quantize#

class torch.ao.quantization.quantize(model, run_fn, run_args, mapping=None, inplace=False)[source]#

Quantize the input float model with post training static quantization.

First it will prepare the model for calibration, then it calls run_fn which will run the calibration step, after that we will convert the model to a quantized model.

Parameters

• model – input float model

• run_fn – a calibration function for calibrating the prepared model

• run_args – positional arguments for run_fn

• inplace – carry out model transformations in-place, the original module is mutated

• mapping – correspondence between original module types and quantized counterparts

Returns

Quantized model.