问题描述
我完全理解为什么会出现此错误，但是我很想知道是否有一种方法可以将文本填充到14个单词。出于上下文目的，这是使用GPT-2的文字热图。如果您有一个简单的想法，我也将不胜感激。要自己测试代码，请执行以下操作：Google Colaboratory。预先感谢您的协助！
def apply(f):
text = f
text = re.sub(r'\W+',' ',text)
res = LM().check_probabilities(text,topk=50)
word_list = f.split()
one = word_list[0]
two = word_list[1]
three = word_list[2]
four = word_list[3]
five = word_list[4]
six = five = word_list[5]
seven = word_list[6]
eight = word_list[7]
nine = word_list[8]
ten = word_list[9]
eleven = word_list[10]
twelve = word_list[11]
thirteen = word_list[12]
fourteen = word_list[13]
data = [[
{'token': '[CLR]','meta': ['','',''],'heat': [1,0]},{'token': ' ','format': True},{'token': one,'meta': res['pred_topk'][0],'heat': [0.13271349668502808,0.4047139883041382,0.23314827680587769,1.0,0.5698219537734985,0.20001010596752167,0.41732218861579895,0.2375192940235138,0.12837326526641846,0.3011391758918762,0.2920743227005005,0.15121395885944366,0.4707326292991638,0.141720250248909,0.1146061047911644,0.3309290111064911,0.2721664309501648,0.38880598545074463,0.28752031922340393,0.30476102232933044,0.40849509835243225,0.12109626829624176,0.236867755651474,0.15692873299121857,0.08568184077739716,0.28222283720970154,0.10787433385848999,0.09868176281452179,0.11645302921533585,0.27660083770751953,0.1150846853852272,0.13137750327587128,0.2834398150444031,0.1425863653421402,0.7729436159133911,0.15550559759140015,0.3342195451259613,0.2743198275566101]},{'token': two,'meta': res['pred_topk'][1],'heat': [0.11053311824798584,0.3417408764362335,0.5805244445800781,0.596860408782959,0.18530210852622986,0.2305091768503189,0.19138814508914948,0.08227257430553436,0.19505015015602112,0.10965480655431747,0.07133453339338303,0.21702361106872559,0.07083487510681152,0.05262206494808197,0.09487571567296982,0.07871642708778381,0.09568451344966888,0.10381820052862167,0.11150145530700684,0.08054117858409882,0.06160977482795715,0.13430000841617584,0.07046942412853241,0.04503295198082924,0.10039176791906357,0.07321848720312119,0.04508531466126442,0.04002087190747261,0.1304282695055008,0.05149686336517334,0.05910608172416687,0.1943625509738922,0.05612911283969879,0.2365487962961197,0.0644913837313652,0.08357883244752884,0.10955799371004105]},{'token': three,'meta': res['pred_topk'][2],'heat': [0.13794338703155518,0.7412312626838684,0.2688325345516205,0.3519371747970581,0.3511815071105957,0.6799001097679138,0.23039610683918,0.10480885207653046,0.29196831583976746,0.24283158779144287,0.08086933195590973,0.3110826909542084,0.16006161272525787,0.07783187925815582,0.23599569499492645,0.2036796659231186,0.25475823879241943,0.39147695899009705,0.4029639661312103,0.16113890707492828,0.08008856326341629,0.4354044497013092,0.14515410363674164,0.05876074731349945,0.21267741918563843,0.11644049733877182,0.08587612956762314,0.08814962208271027,0.363741010427475,0.07122389227151871,0.07023804634809494,0.1380654275417328,0.1375676840543747,0.7550925016403198,0.10494624823331833,0.23596565425395966,0.12745369970798492]},{'token': four,'meta': res['pred_topk'][3],'heat': [0.09374084323644638,0.27613726258277893,0.19584566354751587,0.2668629586696625,0.12618684768676758,0.5485848784446716,0.10671643167734146,0.05578231066465378,0.16895149648189545,0.14708179235458374,0.08301705121994019,0.2549331486225128,0.05449998006224632,0.0407552570104599,0.09658133238554001,0.08113130927085876,0.10979730635881424,0.09126582741737366,0.16856855154037476,0.10670913755893707,0.049128126353025436,0.12720689177513123,0.10207141935825348,0.040946654975414276,0.14924436807632446,0.07131370157003403,0.05912680923938751,0.057828083634376526,0.2358609288930893,0.05285044014453888,0.03720799833536148,0.08448022603988647,0.05244402214884758,0.2379569709300995,0.07916100323200226,0.06218649446964264,0.10799198597669601]},{'token': five,'meta': res['pred_topk'][4],'heat': [0.1723620444536209,0.49656736850738525,0.5609704256057739,0.6928957104682922,0.37088003754615784,0.5890324115753174,0.1961166113615036,0.09367834031581879,0.19113656878471375,0.13310600817203522,0.13753651082515717,0.2627904713153839,0.08134050667285919,0.053574152290821075,0.10540777444839478,0.09048342704772949,0.08953408151865005,0.13667654991149902,0.1143374964594841,0.11026952415704727,0.05795498564839363,0.12386422604322433,0.08859734237194061,0.042766354978084564,0.3162827491760254,0.07349050790071487,0.09265555441379547,0.08770584315061569,0.2039150893688202,0.05270526185631752,0.06614900380373001,0.16070793569087982,0.05872023105621338,0.3202408254146576,0.062171820551157,0.14679910242557526,0.08074744045734406]},{'token': six,'meta': res['pred_topk'][5],0.09048342704772949]},{'token': seven,'meta': res['pred_topk'][6],{'token': eight,'meta': res['pred_topk'][7],{'token': nine,'meta': res['pred_topk'][8],{'token': ten,'meta': res['pred_topk'][9],{'token': eleven,'meta': res['pred_topk'][10],{'token': twelve,'meta': res['pred_topk'][11],{'token': thirteen,'meta': res['pred_topk'][12],{'token': fourteen,'meta': res['pred_topk'][13],{'token': '[SEP]','heat': [0,1]}
]]
from textualheatmap import TextualHeatmap
heatmap = TextualHeatmap(facet_titles = ['BERT'],show_meta=True,width=3800)
heatmap.set_data(data)
print(" ")
解决方法
暂无找到可以解决该程序问题的有效方法，小编努力寻找整理中！
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