runs/!code-decoder-v31-mega-licensed-1/anticurriculum-loss/ckpt/generated.txt

K=10,T=0.8: <data><tab> pt [ d ] = str ( dlat ) + " , " + str ( <UNK> ) + " , " + str ( <UNK> ) <newline> <tab> <tab> <tab> <tab> <tab> <newline> <tab> <tab> <tab> <tab> lpt = i <newline> <tab> <newline> <tab> <tab> <newline> <tab> <tab> <newline> <tab> <tab> <newline> <tab> <newline> <tab> <tab> <newline> <tab> <newline> <tab> <UNK> = 0 <newline> <tab> <UNK> = 0 <newline> <tab> <UNK> = bpy . context . scene . ges _ ot _ path . v _ reduce <newline> <tab> pn = [ ] <newline> <tab> for i in </data>range ( 2 , 8 0 ) : <newline> <tab> <tab> <newline> <tab> <UNK> = <UNK> [ 0 ] <newline> <tab> <newline> <tab> <UNK> = <UNK> = <UNK> <newline> <tab> <UNK> = <UNK> . <UNK> ( 2 ) <newline> <tab> <newline> <tab> <UNK> = <UNK> . <UNK> [ 0 ] <newline> <tab> <UNK> . <UNK> = <UNK> ( <UNK> ) <newline> <newline> <tab> <UNK> = <UNK> = <UNK> [ ] <newline> <tab> <UNK> = <UNK> = <UNK> [ <newline> <tab> <UNK> = <UNK> [ 0 ] <newline> <tab> oo = <UNK> [ <UNK> + <UNK> ] <newline> <tab> <UNK> = 
K=10,T=0.8: <data>_ argument ( ' - - workers ' , type = int , help = ' number of data loading workers ' , default = 8 ) <newline> parser . add _ argument ( ' - - batch _ size ' , type = int , default = 6 4 , help = ' input batch size ' ) <newline> parser . add _ argument ( ' - - res size ' , type = int , default = 2 0 4 8 , help = ' size of visual features ' ) <newline> parser . add _ argument ( </data>' - - gpu ' , type = int , default = 8 6 , help = ' number of memory to be to use . ' ) <newline> parser . add _ argument ( ' - - - gpu _ gpu _ gpu _ gpu _ gpu _ gpu _ gpu _ gpu _ gpu _ gpu ' , default = 1 0 0 0 0 ) <newline> parser . add _ argument ( ' - - gpu _ gpu _ gpu ' , type = str ) <newline> parser . add _ argument ( ' - seed _ 
K=10,T=0.8: <data>, <newline> <tab> field ( ' duration ' , ' > i ' ) , <newline> <tab> field ( ' language ' , ' > h ' ) , <newline> <tab> field ( ' quality ' , ' > h ' ) <newline> ] <newline> <newline> <newline> class <UNK> ( struct ) : <newline> _ fields _ = [ <newline> <tab> field ( ' v ' , ' > b ' ) , <newline> <tab> field ( ' flags ' , ' > 3 b ' ) , <newline> <tab> field ( ' creation _ time ' , ' > </data>b ' ) , <newline> <tab> field ( ' <UNK> ' , ' > b ' ) , <newline> <tab> field ( ' class ' , ' < b > c ' ) , <newline> <tab> field ( ' <UNK> ' , ' > i ' , ' > b ' ) , <newline> <tab> field ( ' default ' , ' < b > ' ) , <newline> <tab> field ( ' default ' , ' < b > b > ' ) , <newline> <tab> field ( ' class ' , ' < a > ' ) , 
K=10,T=0.8: <data><newline> <tab> <tab> ) <newline> <tab> <tab> wait _ for _ enter ( ) <newline> <tab> <tab> self . system ( " vim changelog . md / tmp / changelog _ update . md " ) <newline> <tab> <tab> with open ( " / tmp / changelog _ update . md " , " r " ) as fileobj : <newline> <tab> <tab> <tab> context [ " changelog _ update " ] = fileobj . read ( ) <newline> <newline> <newline> class update readme ( step ) : <newline> <tab> def action ( self , context ) : <newline> <tab> </data><tab> self . _ _ init _ _ ( self . _ _ init _ _ ( self . _ _ init _ ( self . _ _ init _ _ , ) ) <newline> <newline> <tab> def action ( self , context ) : <newline> <tab> <tab> self . _ _ init _ ( self . _ _ init _ _ ( self . _ _ init _ ) , self . _ _ init _ _ ( self . _ _ init _ ( self . _ _ init _ _ ( self . _ _ init _ 
K=10,T=0.8: <data>0 0 } $ _ protect _ identifiers . * false . { 0 , 9 9 } $ select \ ( . * false . { 0 , 9 9 } $ ^ [ ^ \ n ] { 0 , 9 9 } \ $ \ w + [ ^ \ n ] { 0 , 9 9 } \ s + ( and | or ) \ s + [ ^ \ n ] { 0 , 9 9 } \ s in \ s * \ ( [ ^ \ n ] { 0 , 9 </data>9 } $ | | \ d + [ ^ ] { 0 , 9 9 } $ { 0 , 9 9 } $ " ) <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> else : <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <UNK> + = [ ^ \ n + [ ^ \ n + ] { 0 , 9 9 } $ " ) <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> if <UNK> + [ ^ \ n ] { 0 , 0 , 9 9 } $ { 0 
K=10,T=0.8: <data>" description " ] = issue . body . split ( period ) [ 0 ] . replace ( " \ " " , " \ ' " ) + period <newline> <tab> <tab> <tab> <tab> <newline> <tab> <tab> <tab> self . blog base [ list json name ] [ post num ] [ " top " ] = 0 <newline> <tab> <tab> <tab> for event in issue . get _ events ( ) : <newline> <tab> <tab> <tab> <tab> if event . event = = " pinned " : <newline> <tab> <tab> <tab> <tab> <tab> self . blog base </data>[ list json name ] [ " content " ] [ " content " ] . replace ( " \ " \ ' " , " \ ' " ' ) <newline> <tab> <tab> <tab> <tab> self . blog base [ list json name ] [ " content " ] = " \ 0 3 3 [ 0 m " <newline> <tab> <tab> <tab> <tab> self . blog base [ list json name ] [ " content " ] = " \ x 3 3 [ 0 m " <newline> <tab> <tab> <tab> <tab> self . blog base [ list 
K=10,T=0.8: <data>tensor ( np . array ( recon ) ) . permute ( 2 , 0 , 1 ) . unsqueeze ( 0 ) . float ( ) . to ( ' cuda ' ) / 2 5 5 . 0 <newline> <newline> <tab> <tab> <newline> <tab> <tab> psnr = psnr _ fn ( label * 2 - 1 , recon * 2 - 1 ) <newline> <tab> <tab> psnrs . append ( psnr ) <newline> <tab> <tab> <newline> <tab> <tab> lpips _ score = loss _ fn _ alex ( label * 2 - 1 , recon * 2 - </data>1 , recon * 2 - 1 ) <newline> <tab> <tab> psnrs . append ( lpips ) <newline> <newline> <tab> <tab> <newline> <tab> <tab> <newline> <tab> <tab> <newline> <tab> <tab> <newline> <tab> <tab> <newline> <tab> <tab> <newline> <tab> <tab> psnr = psnr _ fn ( img * 2 - 1 ) * 2 <newline> <tab> <tab> psnr = psnr _ fn ( img / 2 5 5 ) . cpu ( ) . numpy ( ) . numpy ( ) . cuda ( ) <newline> <newline> <tab> <tab> <newline> <tab> <tab> psnrs . append ( psnr ) <newline> <tab> <tab> 
K=10,T=0.8: <data>" please select a choice from above : " ) <newline> <tab> try : <newline> <tab> <tab> if active _ wireless _ networks [ int ( choice ) ] : <newline> <tab> <tab> <tab> break <newline> <tab> except : <newline> <tab> <tab> print ( " please try again . " ) <newline> <newline> <newline> <UNK> = active _ wireless _ networks [ int ( choice ) ] [ " bssid " ] <newline> <UNK> = active _ wireless _ networks [ int ( choice ) ] [ " channel " ] . strip ( ) <newline> <newline> <newline> <newline> subprocess </data>. run ( [ " airmon - ng " , " - - ng " , " - - ng " , " - - ng " , " - - ng " , " - - ng " , " - - ng " , " - - ng " , " - - ng " , " - - ng " , " - - ng " , " - - ng " , " - - ng " , " - - ng " , " - - - ng " , " - - ng " 
K=10,T=0.8: <data>parse _ args ( ) <newline> <tab> result = [ ] <newline> <tab> if args . file _ name : <newline> <tab> <tab> with open ( " . / pmi / " + args . file _ name . lower ( ) + " . txt " , ' r ' ) as f : <newline> <tab> <tab> <tab> for line in f : <newline> <tab> <tab> <tab> <tab> result = result + ( list ( line . strip ( ' \ n ' ) . split ( ' , ' ) ) ) <newline> <tab> elif args . task </data>_ name : <newline> <tab> <tab> result = result + ( list ( line [ ' task _ name ' ] ) . split ( ' , ' ) ) <newline> <tab> <tab> print ( result ) <newline> <tab> <tab> result = [ ] <newline> <tab> <tab> if args . file _ path : <newline> <tab> <tab> <tab> results . append ( result ) <newline> <tab> <tab> for line in results : <newline> <tab> <tab> <tab> if line [ ' task _ name ' ] . strip ( ) : <newline> <tab> <tab> <tab> <tab> if args . file _ 
K=10,T=0.8: <data>index = = 1 : <newline> <tab> <tab> <tab> <tab> uri array [ index ] + = param names [ 0 ] + " = " + param value [ 0 ] + " ' , $ or : [ { } , { ' a ' : ' a " + " & " <newline> <tab> <tab> <tab> <tab> uri array [ index ] + = param names [ 1 ] + " = " + " ' } ] , $ comment : ' successful mongo db " <newline> <tab> <tab> <tab> if index = = 2 : </data><newline> <tab> <tab> <tab> <tab> uri array [ index ] + = param names [ index ] + " \ " + " ' } ] <newline> <tab> <tab> <tab> <tab> uri array [ index ] + = param names [ - 1 ] + " ' , $ comment : ' successful mongo db " + str ( index ) + " ' " <newline> <tab> <tab> <tab> uri array [ index ] + = param names [ index ] + " ' " <newline> <tab> <tab> <tab> return uri array [ index ] + " ' " , 
K=10,T=0.8: <data>: str ( item id ) <newline> <tab> <tab> } ] , <newline> <tab> <tab> " session id " : session id , <newline> <tab> <tab> " user id " : str ( user id ) , <newline> <tab> <tab> " shop id " : str ( shop id ) <newline> <tab> } <newline> <tab> act param = aes _ cbc _ encrypt ( json . dumps ( request body ) , encrypt _ key , <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> encrypt _ iv ) <newline> <tab> request body [ ' act param ' ] = act </data>param <newline> <tab> request body [ ' act param ' ] = act param <newline> <tab> return request body [ ' act param ' ] <newline> <newline> def get request body ( ) : <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> request body [ ' post body ' ] = json . dumps ( request body ) <newline> <tab> request body [ ' body ' ] = json . dumps ( request body ) <newline> <tab> request body [ ' body ' ] = body [ ' body ' ] <newline> <newline> <tab> <newline> <tab> request body = request 
K=10,T=0.8: <data><tab> <tab> if model in [ ' digit ' ] : <newline> <tab> <tab> <tab> from nets . models import digit model <newline> <tab> <tab> <tab> model class = digit model <newline> <tab> <tab> else : <newline> <tab> <tab> <tab> raise value error ( f " invalid model : { model } " ) <newline> <tab> elif data in [ ' domain net ' ] : <newline> <tab> <tab> if model in [ ' alexnet ' ] : <newline> <tab> <tab> <tab> from nets . models import alex net <newline> <tab> <tab> <tab> model class = alex net <newline> <tab> </data>elif data in [ ' alexnet ' ] : <newline> <tab> <tab> from nets . models import vgg net class <newline> <tab> <tab> else : <newline> <tab> <tab> <tab> from nets . models import vgg net class <newline> <newline> <tab> <newline> <tab> <newline> <tab> net class = vgg net class <newline> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> def vgg ( self , image , mask _ mask , mask _ mask , mask _ mask , weight _ decay ) : <newline> <tab> <tab> <newline> <tab> <tab> if mask _ mask is none : <newline> <tab> 
K=10,T=0.8: <data><tab> <tab> use pickle = false <newline> <tab> else : <newline> <tab> <tab> print ( " [ helper ] can ' t decide if pickle to use based on extension " ) <newline> <tab> <tab> sys . exit ( ) <newline> <tab> if os . path . isfile ( targetdb ) : <newline> <tab> <tab> if use pickle : <newline> <tab> <tab> <tab> <newline> <tab> <tab> <tab> try : <newline> <tab> <tab> <tab> <tab> targets = pickle . load ( open ( targetdb , " rb " ) ) <newline> <tab> <tab> <tab> <newline> <tab> <tab> <tab> <newline> <tab> <tab> </data><tab> <newline> <tab> <tab> <tab> except ioerror as e : <newline> <tab> <tab> <tab> <tab> print ( " [ helper ] already exists . " ) <newline> <tab> <tab> <tab> <tab> os . makedirs ( idlist ) <newline> <tab> <tab> <tab> os . makedirs ( idlist ) <newline> <newline> <tab> <tab> <newline> <tab> <tab> <newline> <tab> <tab> <newline> <tab> <tab> <newline> <tab> <tab> <newline> <tab> <tab> if os . path . isfile ( idlist ) : <newline> <tab> <tab> <tab> <newline> <tab> <tab> <tab> <newline> <tab> <tab> <tab> if not os . path . exists ( idlist ) : <newline> 
K=10,T=0.8: <data>' <newline> <tab> <tab> <tab> elif modal = = ' d ' : <newline> <tab> <tab> <tab> <tab> <UNK> = ' rgbd - tr ' <newline> <tab> <tab> <tab> elif modal = = ' o ' : <newline> <tab> <tab> <tab> <tab> <UNK> = ' <UNK> - tr ' <newline> <tab> <tab> <tab> elif modal = = ' t ' : <newline> <tab> <tab> <tab> <tab> <UNK> = ' vt 5 0 0 0 - tr ' <newline> <tab> <tab> <tab> set _ name = ' _ ' . join ( ( modal , <UNK> ) ) <newline> <tab> <tab> </data><tab> set _ name = ' _ ' . join ( modal , <UNK> ) <newline> <tab> <tab> <tab> set _ name = ' _ ' . join ( modal , <UNK> ) <newline> <tab> <tab> <tab> set _ name = ' _ ' . join ( modal , <UNK> ) <newline> <tab> <tab> <tab> set _ name = ' _ ' . join ( modal , <UNK> ) <newline> <tab> <tab> <tab> set _ name = ' _ ' . join ( modal , <UNK> ) <newline> <tab> <tab> <tab> set _ name = ' _ ' . join 
K=10,T=0.8: <data>2 1 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 bc 8 f 5 e 5 4 0 0 0 0 0 0 0 0 0 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 <UNK> 6 1 b 6 4 0 9 2 0 8 d 0 1 0 0 0 0 0 0 0 0 0 0 0 0 </data>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 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>file or path : % s ' % fileobj _ or _ path ) <newline> <tab> <tab> elif not os . path . exists ( fileobj _ or _ path ) : <newline> <tab> <tab> <tab> raise value error ( ' no such file : % s ' % fileobj _ or _ path ) <newline> <tab> <tab> else : <newline> <tab> <tab> <tab> result = open ( fileobj _ or _ path , ' rb ' ) <newline> <tab> <tab> return result <newline> <newline> <tab> def _ handle _ io ( self , args , fileobj _ or _ </data>path : binary file = none , index : str ) - > none : <newline> <tab> <tab> <newline> <tab> <tab> index = none <newline> <tab> <tab> index = index + index + index <newline> <tab> <tab> index = index + index + index + index <newline> <tab> <tab> if index < index : <newline> <tab> <tab> <tab> index = index + index + index <newline> <tab> <tab> <tab> index = index <newline> <tab> <tab> <tab> index = index + index <newline> <tab> <tab> <tab> index = index + index <newline> <tab> <tab> <tab> index = index <newline> <tab> <tab> 
K=10,T=0.8: <data>distill _ checkpoint <newline> <tab> <tab> model = load _ and _ convert _ attns ( model , model _ config , <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> accelerator = accelerator , <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> logger = logger , <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> attention _ type = args . attention _ type , <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> checkpoint _ path = checkpoint _ path , <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> </data><tab> <tab> <tab> <tab> logger = logger , <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> accelerator = accelerator , <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> accelerator = accelerator , <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> logger = logger , <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> logger = logger <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> ) <newline> 
K=10,T=0.8: <data>replace ( " - best " , " - 2 5 0 e " ) , epoch , best _ val _ acc = val _ scores , <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> best _ test _ acc = test _ scores , best _ test _ clean = best _ test _ clean ) <newline> <tab> if ( epoch % args . adv _ eval _ freq = = 0 and epoch > args . start _ eval ) or epoch = = num _ adv _ epochs : <newline> <tab> <tab> test </data>_ acc = test _ scores [ 0 ] . detach ( ) . cpu ( ) . numpy ( ) . detach ( ) <newline> <tab> <tab> test _ acc = test _ acc . detach ( ) . cpu ( ) . numpy ( ) . detach ( ) . numpy ( ) <newline> <tab> <tab> test _ acc = test _ test _ acc * test _ acc <newline> <tab> <tab> test _ acc = test _ acc [ 0 ] . detach ( ) . cpu ( ) . numpy ( ) . numpy ( ) 
K=10,T=0.8: <data>for distillation loss ' ) <newline> parser . add _ argument ( ' - - average _ over ' , default = ' holdout ' , type = str , <newline> <tab> <tab> <tab> <tab> <tab> help = " whether to average over different holdout sizes : " <newline> <tab> <tab> <tab> <tab> <tab> <tab> " ' holdout ' , different train percents : ' tp ' " <newline> <tab> <tab> <tab> <tab> <tab> <tab> " or a single run : ' na ' " ) <newline> parser . add _ argument ( ' - - tp ' , default </data>= ' o ' , type = str , <newline> <tab> <tab> <tab> <tab> <tab> help = " the gradient of over different metrics " <newline> <tab> <tab> <tab> <tab> <tab> <tab> " ' " ) <newline> parser . add _ argument ( ' - - n _ epochs ' , default = 5 0 , type = int , <newline> <tab> <tab> <tab> <tab> <tab> help = " epochs to train the number of epochs to perform for testing " <newline> <tab> <tab> <tab> <tab> <tab> " ' " ) <newline> parser . add _ argument ( ' - 
K=10,T=0.8: <data>2 0 _ stoi = 0 <newline> score _ 1 0 _ stoi = 0 <newline> score _ 1 5 _ stoi = 0 <newline> score _ 0 _ stoi = 0 <newline> score _ 5 _ stoi = 0 <newline> score _ _ 5 _ stoi = 0 <newline> score _ 2 0 _ pesq _ gl = 0 <newline> score _ 1 0 _ pesq _ gl = 0 <newline> score _ 1 5 _ pesq _ gl = 0 <newline> score _ 0 _ pesq _ gl = 0 <newline> score _ 5 _ pesq _ gl </data>= 0 <newline> score _ 0 _ pesq _ gl = 0 <newline> score _ 1 0 _ stoi _ gl _ gl = 0 <newline> score _ 0 _ stoi _ gl = 0 <newline> <newline> <newline> def _ _ getitem _ _ ( self , index ) : <newline> <tab> <newline> <tab> <newline> <tab> if self . _ _ getitem _ _ = = index : <newline> <tab> <newline> <tab> if self . _ _ setitem _ _ ( index , index ) : <newline> <tab> <tab> <newline> <tab> <tab> <newline> <tab> <tab> self . _ _ delitem 
K=10,T=0.8: <data>. 4 6 3 8 . 6 9 safari / 5 3 7 . 3 6 ' , <newline> <tab> <tab> <tab> ' referer ' : ' https : / / www . <UNK> . com / ' , <newline> <tab> <tab> } <newline> <tab> <tab> url = ' https : / / app - sc . <UNK> . com / vms - match / v 3 / <UNK> / basic / basic - data / { } ' . format ( self . rid ) <newline> <newline> <tab> <tab> with requests . session ( ) as session : <newline> </data><tab> <tab> <tab> for key in session . query : <newline> <tab> <tab> <tab> <tab> session . query [ key ] = self . rid <newline> <newline> <tab> <tab> <newline> <tab> <tab> if url is none : <newline> <tab> <tab> <tab> <tab> url = f ' https : / / www . <UNK> . com / <UNK> - match / v 3 / <UNK> / basic - data / { } / <UNK> / <UNK> / * / { } ' <newline> <tab> <tab> <tab> <tab> if not url : <newline> <tab> <tab> <tab> <tab> <tab> raise value error ( 
K=10,T=0.8: <data>, dtype = torch . long ) ] , dim = 0 ) <newline> <tab> <tab> <tab> attention _ masks [ i ] = torch . cat ( [ attention _ masks [ i ] , torch . zeros ( pad _ length ) ] , dim = 0 ) <newline> <newline> <tab> <tab> input _ embeddings = torch . stack ( input _ embeddings ) . to ( self . device ) <newline> <tab> <tab> target _ labels = torch . stack ( target _ labels ) . to ( self . device ) <newline> <tab> <tab> attention _ </data>masks [ i , : , : , : , : , : , : , : ] = torch . stack ( attention _ masks ) . to ( self . device ) <newline> <tab> <tab> attention _ masks [ i , : , : , : , : , : , : ] = attention _ masks [ i , : , : , : , : , : , : : , : : , : , : ] * attention _ masks [ i , : , : , : , - : , : ] 
K=10,T=0.8: <data>sub ( r " \ ' re " , " \ ' re " , string ) <newline> <tab> string = re . sub ( r " \ ' d " , " \ ' d " , string ) <newline> <tab> string = re . sub ( r " \ ' ll " , " \ ' ll " , string ) <newline> <tab> string = re . sub ( r " , " , " , " , string ) <newline> <tab> string = re . sub ( r " ! " , " ! " , string </data>) <newline> <tab> string = re . sub ( r " \ ' d " , " \ ' d " , string ) <newline> <tab> string = re . sub ( r " \ ' d " , " \ ' d " , string ) <newline> <tab> string = re . sub ( r " \ ' d " , " \ ' d " , string ) <newline> <tab> string = re . sub ( r " \ ' d " , " " , string ) <newline> <tab> string = re . sub ( r " 
K=10,T=0.8: <data><tab> <tab> <newline> <tab> <tab> headers = { <newline> <tab> <tab> <tab> ' accept - encoding ' : ' <UNK> , ' <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> ' <UNK> <UNK> & au & * * <UNK> * * s , ' <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> ' <UNK> , ' <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> ' <UNK> , ' <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> ' <UNK> , ' <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> ' * * * * * * * * * * * </data>* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * 
K=10,T=0.8: <data>( mit ) <newline> <newline> copyright ( c ) 2 0 1 6 <UNK> ltd ( https : / / <UNK> . com ) <newline> <newline> permission is hereby granted , free of charge , to any person obtaining a copy <newline> of this software and associated documentation files ( the " software " ) , to deal <newline> in the software without restriction , including without limitation the rights <newline> to use , copy , modify , merge , publish , distribute , sublicense , and / or sell <newline> copies of the software , and to permit persons </data>to whom the software is furnished to do so , subject to the following conditions : <newline> <newline> <newline> the above copyright notice and this permission notice shall be included in all <newline> copies or substantial portions of the software . <newline> <newline> the software is provided is not , without warranty of any kind , express or implied , including but not limited to the warranties of merchantability , fitness for a particular purpose and noninfringement . in no event shall the authors or copyright holders be liable for any claim , damages or other <newline> liability , whether 
K=10,T=0.8: <data>, blend _ type = ' d ' , use _ colormap = true ) : <newline> <tab> print ( ' blend with spsg ' ) <newline> <tab> blends = [ ] <newline> <tab> blends _ colormap = [ ] <newline> <tab> masks = [ ] <newline> <tab> device = ' cuda ' if torch . cuda . is _ available ( ) else ' cpu ' <newline> <tab> for scene in scene _ images : <newline> <tab> <tab> marker = cv 2 . resize ( marker , ( scene . shape [ 1 ] , scene . shape [ </data>1 ] ) ) <newline> <tab> <tab> marker . append ( marker ) <newline> <tab> <tab> return marker <newline> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> <tab> <newline> 
K=10,T=0.8: <data><tab> return summary _ json <newline> <newline> <tab> def get _ cash _ flow ( self , ticker , fyear , period ) : <newline> <tab> <tab> data = self . _ get _ company _ statements ( ticker , " cf " , fyear , period ) <newline> <tab> <tab> extracted _ data = self . _ extract _ financial _ data ( data ) <newline> <tab> <tab> column _ map = { <newline> <tab> <tab> <tab> " operating activities " : [ <newline> <tab> <tab> <tab> <tab> " change in working capital " , <newline> <tab> <tab> <tab> </data><tab> " <UNK> " : [ <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> " cash activities " , <newline> <tab> <tab> <tab> <tab> <tab> " <UNK> " : [ <newline> <tab> <tab> <tab> <tab> <tab> <tab> " cash activities " , <newline> <tab> <tab> <tab> <tab> <tab> " income " : [ <newline> <tab> <tab> <tab> <tab> <tab> <tab> " cash activities " , <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> " <UNK> " : [ <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <newline> <tab> <tab> <tab> <tab> <tab> <tab> ] , <newline> <tab> <tab> <tab> <tab> 
K=10,T=0.8: <data>% ( levelname ) - 5 . 5 s ] % ( message ) s " ) <newline> <UNK> . set formatter ( log formatter ) <newline> logging . get logger ( ) . add handler ( <UNK> ) <newline> <newline> log = logging . get logger ( " app . " + _ _ name _ _ ) <newline> <newline> <newline> <newline> <newline> def add _ movie ( title , year , imdbid , quality _ profile _ id ) : <newline> <newline> <tab> global movie _ added _ count <newline> <tab> global movie _ exist _ count <newline> </data><tab> <newline> <tab> year = int ( year ) / 4 0 <newline> <tab> year = int ( year ) / 2 <newline> <tab> year = int ( year ) / 2 <newline> <newline> <tab> year = int ( year ) <newline> <tab> year = int ( year ) / 2 <newline> <tab> year = int ( year ) <newline> <tab> <newline> <tab> year = int ( year ) / 2 <newline> <tab> <newline> <tab> year = int ( year ) / 2 <newline> <newline> <tab> <newline> <tab> <newline> <tab> year = int ( year ) / 2 <newline> <newline> 
K=10,T=0.8: <data>" , u " " , u " ` " , " _ " ] ) <newline> <newline> <tab> <tab> self . answer _ tokens = none <newline> <newline> <tab> def set _ question ( self , normalized _ aliases ) : <newline> <tab> <tab> self . answer _ tokens = normalized _ aliases <newline> <newline> <tab> def any _ found ( self , para ) : <newline> <tab> <tab> <newline> <tab> <tab> words = [ w . lower ( ) . strip ( self . strip ) for w in flatten _ iterable ( para ) ] <newline> <tab> </data><tab> for w in words : <newline> <tab> <tab> <tab> words . append ( " [ + ] " ) <newline> <tab> <tab> if w . lower ( ) . endswith ( ' / ' ) : <newline> <tab> <tab> <tab> words . append ( " [ + ] " ) <newline> <newline> <tab> <tab> if ( words = = " [ + ] " ) : <newline> <tab> <tab> <tab> return word . lower ( ) . replace ( ' \ n ' , ' ' ) . replace ( ' \ n ' , ' ' ) <newline> 
K=10,T=0.8: <data>add ( avg pool 2 d ( pool _ size = ( 2 , 1 ) , padding = ' same ' ) ) <newline> <tab> model . add ( flatten ( ) ) <newline> <tab> model . add ( dense ( 1 0 0 , activation = ' elu ' ) ) <newline> <tab> model . add ( dense ( n _ outputs , activation = ' softmax ' ) ) <newline> <tab> <newline> <tab> plot _ model ( model , show _ shapes = true , to _ file = ' two d _ cnn . png ' </data>) <newline> <tab> plot _ model ( model , show _ shapes = true , to _ file = ' two d _ cnn . png ' ) <newline> <tab> plot _ model ( model , show _ shapes = true , to _ file = ' two d _ cnn . png ' ) <newline> <tab> print ( f " \ n \ n \ n \ n \ n \ n \ n \ n \ n \ n " ) <newline> <newline> def plot _ model ( model , show _ shapes = true , to _