- class torch.quantization.quantize(model, run_fn, run_args, mapping=None, inplace=False)¶
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.
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