class, qscheme=torch.per_tensor_affine, reduce_range=False, quant_min=None, quant_max=None, factory_kwargs=None, memoryless=False)[source]

Observer module for computing the quantization parameters based on the running min and max values.

This observer uses the tensor min/max statistics to compute the quantization parameters. The module records the running minimum and maximum of incoming tensors, and uses this statistic to compute the quantization parameters.

  • dtype – Quantized data type

  • qscheme – Quantization scheme to be used

  • reduce_range – Reduces the range of the quantized data type by 1 bit

  • quant_min – Minimum quantization value. If unspecified, it will follow the 8-bit setup.

  • quant_max – Maximum quantization value. If unspecified, it will follow the 8-bit setup.

  • memoryless – Boolean that controls whether observer removes old data when a new input is seen. This is most useful for simulating dynamic quantization, especially during QAT.

Given running min/max as xminx_\text{min} and xmaxx_\text{max}, scale ss and zero point zz are computed as:

The running minimum/maximum xmin/maxx_\text{min/max} is computed as:

xmin={min(X)if xmin=Nonemin(xmin,min(X))otherwisexmax={max(X)if xmax=Nonemax(xmax,max(X))otherwise\begin{array}{ll} x_\text{min} &= \begin{cases} \min(X) & \text{if~}x_\text{min} = \text{None} \\ \min\left(x_\text{min}, \min(X)\right) & \text{otherwise} \end{cases}\\ x_\text{max} &= \begin{cases} \max(X) & \text{if~}x_\text{max} = \text{None} \\ \max\left(x_\text{max}, \max(X)\right) & \text{otherwise} \end{cases}\\ \end{array}

where XX is the observed tensor.

The scale ss and zero point zz are then computed as:

if Symmetric:s=2max(xmin,xmax)/(QmaxQmin)z={0if dtype is qint8128otherwiseOtherwise:s=(xmaxxmin)/(QmaxQmin)z=Qminround(xmin/s)\begin{aligned} \text{if Symmetric:}&\\ &s = 2 \max(|x_\text{min}|, x_\text{max}) / \left( Q_\text{max} - Q_\text{min} \right) \\ &z = \begin{cases} 0 & \text{if dtype is qint8} \\ 128 & \text{otherwise} \end{cases}\\ \text{Otherwise:}&\\ &s = \left( x_\text{max} - x_\text{min} \right ) / \left( Q_\text{max} - Q_\text{min} \right ) \\ &z = Q_\text{min} - \text{round}(x_\text{min} / s) \end{aligned}

where QminQ_\text{min} and QmaxQ_\text{max} are the minimum and maximum of the quantized data type.


dtype can only take torch.qint8 or torch.quint8.


If the running minimum equals to the running maximum, the scale and zero_point are set to 1.0 and 0.


Calculates the quantization parameters.


Records the running minimum and maximum of x.


Resets the min/max values.


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