def METHOD_NAME(vec: Tensor, parameters: Iterable[Tensor]) -> None:
    r"""Convert one vector to the parameters
    The method is consistent with PyTorch.
    The documentation is referenced from:
    https://pytorch.org/docs/stable/generated/torch.nn.utils.vector_to_parameters.
    Args:
        vec (Tensor): a single vector represents the parameters of a model.
        parameters (Iterable[Tensor]): an iterator of Tensors that are the
            parameters of a model.
    """
    # Ensure vec of type Tensor
    if not isinstance(vec, Tensor):
        raise TypeError("expected flow.Tensor, but got: {}".format(flow.typename(vec)))
    # Flag for the device where the parameter is located
    param_device = None
    # Pointer for slicing the vector for each parameter
    pointer = 0
    for param in parameters:
        # Ensure the parameters are located in the same device
        param_device = _check_param_device(param, param_device)
        # The length of the parameter
        num_param = param.numel()
        # Slice the vector, reshape it, and replace the old data of the parameter
        param.data = vec[pointer : pointer + num_param].view_as(param).data
        # Increment the pointer
        pointer += num_param