pi6&>ddlmZmZmZddlZddlmZddlmZddl m Z m Z m Z ddl mZmZmZgdZGddej$j&j(ZGd d eej*ZGd d eej,ZGd deej.Zy))ClassVarLiteralUnionN) _FusedModule) _size_1_t _size_2_t _size_3_t)_pair_single_triple)Conv1dConv2dConv3dceZdZUeeej jje d< dde de de e dfde e dfde e e e dffd e e dfd ed e e dfd e d ededddfdZdZeddZdZy)_ConvNd _FLOAT_MODULEN in_channels out_channels kernel_size.stridepaddingdilation transposedoutput_paddinggroupsbias padding_modezerosreflect replicatecircularreturnc| |d}tjjjj|||||||||| | | f i|| sJd| |_| j ||_y)N)devicedtypez'qconfig must be provided for QAT module)factory_kwargs)nnmodulesconvr__init__qconfigweightweight_fake_quant)selfrrrrrrrrrrrr,r%r&r's ^/opt/services/ai/voice_agent/venv/lib/python3.12/site-packages/torch/ao/nn/qat/modules/conv.pyr+z_ConvNd.__init__s"%+U; ((              AAAw !(~!Ncn|j||j|j|jSN _conv_forwardr.r-rr/inputs r0forwardz_ConvNd.forward6*!!%)?)? )LdiiXXr1c Rt||jk(s.Jd|jzdz|jjzt|dsJd|jsJdt t|t r|d}|j}||j|j|j|j|j|j|j|jdu|j| }|j |_|j|_|S) zCreate a qat module from a float module Args: `mod`: a float module, either produced by torch.ao.quantization utilities or directly from user zqat.z.from_float only works for r,z,Input float module must have qconfig definedz,Input float module must have a valid qconfigrN)rrrrrrr,)typer__name__hasattrr, issubclassrrrrrrrrrrr-)clsmoduse_precomputed_fake_quantr,qat_convs r0 from_floatz_ConvNd.from_float9s CyC--- ll + ,(( ) - sI&V(VV&{{JJJ{ d3i .a&C++ OO    OO::KK\\::%))  ** r1c t|}|j|j|j|j|j |j |j|j|jdu|j }tjj|jj|_|jrr=rEappendrtraintraining)r/r?r*r)relufuseds r0to_floatz_ConvNd.to_float\s#4j%%          KK LL MM KK IIT !     hh((););)=> 99 **499+;+;+=>DI c< (fG3 45 55))+D NN4 %C%%w/E KK &LKr1)NNNF)r< __module__ __qualname__rr;r(r)r*r__annotations__inttuplerstrboolrr+r8 staticmethodrCrOr1r0rrs D!8!89::#O#O#O38_ #O c3h #O sE#s(O+, #OS/#O#Oc3h#O#O#OIJ#O !#OJY  Dr1rc eZdZUdZej Zeeej e d<ej Z eeej e d< dde de de de d e ee fd e d e d ed edddffd Zedfd ZxZS)r aZ A Conv1d module attached with FakeQuantize modules for weight, used for quantization aware training. We adopt the same interface as :class:`~torch.nn.Conv1d` Similar to :class:`~torch.nn.Conv2d`, with FakeQuantize modules initialized to default. Attributes: weight_fake_quant: fake quant module for weight rrFNrrrrrrrrrrr#c t|} t|}t|tr|n t|}t|}t|||| |||dtd||| | | | yNFr) rrrrrrrrr,r%r&)r isinstancerVsuperr+r/rrrrrrrrrr,r%r& kernel_size_stride_padding_ dilation_ __class__s r0r+zConv1d.__init__w{+ &/(#67GGrs|++ .AA:: )kbjjoo%%k\9 Wbii9 x> Wbii> B> Wbii> r1