I2V

概述

使用自己提供的任一预训练模型（给出模型存放路径即可）将给定的题目文本转成向量。

  • 优点：可以使用自己的模型，另可调整训练参数，灵活性强。

导入类

[1]:

from EduNLP.I2V import D2V

输入

类型：str
内容：题目文本 （text）
[37]:

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}$"
}

输出

[34]:

model_path = "../test_model/test_gensim_luna_stem_tf_d2v_256.bin"
i2v = D2V("text","d2v",filepath=model_path, pretrained_t2v = False)
i2v

[34]:

<EduNLP.I2V.i2v.D2V at 0x7fe2517f97c0>

[35]:

i2v(item)

[35]:

([array([ 4.76559885e-02, -1.60574958e-01,  1.94614579e-03,  2.40295693e-01,
          2.24517003e-01, -3.24351490e-02,  4.35789041e-02, -1.65670961e-02,
         -7.77302235e-02,  4.23757173e-02,  4.62658405e-02,  7.54115507e-02,
         -4.54682261e-02, -1.82153687e-01,  5.55203669e-02,  4.23391759e-02,
          8.86691213e-02,  6.97413310e-02, -2.47167766e-01,  2.54209518e-01,
         -3.76413465e-02,  3.58376503e-02, -1.39907554e-01, -8.55517760e-02,
         -1.62535697e-01, -4.44540828e-02, -3.99694731e-03,  1.83905549e-02,
         -8.03738683e-02, -9.05910060e-02,  1.45633578e-01,  9.63102728e-02,
         -7.19666481e-02, -8.49684048e-03, -1.51718438e-01, -1.46381939e-02,
          8.34727809e-02, -7.11122975e-02,  1.66607365e-01, -1.14558250e-01,
         -1.72963589e-01,  4.86062802e-02, -1.63086802e-02, -3.68945636e-02,
          2.46143237e-01,  5.40899672e-03,  5.04904091e-02,  1.16586924e-01,
          7.59096816e-02,  1.20751150e-02,  1.04407202e-02,  3.19544263e-02,
         -6.02783300e-02,  1.18572332e-01, -2.19343737e-01,  2.67594811e-02,
          1.01860933e-01, -2.87170410e-02,  5.16606905e-02,  1.62313670e-01,
         -5.12879491e-02, -1.62193626e-02, -6.77167401e-02,  1.67254247e-02,
          1.10977821e-01,  8.02466944e-02, -2.00764649e-02,  1.28788516e-01,
         -7.20706284e-02, -6.22547232e-02,  1.06899485e-01,  4.60059335e-03,
         -1.99650228e-01, -1.38489634e-01,  7.20307231e-02, -4.98757213e-02,
         -1.94095057e-02, -5.85906627e-03,  1.47433639e-01,  4.68258560e-02,
          9.31144804e-02, -4.59938832e-02,  3.38427201e-02,  4.83937971e-02,
         -1.27312467e-01,  2.01561809e-01,  1.10482745e-01, -1.70595810e-01,
         -9.55015421e-02, -7.73611516e-02,  4.43056040e-02, -1.65684260e-02,
          1.65379923e-02, -1.26138464e-01,  8.31304193e-02,  2.06687212e-01,
         -1.69529378e-01,  3.43789416e-03,  1.19198427e-01, -1.38129979e-01,
         -1.87937781e-01, -8.27087983e-02, -1.76488962e-02,  8.51018950e-02,
          8.15693215e-02,  2.30262652e-02,  1.05074964e-01,  3.13350782e-02,
          1.53877333e-01,  1.01772640e-02,  9.17675197e-02, -1.32400826e-01,
          5.29836975e-02,  2.52282787e-02, -6.19753152e-02, -5.56256585e-02,
          3.87686864e-02,  4.30755690e-02,  7.57815093e-02,  2.63280701e-02,
          4.59217802e-02, -1.17288530e-01,  1.76368475e-01,  9.27482091e-04,
          2.64808517e-02,  9.73805785e-03,  1.90501258e-01,  1.02596413e-02,
         -5.55249080e-02, -1.17555618e-01, -9.98716354e-02,  1.28057361e-01,
         -4.52451073e-02,  7.51599446e-02, -3.01250312e-02,  6.24186322e-02,
          5.77449016e-02,  2.07213312e-02, -2.53734970e-03, -1.69801563e-01,
         -2.28750743e-02, -2.55512260e-02,  1.70693725e-01,  2.35232189e-01,
         -2.71384805e-01, -1.84327438e-01,  4.16823551e-02,  8.70332569e-02,
          1.82847306e-01,  2.76729286e-01, -4.31840494e-02, -1.38212308e-01,
         -3.26297544e-02, -4.25132550e-02, -1.62892416e-01,  1.91870285e-03,
          1.52552709e-01, -1.01523520e-02, -9.16219354e-02, -5.46490997e-02,
          6.06994517e-02, -6.42470419e-02,  7.96310753e-02, -5.70830703e-02,
         -8.82780831e-03, -3.94574478e-02,  9.63162258e-02,  1.54309124e-01,
          1.81100428e-01,  8.63620341e-02,  1.56518817e-02, -4.08006124e-02,
          5.20652272e-02,  8.38029310e-02, -1.55516326e-01,  3.57730500e-03,
         -1.50946556e-02,  2.84812655e-02,  1.37905419e-01,  8.77659023e-02,
          8.23542774e-02, -1.04377635e-01,  4.80731949e-03,  1.18891411e-02,
          9.32120830e-02,  7.88019150e-02, -1.44494563e-01, -7.53350407e-02,
         -1.13602541e-01,  5.43805361e-02,  1.64935380e-01, -2.00515296e-02,
          1.92917317e-01, -4.35359031e-02,  8.92477036e-02, -4.37481068e-02,
          4.01461311e-02, -2.59898454e-01, -1.11872263e-01, -1.25746787e-01,
         -2.34577611e-01, -6.69524372e-02,  5.55978045e-02, -1.91931397e-01,
          5.87355606e-02,  1.01886272e-01, -2.64038593e-01, -2.05450356e-02,
         -1.97510555e-01,  9.13371146e-02,  1.49546817e-01, -3.91026959e-02,
          5.94646595e-02,  1.29657034e-02, -3.72891256e-04,  5.56622408e-02,
          1.61776438e-01,  2.29037628e-02, -1.94774106e-01, -5.02247922e-02,
         -5.45939505e-02,  5.31783216e-02,  1.26433298e-01, -1.23263724e-01,
          8.53074417e-02, -1.41412809e-01, -7.71067888e-02,  1.21865064e-01,
          4.73318882e-02,  7.20091909e-02, -9.83269960e-02,  1.99413914e-02,
         -1.88907124e-02, -2.14710683e-02, -4.93260436e-02,  1.64937660e-01,
         -1.07827298e-01, -7.75848776e-02, -6.23578345e-03, -1.05760902e-01,
         -4.14819457e-02,  5.95730543e-02,  4.11023498e-02, -2.18305327e-02,
         -2.30057724e-02, -3.34391668e-02,  1.30382255e-01,  5.10290638e-02,
         -1.21569566e-01, -1.23630039e-01, -1.83883369e-01,  1.10945016e-01,
         -1.05633408e-01, -8.24846700e-02, -3.76710802e-01, -4.50239740e-02],
        dtype=float32)],
 None)