runs/code-decoder-v28-fullset-experiment/anticurriculum-loss/ckpt/generated.txt

K=10,T=0.8: <data>i ] = numpy . argsort ( d [ i ] ) [ : : - 1 ] ranks [ 5 * index + i ] = numpy . where ( inds [ i ] = = index ) [ 0 ] [ 0 ] r 1 = 1 0 0 . 0 * len ( numpy . where ( ranks < 1 ) [ 0 ] ) / len ( ranks ) r 5 = 1 0 0 . 0 * len ( numpy . where ( ranks < 5 ) [ 0 ] ) / len ( ranks </data>) [ 0 ] = len ( tp ) + int ( tp 1 [ 0 ] - 2 ) ) if r 1 = = 0 : print ( ' - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 
K=10,T=0.8: <data>content . replace ( " < original _ apk _ signature > " , signature ) script _ content = script _ content . replace ( " / / spoof signature ( ) " , " spoof signature ( ) " ) f _ dest = open ( dest , " w " ) f _ dest . write ( script _ content ) f _ dest . close ( ) return dest def create _ config _ file ( ) : filepath = os . path . join ( temp _ folder , " <UNK> . config . so </data>_ % s _ % s _ % s _ % s . . " % filepath , filename ) if filepath [ ' filename ' ] ! = ' filename ' : filepath = os . path . join ( temp _ folder , filepath ) if filepath [ ' filename ' ] ! = ' filename ' : filepath = os . path . join ( temp _ folder , filepath ) else : filepath = os . path . join ( temp _ folder , filepath , filepath ) if filepath [ ' filename ' ] > 
K=10,T=0.8: <data>" id " in item : eid = item [ " id " ] else : eid = none if " name " in item : name = item [ " name " ] else : name = none if " config " in item : config = item [ " config " ] else : config = extractor _ default _ config if " exclude " in item : exclude = item [ " exclude " ] else : exclude = extractor _ default _ exclude if " enabled " in item : enabled = item [ " enabled </data>" ] if not settings . exclude _ and ( exclude ) or " enabled " in item [ " enabled " ] : if ( exclude ) : exclude = item [ " enabled " ] if not exclude and " enabled " in item [ " enabled " ] : if " enabled " in item [ " enabled " ] : exclude = item [ " enabled " ] if not exclude : exclude = item [ " enabled " ] if not exclude : exclude = item [ " enabled " ] if exclude else exclude 
K=10,T=0.8: <data>( " set subdomain for the redirector : " + domain ) subdomain = input ( " > " ) return subdomain def update _ operation ( domains _ brn , redirects _ brn , domains _ in _ use , c 2 , redirects ) : if bool ( domains _ brn ) : full _ message = " " for i in domains _ brn : full _ message = full _ message + " \ n [ + ] domain burned : " + i [ " domains " ] + " \ n " for j </data>in domains _ droplet : full _ message = full _ message + " \ n [ ! ] \ n [ + ] domains : " + i [ " domains " ] + " \ n [ + ] domain " return full _ message def get _ domain _ domains _ domains _ domains ( domains _ domains _ queu _ domains , domains _ domains , domains _ in _ use , c 2 , domains _ domains _ domains _ domains _ domains _ domains _ domains _ domains _ domains _ domains _ domains 
K=10,T=0.8: <data>num _ workers = configs . workers , pin _ memory = true ) model = get _ model ( ) model . cuda ( ) if configs . loss _ func = = " label smooth ce " : criterion = label smoothing loss ( 0 . 1 , configs . num _ classes ) . cuda ( ) elif configs . loss _ func = = " cross entropy " : criterion = nn . cross entropy loss ( ) . cuda ( ) elif configs . loss _ func = = " focal loss " : criterion </data>= torch . nn . cross entropy loss ( 0 . 0 , configs . num _ classes ) . cuda ( ) elif configs . loss _ func = = " cross entropy " : criterion = torch . nn . cross entropy loss ( 0 . 0 , configs . num _ classes ) . cuda ( ) elif configs . loss _ func = = " cross entropy " : criterion = torch . nn . cross entropy loss ( 0 . 0 , configs . num _ classes , 1 0 ) elif configs . loss 
K=10,T=0.8: <data>self . real _ nic ) ) self . _ check _ call ( ' tc filter replace dev { 0 } parent ffff : protocol ip prio 1 ' ' u 3 2 match u 3 2 0 0 flowid 1 : 1 action <UNK> <UNK> redirect ' ' dev { 1 } ' . format ( self . real _ nic , self . nic ) ) self . _ call ( ' tc qdisc del root dev { 0 } ' . format ( self . nic ) ) self . _ check _ call ( ' </data>tc filter ' ) def check _ call ( self , nic ) : if self . nic = = ' ' : if self . nic = = ' ' 0 : return self . nic = ' ' 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 
K=10,T=0.8: <data>) . cuda ( ) reduced _ target _ s = torch . from _ numpy ( target _ s ) . cuda ( ) dist . all _ reduce ( reduced _ intersection _ s ) dist . all _ reduce ( reduced _ union _ s ) dist . all _ reduce ( reduced _ target _ s ) intersection _ meter _ student . update ( reduced _ intersection _ s . cpu ( ) . numpy ( ) ) union _ meter _ student . update ( reduced _ union _ s . cpu ( ) </data>. numpy ( ) ) dist . all _ reduce ( reduced _ intersection _ s ) dist . all _ reduce ( reduced _ intersection _ s . cpu ( ) . numpy ( ) ) ) dist . all _ reduce ( reduced _ intersection _ s . cpu ( ) . numpy ( ) ) return dist def get _ rank ( self , rank ) : rank = rank . get _ rank ( ) if rank in [ 1 , 0 ] : rank = rank . get _ rank ( ) rank = rank 
K=10,T=0.8: <data>fc " , " sy " : 1 , " sx " : 1 , " out _ sx " : 1 , " out _ sy " : 1 , " stride " : 1 , " pad " : 0 , " out _ depth " : % s , " in _ depth " : % s , " biases " : % s , " gamma " : % s , " beta " : % s , " filters " : % s } ; var layer _ % s = { " layer _ </data>% s " % % " % ( var layer _ % s , " filt _ % s " % % ( var layer _ % s , " filt _ % s " % ( var layer _ % s , " filt _ % s " % ( var layer _ % s , " filt _ % s " % var layer _ % s ) , " filt _ % s " % var layer _ % s , " filt _ % s " % var layer _ % s " % var layer 
K=10,T=0.8: <data>i ) for i in range ( 2 6 ) } ) self . map . update ( { 3 6 : ' def get _ classifier ( self , rank ) : from easydict import easy dict as edict from lib . model _ zoo . get _ model import get _ model from lib . optimizer . get _ optimizer import get _ optimizer cfg = cfguh ( ) . cfg cfgm = edict ( ) cfgm . resnet = edict ( ) cfgm . resnet . model _ tags = [ ' resnet 5 0 ' ] </data>* 8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0