convert#

classtorch.ao.quantization.convert(module,mapping=None,inplace=False,remove_qconfig=True,is_reference=False,convert_custom_config_dict=None,use_precomputed_fake_quant=False)[source]#

Converts submodules in input module to a different module according tomappingby callingfrom_float method on the target module class. And remove qconfig at theend if remove_qconfig is set to True.

Parameters

• module – prepared and calibrated module

• mapping – a dictionary that maps from source module type to targetmodule type, can be overwritten to allow swapping user definedModules

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

• convert_custom_config_dict – custom configuration dictionary for convert function

• use_precomputed_fake_quant – a flag to enable use of precomputed fake quant

# Example of convert_custom_config_dict:convert_custom_config_dict={# user will manually define the corresponding quantized# module class which has a from_observed class method that converts# observed custom module to quantized custom module"observed_to_quantized_custom_module_class":{ObservedCustomModule:QuantizedCustomModule}}