class<class ''>, quant_min=None, quant_max=None, is_dynamic=False, **observer_kwargs)[source]

Simulate the quantize and dequantize operations in training time.

The output of this module is given by:

x_out = (
  clamp(round(x/scale + zero_point), quant_min, quant_max) - zero_point
) * scale
  • is_dynamic indicates whether the fake quantie is a placeholder for dynamic quantization operators (choose_qparams -> q -> dq) or static quantization operators (q -> dq)

  • scale defines the scale factor used for quantization.

  • zero_point specifies the quantized value to which 0 in floating point maps to

  • fake_quant_enabled controls the application of fake quantization on tensors, note that statistics can still be updated.

  • observer_enabled controls statistics collection on tensors

  • dtype specifies the quantized dtype that is being emulated with fake-quantization,

    allowable values are torch.qint8 and torch.quint8.

  • observer (module) – Module for observing statistics on input tensors and calculating scale and zero-point.

  • observer_kwargs (optional) – Arguments for the observer module


activation_post_process (Module) – User provided module that collects statistics on the input tensor and provides a method to calculate scale and zero-point.


Access comprehensive developer documentation for PyTorch

View Docs


Get in-depth tutorials for beginners and advanced developers

View Tutorials


Find development resources and get your questions answered

View Resources