get_pretrained_i2v¶

概述¶

使用 EduNLP 项目组给定的预训练模型将给定的题目文本转成向量。

优点：简单方便。
缺点：只能使用项目中给定的模型，局限性较大。

导入功能块¶

[1]:

from EduNLP import get_pretrained_i2v

输入¶

类型：str

内容：题目文本（text）

[2]:

item = {
"如图来自古希腊数学家希波克拉底所研究的几何图形．此图由三个半圆构成，三个半圆的直径分别为直角三角形$ABC$的斜边$BC$, 直角边$AB$, $AC$.$\bigtriangleup ABC$的三边所围成的区域记为$I$,黑色部分记为$II$, 其余部分记为$III$.在整个图形中随机取一点，此点取自$I,II,III$的概率分别记为$p_1,p_2,p_3$,则$\SIFChoice$$\FigureID{1}$"
}

模型选择与使用¶

根据题目所属学科选择预训练模型：

预训练模型名称	模型训练数据的所属学科
d2v_all_256	全学科
d2v_sci_256	理科
d2v_eng_256	英语
d2v_lit_256	文科

[3]:

i2v = get_pretrained_i2v("d2v_sci_256")

EduNLP, INFO Use pretrained t2v model d2v_sci_256
downloader, INFO http://base.ustc.edu.cn/data/model_zoo/EduNLP/d2v/general_science_256.zip is saved as /home/lvrui/.EduNLP/model/general_science_256.zip
downloader, INFO file existed, skipped

注意：默认的 EduNLP 项目存储地址为根目录(~/.EduNLP)，模型存储地址为项目存储地址下的 model 文件夹。您可以通过修改下面的环境变量来修改模型存储地址：
- EduNLP 项目存储地址：EDUNLPPATH = xx/xx/xx
- 模型存储地址：EDUNLPMODELPATH = xx/xx/xx

[4]:

print(i2v(item))

([array([-2.38860980e-01,  7.09681511e-02, -2.71706015e-01,  1.64714813e-01,
        2.81243492e-02, -1.82386801e-01,  9.22331214e-02,  1.31783364e-02,
        9.15176645e-02,  3.14464062e-01,  9.37800854e-02, -2.28523940e-01,
       -2.60597020e-01,  6.49375990e-02,  9.75619778e-02, -1.97933778e-01,
        8.29798505e-02, -2.26491719e-01, -1.77030653e-01, -3.56038064e-02,
        6.22844934e-01, -2.66110301e-01,  8.00080523e-02, -1.60827965e-01,
       -1.78654417e-01, -1.33000776e-01,  2.76004016e-01,  1.79546073e-01,
        8.71006995e-02,  2.33958483e-01,  1.76031828e-01,  1.55402005e-01,
       -1.38987333e-01, -1.92975491e-01, -1.09528497e-01,  1.12305783e-01,
        2.32549626e-02,  7.75609687e-02, -2.43636876e-01,  6.35311157e-02,
       -4.82399836e-02, -2.24204548e-02,  7.49862418e-02, -1.91449642e-01,
        9.72701237e-02,  4.00750965e-01,  2.81992704e-01,  3.07581365e-01,
       -4.68867749e-01, -3.03025767e-02, -1.95257351e-01,  1.79073047e-02,
       -2.15334237e-01,  9.98005569e-02, -2.62755096e-01, -2.39337608e-01,
        3.44270498e-01,  1.50241479e-01, -2.96006531e-01, -3.81666899e-01,
       -1.19041964e-01,  6.18071109e-02,  6.49120063e-02,  9.94637012e-02,
        1.23297565e-01,  1.29930690e-01,  1.27305657e-01, -1.53804764e-01,
        7.04720244e-03, -1.33500487e-01, -1.51161134e-01,  1.13862932e-01,
       -2.44814962e-01, -8.95622373e-02,  4.76458520e-02, -5.92206642e-02,
        2.88407020e-02, -5.88610955e-02, -4.25557904e-02,  3.20446432e-01,
       -2.61463765e-02,  7.19539896e-02, -1.32161498e-01,  1.62227061e-02,
        1.20197656e-03, -2.03355268e-01, -6.83294982e-03, -2.82588631e-01,
       -1.61395460e-01, -5.05547188e-02, -2.27462381e-01, -1.70932785e-01,
        1.41351461e-01, -1.30069017e-01, -1.83039993e-01, -6.79691881e-02,
       -2.15642393e-01, -7.84436688e-02,  1.77202985e-01,  4.50607650e-02,
        7.02605024e-02,  8.01992565e-02, -1.55584306e-01, -2.00563252e-01,
        1.17082551e-01,  9.73844752e-02, -1.10356934e-01, -1.37866074e-02,
       -8.57235789e-02, -5.56467362e-02, -9.36827138e-02,  6.82030804e-03,
        6.92379624e-02, -2.28701755e-01,  6.70390204e-02,  1.34586483e-01,
        2.25231394e-01,  1.33322045e-01, -8.82911906e-02,  1.42205298e-01,
        2.41012901e-01,  7.94170424e-03, -7.02124536e-02,  2.51370400e-01,
        1.04983136e-01, -6.39194548e-02,  5.24720028e-02,  7.16757867e-03,
       -1.08169973e-01, -1.08731678e-02,  1.69618204e-02,  7.87692815e-02,
       -2.26539060e-01,  3.29003595e-02,  1.91522852e-01,  2.75921494e-01,
       -1.64055750e-01,  5.83723187e-02,  9.84422341e-02,  3.21688712e-01,
       -2.62310840e-02, -2.08140060e-01,  1.14425711e-01,  1.23823956e-01,
       -8.62085819e-03, -4.14005108e-02, -3.41566652e-02,  1.34680912e-01,
        4.27634180e-01,  1.42883554e-01, -1.54787973e-01,  7.96157196e-02,
        1.40678003e-01,  1.39171826e-02,  1.66003749e-01, -4.85638082e-02,
        5.88261709e-02,  9.51106697e-02,  1.81014258e-02,  1.44485429e-01,
        4.01205927e-01,  6.77596256e-02, -5.52676022e-01, -1.87850371e-01,
        1.12366609e-01, -6.84190989e-02,  9.48949978e-02,  2.23454669e-01,
       -1.69843137e-01,  2.09085494e-01,  4.29946512e-01, -3.36349100e-01,
        6.12608856e-03, -1.46142125e-01, -5.11092655e-02,  8.06671828e-02,
        1.81744993e-01, -6.78945482e-02, -5.77093139e-02,  1.52337164e-01,
        2.21259117e-01,  3.35705757e-01, -2.51778495e-02,  1.03662543e-01,
       -4.21361588e-02,  1.43061429e-01, -3.92947495e-01, -4.89463992e-02,
       -9.15660262e-02, -1.00108273e-01,  3.86523217e-01, -4.25569601e-02,
        4.10154127e-02, -3.41399819e-01,  2.13903114e-02,  8.09015241e-03,
        9.56344381e-02,  1.12729572e-01,  7.25207478e-02, -6.64384067e-02,
       -2.73666024e-01, -2.79651750e-02,  1.18422434e-01, -5.22459708e-02,
       -2.47057881e-02,  2.84700710e-02,  2.07451075e-01, -9.74238589e-02,
        8.08936954e-02,  4.07307222e-02, -1.35277033e-01,  2.18436554e-01,
        1.28792310e-02, -1.20433331e-01,  2.41929386e-02,  1.28128864e-02,
       -7.39881098e-02, -1.12995692e-01,  7.69245178e-02, -2.87000872e-02,
        1.64782573e-02, -2.78794408e-01, -2.64403820e-01, -2.43874848e-01,
        1.77457914e-01,  4.11631197e-01, -6.09753132e-02,  2.84967333e-01,
        9.81074646e-02, -2.68213183e-01,  1.52153388e-01,  2.42148209e-02,
        1.24371536e-01,  6.02926640e-03,  8.22689310e-02,  2.82294262e-04,
       -1.40584474e-02,  4.09389734e-02, -2.58334547e-01, -9.83026102e-02,
       -1.91695184e-01, -2.61005852e-02, -2.21736208e-01, -4.36628833e-02,
        9.49840024e-02, -5.16017936e-02,  2.17577979e-01,  2.58604765e-01,
        6.33814484e-02, -7.10158283e-03,  9.87893157e-03, -2.26405971e-02,
        1.67435139e-01,  2.90897069e-03,  2.35914681e-02,  5.43428905e-06],
      dtype=float32)], None)