def quantize_no_absmax(A: Tensor, code: Tensor, out: Optional[torch.Tensor] = None) -> Tensor:
    """
    Quantizes input tensor to 8-bit.

    Quantizes the 32-bit input tensor `A` to the 8-bit output tensor
    `out` using the quantization map `code`.

    Parameters
    ----------
    A : torch.Tensor
        The input tensor.
    code : torch.Tensor
        The quantization map.
    out : torch.Tensor, optional
        The output tensor. Needs to be of type byte.

    Returns
    -------
    torch.Tensor:
        Quantized 8-bit tensor.
    """
    with _cuda_device_of(A):
        if out is None:
            out = torch.zeros_like(A, dtype=torch.uint8)
        is_on_gpu([A, out])
        lib.cquantize(get_ptr(code), get_ptr(A), get_ptr(out), ct.c_int(A.numel()))

    return out

    Quantizes input tensor to 8-bit.

    Quantizes the 32-bit input tensor `A` to the 8-bit output tensor
    `out` using the quantization map `code`.

    Parameters
    ----------
    A : torch.Tensor
        The input tensor.
    code : torch.Tensor
        The quantization map.
    out : torch.Tensor, optional
        The output tensor. Needs to be of type byte.

    Returns
    -------
    torch.Tensor:
        Quantized 8-bit tensor.
    
bitsandbytes/functional.py