def create_linear_map()

in bitsandbytes/functional.py [0:0]

• 12 lines of code
• 7 McCabe index (conditional complexity)

def create_linear_map(signed=True, total_bits=8, add_zero=True):
    sign = -1.0 if signed else 0.0
    total_values = 2**total_bits
    if add_zero or total_bits < 8:
        # add a zero
        # since we simulate less bits by having zeros in the data type, we
        # we need to center the quantization around zero and as such lose
        # a single value
        total_values = 2**total_bits if not signed else 2**total_bits - 1

    values = torch.linspace(sign, 1.0, total_values)
    gap = 256 - values.numel()
    if gap == 0:
        return values
    else:
        l = values.numel() // 2  # noqa: E741
        return torch.Tensor(values[:l].tolist() + [0] * gap + values[l:].tolist())