o i@srddlmZmZddlZddlmZddlmZgdZGdddejZ Gdd d ejZ Gd d d ejZ dS) )AnyOptionalN)nn)QConfig) QuantStub DeQuantStub QuantWrappercBeZdZdZd deeffdd Zdejdejfdd Z Z S) raQuantize stub module, before calibration, this is same as an observer, it will be swapped as `nnq.Quantize` in `convert`. Args: qconfig: quantization configuration for the tensor, if qconfig is not provided, we will get qconfig from parent modules Nqconfigct|r ||_dSdSNsuper__init__r selfr  __class__X/home/ubuntu/veenaModal/venv/lib/python3.10/site-packages/torch/ao/quantization/stubs.pyr  zQuantStub.__init__xreturncC|Sr rrrrrrforwardzQuantStub.forwardr ) __name__ __module__ __qualname____doc__rrrtorchTensorr __classcell__rrrrr rcr ) raDequantize stub module, before calibration, this is same as identity, this will be swapped as `nnq.DeQuantize` in `convert`. Args: qconfig: quantization configuration for the tensor, if qconfig is not provided, we will get qconfig from parent modules Nr cr r r rrrrr&rzDeQuantStub.__init__rrcCrr rrrrrr+rzDeQuantStub.forwardr ) rrrr rrrr!r"rr#rrrrrr$rcsZeZdZUdZeed<eed<ejed<dejffdd Z de j de j fd d Z Z S) raA wrapper class that wraps the input module, adds QuantStub and DeQuantStub and surround the call to module with call to quant and dequant modules. This is used by the `quantization` utility functions to add the quant and dequant modules, before `convert` function `QuantStub` will just be observer, it observes the input tensor, after `convert`, `QuantStub` will be swapped to `nnq.Quantize` which does actual quantization. Similarly for `DeQuantStub`. quantdequantmodulecsRtt|dd}|dt||dt||d|||jdS)Nr r%r&r')rrgetattr add_modulerrtraintraining)rr'r rrrr?s   zQuantWrapper.__init__XrcCs||}||}||Sr )r%r'r&)rr,rrrrGs   zQuantWrapper.forward)rrrr r__annotations__rrModulerr!r"rr#rrrrr/s   r) typingrrr!rtorch.ao.quantizationr__all__r.rrrrrrrs