is cartesian; `"ij"` is matrix
            indexing of output. Defaults to `"xy"`.

    Returns:
        Sequence of N tensors.

    Example:
    >>> from keras.src import ops
    >>> x = ops.array([1, 2, 3])
    >>> y = ops.array([4, 5, 6])

    >>> grid_x, grid_y = ops.meshgrid(x, y, indexing="ij")
    >>> grid_x
    array([[1, 1, 1],
           [2, 2, 2],
           [3, 3, 3]])
    >>> grid_y
    array([[4, 5, 6],
           [4, 5, 6],
           [4, 5, 6]])
    
keras/src/ops/numpy.py