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def transcribe _ file _ with _ metadata ( ) - > speech. recognizeresponse : # [ start speech _ transcribe _ recognition _ metadata _ beta ] from google. cloud import speech _ v1p1beta1 as speech client = speech. speechclient ( ) speech _ file = " resources / commercial _ mono. wav " with open ( speech _ file, " rb " ) ...
[ 0.527310311794281, -0.6392435431480408, 0.9125540256500244, -0.028411582112312317, 0.39118513464927673, -0.21490953862667084, -0.23686718940734863, 0.10499359667301178, -0.5140056610107422, 1.087482213973999, -1.0444915294647217, 0.3450378179550171, -0.062418077141046524, -0.25815820693969...
def gradient ( self, params : ztyping. paramtypeinput = none ) - > list [ tf. tensor ] : params = self. _ input _ check _ params ( params ) numgrad = self. _ options [ " numgrad " ] params = { p. name : p for p in params } return self. _ gradient ( params = params, numgrad = numgrad )
[ -1.6461094617843628, 0.37440189719200134, 0.6004192233085632, 0.3863472044467926, 1.1109589338302612, 0.10643503814935684, 0.8013909459114075, -0.24223701655864716, -0.5372573733329773, 0.7553969025611877, -0.5279509425163269, 0.3917013108730316, -0.6920145153999329, 0.698070228099823, -...
def task ( self ) : return self. _ task
[ -0.0541563481092453, -0.24437493085861206, 0.2779902219772339, 0.6491332650184631, -0.028514599427580833, 0.7472372651100159, 1.098099708557129, -0.006108419504016638, 0.13787072896957397, -0.6516087055206299, -0.7184553742408752, 0.19487713277339935, 0.5946506857872009, -0.654489874839782...
def plotwccdistr _ pneanet ( * args ) : return _ snap. plotwccdistr _ pneanet ( * args )
[ -0.8597562909126282, 0.13990440964698792, 0.1430703103542328, -0.7584575414657593, -0.6933656930923462, 0.14821948111057281, -0.26538440585136414, -0.30249854922294617, -0.3625364899635315, -0.2247476875782013, -0.0012174774892628193, 0.05378182977437973, -0.48254579305648804, 0.5846617817...
def cleanse _ dataframe ( df : pd. dataframe, axis : list = none ) - > pd. dataframe : # check if axis has been specified if axis is none : axis = [ 0, 1 ] # clean rows if 0 in axis : df = df. dropna ( axis = 0, how ='all') # clean columns if 1 in axis : df = df. dropna ( axis = 1, how ='all') # return return df
[ -0.026179000735282898, 0.2608654201030731, 0.5817921161651611, 1.0508816242218018, -0.2760402262210846, -0.12040442228317261, 0.596544623374939, 0.6085329055786133, -0.011907667852938175, 0.19463728368282318, 0.21090799570083618, 0.6796841025352478, 0.36188217997550964, 0.39508217573165894...
def getnodesathops _ pneanet ( * args ) : return _ snap. getnodesathops _ pneanet ( * args )
[ -1.4714897871017456, 0.7646479606628418, 0.5098288059234619, 0.32540830969810486, 0.6901171207427979, 0.2704315781593323, 0.15435267984867096, -1.1964421272277832, -0.49643853306770325, -0.4728555679321289, -0.1299711912870407, -1.736228346824646, 0.13689877092838287, 0.16345898807048798, ...
def splitonallch ( self, * args ) : return _ snap. tstr _ splitonallch ( self, * args )
[ -0.2401627153158188, 0.15826928615570068, 0.2576788663864136, -0.09140971302986145, -0.289649099111557, -0.14297452569007874, 0.7692712545394897, 0.18836456537246704, -0.4762129485607147, 0.18480190634727478, -0.5508825778961182, -0.3190299868583679, 0.27406027913093567, 0.3947236835956573...
def getintattrinddatn ( self, * args ) : return _ snap. pneanetmp _ getintattrinddatn ( self, * args )
[ -1.0812853574752808, -0.5843749046325684, 0.5065653920173645, 0.11800070106983185, 0.43552201986312866, 0.7366085648536682, 0.3348551094532013, -0.7136483788490295, -0.9739857912063599, -1.1396732330322266, -0.335537850856781, -0.035022296011447906, -1.4813750982284546, 0.5386450886726379,...
def simplify _ geojson ( self, tol = 0. 001, buf = 0. 002 ) : for i, r in enumerate ( self. region ) : simplified _ poly = r. simplify ( tol, preserve _ topology = false ). buffer ( buf ) self. simplified _ geojson [ i ] ['geometry'] = mapping ( simplified _ poly )
[ 0.06030973047018051, -0.41819581389427185, 0.4148183763027191, -0.7097880840301514, -0.6584274172782898, 0.5257417559623718, 0.46028757095336914, -0.09575539827346802, 0.4490121006965637, -0.2024293690919876, -1.7281057834625244, -0.12693555653095245, 0.5406706929206848, -0.506253957748413...
def time _ indication ( df _ option, time _ string ) : # check if the dataframe is defined df _ option. check _ type ( pd. core. frame. dataframe, inspect. stack ( ) [ 0 ] [ 3 ] ) df = df _ option. get ( ) # add the attribute'details'if df does not have it if not hasattr ( df,'details') : df = misc _ func. details _ in...
[ -0.20348595082759857, 0.7535786032676697, 0.4653991162776947, -0.8464376926422119, 1.0807228088378906, -0.8373482823371887, -0.21983850002288818, 0.2716226875782013, -0.4001369774341583, 0.6747642755508423, 0.3084539473056793, 0.17875085771083832, 0.14328309893608093, 0.22358928620815277, ...
def size _ min ( self ) : return int ( self. get ('size _ min') )
[ 0.18541082739830017, -0.09313645213842392, 0.17038674652576447, 0.262696236371994, 0.40553924441337585, 0.5555004477500916, -0.03575040400028229, -0.8783602118492126, 0.6415312886238098, -0.9787575006484985, -0.11897852271795273, -0.3084692358970642, -0.34494784474372864, -0.36467024683952...
def mt _ caption _ eval _ collate ( data ) : # separate source and target sequences src _ sent, att _ feats, img _ masks, box _ feats, img _ ids = list ( zip ( * data ) ) # t2i def generate _ inputs ( ) : # sent = np. array ( sent ) x _ img = torch. stack ( att _ feats, dim = 0 ) img _ loc = torch. stack ( box _ feats,...
[ -0.6351207494735718, -0.891373872756958, 0.9554938077926636, -0.4859411418437958, -0.5567559599876404, -0.3843420445919037, 0.18633870780467987, -0.2992582619190216, -0.24633608758449554, 0.7093008160591125, -0.1537618190050125, -0.31854331493377686, 0.726681649684906, 0.48944520950317383,...
def positive _ pa ( pa : float ) : # require it be positive if pa < 0. : pa + = 360. # now the complement - - also require it be positive comp _ pa = pa - 180. if pa > 180. else pa + 180. # return return pa, comp _ pa
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def bsort ( self, * args ) : return _ snap. tintprv _ bsort ( self, * args )
[ -1.082282304763794, 0.1827356070280075, 0.6267117261886597, 0.8699444532394409, 0.018359694629907608, -0.19451096653938293, 0.2795155942440033, -0.644092321395874, -1.3288170099258423, -0.6673203706741333, -0.35665038228034973, 0.8142019510269165, -2.5034570693969727, 0.7234699726104736, ...
def ttable _ load ( * args ) : return _ snap. ttable _ load ( * args )
[ -1.639811396598816, 0.7418199181556702, 0.5537433624267578, 0.16041326522827148, -0.2924361824989319, 0.291408509016037, 0.6786358952522278, -0.6858587265014648, -1.3122243881225586, 0.8851638436317444, -0.8871635794639587, -1.4115638732910156, 0.007604449987411499, -0.17723380029201508, ...
def check _ if _ identifier _ exists ( self, native _ identifier _ sid ) : checkexistsdict = { } try : sys _ meta = self. client. getsystemmetadata ( native _ identifier _ sid ) except d1 _ common. types. exceptions. notfound : checkexistsdict ['outcome'] ='no'return checkexistsdict except exception, e : logging. error...
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def matrix2sheet ( self, float _ row, float _ col ) : xoffset = float _ col * self. _ _ xstep if isinstance ( self. lbrt [ 0 ], datetime _ types ) : xoffset = np. timedelta64 ( int ( round ( xoffset ) ), self. _ time _ unit ) x = self. lbrt [ 0 ] + xoffset yoffset = float _ row * self. _ _ ystep if isinstance ( self. l...
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def getimageforindex ( self, index : int ) - > optional [ str ] : if len ( self. _ overlayimages ) > index > = 0 : return self. _ overlayimages [ index ] else : return none
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def test _ can _ retrieve _ blocked _ community _ staff _ post ( self ) : user = make _ user ( ) community _ owner = make _ user ( ) community = make _ community ( creator = community _ owner ) headers = make _ authentication _ headers _ for _ user ( user ) post = community _ owner. create _ community _ post ( text = m...
[ 1.185163974761963, 0.6106938719749451, 0.5508681535720825, 1.0330439805984497, 0.4822149872779846, 0.5221717953681946, 0.20756317675113678, -1.0318045616149902, -1.0658037662506104, -0.8719781637191772, -0.5623921751976013, -0.3562979996204376, -0.44887787103652954, -0.2849610149860382, ...
def _ get _ dataid ( self, * args, * * kwargs ) : raise notimplementederror
[ -0.171683669090271, 0.11946148425340652, 0.24396809935569763, -0.524129331111908, -0.08588089048862457, 0.9562587141990662, -0.352741003036499, 0.034121811389923096, -0.006647799629718065, -0.22098782658576965, -0.36417776346206665, 1.184865951538086, 0.262783944606781, 0.5932751893997192,...
def _ _ init _ _ ( self, * args ) : _ snap. tuint64hi _ swiginit ( self, _ snap. new _ tuint64hi ( * args ) )
[ -0.5849996209144592, 0.5873690247535706, -0.12418104708194733, 1.3018927574157715, -0.22412677109241486, 0.08568526059389114, 0.030433623120188713, 0.6274497509002686, -1.8336808681488037, 0.1649780422449112, -0.21316753327846527, -1.388572335243225, -0.2534187436103821, 0.2075498849153518...
def merge _ sort ( _ list, begin, end ) : if begin < end : middle = divmod ( ( begin + end ), 2 ) [ 0 ] merge _ sort ( _ list, begin, middle ) merge _ sort ( _ list, middle + 1, end ) merge ( _ list, begin, middle, end )
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def _ _ str _ _ ( self ) : return self. simbolo
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def set _ logger _ config ( logger : logging. logger, main _ python _ file _ name : str, level : int = logging. info, format : str = " % ( asctime ) s - % ( name ) s - % ( levelname ) s - % ( message ) s ", log _ dir : optional [ str ] = none, ) : main _ python _ file _ name _ root = get _ file _ name _ root ( main _ p...
[ -0.17058177292346954, -1.2080261707305908, 0.7328284978866577, -0.6617177128791809, -0.06873912364244461, 0.23100613057613373, -0.3040338456630707, 0.7508749961853027, -0.9656221270561218, -0.4632595181465149, -0.23537331819534302, 0.11597415804862976, 0.4225766956806183, 1.514214277267456...
def select _ playlist ( ) : default = os. listdir ( ) print ( " enter the playlist you want to play : \ n " ) print ( " 0 : default playlist ( all songs ) \ n " ) print ( " 1 : current playlist \ n " ) print ( " 2 : favourite playlist \ n " ) lst _ id = int ( input ( " enter the id of the playlist to play : " ) ) if ls...
[ -0.20004478096961975, -0.01439972035586834, 0.42477694153785706, 0.5420038104057312, 0.4998075067996979, 0.24052594602108002, 1.1005609035491943, -0.4608128070831299, 0.9158331155776978, -0.05708561837673187, -0.5110180974006653, 0.35060814023017883, -1.1453568935394287, -0.035823859274387...
def compute _ voi _ volume ( self, mode ='mb') : if mode = ='mb': return self. _ _ voi _ mb. sum ( ) * self. _ _ res _ 3 * nm3 _ to _ um3 elif mode = ='lm': return self. _ _ voi _ lm. sum ( ) * self. _ _ res _ 3 * nm3 _ to _ um3 elif mode = ='mb - lm': return ( self. _ _ voi _ mb. sum ( ) + self. _ _ voi _ lm. sum ( ) ...
[ -0.4753064513206482, 0.029587341472506523, 0.7504295706748962, 0.2550208866596222, -0.3250049352645874, 0.3538452088832855, 0.2078561931848526, -0.03288780897855759, 0.30986008048057556, 0.25434979796409607, -0.16424840688705444, -0.7753728032112122, -0.8887475728988647, -0.255762726068496...
def get _ img _ item ( self, file _ name, image _ id, size ) : image = ordereddict ( ) image ['file _ name'] = file _ name image ['height'] = int ( size ['height'] ) image ['width'] = int ( size ['width'] ) image ['id'] = image _ id return image
[ -0.3261982202529907, -0.3071475028991699, 0.2360551655292511, -0.6478925943374634, -0.46791213750839233, -0.3817947804927826, -1.511562705039978, -0.038999173790216446, -1.3435280323028564, 0.3255003094673157, -0.41246601939201355, -0.15376324951648712, 0.37393563985824585, -0.100143596529...
def sesames ( self ) : response = self. request ('get ', api _ sesame _ list _ endpoint ) if response is not none and response. status _ code = = 200 : return json. loads ( response. text ) ['sesames'] indigo. server. log ( message = " unable to get sesames ", iserror = true ) return [ ]
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def get _ data ( nrows = 10000, local = false, optimize = false, * * kwargs ) : # add client ( ) here client = storage. client ( ) if local : path = " data / data _ data _ 10mill. csv " else : path = " gs : / / { } / { } ". format ( bucket _ name, bucket _ train _ data _ path ) df = pd. read _ csv ( path, nrows = nrows...
[ -0.07433988898992538, 0.9956443309783936, 0.4400670528411865, 0.44339483976364136, 0.656342089176178, 0.15570135414600372, -0.14577335119247437, -0.004339610226452351, -0.933513343334198, -0.5320061445236206, -0.2903400659561157, 1.0779019594192505, -0.26354700326919556, -1.084525108337402...
def pair _ store ( store, fname, pairs ) : from itertools import combinations as comb totals = 10 * pairs print " pairing on store ", store print " positive pairs / negative pairs ", totals, totals store = get _ store ( fname = store ) inpts = store ['inpts'] lbls = store ['trgts'] positives = [ ] classes = { } # stl -...
[ -1.4381613731384277, -0.2765952944755554, 0.9547983407974243, -0.23828843235969543, -0.19341827929019928, 0.6649181842803955, 0.513393759727478, -0.03806717321276665, 0.3959016799926758, 0.3614148199558258, 0.27151793241500854, -0.5699235796928406, 0.4952622652053833, 0.28461650013923645, ...
def handleevent ( self, event ) : self. sprite. handle _ event ( event )
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def on _ clockwise _ rotate ( self ) : if not self. edit _ mode : self. curr _ action = ( self. curr _ action + 1 ) % self. len else : self. inc _ val ( ) self. update _ screen ( )
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def _ compute _ dqn _ loss ( self, samples : dict [ str, np. ndarray ], gamma : float = 0. 99 ) - > torch. tensor : gamma = self. gamma device = self. device state = torch. floattensor ( samples [ " obs " ] ). to ( device ) next _ state = torch. floattensor ( samples [ " next _ obs " ] ). to ( device ) action = torch. ...
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def compose ( self, other _ fst, new _ fst _ base ) : other _ fst. sort ( how = " ilabel " ) call = " fstcompose % s % s % s. fst " % ( self. fst _ fn, other _ fst. fst _ fn, new _ fst _ base ) subprocess. call ( [ call ], shell = true ) # postprocess new fst new _ fst = fst ( new _ fst _ base ) new _ fst. isymbols _ f...
[ -0.4815851151943207, -1.1466825008392334, 0.7540604472160339, -0.08901165425777435, -0.1244191899895668, -0.9553865790367126, -0.4249890446662903, -0.40919387340545654, -0.28129106760025024, -0.6412983536720276, -0.6529502868652344, -0.0560118742287159, -0.43483608961105347, 0.294568568468...
def _ _ getitem _ _ ( self, key ) : if self. households. has _ key ( key ) : return self. households [ key ] else : return none
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def extract _ pano _ neural _ features ( nfov _ projector, im _ processor, pano _ np, heading _ angles, pitch _ angles ) : pano _ image _ features = [ ] for pitch in pitch _ angles : pitch _ features = [ ] for heading in heading _ angles : # normalize heading and pitch to [ 0, 1 ] interval. center _ point = np. array (...
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def _ _ gt _ _ ( self, other ) : if isinstance ( other, ( int, float ) ) : return np. greater ( self. val, other ) elif isinstance ( other, reverse ) : return np. greater ( self. val, other. val ) else : raise typeerror ( " please only compare reverse object with another reverse object or int or float. " )
[ -0.993407130241394, 0.0705837681889534, 0.9638371467590332, 0.39224880933761597, 0.18432942032814026, 0.6458092927932739, -0.4301888048648834, -1.319040298461914, -0.5778529644012451, -0.32972627878189087, 0.57157963514328, 0.8099512457847595, 0.0011606552870944142, 0.35707470774650574, ...
def write _ file ( text = " " ) : while ( true ) : print ( " \ t \ t \ t | - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - | " ) print ( " \ t \ t \ t | proceed file writing? | " ) print ( " \ t \ t \ t | yes ( y ) or no ( n ) | " ) print ( " \ t \ t \ t | - - - - - - - - - - - - - - - - - -...
[ 0.1556219905614853, 0.05610194429755211, 1.2705446481704712, 0.13113462924957275, -0.5091107487678528, 0.6939550638198853, 0.28582414984703064, -0.6041604280471802, -0.9081333875656128, 0.08452962338924408, -0.5662624835968018, -0.22544072568416595, -1.2291632890701294, 0.3859136998653412,...
def add ( self, card ) : self. cards. append ( card )
[ -0.7995613813400269, -0.10602670907974243, 0.186562180519104, -0.5522255897521973, 0.8112101554870605, 1.0481081008911133, -1.2576475143432617, 0.6324520111083984, 0.7538213133811951, -0.7631750106811523, -0.08997277915477753, 0.679291307926178, -0.009344658814370632, 0.8066788911819458, ...
def get _ selection _ values _ using _ baseline ( self, output _ filepath = none, temp _ data _ dirpath = none, group _ sel _ stats = false ) : if temp _ data _ dirpath = = none and output _ filepath = = none : print'both " temp _ data _ dirpath " and " output _ filepath " cannont equal none. aborting'return if not tem...
[ -0.48420199751853943, -0.5225074887275696, 1.0586131811141968, 0.2609477937221527, 0.03255134075880051, -0.15849357843399048, 0.5997519493103027, 0.03301733359694481, -0.6177964210510254, 0.2011076956987381, -0.052912306040525436, 0.5424686074256897, -0.1918545812368393, 0.3918447494506836...
def dom _ timestamp ( ts ) : k = list ( ) mon = - 1 doy = - 1 dom = 0 for t in ts : m = t. month if mon! = m : dom = 1 doy = t. dayofyear mon = m elif t. dayofyear! = doy : dom + = 1 doy = t. dayofyear k. append ( dom ) return np. array ( k )
[ -1.2874233722686768, -0.205396831035614, 1.036622166633606, 0.5876578688621521, 0.12848760187625885, 0.1539163440465927, 0.1747402399778366, 0.3299829661846161, 1.3452868461608887, 0.2818218469619751, -0.3363153338432312, -0.057977065443992615, 1.1261990070343018, 0.029540935531258583, -...
def discover _ structure ( self, sequences ) : _, _, event _ sequences = self. create _ ordered _ event _ sequences ( sequences ) event _ sequences, nodes = self. number _ event _ sequences ( event _ sequences ) self. data = self. get _ datastructure ( event _ sequences ) edges = self. discover _ structure _ from _ sta...
[ -0.2458612471818924, -0.11842341721057892, 0.36897891759872437, -0.37519359588623047, -0.06592005491256714, -1.0762286186218262, 0.4717022180557251, -0.6749913096427917, 0.7781364917755127, -0.23067356646060944, -0.23983825743198395, 0.16623114049434662, 0.4653494358062744, 0.2293843924999...
def handler ( self, f ) : self. add _ handler ( f, type ='all') return f
[ -0.035958196967840195, -0.1853727102279663, 0.466983437538147, 0.5877752900123596, -0.34648454189300537, 0.5628852248191833, -0.11554031819105148, 0.9375190138816833, 0.11064291000366211, -1.5901751518249512, -0.12145974487066269, 0.03265560790896416, 0.41937944293022156, 0.343434482812881...
def is _ boostworthy ( mastodon, post ) : relations = mastodon. account _ relationships ( post. account. id ) for r in relations : if r. id = = post. account. id and r. following and not post. reblogged : return true return false
[ 1.7014267444610596, 0.46051713824272156, 0.5709035396575928, 1.2115956544876099, -0.026373663917183876, 0.2821783721446991, -0.028420714661478996, -0.8960838317871094, 0.3268314301967621, -0.08301524072885513, -0.6320205926895142, 0.4950594902038574, -0.6875530481338501, 0.9317034482955933...
def put ( self, request ) : { { cookiecutter. panel } } = client. { { cookiecutter. panel } } _ create ( request, * * request. data ) return rest _ utils. createdresponse ('/ api / { { cookiecutter. api _ module } } / { { cookiecutter. panel } } / % s'% { { cookiecutter. panel } }. uuid, { { cookiecutter. panel } }. to...
[ -1.7847872972488403, -0.5051576495170593, 0.3927362859249115, -0.6842857599258423, 0.2240191251039505, -0.21711426973342896, 0.11842723190784454, 0.08811882138252258, -0.2842605412006378, 1.175331950187683, -0.8269618153572083, 0.7859018445014954, -1.3539609909057617, -0.560089111328125, ...
def seturl ( self, url ) : self. _ url = url
[ -0.3926209807395935, 0.2837112843990326, 0.037243619561195374, 0.12903963029384613, 0.0680348351597786, 1.0118250846862793, 0.19453169405460358, 0.8870110511779785, -0.1549759954214096, -0.13135921955108643, -1.1859534978866577, 0.46722227334976196, -0.39784693717956543, 0.592373788356781,...
def tstrhashf _ djb _ getprimhashcd ( * args ) : return _ snap. tstrhashf _ djb _ getprimhashcd ( * args )
[ 1.2811059951782227, 0.44613945484161377, 0.3353944718837738, 0.09492886811494827, -0.3813420236110687, 0.5574641823768616, 0.06489057093858719, 0.7570019364356995, -0.24908564984798431, -0.6357608437538147, 0.2180316299200058, -0.4823604226112366, -0.6056626439094543, -0.2500058114528656, ...
def test _ remove _ stop _ words _ no _ stop _ words ( self ) : expected = ['token1 ','token2'] actual = remove _ stop _ words ( ['token1 ','token2'], [ ] ) self. assertequal ( expected, actual )
[ -0.9253298044204712, -0.1268700808286667, 0.39727532863616943, 0.33910298347473145, 0.1029408872127533, 0.14199259877204895, -0.8743605613708496, 0.7908583283424377, -0.7254443168640137, 0.30070385336875916, -1.3447240591049194, -0.2897610366344452, -0.6627888083457947, -0.0451212823390960...
def teardown ( self ) : with self. app. app _ context ( ) : classic. drop _ all ( )
[ 0.7084092497825623, -0.05195803567767143, 0.4703110158443451, 0.6501502394676208, 1.0343940258026123, 1.395060420036316, 0.5088305473327637, -0.40635010600090027, 0.4575634002685547, 0.46498164534568787, 0.2666095197200775, 0.12260191142559052, 0.0963134765625, 0.03943895921111107, -0.43...
def vgg11 _ bn _ imagenet ( pretrained = false, * * kwargs ) : model = vgg _ imagenet ( make _ layers ( cfg _ imagenet ['a'], batch _ norm = true ), * * kwargs ) if pretrained : model. load _ state _ dict ( model _ zoo. load _ url ( model _ urls ['vgg11 _ bn'] ) ) return model
[ -0.3884138762950897, 0.2752252519130707, 0.4168287217617035, 0.9899107813835144, 0.1550656110048294, 0.3111552596092224, 0.22282841801643372, 0.46750932931900024, -0.1775044947862625, 0.4655234217643738, -0.1443643569946289, 0.054566215723752975, -0.16060152649879456, 0.3320540189743042, ...
def make _ stems ( ) : x = numpy. zeros ( [ 2, self. peaks. mz. size ], dtype = " float " ) y = numpy. zeros ( x. shape ) x [ :, : ] = numpy. tile ( self. peaks. mz, ( 2, 1 ) ) y [ 1, : ] = self. peaks. intensities return x, y
[ 0.07006891816854477, -0.050801780074834824, 0.46275123953819275, -0.48881256580352783, 0.06067409738898277, -0.07665331661701202, 0.39997124671936035, -0.17510032653808594, 0.21902650594711304, 0.26237303018569946, -0.5107300281524658, 0.16133961081504822, 0.613166093826294, -0.41476202011...
def match ( self, text ) : results = [ ] for pattern in self. pattern _ action : res = pattern. search ( text ) if res : data = { } # create keyword arguments starting with the defaults. # deep copy is used here to avoid exposing the reference # outside the match function. data. update ( copy. deepcopy ( self. pattern ...
[ 0.13436093926429749, 0.11888442933559418, 0.5184676647186279, -0.017802180722355843, -0.16503699123859406, -0.4221656024456024, -0.1445915699005127, 0.20486727356910706, -0.10120998322963715, 0.3746028244495392, -0.34519162774086, 0.0851336345076561, -0.48628106713294983, 0.182427212595939...
def is _ auto _ enabled ( * args ) : return _ ida _ auto. is _ auto _ enabled ( * args )
[ -0.8255597352981567, 0.20734992623329163, 0.18226909637451172, 1.2451074123382568, 0.831453263759613, -0.7912043333053589, 0.6624905467033386, 0.2670058310031891, -0.6827592849731445, -0.2922618091106415, -1.525208830833435, 0.12045079469680786, -0.8615737557411194, -0.044246040284633636, ...
def subtitles _ preprocessing ( args ) : subs = pysrt. open ( args. subtitles, encoding ='iso - 8859 - 1') subs _ text = [ ] subs _ time = [ ] for sub in subs : sub _ string = str ( sub ) sub _ time = sub _ string. split ('\ n') [ 1 ] sub _ text = sub _ string. split ('\ n') [ 2 ] subs _ text. append ( tokenizer ( sub ...
[ -0.34526267647743225, -0.7965526580810547, 0.626342236995697, -0.13716286420822144, -0.7877886891365051, -0.6626390814781189, -1.0222827196121216, 0.9371638894081116, -0.44697949290275574, 0.7095112204551697, -0.624315083026886, 0.27443191409111023, 0.2608850300312042, 0.6625679135322571, ...
def _ decode _ iq _ item ( self, encoded ) : try : item _ decoded = json. loads ( encoded. decode ( self. encoding ) ) except ( unicodedecodeerror, valueerror ) as exc : raise valueerror ( exc ) from exc if not isinstance ( item _ decoded, list ) or len ( item _ decoded )! = 2 : raise valueerror ( " must be an array of...
[ -0.9811173677444458, -1.2482070922851562, 0.6599611043930054, -1.0234650373458862, -0.3711884617805481, -0.34460026025772095, -0.3392939269542694, 0.03302416950464249, 0.7266845703125, -0.026669980958104134, -0.6941985487937927, 0.6289660930633545, -0.44874459505081177, -1.1354976892471313...
def getuploadpath ( self ) : return self. _ _ swift. getuploadpath ( )
[ -0.2513127028942108, 0.116964191198349, 0.6680271625518799, 0.500117301940918, 0.5481832027435303, 0.7071518898010254, 0.7749305367469788, -0.15329240262508392, -0.8175421357154846, 0.01928994245827198, 0.493004709482193, 0.01320120319724083, -1.4297561645507812, 0.2710113525390625, 0.37...
def test _ initial ( self ) : field = omnifloatfield. _ meta. get _ field ('initial _ data') self. assertisinstance ( field, models. floatfield ) self. asserttrue ( field. blank ) self. asserttrue ( field. null )
[ 0.9861160516738892, 0.4906168282032013, 0.3631606996059418, -0.2033918797969818, 1.122572898864746, 1.090872049331665, 0.05651208013296127, 0.21673808991909027, 0.2885809540748596, -0.8205670714378357, -0.5965307950973511, 0.03787428140640259, -0.17295531928539276, 0.7151222825050354, -0...
def is _ equal ( array1, array2 ) : assert array1. size = = array2. size return all ( array2 = = array1 )
[ 0.09262736886739731, -0.4941502809524536, 0.5879759192466736, 1.290008306503296, 0.6579257845878601, 0.6052002310752869, -0.8598311543464661, -0.2819255590438843, 0.4728180170059204, 0.853835940361023, -0.8978198766708374, 1.32619309425354, -0.49223068356513977, 0.4981643259525299, 0.075...
def dipolar ( cls, spin _ particle1, spin _ particle2, dipolar _ matrix ) : return cls. mkh2 ( spin _ particle1, spin _ particle2, dipolar _ matrix )
[ 0.31307244300842285, -0.5797020196914673, 0.3587910234928131, 0.35259026288986206, -0.8019453883171082, 0.6797807216644287, -1.3032125234603882, 0.36517977714538574, -0.7276999354362488, 0.05280766636133194, -0.011125301942229271, 0.21313215792179108, -0.33115944266319275, -0.9944955706596...
def _ _ average _ matrix ( self ) : transitionmatrices = self. get _ matrices ( ) n = len ( transitionmatrices ) centroidmatrix = np. zeros ( transitionmatrices [ 0 ]. shape ) for tm in transitionmatrices : centroidmatrix + = tm centroidmatrix / = n return centroidmatrix
[ -0.4471430778503418, -0.5958088636398315, 0.3231155276298523, -0.2565684914588928, 0.09585236012935638, -0.06237746402621269, 0.7046236991882324, 0.30963483452796936, 0.16223466396331787, 0.9592744708061218, 0.4791232645511627, -0.0792718157172203, -0.42981499433517456, 0.5470291972160339,...
def can _ archive _ forum ( self, forum, user ) : return self. _ perform _ basic _ permission _ check ( forum, user, " can _ archive _ forum " )
[ -0.5009323954582214, 0.3739926815032959, 0.36941981315612793, 1.986045002937317, -0.5366425514221191, -0.19967572391033173, 0.18033578991889954, 0.4133162200450897, -0.6271293759346008, -0.04821782186627388, -0.18304355442523956, 0.9896286129951477, -0.933262288570404, 0.37885817885398865,...
def test _ intuit ( inp, fmt, exp ) : pytest. debug _ func ( ) later = nldt. moment ( inp, itz ='local') # payload assert later ( fmt ) = = exp
[ -0.033512238413095474, -0.6659209728240967, 0.19429032504558563, -0.20569466054439545, 0.3190404176712036, 0.9771811366081238, -0.460440456867218, -0.13463249802589417, -0.046266116201877594, -0.9639990329742432, -0.17908471822738647, -0.0997728630900383, -0.6970895528793335, 0.75515639781...
def addedge ( self, * args ) : return _ snap. pungraph _ addedge ( self, * args )
[ -1.043656826019287, 1.09444260597229, 0.29731905460357666, 1.1897729635238647, 0.8054175972938538, 0.2516390085220337, 0.41837745904922485, 0.6921719312667847, 0.12145230174064636, -1.0321526527404785, -0.47824329137802124, -0.9612371921539307, -1.993378758430481, 0.6204172968864441, 0.7...
def count ( self, * args ) : return _ snap. tcncomv _ count ( self, * args )
[ -0.24434682726860046, 0.2694995701313019, 0.31105467677116394, -0.4903554618358612, 1.051897644996643, -0.10657006502151489, 0.9026527404785156, 0.14595508575439453, -1.0420368909835815, -0.09808269888162613, -0.673768162727356, -1.2224955558776855, 0.024576663970947266, 1.3593946695327759...
def temperature _ smooth ( sampling _ probs, temperature ) : if not isinstance ( sampling _ probs, np. ndarray ) : raise typeerror ( " sampling _ probs must be numpy array. " ) if temperature < = 0 : raise valueerror ( " temperature must be positive. " ) if not np. isfinite ( temperature ) : raise valueerror ( " temper...
[ 0.3366714417934418, -0.6204892992973328, 0.5076216459274292, 0.4698685109615326, -1.0503689050674438, 0.5284011960029602, 0.04015407711267471, 0.1867281049489975, 0.08021657913923264, 1.6223269701004028, 0.5978641510009766, 0.01593310758471489, -0.4682757556438446, -0.4314936101436615, -...
def _ test _ run _ tests _ 2 ( self ) : # todo test disabled until testrunner _ command can be injected to mock _ executor testrunner _ command ='sh - c " exit 1 "'executor = mock _ executor ( self. testrun, self. stand _ alone, self. responseclient, " hostname ", testrunner _ command ) executor. target = stub _ hardwa...
[ -0.24740789830684662, 0.4156130254268646, 0.5997952222824097, 0.4457876682281494, 1.2508108615875244, 0.34377509355545044, 1.4079614877700806, 0.5891900658607483, -0.39604899287223816, -0.7716967463493347, -0.5800833106040955, -0.5193184018135071, -0.111053965985775, 0.7890908122062683, ...
def load _ form ( self, req : flask. request, schema : ma. schema ) - > typing. any : return self. _ makeproxy ( req. form, schema )
[ -0.7084782719612122, 0.42034319043159485, 0.5581122636795044, -0.20928899943828583, -0.41442185640335083, -0.2778312563896179, -0.640408992767334, 0.21588881313800812, 0.13996601104736328, -1.047421932220459, -0.16499003767967224, -0.29430800676345825, -0.560648500919342, 0.221621066331863...
def test _ retrieves _ follower _ by _ name ( self ) : user = make _ user ( ) headers = make _ authentication _ headers _ for _ user ( user ) post _ creator = make _ user ( ) post = post _ creator. create _ public _ post ( text = make _ fake _ post _ text ( ) ) follower = make _ user ( ) follower. follow _ user ( user ...
[ 0.47030991315841675, 0.12283031642436981, 0.6245498061180115, 0.6061188578605652, 0.022702788934111595, 0.40650537610054016, -0.1179104670882225, -0.8937968015670776, -0.1956474930047989, -0.7160177826881409, -1.6206061840057373, -0.5761791467666626, -0.7519320249557495, 0.1136928945779800...
def validate _ zone _ soa ( domain, master _ domain ) : if not domain : raise exception ( " you called this function wrong " ) if not domain. soa : return zone _ domains = domain. soa. domain _ set. all ( ) root _ domain = find _ root _ domain ( domain. soa ) if not root _ domain : # no one is using this domain. return...
[ 0.09595529735088348, -0.42259034514427185, 0.39572760462760925, 0.39133256673812866, 0.035147152841091156, -0.6499475836753845, 1.4470492601394653, 0.19743618369102478, 0.8239021301269531, -0.06363129615783691, 1.142436146736145, 1.216771125793457, 0.1892360895872116, 0.878646194934845, ...
def fetch ( self ) : r = requests. get ( f'{ self. fetch _ url }? login _ challenge = { self. challenge _ id } ', timeout = self. timeout ) r. raise _ for _ status ( ) fetched _ data = r. json ( ) return fetched _ data ['subject'] if fetched _ data ['skip'] else none
[ -0.27315112948417664, 0.11521060764789581, 0.500629186630249, 0.16778014600276947, -1.0117055177688599, -0.0078066326677799225, -1.17637038230896, -1.2934651374816895, 0.4875113368034363, 0.2380554974079132, 0.18984389305114746, 0.572235107421875, -0.17096452414989471, -0.702511727809906, ...
def simulate _ psdf _ cython ( ) : # input # norm = sim _ input ['norm'] dt = sim _ input ['dt'] psdpar = sim _ input ['psdpar'] inorm = 0 if norm = ='var'else 1 if norm = ='leahy'else 2 sims = [ ] for isim in range ( 1, args. nsim + 1 ) : az. misc. print _ progress ( isim, args. nsim + 1, isim = = args. nsim ) # simul...
[ 0.32197317481040955, 0.5214231014251709, 0.8844561576843262, -0.42757657170295715, 0.12621372938156128, -0.04628521203994751, 0.25692909955978394, -0.5713031888008118, -0.36432182788848877, -0.4352761507034302, 0.09535159170627594, 0.11209956556558609, -0.3888669013977051, 0.49672016501426...
def loadconnlist _ pneanet ( * args ) : return _ snap. loadconnlist _ pneanet ( * args )
[ -2.1220452785491943, 0.10435063391923904, 0.384558767080307, 0.7773774862289429, -0.010411511175334454, -0.5489507913589478, -1.1473886966705322, -0.3037254810333252, -0.23918047547340393, -0.2864781618118286, -1.3165898323059082, -1.204298973083496, -0.6217820048332214, 0.4630635976791382...
def banner ( message, border ='*') : # print ( " enter a string " ) # response = input ( ) # take user input print ( border * len ( message ) ) print ( message ) print ( border * len ( message ) )
[ 1.028315544128418, 0.12589994072914124, 0.4340284764766693, 1.3987747430801392, -0.49337467551231384, 1.0980308055877686, 0.8579003810882568, -0.6758884787559509, 0.1744442880153656, -1.336527705192566, -1.0413256883621216, 0.7533619999885559, -1.509348750114441, 0.6312657594680786, 0.87...
def identity _ map ( cls, train _ track ) : # todo rewrite this tt = train _ track max _ num _ branches = tt. num _ branches _ if _ made _ trivalent ( ) assert len ( tt. branches ( ) ) < = max _ num _ branches # identity array of arbitrary - precision python ints. # keep in mind that we fill in ones also in the rows th...
[ -0.7564742565155029, -0.17191287875175476, 0.9782576560974121, -0.009277280420064926, 0.25108015537261963, 0.5076171159744263, 1.1551880836486816, -0.3067876696586609, -0.38105881214141846, 0.42784640192985535, -0.2480224221944809, -1.014677882194519, 0.3841797709465027, -0.399728417396545...
def fetch _ gevent ( url ) : try : result = urllib2. urlopen ( url ). read ( ) return except urllib2. httperror as e : if e. code = = 404 : logging. info ( " not fund " ) return url else : logging. warn ( " could not fetch the url % s " % url ) return'error '
[ -0.39191821217536926, -0.057292476296424866, 0.6092641353607178, -0.004396356176584959, -0.1327461302280426, 0.6407010555267334, -0.434635728597641, 0.20290718972682953, 0.20944200456142426, 0.09440808743238449, 0.5421871542930603, 0.14148615300655365, 0.1087435781955719, 0.133780911564826...
def test _ get _ form _ class _ name ( self ) : self. assertequal ('omniformtestmodel ', self. omniform. _ get _ form _ class _ name ( ) )
[ -0.14911794662475586, -0.524219810962677, 0.13503067195415497, 0.5930060744285583, 0.48887500166893005, 0.37587884068489075, -0.20177625119686127, -0.25532057881355286, 0.6445927023887634, -0.9474717974662781, -1.0480576753616333, -1.0082731246948242, 0.5337642431259155, 0.6690866351127625...
def breadthfirstsearch ( graph, root ) : # nodes we've visited. visited = set ( ) # nodes whose location we know, but we have yet to actually visit. queue = [ root ] while queue : next _ node = queue. pop ( ) if next _ node not in visited : visited. add ( next _ node ) queue. extend ( graph [ next _ node ] - visited ) ...
[ 0.11592181026935577, 0.7499045729637146, 0.5735609531402588, 0.3659922182559967, 0.17556054890155792, -1.0455585718154907, 0.029115205630660057, -0.38012781739234924, -0.23580968379974365, 0.10483722388744354, -0.007647242397069931, 1.3138031959533691, -0.3018985092639923, 0.00919368863105...
def buffered _ bounded _ lemire _ uint8 ( bitgen, rng, bcnt, buf ) : # note : ` rng ` should not be 0xff. when this happens ` rng _ excl ` becomes # zero. rng _ excl = uint8 ( rng ) + uint8 ( 1 ) assert ( rng! = 0xff ) # generate a scaled random number. n, bcnt, buf = buffered _ uint8 ( bitgen, bcnt, buf ) m = uint16 (...
[ 0.6378551721572876, -0.10250642150640488, 0.6344448924064636, -0.9702072143554688, -0.24393707513809204, 0.4154358506202698, -0.6012018322944641, 0.07600145787000656, 0.6527814269065857, -0.3913889527320862, -0.856676459312439, 0.3479149639606476, -0.5500614047050476, 0.017871350049972534,...
def is _ timeout ( ioerror ) : try : # all ioerrors returned by pyusb contain # msg, errno, and should be unpackable. err, msg = ioerror except valueerror : # but, sometimes we can't unpack. i don't # know what is raising theses ioerrors # just assume its a timeout, so operation # is retried return true else : return (...
[ -0.16769497096538544, 0.10253865271806717, 0.42953282594680786, 0.8033901453018188, -0.3642956614494324, -0.21550709009170532, -0.17981363832950592, 0.5001109838485718, 1.0747535228729248, 0.6000410914421082, 0.1563229262828827, -0.60692298412323, -0.5444984436035156, -0.5487959980964661, ...
def alpha _ shape ( points, alpha ) : if len ( points ) < 4 : # when you have a triangle, there is no sense # in computing an alpha shape. return multipoint ( list ( points ) ). convex _ hull def add _ edge ( edges, edge _ points, coords, i, j ) : " " " add a line between the i - th and j - th points, if not in the lis...
[ 0.5610959529876709, -0.2013963758945465, 0.8792493343353271, -0.19531814754009247, -0.08088657259941101, -0.1632407307624817, 0.49632325768470764, 1.1234252452850342, 0.9758037328720093, 0.8292503952980042, -0.14826522767543793, 0.40617796778678894, -0.24243700504302979, 0.0604401528835296...
def getpoissondev ( self, * args ) : return _ snap. trnd _ getpoissondev ( self, * args )
[ 0.20889131724834442, 0.7969833612442017, 0.45904067158699036, 0.3878760039806366, 1.0459095239639282, -0.04036784917116165, 0.8009564876556396, 0.12109769880771637, -1.0641095638275146, -1.563280701637268, -0.1669699102640152, 0.051110852509737015, -0.13631649315357208, 0.4622204303741455,...
def onsearchfieldchanged ( self ) : # add ". * " to enable partial matching if self. searchregexcheckbox. ischecked ( ) : regex = qregexp ( ". * " + self. searchlineedit. text ( ) + ". * ", qt. caseinsensitive ) else : regex = qregexp ( self. searchlineedit. text ( ), qt. caseinsensitive ) for model in ( self. newproxy...
[ -0.6340410113334656, -0.45314905047416687, 0.6452012658119202, 0.06331247091293335, 0.8363718390464783, 0.4426157772541046, 0.5477176904678345, 0.276767373085022, -0.5119534134864807, 0.4647555351257324, -0.8086305856704712, -0.004831723868846893, -0.531455934047699, 0.18340861797332764, ...
def make _ likes ( max _ likes, min _ likes ) : if isinstance ( max _ likes, str ) and max _ likes. isnumeric ( ) : max _ likes = int ( max _ likes ) if not isinstance ( max _ likes, int ) : print ('max _ likes user is not integer or exist') return if isinstance ( min _ likes, str ) and min _ likes. isnumeric ( ) : min...
[ -0.520995020866394, 0.34671202301979065, 0.6893095970153809, 0.47129493951797485, -0.10286401957273483, 1.4655269384384155, -0.2843054234981537, -0.39462777972221375, -0.4502040147781372, -0.28244832158088684, -0.2928936183452606, 0.839826226234436, -0.15407411754131317, 0.0776354521512985...
def social _ connectivity ( filename, n ) : connectivity _ graf = unionfind ( n ) timestamp = 0 if connectivity _ graf. components < = 1 : return timestamp with open ( filename ) as f : for row in f : timestamp, friend1, friend2 = row. split ( ", " ) friend1, friend2 = int ( friend1 ), int ( friend2 ) connectivity _ gr...
[ -0.37217193841934204, -0.22798098623752594, 0.4286891222000122, 0.46349576115608215, 0.24442337453365326, -0.1935921013355255, 0.5044997334480286, -0.059774674475193024, -0.4144167900085449, 0.36159661412239075, 0.4617801904678345, -1.1641526222229004, -0.7008830904960632, 0.11729050427675...
def spellcurrentitem ( self, itemstring ) : for character in itemstring : self. speakcharacter ( character )
[ -0.941925048828125, -1.924808144569397, 0.044808316975831985, -0.18256047368049622, 0.2671681046485901, 0.269538938999176, -0.06275976449251175, -0.023710209876298904, 0.5288826823234558, 0.4602165222167969, -0.0998712107539177, 0.1266789585351944, -1.0945649147033691, -0.8891955614089966,...
def get _ global _ link _ rpy ( self, link : str, q : arraytype ) - > casadiarraytype : return quaternion. fromvec ( self. get _ global _ link _ quaternion ( link, q ) ). getrpy ( )
[ -0.4809496998786926, -0.40974533557891846, 0.28247731924057007, -0.14982670545578003, 0.631418764591217, 0.09872789680957794, -0.30811697244644165, -0.7446541786193848, 0.5667228698730469, -0.0536016970872879, -0.01115352287888527, 1.6330114603042603, -1.266418218612671, -0.176106482744216...
def export _ stock _ in _ shopify ( self, instance, product _ ids ) : common _ log _ line _ obj = self. env [ " common. log. lines. ept " ] product _ obj = self. env [ " product. product " ] log _ line _ array = [ ] model = " shopify. product. product. ept " model _ id = common _ log _ line _ obj. get _ model _ id ( mo...
[ -1.2500754594802856, -0.49365440011024475, 0.8076101541519165, 0.270905077457428, 0.5653140544891357, 0.2667221426963806, 0.34958168864250183, -0.7527914643287659, 0.9135652780532837, 1.0784382820129395, -0.45681098103523254, 0.4851156175136566, 0.2144346833229065, 0.7248716950416565, -0...
def tokenize ( texts ) : max _ len = 512 splited _ texts = [ ] for text in texts : splited _ text = tokenizer. tokenize ( _ convert _ num _ half _ to _ full ( text. replace ('。 \ n ','\ n'). replace ('\ n ','。 \ n') ) ) if len ( splited _ text ) > ( max _ len - 2 ) : splited _ text = splited _ text [ : max _ len - 2 ] ...
[ -0.3729388117790222, -0.6044096350669861, 0.6892406940460205, 0.8982803225517273, -1.2320584058761597, -1.1889609098434448, -0.099822498857975, 0.7541357278823853, 0.2529798448085785, -0.276454359292984, -0.7229757308959961, -0.2025385946035385, -0.11519898474216461, 0.4826892614364624, ...
def to _ entity ( self, item ) : return self. session. query ( entity ) \. filter _ by ( url = item. url, c4 = item. c4 ) \. options ( joinedload ('meta') ) \. one ( )
[ -0.4386272728443146, -0.21761369705200195, 0.3230244815349579, -0.2325136959552765, 1.3388985395431519, -0.2532198429107666, 0.19794489443302155, -0.310089111328125, 1.032200813293457, -0.08832815289497375, -0.11873623728752136, -0.10341008007526398, 0.10532504320144653, -0.765360891819000...
def start ( ) : global running running = true if len ( city _ f. get ( ) ) = = 0 or len ( unit. get ( ) ) = = 0 or len ( second. get ( ) ) = = 0 : tkinter. messagebox. showinfo ( " error ", " entry is empty " ) else : scanning ( ) tkinter. messagebox. showinfo ( " successful ", " process has been started! " )
[ 0.5070578455924988, -0.3691823184490204, 0.5158004760742188, 0.04367128014564514, -0.1009339690208435, 0.8473752737045288, 0.07399733364582062, 0.4461199641227722, -0.44251999258995056, -0.41138550639152527, 0.10186153650283813, 0.7732447385787964, -0.7929262518882751, 0.8541969656944275, ...
def _ _ init _ _ ( self ) : super ( ). _ _ init _ _ ( ) self. pillar _ sprite = pygame. sprite. group ( ) self. all _ sprite = pygame. sprite. group ( ) self. bird = bird ( ) self. all _ sprite. add ( self. bird ) self. speed = 0 self. g = 0. 5 pillar1, pillar2 = pillar ( ), pillar ( ) pillar1. rect. y = randint ( - 15...
[ -0.5232505202293396, 0.10067009925842285, 0.6922016143798828, -0.44937247037887573, 0.6732625365257263, 0.4439573585987091, 0.49792560935020447, -0.10684973746538162, -0.21924155950546265, 0.48536521196365356, -1.1806126832962036, 0.37428921461105347, -1.1146844625473022, 0.760247468948364...
def set _ args ( ) : parser = argparse. argumentparser ( ) parser. add _ argument ( " - f ", " - - file _ path ", help = " specify path for the file you want to process ", dest ='file ', type = str, required = true, ) parser. add _ argument ( " - nf ", " - - new _ file _ path ", help = " specify name and path in which ...
[ 0.06902100145816803, -0.3676164746284485, 0.5399676561355591, -0.45035219192504883, 1.122068166732788, 0.20939438045024872, -0.48310136795043945, 0.6743915677070618, -1.7494765520095825, 0.31681767106056213, -0.005170836579054594, 0.055339597165584564, -0.19984956085681915, 1.0457434654235...
def _ _ init _ _ ( self, * args ) : _ snap. tintset _ swiginit ( self, _ snap. new _ tintset ( * args ) )
[ -0.4405916929244995, 0.1749732941389084, -0.022810770198702812, 0.46219655871391296, -0.5816110372543335, -0.6606947779655457, 0.9473357200622559, -0.3284679651260376, -0.48134374618530273, -0.03335406631231308, -0.11403456330299377, 0.4977118968963623, -0.5382904410362244, 0.8054245114326...
def to _ device ( tt : torch. tensor, device : optional [ types. device ] = " cpu ", non _ blocking : bool = false ) - > torch. tensor : return tt. to ( device, non _ blocking = non _ blocking )
[ -0.18519210815429688, 1.4317095279693604, 0.2953442931175232, 0.4304051697254181, -0.3564813435077667, 0.4049127697944641, 0.155607670545578, -0.6006800532341003, -0.41275086998939514, 1.00108802318573, -0.31026771664619446, 0.25214317440986633, -0.22228586673736572, -1.0355576276779175, ...
def fetch _ cnbc _ urls ( ) : tesla _ urls = [ ] response = requests. get ( base _ url ) with open ('cnbcbaseurl. xml ','wb') as file _ handler : file _ handler. write ( response. content ) df = pdx. read _ xml ( " cnbcbaseurl. xml ", ['sitemapindex'] ) xml _ url _ list = [ x ['loc'] for x in df. sitemap ] print ( xml ...
[ 0.1882530301809311, -0.055474914610385895, 0.49255311489105225, 0.17384427785873413, 0.6484801769256592, 0.12693649530410767, -0.34571897983551025, 0.8611156940460205, -0.06204935163259506, 0.190384641289711, -0.44643524289131165, 0.4488055408000946, 0.5296686291694641, 0.5741708874702454,...
def is _ ( self, state ) : translator = self. _ meta ['translator'] state = translator. translate ( state ) return self. actual _ state = = state
[ -0.3973419964313507, -0.056689463555812836, 0.3312988877296448, -0.1941404938697815, -0.5265426635742188, -0.22914204001426697, -1.083943486213684, 0.1411665380001068, 1.2188440561294556, 0.15854087471961975, -0.4952290654182434, -0.1112271249294281, 0.866446852684021, -0.707755446434021, ...
def getnastri ( self, * args ) : return _ snap. pneanetmp _ getnastri ( self, * args )
[ 0.5594030618667603, 0.033219046890735626, 0.1992097944021225, 0.6061034798622131, 1.0343692302703857, -0.12757496535778046, 0.009181976318359375, -1.0531609058380127, -0.5082491040229797, -0.9614225625991821, -0.8292136788368225, -0.6806467175483704, -0.7417831420898438, 0.5975632667541504...
def plotoutdegdistr _ pungraph ( * args ) : return _ snap. plotoutdegdistr _ pungraph ( * args )
[ -0.7806054353713989, 1.0242507457733154, 0.26355263590812683, -0.5923810005187988, -0.6286530494689941, 0.3503638505935669, 0.8091764450073242, 0.9318576455116272, 0.1875723898410797, -0.19389311969280243, -0.17331677675247192, 0.1125081405043602, 0.04267348721623421, -0.2212091088294983, ...
def addbacksorted ( self, * args ) : return _ snap. tfltv _ addbacksorted ( self, * args )
[ -0.41917654871940613, 1.0290459394454956, 0.47657325863838196, -0.02915760688483715, 1.0323259830474854, -1.005090594291687, 0.7545496821403503, -0.03438185527920723, -1.0976407527923584, -0.8791369795799255, -0.31240618228912354, -0.5239432454109192, -1.2533900737762451, 1.087566137313842...
def addintvattrdate ( self, * args ) : return _ snap. tneanet _ addintvattrdate ( self, * args )
[ -0.271980345249176, 0.17251372337341309, 0.4481711685657501, -1.0421321392059326, 0.5485615134239197, 0.6829387545585632, -0.12274430692195892, -0.5268376469612122, -0.355258047580719, 0.37496018409729004, 0.7436266541481018, -1.2548723220825195, -0.704208493232727, 0.12696528434753418, ...