MappingType¶
- class torch.ao.quantization.observer.MappingType(value)[source][source]¶
How floating point number is mapped to integer number
symmetric mapping means floating point range is symmetrically mapped to integer range let’s say we have floating point range (-3.5, 10.2) and integer range (-8, 7) (int4) we’ll use (-10.2, 10.2) as the range for floating point and map that to (-8, 7) e.g. scale = (10.2 - (-10.2)) / (7 - (-8))
SYMMETRIC_NO_CLIPPING_ERR is a variant of symmetric mapping, where the scale is the max of smin and smax, where smin = min_val_neg / quant_min, and smax = max_val_pos / quant_max. By calculating smin and smax individually, there can be less round error on negative values, and no out-of-range of all floating point values.
asymmetric mapping means we just directly map the floating point range to integer range, for the above example, we will map (-3.5, 10.2) to (-8, 7) and calculate quantization parameter based on this mapping e.g. scale = (10.2 - (-3.5)) / (7 - (-8))
