K=10,T=0.8: <data><tab> <tab> ' pass _ info ' : [ ' password ' , ' pass _ dict / 1 - <UNK> . txt ' ] , <newline> <tab> <tab> <tab> ' button ' : [ ' a ' ] , <newline> <tab> <tab> <tab> ' captcha ' : [ ] , <newline> <tab> <tab> <tab> ' suc ' : [ ' ' ] , <newline> <tab> <tab> <tab> ' fail ' : [ ' ' ] , <newline> <tab> <tab> <tab> ' logic ' : [ ' or ' ] , <newline> <tab> <tab> } , <newline> <tab> <tab> ' </data><UNK> ' : [ ' ] , <newline> <tab> <tab> ' <UNK> ' : [ ' <UNK> ' ] , <newline> <tab> <tab> ' <UNK> ' : [ ' <UNK> ' ] , <newline> <tab> ' <UNK> ' : [ ' <UNK> ' , ' <UNK> ' ] , <newline> <tab> ' <UNK> ' : [ ' <UNK> ' ] , <newline> <tab> ' <UNK> ' : [ ' <UNK> ' , ' <UNK> ' , ' <UNK> ' , ' <UNK> ' , <newline> <tab> <tab> ' <UNK> ' : [ ' <UNK> ' , ' ] , <newline> 
K=10,T=0.8: <data>. 0 . 1 " , <newline> <tab> <tab> <tab> " mozilla / 5 . 0 ( windows nt 5 . 1 ; rv : 5 . 0 ) gecko / 2 0 1 0 0 1 0 1 firefox / 5 . 0 " , <newline> <tab> <tab> <tab> " mozilla / 5 . 0 ( windows nt 5 . 2 ; rv : 1 0 . 0 . 1 ) gecko / 2 0 1 0 0 1 0 1 firefox / 1 0 . 0 . 1 sea monkey / 2 . 7 . 1 " , </data><newline> <tab> <tab> " " : 5 . 0 . 0 3 2 0 ( khtml , like gecko / 1 0 1 0 . 0 . 2 . 0 2 3 . 4 ) / 1 0 . 0 . 0 . 0 0 1 " , <newline> <tab> <tab> " accept " : 5 5 . 0 ( ) , <newline> <tab> <tab> " referer " : 5 . 0 . 0 0 , <newline> <tab> <tab> " accept " : 1 . 1 . 0 . 0 0 0 0 . 0 0 5 , <newline> <tab> 
K=10,T=0.8: <data>( ) <newline> <tab> <newline> <tab> <newline> def main ( options ) : <newline> <tab> if not os . path . exists ( options . checkpoint _ dir ) : <newline> <tab> <tab> os . system ( " mkdir - p % s " % options . checkpoint _ dir ) <newline> <tab> <tab> pass <newline> <tab> if not os . path . exists ( options . test _ dir ) : <newline> <tab> <tab> os . system ( " mkdir - p % s " % options . test _ dir ) <newline> <tab> <tab> pass <newline> <newline> <tab> </data><newline> <tab> <newline> <tab> options . test _ dir = options . test _ dir <newline> <tab> options . test _ dir = options . test _ dir <newline> <tab> options . test _ dir = options . test _ dir <newline> <newline> <tab> options . test _ dir = options . test _ dir <newline> <tab> options . test _ dir = options . test _ dir <newline> <tab> options . test _ dirs = options . test _ dir <newline> <tab> options . test _ dir = options . test _ dir <newline> <tab> options . test _ 
K=10,T=0.8: <data><tab> repos = [ ] <newline> <tab> <tab> for repo in repository _ list : <newline> <tab> <tab> <tab> owner , repo _ name = repo . split ( " / " ) <newline> <tab> <tab> <tab> repository _ obj = github _ connection . repository ( owner , repo _ name ) <newline> <tab> <tab> <tab> repos . append ( repository _ obj ) <newline> <newline> <tab> all _ contributors = [ ] <newline> <tab> if repos : <newline> <tab> <tab> for repo in repos : <newline> <tab> <tab> <tab> repo _ contributors = get _ contributors ( repo </data>_ name , repo _ name ) <newline> <tab> <tab> <tab> repo _ url = repo _ url . get ( repo _ url ) <newline> <tab> <tab> repo _ url = repo _ url . get ( repo _ url ) <newline> <tab> <tab> repo _ url = repo _ url . search ( repo _ url ) <newline> <tab> <tab> repo _ url = repo _ url . get ( repo _ url , repo _ url ) <newline> <tab> <tab> repo _ repo _ url . get ( repo _ url ) <newline> <tab> <tab> repo _ 
K=10,T=0.8: <data>from running _ state import <UNK> <newline> <newline> <newline> <newline> torch . set _ default _ tensor _ type ( ' torch . double tensor ' ) <newline> pi = torch . double tensor ( [ 3 . 1 4 1 5 9 2 6 ] ) <newline> <newline> parser = argparse . argument parser ( description = ' py torch actor - critic example ' ) <newline> parser . add _ argument ( ' - - gamma ' , type = float , default = 0 . 9 9 5 , metavar = ' g ' , <newline> <tab> </data><tab> <tab> <tab> <tab> <tab> <tab> help = ' gamma for gamma value ' ) <newline> parser . add _ argument ( ' - - gamma ' , type = float , default = 0 . 2 5 , metavar = ' gamma for gamma value ' ) <newline> parser . add _ argument ( ' - - beta ' , type = float , default = 0 . 4 5 , metavar = ' beta for gamma value ' ) <newline> parser . add _ argument ( ' - - gamma ' , type = float , default = 
K=10,T=0.8: <data>is _ vec ' : best _ is _ vec } ) <newline> <tab> <tab> <tab> print ( " id : % 0 3 d " % id , " qitem : % 0 3 d " % q _ ct , " res <newline> <tab> <tab> <tab> <tab> " current : % d " % ( np . sum ( n is _ vec _ local ) ) , " best : % d " % best _ is _ num , " reduction " ) <newline> <tab> <tab> <tab> return true <newline> <tab> <tab> adj = adj _ </data>adj <newline> <tab> <tab> adj = adj _ adj _ adj _ adj _ adj _ adj _ adj _ adj <newline> <tab> <tab> adj = adj _ adj _ adj _ adj _ adj _ adj _ adj <newline> <tab> <tab> adj = adj _ adj _ adj _ adj _ adj _ adj _ adj _ adj _ adj <newline> <tab> <tab> adj = adj _ adj _ adj _ adj _ adj _ adj _ adj _ adj _ adj _ adj _ adj _ adj _ adj _ adj _ adj _ adj _ adj _ 
K=10,T=0.8: <data><tab> if isinstance ( call . func , <newline> <tab> <tab> <tab> <tab> <tab> <tab> ast . name ) and call . func . id in self . stmts : <newline> <tab> <tab> <tab> <tab> macro = self . stmts [ call . func . id ] <newline> <tab> <tab> <tab> <tab> return macro . f ( none , * call . args ) <newline> <tab> <tab> return self . generic _ visit ( node ) <newline> <newline> <tab> def visit _ call ( self , node : ast . call ) : <newline> <tab> <tab> if isinstance ( node </data>, ast . function ) or call . func . id in self . ast : <newline> <tab> <tab> <tab> return none <newline> <tab> <tab> return ( self . ast ( ) , ' call ' ) if self . ast else self . ast ) <newline> <newline> def get _ expr ( self , expr : ast . call ) : <newline> <tab> if expr . lineno . lineno = = 2 : <newline> <tab> <tab> assert expr . col . col . col = = 2 <newline> <tab> <tab> return expr . col . col <newline> <tab> def 
K=10,T=0.8: <data>data _ dir _ city , args . data _ city _ list , crop _ size = ( 2 0 4 8 * 0 . 6 , 1 0 2 4 * 0 . 6 ) , mean = img _ mean , <newline> <tab> <tab> <tab> <tab> <tab> <tab> scale = false , mirror = false , set = args . set ) , <newline> <tab> <tab> batch _ size = 1 , shuffle = false , places = place ) <newline> <newline> <tab> for index , batch in enumerate ( testloader 1 ) : <newline> <tab> <tab> </data>batch _ size = batch [ index ] . size ( 1 ) <newline> <tab> <tab> batch _ size = batch [ index ] . size ( 1 ) <newline> <tab> <tab> batch _ size = batch [ 0 ] . size ( 1 ) <newline> <newline> <tab> <tab> batch _ size = batch [ 0 ] . size ( 1 ) <newline> <tab> <tab> batch _ size = batch [ index ] . size ( 1 ) <newline> <tab> <tab> batch _ size = batch [ 0 ] . size ( 1 ) <newline> <tab> <tab> if args . 
K=10,T=0.8: <data>nid , dirent . file _ type ) <newline> <tab> <tab> <tab> if dirent . file _ type = = file type . erofs _ ft _ symlink : <newline> <tab> <tab> <tab> <tab> os . symlink ( child _ inode . get _ symlink _ dest ( ) , out _ path ) <newline> <tab> <tab> <tab> elif dirent . file _ type = = file type . erofs _ ft _ dir : <newline> <tab> <tab> <tab> <tab> os . mkdir ( out _ path ) <newline> <tab> <tab> <tab> <tab> <newline> <tab> <tab> <tab> <tab> os . </data>symlink ( child _ dirent . get _ symlink _ dest ( ) , out _ path ) <newline> <tab> <tab> <tab> else : <newline> <tab> <tab> <tab> <tab> os . symlink ( child _ inode . get _ symlink _ dest ( ) , out _ path ) <newline> <newline> <tab> <newline> <tab> for i , files in enumerate ( files ) : <newline> <tab> <tab> <newline> <tab> <tab> if i > 0 : <newline> <tab> <tab> <tab> os . symlink ( child _ inode . get _ symlink ( i ) , os . path . basename ( 
K=10,T=0.8: <data>; ' , 1 ) [ 0 ] <newline> <tab> <tab> <tab> found _ comment = true <newline> <tab> <tab> if not self . opts [ ' no _ hashes ' ] and ' <newline> <tab> <tab> <tab> line = line . split ( ' <newline> <tab> <tab> <tab> found _ comment = true <newline> <tab> <tab> if found _ comment : <newline> <tab> <tab> <tab> comment _ count + = 1 <newline> <tab> <tab> return ( line , comment _ count ) <newline> <newline> <tab> def get _ key _ value ( self , line ) : <newline> <tab> </data><tab> if not self . opts [ ' key ' ] : <newline> <tab> <tab> <tab> return none <newline> <tab> <tab> elif not self . opts [ ' key ' ] : <newline> <tab> <tab> <tab> return none <newline> <tab> <tab> return self . opts [ ' key ' ] <newline> <tab> <tab> return self . opts [ ' key ' ] <newline> <newline> <tab> def get _ keys ( self , item ) : <newline> <tab> <tab> return self . opts [ ' keys ' ] <newline> <newline> <tab> def get _ keys ( self , item ) : 
K=10,T=0.8: <data>" kill cd " ] = = 0 . 0 <newline> <newline> <newline> def set _ can _ vote _ false ( ) - > none : <newline> <tab> with open ( can _ vote _ path , " w " ) as f : <newline> <tab> <tab> f . write ( " 0 " ) <newline> <newline> def get _ task _ position ( data , i ) : <newline> <tab> <newline> <tab> global ship _ task _ types , airship _ task _ types , pb _ task _ types , hq _ task _ types , map </data>_ dict _ list = get _ task _ type _ types ( data , i ) <newline> <tab> task _ types = get _ task _ type _ types ( data , j ) <newline> <tab> for task in task _ types : <newline> <tab> <tab> if task _ types : <newline> <tab> <tab> <tab> task = task [ task [ task [ task [ task [ task [ task [ task [ task [ task [ task [ task [ task [ task [ task [ task [ task [ task [ task [ task [ task [ 
K=10,T=0.8: <data>game _ task . result ( ) <newline> <tab> <tab> <tab> zip _ path = path ( " data " ) / f ' { game . cur _ world . name } . zip ' <newline> <tab> <tab> <tab> zipped _ file = await zip _ files ( game . game _ path , zip _ path ) <newline> <newline> <tab> <tab> <tab> async with aiofiles . open ( zip _ path , ' rb ' ) as f : <newline> <tab> <tab> <tab> <tab> data = await f . read ( ) <newline> <tab> <tab> <tab> <tab> yield </data>json . loads ( data . encode ( " utf - 8 " ) ) <newline> <newline> <tab> def test _ file ( self ) : <newline> <tab> <tab> <newline> <tab> <tab> <newline> <tab> <tab> try : <newline> <tab> <tab> <tab> yield json . loads ( data . encode ( " utf - 8 " ) ) <newline> <tab> <tab> except : <newline> <tab> <tab> <tab> yield json . loads ( data . encode ( " utf - 8 " ) ) <newline> <tab> <tab> <tab> yield json . loads ( data . encode ( " utf - 8 " 
K=10,T=0.8: <data>writing predictions to : % s " , ( output _ prediction _ file ) ) <newline> <newline> result _ dict , cls _ dict = { } , { } <newline> result _ dict , cls _ dict = accumulate _ predictions _ v 2 ( result _ dict , cls _ dict , all _ examples , <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> all _ features , all _ results , n _ best _ size , max _ answer _ length , <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> start </data>_ time _ secs = start _ time _ secs , <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> start _ time _ secs = start _ time _ secs , <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> start _ duration _ secs = start _ time _ secs , <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> start _ time _ secs = start _ time _ secs , <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> start _ time _ secs = start _ time _ secs , <newline> <tab> <tab> <tab> 
K=10,T=0.8: <data>( " total train batch : " , total _ batch ) <newline> <newline> <tab> test _ loader = load _ data ( pretrain _ path = args . data _ root _ lrs 3 _ pretrain , train _ path = args . data _ root _ lrs 3 _ train , noise _ path = args . noise _ data _ root , num _ workers = hparams . hparams . num _ workers , batch _ size = hparams . hparams . batch _ size , shuffle = false , split = ' val ' ) <newline> </data><tab> test _ loader = load _ data ( pretrain _ path = args . data _ root _ lrs 3 _ train , noise _ path = args . noise _ paths , batch _ size = hparams . hparams . batch _ size , shuffle = true , split = ' val ' ) <newline> <tab> test _ loader = load _ data ( pretrain _ path = args . data _ root _ lrs 3 _ val , noise _ path = args . noise _ path , shuffle = true , split = ' validation ' 
K=10,T=0.8: <data>' % parafile ) <newline> <tab> return str _ value <newline> <newline> def get _ area _ name _ remark _ time ( area _ ini ) : <newline> <tab> area _ name = get _ string _ parameters ( area _ ini , ' area _ name ' ) <newline> <tab> area _ remark = get _ string _ parameters ( area _ ini , ' area _ remark ' ) <newline> <tab> area _ time = get _ string _ parameters ( area _ ini , ' area _ time ' ) <newline> <tab> area _ name _ </data>remark = get _ string _ parameters ( area _ ini , ' area _ time ' ) <newline> <tab> area _ area _ time = get _ string _ parameters ( area _ area _ ini , ' area _ time ' ) <newline> <tab> area _ time = get _ string _ parameters ( area _ log , ' area _ time ' ) <newline> <newline> <tab> area _ list = get _ string _ parameters ( area _ list , ' area _ list ' ) <newline> <tab> area _ list = get _ list _ parameters 
K=10,T=0.8: <data>labels _ string = " " . join ( docname _ labels [ 1 ] ) <newline> <tab> <tab> <tab> <tab> if docname not in self . rouge _ dict : <newline> <tab> <tab> <tab> <tab> <tab> self . rouge _ dict [ docname ] = { final _ labels _ string : rougescore } <newline> <tab> <tab> <tab> <tab> else : <newline> <tab> <tab> <tab> <tab> <tab> self . rouge _ dict [ docname ] [ final _ labels _ string ] = rougescore <newline> <tab> <tab> <tab> <newline> <tab> <tab> <tab> os . system ( " rm - </data>rf _ { } " . format ( self . rouge _ dict [ doc ] ) ) <newline> <tab> <tab> <tab> if not os . system ( " rm - rf _ { } " . format ( self . rouge _ dict [ doc ] ) ) : <newline> <tab> <tab> <tab> <tab> self . rouge _ dict [ doc ] [ " rouge _ dict " ] + = { <newline> <tab> <tab> <tab> <tab> <tab> <tab> " rouge _ dict [ doc ] [ " rouge _ dict " ] + = { <newline> <tab> <tab> 
K=10,T=0.8: <data><newline> <newline> def call _ delete _ msg ( <newline> <tab> interval : int , <newline> <tab> func : callable [ [ int , int | tuple [ int , . . . ] ] , coroutine [ none , none , bool ] ] , <newline> <tab> target _ id : int , <newline> <tab> msg _ : int | tuple [ int , . . . ] , <newline> ) - > none : <newline> <tab> asyncio . get _ event _ loop ( ) . call _ later ( interval , func , target _ id , </data>message _ ) <newline> <tab> asyncio . put _ event _ loop ( ) . call _ ack ( ) . call _ ack ( ) . call _ ack ( ) . call _ ack ( ) . call _ ack ( ) . call _ ack ( ) . call _ ack ( ) . call _ ack ( ) ) . call _ ack ( ) . call _ ack ( ) . call _ ack ( ) . call _ ack ( ) . call _ ack ( ) . call _ ack ( ) . 
K=10,T=0.8: <data>. cond = nn . conv 1 d ( gin _ channels , upsample _ initial _ channel , 1 ) <newline> <newline> <tab> def forward ( self , x , g = none ) : <newline> <tab> <tab> x = self . conv _ pre ( x ) <newline> <tab> <tab> if g is not none : <newline> <tab> <tab> x = x + self . cond ( g ) <newline> <newline> <tab> <tab> for i in range ( self . num _ upsamples ) : <newline> <tab> <tab> <tab> x = x + ( 1 / self . </data>num _ kernels ) / self . num _ kernels <newline> <newline> <tab> <tab> <tab> return x <newline> <newline> <tab> def forward ( self , x , g = none ) : <newline> <tab> <tab> x = self . conv _ pre ( x ) <newline> <newline> <tab> <tab> x = x + self . cond ( g ) <newline> <newline> <tab> <tab> x = x + self . cond ( g ) <newline> <tab> <tab> x = self . cond ( g ) <newline> <newline> <tab> <tab> x = self . cond ( g ) <newline> <tab> <tab> x 
K=10,T=0.8: <data>. ifg ) , interpolation = " none " ) ; plt . colorbar ( ) <newline> plt . figure ( ) ; plt . imshow ( np . abs ( sim . ifg _ noisy ) , interpolation = " none " ) ; plt . colorbar ( ) <newline> plt . figure ( ) ; plt . imshow ( sim _ <UNK> , interpolation = " none " , cmap = " greys _ r " ) ; plt . colorbar ( ) <newline> <newline> <newline> < filesep > <newline> <newline> import csv <newline> import numpy as np </data><newline> import os . path as osp <newline> import matplotlib <newline> <newline> <newline> from tqdm import tqdm <newline> from pil import image <newline> from datasets import load _ dataset <newline> <newline> <newline> class preprocess ( dataset ) : <newline> <tab> def _ _ init _ _ ( self , <newline> <tab> <tab> <tab> <tab> <tab> <tab> data _ dir : str = " . / data / datasets / dataset " , <newline> <tab> <tab> <tab> <tab> <tab> <tab> data _ dir : str = " . / data / datasets / dataset " , <newline> <tab> <tab> <tab> <tab> 
K=10,T=0.8: <data>[ ' gift ' ] [ j ] [ ' raffle id ' ] <newline> <tab> <tab> <tab> <tab> if statistics ( ) . check _ <UNK> ( raffleid ) : <newline> <tab> <tab> <tab> <tab> <tab> type = json _ response [ ' data ' ] [ ' gift ' ] [ j ] [ ' type ' ] <newline> <tab> <tab> <tab> <tab> <tab> time _ wait = json _ response [ ' data ' ] [ ' gift ' ] [ j ] [ ' time _ wait ' ] <newline> <tab> <tab> <tab> <tab> <tab> time </data>_ wait = json _ response [ ' response ' ] [ ' time _ wait ' ] <newline> <tab> <tab> <tab> <tab> time _ wait = json _ response [ ' data ' ] [ ' time _ wait ' ] <newline> <newline> <tab> <tab> <tab> <tab> <tab> if time _ wait in [ ' 0 ' , ' 0 ' , ' 0 ' ] : <newline> <tab> <tab> <tab> <tab> <tab> <tab> time _ wait = json _ response [ ' data ' ] [ ' time _ wait ' ] <newline> <tab> <tab> <tab> <tab> <tab> 
K=10,T=0.8: <data>bean 4 . 3 . x " , " 1 9 " : " kit kat 4 . 4 - 4 . 4 . 4 " , " 2 1 " : " <UNK> 5 . 0 " , " 2 2 " : " <UNK> 5 . 1 " , " 2 3 " : " marshmallow 6 . 0 " , " 2 4 " : " <UNK> 7 . 0 " , " 2 5 " : " <UNK> 7 . 1 " , " 2 6 " : " <UNK> 8 . 0 " , " </data>2 6 " : " <UNK> 7 . 1 " , " 2 1 " : " <UNK> 2 8 . 0 " , " 2 1 " : " <UNK> 7 . 1 " , " 2 1 " : " <UNK> 8 . 0 " , " 2 2 " : " <UNK> 7 . 0 " , " 2 2 " : " <UNK> 8 . 0 " , " 2 5 " : " <UNK> 7 . 2 " , " 2 0 " : " <UNK> 8 . 0 " , " 2 3 " 
K=10,T=0.8: <data>a <newline> <tab> <tab> successful match . this may raise exceptions for eof or timeout . to <newline> <tab> <tab> avoid the eof or timeout exceptions add eof or timeout to the pattern <newline> <tab> <tab> list . that will cause expect to match an eof or timeout condition <newline> <tab> <tab> instead of raising an exception . <newline> <newline> <tab> <tab> if you pass a list of patterns and more than one matches , the first match <newline> <tab> <tab> in the stream is chosen . if more than one pattern matches at that point , <newline> <tab> <tab> </data>in the stream is chosen . <newline> <newline> <tab> <tab> returns the stream , but can be used . <newline> <tab> <tab> the stream is rejected . this may see <newline> <tab> <tab> <newline> <tab> <tab> the stream is rejected . this may be used . <newline> <newline> <tab> <tab> returns the stream , but can be used . this may be used . <newline> <newline> <tab> <tab> returns the stream , but can be used . this may be used . <newline> <newline> <tab> <tab> returns the stream , but can be used . the <newline> <tab> <tab> the 
K=10,T=0.8: <data>dst _ host _ count " , " dst _ host _ srv _ count " , " dst _ host _ same _ srv _ rate " , " dst _ host _ diff _ srv _ rate " , " dst _ host _ same _ src _ port _ rate " , " dst _ host _ srv _ diff _ host _ rate " , " dst _ host _ serror _ rate " , " dst _ host _ srv _ serror _ rate " , " dst _ host _ rerror _ rate " </data>, " dst _ host _ srv _ rate " , " dst _ host _ srv _ rate " , " dst _ host _ srv _ rate " , " dst _ host _ srv _ rate " , " dst _ host _ srv _ rate " , " dst _ host _ srv _ rate " , " dst _ host _ srv _ rate " , " dst _ host _ srv _ rate " , " dst " , " dst _ host _ srv _ rate " , " dst _ host _ 
K=10,T=0.8: <data><tab> <tab> for part in new _ path . split ( ' / ' ) : <newline> <tab> <tab> <tab> <tab> if part = = ' . . ' : <newline> <tab> <tab> <tab> <tab> <tab> orig . pop ( ) <newline> <tab> <tab> <tab> <tab> else : <newline> <tab> <tab> <tab> <tab> <tab> orig . append ( part ) <newline> <newline> <tab> <tab> <tab> if orig = = [ ' ' ] : <newline> <tab> <tab> <tab> <tab> self . current _ path = ' / ' <newline> <tab> <tab> <tab> else : <newline> <tab> <tab> <tab> <tab> self </data>. current _ path = ' / ' <newline> <newline> <tab> def <UNK> ( self ) : <newline> <tab> <tab> return self . current _ path / ' / ' <newline> <newline> <tab> def <UNK> ( self , old _ path ) : <newline> <tab> <tab> return old _ path <newline> <newline> <tab> def <UNK> ( self ) : <newline> <tab> <tab> return self . current _ path / ' / ' <newline> <newline> <tab> def <UNK> ( self , old _ path ) : <newline> <tab> <tab> return old _ path <newline> <newline> <tab> def <UNK> ( self ) 
K=10,T=0.8: <data>else <UNK> ) <newline> <tab> print ( line ) <newline> <tab> create _ structure _ scan ( r , url , stat , u _ agent , thread , subdomains , before start ) <newline> <newline> <newline> <newline> if _ _ name _ _ = = ' _ _ main _ _ ' : <newline> <tab> <newline> <tab> parser = argparse . argument parser ( add _ help = true ) <newline> <tab> parser = argparse . argument parser ( description = ' \ 0 3 3 [ 3 2 m version 2 . 3 | contact : https : </data>/ / github . com / ultralytics / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / master / 
K=10,T=0.8: <data>true ) <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <newline> <tab> <tab> <tab> <tab> user _ category = user _ category . cuda ( non _ blocking = true ) <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <newline> <tab> <tab> <tab> <tab> user _ sub category = user _ sub category . cuda ( non _ blocking = true </data>) <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <newline> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> <tab> 
K=10,T=0.8: <data>return df [ " rmi " ] <newline> <newline> def <UNK> _ atr ( dataframe , length = 7 ) : <newline> <tab> <newline> <tab> df = dataframe . copy ( ) <newline> <newline> <tab> df [ ' atr ' ] = ta . atr ( df , timeperiod = 1 4 ) <newline> <tab> df [ ' sma high ' ] = df [ ' high ' ] . rolling ( length ) . mean ( ) + df [ ' atr ' ] <newline> <tab> df [ ' sma low ' ] = df [ ' low ' </data>] <newline> <tab> df [ ' sma high ' ] = df [ ' sma high ' ] . rolling ( length ) . mean ( ) + df [ ' sma low ' ] <newline> <tab> df [ ' sma low ' ] = df [ ' sma high ' ] . rolling ( length ) . mean ( ) + df [ ' sma high ' ] <newline> <tab> df [ ' sma low ' ] = df [ ' sma high ' ] <newline> <tab> df [ ' sma high ' ] = df [ ' sma 
K=10,T=0.8: <data>. sma _ indicator ( data [ " close " ] , window = 5 0 ) <newline> <tab> data [ " rsi " ] = ta . momentum . rsi ( data [ " close " ] , window = 1 4 ) <newline> <tab> data [ " macd " ] = ta . trend . macd _ diff ( data [ " close " ] ) <newline> <tab> data [ " bb _ upper " ] , data [ " bb _ middle " ] , data [ " bb _ lower " ] = ( <newline> <tab> </data><tab> data [ " bb _ upper " ] , data [ " bb _ lower " ] , data [ " bb _ lower " ] , data [ " bb _ upper " ] ) <newline> <tab> data [ " rsi " ] = ta . <UNK> . rsi ( data [ " rsi " ] , data [ " bb _ upper " ] ) <newline> <tab> data [ " rsi " ] = ta . <UNK> . rsi ( data [ " rsi " ] , data [ " rsi " ] , data [ " 
K=10,T=0.8: <data>ma + recall _ se ) / 4 <newline> <tab> <tab> <tab> pre = ( pre _ ex + pre _ he + pre _ ma + pre _ se ) / 4 <newline> <tab> <tab> <tab> acc = ( acc _ ex + acc _ he + acc _ ma + acc _ se ) / 4 <newline> <tab> <tab> <tab> dice = ( dice _ ex + dice _ he + dice _ ma + dice _ se ) / 4 <newline> <tab> <tab> <tab> io u = ( io u _ ex + io u _ he </data>+ io u _ he + io u _ he + io u _ he + io u _ he + io u _ he + io u _ he - io u _ he + io u _ he + io u _ he + io u _ he ) / 5 <newline> <tab> <tab> <tab> io u = io u _ ex + io u _ tw <newline> <newline> <tab> <tab> <tab> io u = io u _ ex + io u _ he + io u _ he + io u _ he + io u _ 
K=10,T=0.8: <data>" role " : " system " , " content " : self . _ system _ prompt } , <newline> <tab> <tab> <tab> <tab> { " role " : " user " , " content " : input } , <newline> <tab> <tab> <tab> ] , <newline> <tab> <tab> ) <newline> <tab> <tab> model _ output = response [ " choices " ] [ 0 ] [ " message " ] [ " content " ] <newline> <newline> <tab> <tab> <newline> <tab> <tab> accepted = " accepted " in model _ output <newline> <newline> <tab> <tab> return model _ </data>output <newline> <newline> <tab> def get _ response _ content ( self , content , prompt ) : <newline> <tab> <tab> content = content . encode ( " utf - 8 " ) <newline> <newline> <tab> <tab> <newline> <tab> <tab> return content <newline> <newline> <tab> def get _ response _ content ( self , content , prompt ) : <newline> <tab> <tab> content . find ( " \ n " ) <newline> <tab> <tab> return content <newline> <tab> <newline> <tab> <newline> <tab> def get _ response _ content ( self , content , response ) : <newline> <tab> <tab> content