Convert gensim word2vec to tensorboard visualized model, detail: https://eliyar.biz/using-pre-trained-gensim-word2vector-in-a-keras-model-and-visualizing/

w2v_visualizer-v2.py

from gensim.models import KeyedVectors

# Load gensim word2vec
w2v_path = '<Gensim File Path>'
w2v = KeyedVectors.load_word2vec_format(w2v_path)

import io

# Vector file, `\t` seperated the vectors and `\n` seperate the words
"""
0.1\t0.2\t0.5\t0.9
0.2\t0.1\t5.0\t0.2
0.4\t0.1\t7.0\t0.8
"""
out_v = io.open('vecs.tsv', 'w', encoding='utf-8')

# Meta data file, `\n` seperated word
"""
token1
token2
token3
"""
out_m = io.open('meta.tsv', 'w', encoding='utf-8')

# Write meta file and vector file
for index in range(len(w2v.index2word)):
    word = w2v.index2word[index]
    vec = w2v.vectors[index]
    out_m.write(word + "\n")
    out_v.write('\t'.join([str(x) for x in vec]) + "\n")
out_v.close()
out_m.close()

# Then we can visuale using the `http://projector.tensorflow.org/` to visualize those two files.

# 1. Open the Embedding Projector.
# 2. Click on "Load data".
# 3. Upload the two files we created above: vecs.tsv and meta.tsv.

w2v_visualizer.py

# encoding: utf-8
"""
@author: BrikerMan
@contact: [email protected]
@blog: https://eliyar.biz
@version: 1.0
@license: Apache Licence
@file: w2v_visualizer.py
@time: 2017/7/30 上午9:37
"""
import sys
import os
import pathlib
import numpy as np
from gensim.models.keyedvectors import KeyedVectors
import tensorflow as tf
from tensorflow.contrib.tensorboard.plugins import projector


def visualize(model, output_path):
    meta_file = "w2x_metadata.tsv"
    placeholder = np.zeros((len(model.wv.index2word), model.vector_size))

    with open(os.path.join(output_path, meta_file), 'wb') as file_metadata:
        for i, word in enumerate(model.wv.index2word):
            placeholder[i] = model[word]
            # temporary solution for https://github.com/tensorflow/tensorflow/issues/9094
            if word == '':
                print("Emply Line, should replecaed by any thing else, or will cause a bug of tensorboard")
                file_metadata.write("{0}".format('<Empty Line>').encode('utf-8') + b'\n')
            else:
                file_metadata.write("{0}".format(word).encode('utf-8') + b'\n')

    # define the model without training
    sess = tf.InteractiveSession()

    embedding = tf.Variable(placeholder, trainable=False, name='w2x_metadata')
    tf.global_variables_initializer().run()

    saver = tf.train.Saver()
    writer = tf.summary.FileWriter(output_path, sess.graph)

    # adding into projector
    config = projector.ProjectorConfig()
    embed = config.embeddings.add()
    embed.tensor_name = 'w2x_metadata'
    embed.metadata_path = meta_file

    # Specify the width and height of a single thumbnail.
    projector.visualize_embeddings(writer, config)
    saver.save(sess, os.path.join(output_path, 'w2x_metadata.ckpt'))
    print('Run `tensorboard --logdir={0}` to run visualize result on tensorboard'.format(output_path))


if __name__ == "__main__":
    """
    Use model.save_word2vec_format to save w2v_model as word2evc format
    Then just run `python w2v_visualizer.py word2vec.text visualize_result`
    """
    try:
        model_path = sys.argv[1]
        output_path = sys.argv[2]
    except:
        print("Please provice model path and output path")
    model = KeyedVectors.load_word2vec_format(model_path)
    pathlib.Path(output_path).mkdir(parents=True, exist_ok=True)
    visualize(model, output_path)

may i know which tensorflow version do you use ?

may i know which tensorflow version do you use ?

1.14.0, 1.15.0

@sherringzhang try the v2 version, no need to use tensorflow.

Thanks!

Any help with this issue would be much appreciated.
I have saved my word2vec model as below

import gensim
import tensorflow
cbow = gensim.models.Word2Vec.load("word2vec-cbow-trained.model")
cbow.wv.save_word2vec_format("saves", binary=False, write_header=False)

While running python w2v_visualizer-v2.py I am getting the following error

Traceback (most recent call last):
  File "w2v_visualizer-v2.py", line 5, in <module>
    w2v = KeyedVectors.load_word2vec_format(w2v_path)
  File "/opt/anaconda3/lib/python3.7/site-packages/gensim/models/keyedvectors.py", line 1632, in load_word2vec_format
    limit=limit, datatype=datatype, no_header=no_header,
  File "/opt/anaconda3/lib/python3.7/site-packages/gensim/models/keyedvectors.py", line 1903, in _load_word2vec_format
    vocab_size, vector_size = [int(x) for x in header.split()]  # throws for invalid file format
  File "/opt/anaconda3/lib/python3.7/site-packages/gensim/models/keyedvectors.py", line 1903, in <listcomp>
    vocab_size, vector_size = [int(x) for x in header.split()]  # throws for invalid file format
ValueError: invalid literal for int() with base 10: 'the'

Note that my saves file has the following structure

the 0.17685317 -1.9532617 1.5539714 0.25966546 -0.2790604 -2.2597713 1.4972197 0.10902006 1.2890892 -3.6024532 -2.989032 0.34657598 0.7236928 -2.42964 -0.8789496 -1.7872599 -0.44978893 0.60331094 3.6287258 -3.4678683 0.44643888 -2.4881196 -0.4031334 1.1506665 0.85839635 -0.074375466 0.8728451 -0.7151794 0.1678528 -0.799362 0.6072906 -1.508202 0.25062883 -0.86469465 -1.2192433 -1.1580321 -1.9778714 -1.3886946 1.4056126 -0.8735327 0.35347122 -0.86999214 -0.45525596 -0.42418057 -1.059203 1.8854493 0.15196545 -0.6945364 1.1803597 0.37946966 1.4427571 -1.1902769 -1.9924257 -1.8601042 1.4197625 4.008973 -1.056887 -2.7531395 -3.6723409 0.7010601 1.7005075 1.0070549 -1.214978 -0.7066994 -2.7889273 -1.3718377 -4.142946 2.6858153 -0.43708274 -2.88627 -1.2278798 0.50436705 -1.9579133 1.8198298 1.4223633 -0.7244085 -0.6265867 -1.4257486 -2.4365761 1.2560792 0.038024887 -1.0622818 -0.61398774 1.3327323 0.2054318 -0.64971733 -3.3743927 1.5060719 3.2805905 0.7192133 -1.5339907 1.2716265 0.1824157 -1.0124737 0.050999433 1.4663799 -1.1016992 -1.2143117 -2.4511175 -0.10557431
of 3.0460706 1.3373663 1.196816 -0.19556047 -0.8811049 -3.2064245 2.7241864 -0.7885825 0.9971016 -1.9416411 -1.2840354 -0.34925482 -0.45565912 -1.5531577 1.5190945 1.3647329 -1.002623 1.2740299 -0.4051151 -1.9208825 2.4888372 -1.7555032 -3.0612128 1.8195832 2.4814606 1.7883114 -2.1521654 -1.0710764 -1.5177658 -0.028148778 1.1640902 -1.8277678 0.15703708 -1.4029969 -2.1030195 1.4702427 0.4488853 1.5654148 3.3290143 -0.7383135 -1.8343161 -0.68447036 -0.043044392 0.26769924 -0.40439782 -0.18810375 -1.1142554 -0.46278685 0.24317823 -1.2461005 -1.8464402 -1.2612877 -0.8662675 2.1412709 -0.13359068 3.4847245 0.057869047 -2.790783 -2.7549887 -0.6750809 2.1154828 -1.2982407 0.10796748 2.1213553 -1.436385 2.1015587 -1.6171037 2.3242743 0.7234685 -1.8758755 -1.4552547 2.0747006 -1.8497071 -1.2190679 2.581521 0.15189165 0.52188194 -1.6772207 -1.1163213 1.2301515 2.924736 -0.7979048 1.7843307 0.90919286 0.84954226 -1.6375353 -0.97743297 1.2929957 2.3574789 -0.80276364 -1.1635864 1.6928878 -2.0798647 -2.6221583 -1.0339357 0.3908198 0.84976274 -2.3748333 -1.5945665 0.39038292
and 1.1219313 -0.57287216 2.8233395 2.1360872 0.7092419 -1.4452188 0.056862712 -0.8650348 -1.2400309 -1.7934142 2.912096 -0.8492032 -1.3192874 -2.6795244 -0.9867547 -0.32589948 0.5089368 -3.0507712 0.05717876 0.9776794 0.26174447 0.3085299 -0.1887419 2.034681 2.9300737 -1.4973634 -0.23923938 -2.1425972 1.4168317 -1.8936833 0.20425037 -0.76487523 -0.36804277 1.9585862 -0.33642375 -0.39844537 1.2265253 2.8116388 -0.079485364 -0.82307726 0.7894203 0.79567325 -1.8632652 1.388837 -2.1622436 0.42561036 -0.2638307 0.7827761 -2.921315 -0.85548234 -0.37340742 -1.8249861 -0.23272651 -0.23085229 -0.9447633 2.861003 -0.6493189 -0.5078093 -4.5068545 -0.09463242 1.7309222 2.2277017 1.6091677 -2.0859606 -2.2346895 0.62350595 -0.33926424 3.4101918 -0.43544188 -0.42850614 -0.34875816 0.9752414 -2.7059336 -0.83867943 -1.4181806 0.039321333 -1.5695908 -2.3829415 -3.8533163 -0.15862149 1.3913755 -0.7142783 -1.4000473 0.6372149 0.07471319 -0.15135452 -2.1134727 1.186361 1.4265207 2.1556866 -3.1364825 0.6773747 0.19556485 -0.2499766 0.0012382956 0.73377067 0.24287009 -0.25204325 -2.0515716 -0.8586815
in 0.4679107 -0.7147363 0.6870513 2.3970296 0.23133335 -2.0088308 0.96192807 -0.70336884 2.7202427 -3.295829 -0.111902796 0.84575987 -2.091557 -1.4566486 -1.2371515 -0.46427134 -0.57429343 -0.8059568 -1.232483 0.8712659 1.7126014 -1.8753738 -0.4192433 1.6890231 1.4969786 -3.532354 -3.5461607 1.8652811 -1.9688314 -2.7284658 1.1998934 -2.7128458 -0.14551273 1.485711 -2.0984075 -0.11708992 0.3388792 0.92114073 0.4436177 1.2787954 -0.43780327 -1.2907416 -3.675929 0.19476354 1.2023387 0.21112837 -0.048462275 0.5956885 -2.4125252 0.5563255 0.67015076 -3.0510373 -2.4840655 -0.9940212 -0.19181994 2.089644 -0.67003036 0.13005632 -3.5958734 1.4169023 2.415284 0.6011981 1.6696676 0.94127685 0.12856282 -1.1206942 0.44963643 3.4322197 1.6712409 -2.8097441 -0.056743283 0.885703 0.22115222 1.0445929 1.0310951 -0.17957939 -0.47198862 0.6815261 1.1931702 1.0212876 1.3147619 0.5675771 0.23508233 0.7991027 -0.93111813 -1.7462871 -0.37885237 0.8413612 5.558045 -0.12530512 -0.45482203 0.9609325 -2.6102614 -2.2339709 -1.5555964 1.4071726 -0.7291663 -3.266579 -0.319394 -0.9037868
to -3.8821414 4.21567 -4.2841916 1.9992005 8.387515 -1.866365 -1.7139552 1.5717068 -3.7546477 -6.2972994 -4.429308 0.3561993 -2.228322 -6.24198 -4.754417 -2.489323 0.33810374 1.5772519 5.625847 0.18966335 0.02501753 1.1203367 2.4982362 4.1448264 -3.023561 -1.5638204 -3.850069 -2.7785816 -1.1669389 2.6075501 -1.1107177 0.020647109 0.6798677 1.9573961 2.033776 2.4727473 0.34439242 -3.4267285 -3.4618797 -1.0767714 1.4911493 0.32205847 -3.8282282 0.46621034 -1.1868904 -0.804156 -2.0668411 -1.1781965 1.4468315 -1.9320458 2.4679568 -0.64231515 -0.9775714 1.0633377 0.9612057 2.0127504 -3.4997683 -4.415362 -7.259522 -0.71372855 -2.7171516 2.8856084 0.9670163 3.0653586 -2.1910143 -0.79722583 -0.74901676 6.434015 0.43257618 -6.0027103 -2.4667065 6.653222 -2.670447 -2.8447676 1.4860531 3.540087 4.0157084 2.0935838 2.4390619 -1.7799611 -2.3248808 -5.28272 -3.1426811 -1.1940547 -5.5037665 -7.4333463 -0.8022476 4.4970007 2.454048 2.0067215 -3.1876593 3.0883808 -0.23921992 1.9851035 -0.62840044 -2.6010897 -0.73158085 2.1242673 -3.8213096 2.5947778
was -4.710589 -3.3772073 0.10955221 -1.7313877 -8.288787 0.05409461 -6.080295 2.1534183 1.5065368 4.335596 -3.5250914 -0.3277998 0.4277706 3.5720081 1.3879797 -6.002331 2.2638056 0.15390304 1.8505913 -5.4874144 5.445016 0.6296176 -1.4566065 1.9769683 -7.294601 1.8752729 -3.8635497 2.6733608 -5.9826574 -2.3535771 -1.3837878 -6.3405747 2.4270785 7.0047126 2.188791 -2.5511227 -1.1451485 -5.0530715 -3.4014251 -2.576176 2.474123 -2.334116 -2.4481807 -2.2739136 3.7661273 4.3733006 -0.45788652 3.7542331 4.0064507 5.5941634 4.0001907 2.9434066 -1.6101458 -0.421224 -1.0708168 1.3551916 -0.9656049 -2.3622172 -1.9253881 0.5219556 3.9598243 5.149903 0.018789774 -0.2614307 6.4478564 -1.781651 2.080866 -5.375572 0.37850425 -1.2678552 -1.1856774 -3.4277577 -0.9645903 4.3355446 1.5985847 -0.2640619 2.1373053 2.773614 5.2806582 2.6934717 3.48066 -0.84807503 1.4767468 5.426377 -0.36306188 0.4825673 -1.2568187 4.875955 0.048968043 -2.151128 7.0404983 -0.026978265 0.9373621 -1.8621575 -5.954047 -1.558388 -3.4180856 -1.6886758 0.6581081 -1.2771552
is -2.4761403 -4.745872 -0.52507603 -4.8229136 -0.52402735 -0.30308694 -5.4508224 1.2384114 0.031921666 9.79006 -8.656783 -2.1981444 2.819296 5.0073905 -0.03273342 -1.577312 0.39155224 4.332872 3.1937835 -5.093693 3.7426393 -2.9764054 -3.7875974 5.7265434 -2.3378108 3.3960438 -6.4622827 1.3165145 -4.0487742 -1.8943297 -3.8854945 -1.9383514 3.5735753 4.4026666 2.4589038 2.4062846 -1.062349 -4.792357 -0.50390446 -5.6058297 2.7092764 -4.3803024 5.283212 0.08074169 1.648946 3.0423262 -6.310893 2.5328448 4.377649 -0.3310825 7.1264014 -5.306405 0.005553321 3.1993332 0.034337055 4.294785 1.8776917 -2.10396 -4.286922 -5.786969 6.3240724 -1.5837121 3.9194334 -2.2896976 2.170305 -0.42724505 -4.6715894 -5.27865 4.3029084 -0.74100006 -2.161638 -4.2911134 0.24633707 6.129507 3.0226285 -2.8621705 -0.694486 2.2658727 1.273172 4.868444 3.1779702 3.3881705 -1.6068625 2.3613548 2.3039763 1.0724328 2.4482958 3.3090308 -3.7438765 0.93811786 7.2100186 2.3706846 -0.030542172 2.9104407 -2.1533716 -1.487372 4.3187037 -3.0258844 -2.2990308 -4.9696674
for 1.3992636 1.5832471 -0.8895734 5.8175335 0.86994433 -0.34137616 1.6965578 0.35610542 -1.8316814 -2.5547972 -1.3647654 -1.2454106 1.1643976 -2.7216268 -1.2922747 -0.55117863 -1.3940042 0.82272893 -0.774639 -0.32584584 -0.93710077 1.6914349 -3.212801 1.291236 2.0006056 -1.2454157 -6.143175 -0.50502014 0.35242376 -1.3001075 0.2543482 -4.1115746 1.4173106 0.10958401 -2.9831893 1.5833054 0.9224081 0.2791168 -0.7371618 1.0639977 1.3920257 -1.8556877 -2.1440988 -1.3849066 1.788669 0.9723513 -2.2321274 3.2100303 -0.39172065 -3.3361773 0.3151164 -2.193909 4.508344 -0.4285582 0.74758065 0.5673972 -2.54101 4.3181605 -6.2061315 3.6213741 1.5109493 -0.060880948 2.5642757 1.9259039 -1.1053112 -0.9859321 -2.713804 1.0688162 -2.3088155 -4.6221027 -0.4982548 -0.3131879 -0.33689672 0.72330076 0.97918767 -0.14906633 4.8335185 -0.5903869 0.2768676 -2.192907 1.3851609 -0.5208601 1.0543551 -0.8356508 -3.2071674 -1.743094 -1.2873502 -0.7846164 1.4788506 2.2974634 -1.6659901 -0.6453968 -3.0161443 -2.2829316 0.5852248 -0.68889207 2.1304712 0.79754585 -2.0810611 2.707873
as -3.2138474 -1.3737184 -0.4900845 2.3804321 0.20644596 -4.7914643 -0.7833128 -2.0857232 -1.3549345 3.6720624 -4.5230885 1.8241613 1.2056868 -3.6549199 0.062405944 0.73604953 -3.194924 -3.3431904 1.0623393 -2.5494397 -3.9093316 -0.44945338 -1.3500556 1.0840981 5.4734097 0.5995898 -2.6338716 -2.935244 0.021404946 -4.6726513 1.904343 -2.0336611 4.1603155 3.9126804 -0.3598954 5.5134354 0.16425803 -1.1597283 -1.3014913 -2.0786629 -1.7961179 -1.0467496 -2.4315042 4.693773 -3.9579918 2.5038486 -1.5581553 2.9967482 -1.3689312 3.024006 3.5176284 -7.4987574 -0.13272764 -0.69940466 2.7831237 -2.0079074 -1.3492281 4.199071 -5.296896 1.6323377 1.0093807 -1.986234 6.2950144 3.50566 0.5140228 -0.69193727 -4.1022754 1.310019 -0.8469194 -2.8981595 -1.8818659 1.3815243 1.3265257 3.5771966 -4.446949 0.944633 0.31574664 -4.452766 -2.1552684 2.4903722 0.7287854 -6.098524 1.0507023 1.452695 3.2640574 -0.8936203 -2.1345525 2.2261577 2.0795228 4.387568 2.726179 1.4903517 -0.58494467 -2.617 1.6112714 2.270486 -4.3453274 1.3762197 -0.31027853 1.0753359
. . .

I have also tried to use bin file but didn't work.
I am also getting the same error with python -m gensim.scripts.word2vec2tensor -i saves -o saves-tf-projector.