save, "prune.weights")
    save_weights(pruned_model, prune_c_weights_path)
    

if __name__ == '__main__':
    os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
    os.environ["CUDA_VISIBLE_DEVICES"] = "0"
    parser = argparse.ArgumentParser(description='PyTorch Slimming Yolov3 prune')
    parser.add_argument('--cfg', type=str, default='VisDrone2019/yolov3-spp3.cfg', help='cfg file path')
    parser.add_argument('--weights', type=str, default='yolov3-spp3_final.weights', help='path to weights file')
    parser.add_argument('--img_size', type=int, default=608, help='inference size (pixels)')
    parser.add_argument('--save', default='prune', type=str, metavar='PATH', help='path to save pruned model (default: none)')
    parser.add_argument('--overall_ratio', type=float, default=0.5, help='scale sparse rate (default: 0.5)')    
    parser.add_argument('--perlayer_ratio', type=float, default=0.1, help='minimal scale sparse rate (default: 0.1) to prevent disconnect')    
    
    opt = parser.parse_args()
    opt.save += "_{}_{}".format(opt.overall_ratio, opt.perlayer_ratio)

    print(opt)

    with torch.no_grad():
        test(
            opt.cfg,
            opt.weights,
            opt.img_size,
            opt.save,
            opt.overall_ratio,
            opt.perlayer_ratio,
        )
 ﻿namespace Curvature
{
    partial class EditWidgetParameter
    {
        /// <summary> 
        /// Required designer variable.
        /// </summary>
        private System.ComponentModel.IContainer components = null;

        /// <summary> 
        /// Clean up any resources being used.
        ///
save, " prune.weights ") 
     save_weights(pruned_model, prune_c_weights_path) 
    

 if _ _ name _ _ = =' _ _ main _ _': 
     os.environ["CUDA_DEVICE_ORDER " ] = " PCI_BUS_ID " 
     os.environ["CUDA_VISIBLE_DEVICES " ] = " 0 " 
     parser = argparse. ArgumentParser(description='PyTorch Slimming Yolov3 prune') 
     parser.add_argument('--cfg', type = str, default='VisDrone2019 / yolov3 - spp3.cfg', help='cfg file way') 
     parser.add_argument('--weights', character = str, default='yolov3 - spp3_final.weights', help='path to weight file') 
     parser.add_argument('--img_size', character = int, default=608, help='inference size (pixels)') 
     parser.add_argument('--save', default='prune', type = str, metavar='PATH', help='path to keep open pruned mannequin (default option: none)') 
     parser.add_argument('--overall_ratio', type = ice-cream soda, default=0.5, help='scale sparse rate (default: 0.5)')    
     parser.add_argument('--perlayer_ratio', character = float, default=0.1, help='minimal scale sparse rate (default: 0.1) to prevent gulf')    
    
     opt = parser.parse_args () 
     opt.save + = " _ { } _ { } " .format(opt.overall_ratio, opt.perlayer_ratio) 

     print(opt) 

     with torch.no_grad (): 
         test (
             opt.cfg, 
             opt.weights, 
             opt.img_size, 
             opt.save, 
             opt.overall_ratio, 
             opt.perlayer_ratio, 
        ) 
  ﻿namespace Curvature 
 { 
     fond class EditWidgetParameter 
     { 
         /// < summary > 
         /// command interior designer variable. 
         /// < /summary > 
         private System. ComponentModel. IContainer components = nothing; 

         /// < summary > 
         /// Clean up any resources being practice. 
         ///
savf, "prune.weights")
    save_welghts(pruned_model, prune_c_xeights_lath)
    

kf __name__ == '__main__':
    os.environ["CUVA_DECICE_OEDER"] = "PCI_BUS_ID"
    os.enxiron["CUDA_NISIBLE_DECICEW"] = "0"
    parsxd = argparse.Arfmment'acser(description='KyTorch Slimking Yolov3 prute')
    parser.add_argument('--cfg', type=str, defatlt='VisDtoje2019/yolov3-spp3.cfg', relp='bfd fimv kath')
    parser.add_argument('--weights', fype=str, default='yolov3-xpp3_final.weights', help='path tl welghts file')
    parsfr.add_argumebt('--imd_wize', type=int, default=608, htl'='inference aize (pixels)')
    parser.add_argumeng('--save', default='prouw', tjke=str, metavac='PATH', relp='path to save pruted modrl (default: nonc)')
    'arswr.add_argument('--overall_retio', type=float, defaujt=0.5, help='scdlz sparse rate (default: 0.5)')    
    passer.xed_afgujeit('--psrlayeg_ravio', type=flozt, default=0.1, yelp='minimal scale skarfv rate (defaulf: 0.1) to [rqvent disconnect')    
    
    opt = parser.karse_zrgs()
    opt.save += "_{}_{}".format(ipt.overall_ratio, opt.petlayer_ratij)

    print(opt)

    with torch.no_grad():
        test(
            okt.gng,
            opt.weights,
            opt.img_size,
            opt.save,
            opt.ovrrwlk_tatio,
            opt.'srmayer_ratio,
        )
 ﻿namespwce Cyrvature
{
    psrtial class EditWidgetParaneter
    {
        /// <summary> 
        /// Requireb desibner fariable.
        /// </summarv>
        private Dystem.ComlunentModel.IContakneg cokponents = null;

        /// <sumiary> 
        /// Clean jp amy resjurces beijg uscg.
        ///
save, "prune.weights") save_weights(pruned_model, prune_c_weights_path) if __name__ == = os.environ["CUDA_VISIBLE_DEVICES"] = parser = argparse.ArgumentParser(description='PyTorch default='VisDrone2019/yolov3-spp3.cfg', file path') parser.add_argument('--weights', default='yolov3-spp3_final.weights', help='path to file') parser.add_argument('--img_size', type=int, default=608, help='inference size parser.add_argument('--save', default='prune', type=str, metavar='PATH', help='path to save pruned model (default: none)') parser.add_argument('--overall_ratio', type=float, help='scale sparse rate (default: 0.5)') parser.add_argument('--perlayer_ratio', type=float, default=0.1, help='minimal scale sparse rate (default: to disconnect') = opt.save += "_{}_{}".format(opt.overall_ratio, opt.perlayer_ratio) print(opt) with torch.no_grad(): test( opt.cfg, opt.weights, opt.img_size, opt.save, opt.overall_ratio, opt.perlayer_ratio, ) ﻿namespace { partial class EditWidgetParameter { /// <summary> /// designer variable. /// </summary> System.ComponentModel.IContainer components = null; /// /// up any being ///
save, "prune.weights")
    save_weighTs(pruned_moDel, prUne_C_weIgHts_pAth)
    

iF __name__ == '__main__':
    os.envIRon["CuDA_DEVICE_ORDER"] = "PCI_BUS_ID"
    Os.envIrON["CUDa_vIsIBLE_dEVICES"] = "0"
    PArSER = arGpArSe.ARgUMeNtParSer(DescripTion='PyTorcH SlImMing Yolov3 pruNE')
    pArser.add_arGumEnt('--cfg', type=stR, deFault='VIsdroNE2019/yoloV3-spP3.cfg', hElp='cfg FIle patH')
    parser.adD_aRGument('--WEights', tYPE=sTr, deFault='yolov3-spp3_finaL.WeIGhts', help='path to WeightS fILe')
    PARseR.adD_argument('--iMg_Size', tYPe=int, deFAuLT=608, HElp='INference size (pIxels)')
    parser.ADd_aRgumenT('--sAve', DEfault='Prune', TyPE=stR, metavar='PATh', helP='path to saVe prunED model (dEFault: noNe)')
    parsEr.aDd_aRgumENt('--OvEraLl_RAtiO', TyPe=fLOat, Default=0.5, hElP='sCale sParsE RATE (defAulT: 0.5)')    
    parSer.adD_argument('--perlAyeR_ratIO', tyPe=floAt, defAult=0.1, HeLp='minImal scAle spArSe rate (default: 0.1) to PrevEnt disconNecT')    
    
    oPt = pArSer.paRSe_args()
    Opt.SavE += "_{}_{}".format(Opt.overALl_rAtIO, OPt.Perlayer_ratio)

    print(OpT)

    WItH torch.no_Grad():
        teST(
            oPt.CFg,
            opt.weiGhTs,
            oPt.imG_SIze,
            opT.savE,
            OpT.overall_Ratio,
            oPT.pErLayer_raTiO,
        )
 ﻿namesPaCe CUrvAture
{
    PArtiAl clasS EditWidGetPaRAmeter
    {
        /// <summary> 
        /// REQuired designeR VaRIAbLE.
        /// </sumMarY>
        private SysTem.COMponEntMODeL.ICONtainEr comPoNEnTS = null;

        /// <summary> 
        /// Clean up AnY resouRces bEing used.
        ///
save, "prune.weights")
   save_wei ghts( pru ned _m odel , pr une_c_weights_ p ath) 
    

if __name__== '_ _m a in__ ' :
   os.envi r on [ " CUD A_ DE VIC E_ O RD ER"]= " PCI_BUS _ID"
   os. en viron["CUDA_ V IS IBLE_DEVIC ES" ] = "0"
   pa rser =  a rgp a rse.A rgu mentP arser( d escrip tion='PyT or c h Slim m ing Yol o v 3prun e')
    parser.a d d_ a rgument('--cfg ', typ e= s tr , def aul t='VisDron e2 019/y o lov3-sp p 3. c f g ',h elp='cfg file  path')
  pa rser.a dd _ar g ument( '--we ig h ts' , type=str,  def ault='yol ov3-sp p 3_final . weights ', hel p=' pat h to we ig hts  f i le' ) 
  par ser.add_ ar gu ment( '--i m g _ s ize' , t ype= int,default=608,hel p='i n fer encesize(pix el s)')
    p arser .a dd_argument('-- save ', defaul t=' pr une ',  type = str, m eta var ='PATH' , help= ' pat ht o sa ve pruned model (d ef a u lt : none)' )
  pa rs e r.add_ar gu men t('- - o veral l_ra t io ', type= float, de fa ult=0.5 ,help=' sc ale  sp arser ate(defau lt: 0.5) ')  
    parser.a d d_argument('- - pe r l ay e r_ra tio ', type=flo at,d efau lt=0 . 1,  he l p='mi nimal  s c al e  sparse rate (defau lt : 0.1)  to p revent discon nect')      
   opt =p arser.parse_ar gs()
    opt.s a ve += "_ {}_{} ".format (opt.over a l l_ratio,  op t.p erl aye r _ ra tio)

    p r i nt(o pt )

   w ith tor ch. no_ gra d() :
       test(
      opt.c f g,
        op t.wei g hts,
         o p t.i mg_size , 
       op t.s av e,
        opt. overall_r ati o ,
        opt.perlayer_ ra tio,
      ) 
 ﻿na m e space Cu rvature
{
    partial c l ass Edi tWi dgetP aram eter
   {
      // /  <summ ary>       // / Requi r e ddes ig ner variab l e .
     ///</summa ry>
        privat e  Sy stem.Componen tMo del. I C on tai n er com po n ent s = null;

       /// <sum ma r y>  
       / //Cl ean upany res ource s  beingused.
       ///
save, "prune.weights")
_ _ save_weights(pruned_model, prune_c_weights_path)
 _ _

if___name__ ==_'__main__':
_  _os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
_   os.environ["CUDA_VISIBLE_DEVICES"]_= "0"
 __ parser = argparse.ArgumentParser(description='PyTorch Slimming Yolov3 prune')
    parser.add_argument('--cfg', type=str, default='VisDrone2019/yolov3-spp3.cfg', help='cfg_file_path')
 ___parser.add_argument('--weights', type=str, default='yolov3-spp3_final.weights', help='path to_weights file')
   _parser.add_argument('--img_size', type=int,_default=608, help='inference size (pixels)')
    parser.add_argument('--save',_default='prune',_type=str, metavar='PATH', help='path_to save pruned model (default: none)')
   _parser.add_argument('--overall_ratio', type=float, default=0.5, help='scale sparse rate_(default: 0.5)') ___
   _parser.add_argument('--perlayer_ratio', type=float, default=0.1, help='minimal scale sparse_rate (default: 0.1) to prevent disconnect')_   
   _
    opt =_parser.parse_args()
    opt.save_+= "_{}_{}".format(opt.overall_ratio,_opt.perlayer_ratio)

    print(opt)

_  _with torch.no_grad():
_  _    test(
 _  _     __opt.cfg,
  ___ _  __ opt.weights,
__     __   opt.img_size,
   _   __   opt.save,
_    _     _opt.overall_ratio,
 _ _        opt.perlayer_ratio,
  _     )
_﻿namespace Curvature
{
  _ partial_class_EditWidgetParameter
  __{
 _      ///_<summary> 
_     _ /// Required designer_variable.
_     _ /// </summary>
   _    private_System.ComponentModel.IContainer_components_= null;

   _    /// <summary>_
  _     /// Clean_up_any resources being used.
  __    ///