K=10,T=0.8: _ only = true ) , " text " : orm . string ( title = " text " , max _ length = 1 0 0 ) , " completed " : orm . boolean ( title = " completed " , default = false ) , } admin = dashboard . dashboard ( tables = [ dashboard . dashboard table ( ident = " notes " , title = " notes " , ) , ) parser . add ( " - 8 " , " - 8 " , default = " , " " , " - 1 " , " , " " ) parser . add ( " , " - 8 " ) , " , help = " , K=10,T=0.8: output _ alias def get json ( self , path ) : if self . use _ https : url = f " https : / / { self . ip } : { self . port } { path } " else : url = f " http : / / { self . ip } : { self . port } { path } " headers = { " authorization " : " bearer " + self . port } " self . port . append ( json . dumps ( { ' password ' } ) if self . port = = = " server " : self . port = self . port self . port = self . port else : self . port = self . port self . port = port self . port = port self . port K=10,T=0.8: ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' pbr ' , ' pbt ' , ' ' , ' ' , ' pcar ' , ' pcb ' , ' pcg ' , ' pch ' , ' pci ' , ' pck ' , ' pcm ' , ' pcn ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , false ' ' , ' ' ) = ' ' = ' ' = ' ' = ' ' = ' = ' ' = ' ' = K=10,T=0.8: ( " 2 " , git add ( ) ) , ( " changelog " , update changelog ( ) ) , ( " readme " , update readme ( ) ) , ( " dist " , make dist ( ) ) , ( " " , push to test py pi ( ) ) , ( " install " , install from test py pi ( ) ) , ( " " , test pi ( ) , ( " " , , " " , update _ version ) , ( " " , " " , " " , " " , " " , " " , " " , " " , ( " " , " " , " " , " " , " " ) , ( " " , " " , " " , K=10,T=0.8: _ all _ utterances batch _ size = params . batch _ size if params . interaction _ level : batch _ size = 1 eval _ fn = evaluate _ interaction _ sample trainbatch _ fn = data . get _ interaction _ batches _ fn = data . get _ random _ interactions _ fn = data . get _ all _ interactions maximum _ output _ length = params . train _ maximum _ output _ length with open _ file ( log _ dir , ' w ' ) as f : f . write ( f ) if params . interaction _ level ! = 1 : logger . error ( f ' number of the { len ( p ) } ' ) K=10,T=0.8: _ only = true ) , " text " : orm . string ( title = " text " , max _ length = 1 0 0 ) , " completed " : orm . boolean ( title = " completed " , default = false ) , } admin = dashboard . dashboard ( tables = [ dashboard . dashboard table ( ident = " notes " , title = " notes " , title = " notes " , title = " notes " , ) ] ) admin = dashboard . dashboard table ( table = table , table = table , table = table , table = table , table = table , table = table , table = table , table = table , ) @ dataclass def validate _ table _ K=10,T=0.8: output _ alias def get json ( self , path ) : if self . use _ https : url = f " https : / / { self . ip } : { self . port } { path } " else : url = f " http : / / { self . ip } : { self . port } { path } " headers = { " authorization " : " bearer " + self . token } headers = self . headers if self . use _ verify : return { " headers " : headers , " content " : content , " content " : content , " content " : content , " content " : content , " content " : content , " content " : content , K=10,T=0.8: ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' pbr ' , ' pbt ' , ' ' , ' ' , ' pcar ' , ' pcb ' , ' pcg ' , ' pch ' , ' pci ' , ' pck ' , ' pcm ' , ' pcn ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' K=10,T=0.8: ( " 2 " , git add ( ) ) , ( " changelog " , update changelog ( ) ) , ( " readme " , update readme ( ) ) , ( " dist " , make dist ( ) ) , ( " " , push to test py pi ( ) ) , ( " install " , install from test py pi ( ) ) , ( " " , test py pi ( ) ) , ( " " , make dist ( ) ) , ( " " , make dist ( ) ) , ) if not is _ valid _ changelog : print ( " error " , error ) if not is _ valid _ changelog : changelog _ md = changelog . md changelog _ md . write ( changelog _ md ) K=10,T=0.8: _ all _ utterances batch _ size = params . batch _ size if params . interaction _ level : batch _ size = 1 eval _ fn = evaluate _ interaction _ sample trainbatch _ fn = data . get _ interaction _ batches _ fn = data . get _ random _ interactions _ fn = data . get _ all _ interactions maximum _ output _ length = params . train _ maximum _ output _ length return max _ output _ length def test _ interaction _ sample ( self ) : assert len ( self . interaction _ level ) > 0 assert len ( self . interactions _ level ) < 0 assert len ( self . interactions _ level ) > 0 assert len ( self . interactions _ level ) < 0 assert len ( self . interactions _ level ) < 0 def test _ interaction _ sample ( K=10,T=0.8: = cv 2 . resize ( marker _ image , ( w , h ) ) marker _ images . append ( marker _ image ) total = len ( scene _ images ) * len ( scene _ images [ 0 ] ) print ( ' input { } x { } scene images ' . format ( len ( scene _ images ) , len ( scene _ images [ 0 ] ) ) ) print ( ' input { } marker images ' . format ( scene _ images [ 0 ] ) ) scene _ images = [ " scene . images " , " scene . images " , " scene . images " ] , " scene . images " ] , " scene . images " ] , " scene . images " scene _ labels = [ " scene . images " , " scene . images K=10,T=0.8: is _ vec ' : best _ is _ vec } ) print ( " id : % 0 3 d " % id , " qitem : % 0 3 d " % q _ ct , " res " current : % d " % ( np . sum ( n is _ vec _ local ) ) , " best : % d " % best _ is _ num , " reduction " ) return true adj = adj _ matrix . to ( self . device ) return adj , adj def get _ best _ adj ( self , adj ) : if not self . is _ vec _ local : adj = adj _ matrix . to ( self . device ) for node in adj : if isinstance ( node , tuple ) : adj = adj _ matrix . to K=10,T=0.8: scalar ( ' train / reg _ tv _ density ' , loss _ tv . detach ( ) . item ( ) , global _ step = global _ step ) if tv _ weight _ app > 0 : tv _ weight _ app * = lr _ factor loss _ tv = tensorf . tv _ loss _ app ( tvreg ) * tv _ weight _ app total _ loss = total _ loss + loss _ tv tv _ weight _ app = tensorf . tv _ loss _ app ( tv . detach ( ) . item ( ) , global _ step = global _ step ) tv _ weight _ app = tensorf . tv _ loss _ app ( tv . detach ( ) . item ( ) , global _ step = global _ step ) tv _ weight _ app = tensorf . tv _ loss _ app ( tv . detach ( ) . K=10,T=0.8: error when connecting to { } : { } : { } " . format ( connect _ ip , connect _ port , e ) ) else : if b ' success ' not in current _ state : raise system exit ( " failure on webshell : { } " . format ( current _ state ) ) print ( " [ * ] server connected to target successfully " ) try : try : if current _ state [ " port " ] = = 0 : port = current _ state [ " port " ] except system exit : port = current _ state [ " port " ] port = current _ state [ " port " ] port = current _ state [ " port " ] K=10,T=0.8: math import multiprocessing as mp from tqdm import tqdm def line _ positions ( file _ path ) : with open ( file _ path ) as f : while true : pos = f . tell ( ) if f . readline ( ) : yield pos else : break def get _ number _ of _ lines ( fobj ) : for line in fobj : for line in fobj . readline ( ) : if line . lower ( ) in line . lower ( ) : line = line . split ( " : " ) if line . lower ( ) in line . lower ( ) : line = line . split ( " \ n " ) line = line . split ( " \ n " K=10,T=0.8: _ only = true ) , " text " : orm . string ( title = " text " , max _ length = 1 0 0 ) , " completed " : orm . boolean ( title = " completed " , default = false ) , } admin = dashboard . dashboard ( tables = [ dashboard . dashboard table ( ident = " notes " , title = " notes " , body = " " , description = " " , description = " " , text = " " , body = " " , ) ] ) admin . set _ name ( " admin " ) admin . set _ name ( " admin " ) admin . set _ name ( " admin " ) admin . set _ name ( " admin " K=10,T=0.8: output _ alias def get json ( self , path ) : if self . use _ https : url = f " https : / / { self . ip } : { self . port } { path } " else : url = f " http : / / { self . ip } : { self . port } { path } " headers = { " authorization " : " bearer " + self . user } " def get json ( self ) : if self . use _ auth : url = f " https : / / { self . ip } : { self . user } " url = f " http : / / { self . ip } : { self . ip } " url = f " http : / / { self . host } : { self . ip } : { self . port } K=10,T=0.8: ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' pbr ' , ' pbt ' , ' ' , ' ' , ' pcar ' , ' pcb ' , ' pcg ' , ' pch ' , ' pci ' , ' pck ' , ' pcm ' , ' pcn ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , ' ' , K=10,T=0.8: ( " 2 " , git add ( ) ) , ( " changelog " , update changelog ( ) ) , ( " readme " , update readme ( ) ) , ( " dist " , make dist ( ) ) , ( " " , push to test py pi ( ) ) , ( " install " , install from test py pi ( ) ) , ( " " , test py pi ( ) ) , ( " " , install from test py pi ( ) ) , ( " " , make dist ( ) ) , ( " " , make dist ( ) ) , ( " " , make dist ( ) ) , ( " " , make dist ( ) ) ) , ( " " , make dist ( ) ) , ( " K=10,T=0.8: _ all _ utterances batch _ size = params . batch _ size if params . interaction _ level : batch _ size = 1 eval _ fn = evaluate _ interaction _ sample trainbatch _ fn = data . get _ interaction _ batches _ fn = data . get _ random _ interactions _ fn = data . get _ all _ interactions maximum _ output _ length = params . train _ maximum _ output _ length _ fn = data . get _ all _ interaction _ fn ( ) _ fn = data . get _ all _ interaction _ fn ( ) max _ output _ length = params . max _ output _ length _ fn = data . get _ all _ interaction _ fn ( ) _ fn = data . get _ all _ interaction _ fn ( ) _ K=10,T=0.8: = cv 2 . resize ( marker _ image , ( w , h ) ) marker _ images . append ( marker _ image ) total = len ( scene _ images ) * len ( scene _ images [ 0 ] ) print ( ' input { } x { } scene images ' . format ( len ( scene _ images ) , len ( scene _ images [ 0 ] ) ) ) print ( ' input { } marker images ' . format ( len ( scene _ images [ 0 ] ) ) ) print ( ' total number of scenes ' . format ( total ) ) if _ _ name _ _ = = ' _ _ main _ _ ' : unittest . main ( ) < filesep > import re import numpy as np import pandas as pd import pandas as pd import pandas as pd import matplotlib import tensorflow . compat . v 1 K=10,T=0.8: is _ vec ' : best _ is _ vec } ) print ( " id : % 0 3 d " % id , " qitem : % 0 3 d " % q _ ct , " res " current : % d " % ( np . sum ( n is _ vec _ local ) ) , " best : % d " % best _ is _ num , " reduction " ) return true adj = adj _ mat . adj ( adj ) adj = adj . adj ( adj ) adj = adj . adj ( adj , adj ) adj = adj . adj ( adj ) adj = adj . adj ( adj ) adj = adj . adj ( adj ) adj = adj . adj ( adj ) adj = adj . adj ( adj ) adj = adj . adj ( adj ) adj K=10,T=0.8: scalar ( ' train / reg _ tv _ density ' , loss _ tv . detach ( ) . item ( ) , global _ step = global _ step ) if tv _ weight _ app > 0 : tv _ weight _ app * = lr _ factor loss _ tv = tensorf . tv _ loss _ app ( tvreg ) * tv _ weight _ app total _ loss = total _ loss + loss _ tv tv _ weight _ app / = tv _ weight _ app tv _ loss = tv _ weight _ app / tv _ weight _ app tv _ weight _ app / = tv _ weight _ app / tv _ weight _ app tv _ weight _ app / = tv _ weight _ app tv _ weight _ app / = tv _ weight _ app / tv _ K=10,T=0.8: error when connecting to { } : { } : { } " . format ( connect _ ip , connect _ port , e ) ) else : if b ' success ' not in current _ state : raise system exit ( " failure on webshell : { } " . format ( current _ state ) ) print ( " [ * ] server connected to target successfully " ) if b ' success ' not in current _ state : print ( " [ * ] server connected to target successfully " ) if b ' success ' not in current _ state : print ( " [ * ] server connected to target successfully " ) if b ' success ' not in current _ state : print ( " [ * ] server success to target successfully " ) if b ' success ' not in current K=10,T=0.8: math import multiprocessing as mp from tqdm import tqdm def line _ positions ( file _ path ) : with open ( file _ path ) as f : while true : pos = f . tell ( ) if f . readline ( ) : yield pos else : break def get _ number _ of _ lines ( fobj ) : while true : for line in b . splitlines ( ) : if line . startswith ( ' \ 0 ' ) : line = line . split ( ) - 1 for line in line . strip ( ) : if line . startswith ( ' \ 0 ' ) : yield line [ 2 : ] except exception : K=10,T=0.8: : 1 . the output of the current node that should be passed to the next node . 2 . a reason object that explains how the output was generated for debugging . add the > > operator , which creates a then node . wrap any strings in a string node first , to allow for code like setup node > > " command to run " > > node add the > > node , which create a node first , to allow for code like add the > > > operator add the > > > node , which create a node first , to allow for code like add the > > node , which create a node first , to allow for code like add the > > > node , which create a node first , K=10,T=0.8: , layer 2 ) : super ( concat table , self ) . _ _ init _ _ ( ) self . layer 1 = layer 1 self . layer 2 = layer 2 def forward ( self , x ) : y = [ self . layer 1 ( x ) , self . layer 2 ( x ) ] return y class flatten ( nn . module ) : def _ _ init _ _ ( self , dim ) : super ( flatten , self ) . _ _ init _ _ ( ) self . dim = dim self . dim = dim self . layer 3 = dim self . layer 3 = dim self . layer 3 = dim self . layer 4 = layers . nn . layer 4 ( dim ) self . layer 4 = layers . nn . layer 4 ( dim K=10,T=0.8: metadata [ " chunk _ size " ] , metadata [ " chunk _ overlap " ] , metadata [ " max _ chunk _ num " ] , ) df _ merged = pd . merge ( df _ docs , df _ remove , on = [ " md 5 " , " file _ path " ] , how = " inner " ) remove _ ids = np . array ( df _ merged ) remove _ ids = np . array ( remove _ ids ) add _ ids = np . array ( remove _ ids ) if self . config . use _ cuda : if self . config . use _ cuda : self . device = self . device elif self . config . use _ cuda : self K=10,T=0.8: x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ xf 7 \ x 9 e \ xf 7 \ x 9 2 \ x 0 0 \ x 0 0 \ xf 7 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 \ x 0 0 K=10,T=0.8: console . set level ( logging . error ) formatter = logging . formatter ( ' [ % ( levelname ) s ] % ( message ) s ' ) console . set formatter ( formatter ) logging . get logger ( ' ' ) . add handler ( console ) self . waves = asset ( ' ' ) self . btc = asset ( ' 8 8 f 7 p 5 d 5 7 gt s 3 7 9 2 3 5 0 3 9 5 9 4 7 9 2 1 6 7 7 4 9 5 6 3 9 5 2 3 6 9 6 6 5 9 6 2 7 3 3 6 1 5 9 6 0 3 4 2 3 5 9 5 2 1 5 9 3 2 2 4