visual attention weights of different words in the same sentence are very close

[hemingkx]

Hello, thanks very much for your work!
I notice that after running the code, the visual attention weights of different words in the same sentence are very close, for example, I print visual attention weights of a sentence

weights:
[[0.004172074 0.0034705396 0.005776301 0.009476504 0.010787735
0.007844045 0.0072886064 0.018129287 0.01658065 0.042555813
0.019871514 0.005650495 0.00589472 0.0107222935 0.011110017
0.014842661 0.024159448 0.03624352 0.041397233 0.026511833
0.022098852 0.008615618 0.009687237 0.012540557 0.013420546
0.016871117 0.0139823835 0.0050038993 0.006192984 0.017607428
0.022137564 0.030760903 0.051660698 0.040596966 0.009957594
0.009624805 0.008910388 0.03181149 0.048867363 0.022865675
0.013254004 0.010757171 0.011077568 0.019045336 0.057793543
0.051242627 0.053584214 0.045082234 0.012463981 ]
[0.0041720746 0.0034705396 0.0057763015 0.009476503 0.010787732
0.007844043 0.007288607 0.018129291 0.016580645 0.042555816
0.01987151 0.0056504956 0.0058947187 0.010722294 0.011110017
0.014842664 0.024159458 0.036243536 0.041397225 0.02651184
0.022098847 0.008615616 0.009687238 0.012540558 0.01342055
0.016871123 0.013982381 0.0050038984 0.0061929845 0.017607424
0.022137558 0.030760888 0.051660717 0.040596966 0.009957595
0.009624803 0.008910388 0.031811494 0.048867352 0.022865677
0.013254008 0.010757169 0.011077569 0.019045338 0.057793517
0.051242627 0.053584192 0.045082234 0.012463982 ]
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0.007844044 0.007288607 0.01812929 0.016580645 0.04255584
0.019871516 0.0056504966 0.005894719 0.010722292 0.011110015
0.014842664 0.024159452 0.036243524 0.041397218 0.026511827
0.022098847 0.008615617 0.009687237 0.012540556 0.013420547
0.016871113 0.013982381 0.0050038984 0.0061929845 0.017607432
0.022137554 0.030760888 0.051660705 0.040596966 0.009957593
0.009624806 0.008910388 0.031811487 0.048867352 0.022865674
0.013254002 0.010757166 0.011077566 0.019045334 0.057793505
0.05124263 0.053584203 0.04508225 0.012463979 ]
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0.007844044 0.007288607 0.018129291 0.016580645 0.042555835
0.01987151 0.0056504956 0.0058947187 0.010722296 0.011110017
0.014842664 0.024159458 0.036243536 0.041397236 0.02651184
0.022098847 0.008615618 0.009687238 0.012540556 0.01342055
0.016871117 0.013982381 0.0050038993 0.006192986 0.01760743
0.022137566 0.030760895 0.0516607 0.040596977 0.009957595
0.009624805 0.008910389 0.031811494 0.048867352 0.022865683
0.0132540045 0.010757172 0.011077569 0.019045334 0.057793517
0.051242642 0.053584192 0.045082234 0.012463982 ]
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0.007844044 0.007288607 0.018129287 0.016580643 0.04255584
0.01987151 0.0056504947 0.0058947173 0.010722297 0.011110017
0.014842664 0.024159452 0.036243524 0.041397225 0.026511835
0.022098847 0.008615618 0.009687239 0.012540556 0.013420551
0.016871113 0.013982381 0.0050038984 0.0061929864 0.017607432
0.02213756 0.030760888 0.051660713 0.040596973 0.009957593
0.009624806 0.00891039 0.031811494 0.048867345 0.022865683
0.013254005 0.010757169 0.011077568 0.019045334 0.057793505
0.05124263 0.053584192 0.045082238 0.012463979 ]
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0.007844043 0.007288605 0.01812929 0.016580647 0.042555824
0.019871505 0.0056504942 0.00589472 0.010722292 0.011110017
0.014842658 0.02415945 0.03624353 0.041397225 0.026511827
0.022098849 0.008615617 0.009687236 0.012540555 0.01342055
0.016871117 0.0139823835 0.0050038984 0.0061929845 0.017607428
0.022137552 0.030760879 0.051660713 0.040596966 0.009957592
0.009624808 0.008910388 0.03181149 0.04886734 0.022865683
0.013254001 0.010757169 0.011077569 0.019045332 0.05779353
0.051242623 0.053584218 0.045082234 0.0124639785]
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0.007844045 0.007288608 0.018129293 0.016580647 0.04255582
0.019871512 0.0056504966 0.005894719 0.010722295 0.011110019
0.014842662 0.024159448 0.03624352 0.04139721 0.026511837
0.022098849 0.008615617 0.009687239 0.012540559 0.013420548
0.016871115 0.013982383 0.005003899 0.0061929855 0.017607432
0.022137562 0.030760884 0.051660694 0.04059696 0.009957596
0.009624804 0.008910388 0.031811498 0.048867334 0.022865681
0.013254006 0.0107571725 0.01107757 0.019045336 0.057793524
0.051242646 0.05358421 0.04508223 0.012463981 ]
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0.019871516 0.0056504947 0.0058947173 0.010722294 0.011110017
0.014842664 0.024159452 0.036243524 0.041397218 0.026511835
0.02209886 0.008615619 0.009687239 0.012540556 0.013420551
0.016871113 0.013982384 0.0050038984 0.0061929845 0.017607428
0.02213756 0.030760888 0.051660728 0.040596966 0.009957593
0.009624809 0.008910388 0.031811498 0.048867345 0.02286568
0.013254005 0.010757172 0.011077568 0.019045329 0.057793505
0.051242616 0.053584192 0.045082238 0.012463979 ]
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0.007844044 0.007288605 0.018129284 0.016580641 0.042555824
0.019871514 0.005650497 0.00589472 0.0107222935 0.011110015
0.014842663 0.02415945 0.036243524 0.041397214 0.026511833
0.022098849 0.008615618 0.009687241 0.012540558 0.01342055
0.016871113 0.013982387 0.0050038984 0.0061929845 0.017607434
0.022137564 0.030760908 0.051660713 0.040596966 0.009957592
0.009624808 0.008910388 0.03181149 0.04886734 0.022865683
0.0132540045 0.010757169 0.011077566 0.019045338 0.05779353
0.051242623 0.053584203 0.045082234 0.012463982 ]
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0.007844043 0.007288607 0.018129295 0.01658064 0.04255584
0.019871505 0.0056504947 0.005894719 0.010722294 0.011110017
0.014842667 0.024159452 0.03624353 0.041397225 0.026511835
0.022098852 0.008615618 0.00968724 0.012540559 0.013420551
0.016871123 0.013982378 0.0050038984 0.0061929864 0.017607428
0.022137554 0.030760895 0.051660728 0.04059696 0.009957593
0.009624809 0.00891039 0.031811487 0.048867363 0.022865674
0.013254008 0.010757172 0.011077568 0.019045338 0.057793505
0.05124263 0.053584192 0.045082238 0.012463979 ]
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0.007844044 0.007288605 0.018129291 0.016580645 0.042555828
0.01987151 0.0056504956 0.0058947187 0.010722294 0.011110015
0.014842664 0.024159458 0.036243517 0.041397236 0.026511833
0.022098847 0.008615616 0.009687238 0.012540558 0.013420546
0.016871117 0.013982384 0.0050038993 0.0061929845 0.01760743
0.022137558 0.030760895 0.0516607 0.040596955 0.009957595
0.009624804 0.008910388 0.031811494 0.048867363 0.022865683
0.013254008 0.010757169 0.011077566 0.019045329 0.057793517
0.051242627 0.053584192 0.045082226 0.012463979 ]
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0.007844044 0.0072886064 0.01812929 0.016580645 0.042555813
0.019871509 0.0056504947 0.005894718 0.0107222935 0.011110018
0.014842662 0.024159456 0.036243528 0.041397225 0.026511833
0.022098845 0.008615619 0.009687239 0.0125405565 0.013420546
0.016871117 0.01398238 0.0050038993 0.0061929873 0.017607426
0.022137558 0.030760903 0.051660724 0.04059697 0.009957594
0.009624806 0.008910387 0.03181149 0.048867337 0.022865687
0.013254006 0.010757168 0.011077568 0.019045336 0.057793487
0.05124264 0.0535842 0.045082234 0.012463982 ]
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0.014842664 0.024159444 0.036243517 0.041397218 0.02651184
0.022098852 0.008615616 0.0096872365 0.012540553 0.013420547
0.01687111 0.013982381 0.0050038984 0.0061929845 0.017607426
0.022137554 0.030760882 0.051660705 0.040596966 0.009957593
0.009624806 0.008910387 0.031811487 0.048867352 0.022865674
0.013254005 0.010757168 0.011077566 0.019045338 0.057793505
0.051242616 0.053584203 0.04508225 0.012463977 ]
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0.007844044 0.007288607 0.018129291 0.016580645 0.042555835
0.019871514 0.0056504956 0.0058947187 0.010722294 0.011110016
0.014842667 0.024159458 0.036243536 0.041397236 0.026511833
0.022098847 0.008615616 0.009687239 0.012540556 0.013420546
0.016871123 0.013982381 0.0050038993 0.0061929845 0.01760743
0.022137558 0.030760895 0.051660687 0.040596966 0.009957593
0.009624805 0.008910388 0.031811494 0.048867345 0.022865683
0.0132540045 0.010757172 0.011077569 0.019045338 0.057793517
0.051242627 0.053584203 0.045082234 0.012463979 ]
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0.007844044 0.007288608 0.018129293 0.016580647 0.04255583
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0.014842665 0.02415944 0.03624354 0.04139722 0.026511837
0.022098849 0.008615617 0.009687239 0.012540554 0.013420548
0.016871119 0.013982379 0.005003899 0.0061929855 0.017607432
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0.013254006 0.01075717 0.011077568 0.019045344 0.057793524
0.051242635 0.053584196 0.045082252 0.012463978 ]
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0.01484266 0.024159452 0.036243517 0.041397225 0.02651184
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0.009624809 0.008910388 0.031811494 0.048867352 0.022865674
0.013254005 0.010757172 0.011077567 0.019045329 0.057793505
0.05124263 0.053584192 0.045082238 0.012463983 ]
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0.022098847 0.008615617 0.009687239 0.012540556 0.013420544
0.016871113 0.013982381 0.0050038984 0.0061929864 0.017607428
0.02213756 0.030760888 0.051660676 0.04059696 0.009957593
0.009624804 0.008910387 0.031811494 0.048867363 0.022865683
0.013254008 0.010757171 0.011077566 0.019045334 0.057793505
0.05124263 0.053584192 0.045082226 0.012463979 ]
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0.007844043 0.007288607 0.018129295 0.016580645 0.042555816
0.019871501 0.0056504956 0.0058947187 0.010722294 0.011110016
0.014842664 0.024159458 0.036243524 0.041397236 0.026511827
0.022098847 0.008615616 0.009687239 0.012540556 0.013420545
0.016871113 0.013982384 0.0050038993 0.0061929845 0.017607432
0.022137558 0.030760888 0.051660717 0.040596955 0.009957593
0.009624804 0.008910389 0.031811483 0.048867363 0.022865683
0.0132540045 0.010757169 0.011077569 0.019045329 0.057793517
0.051242627 0.053584192 0.045082234 0.012463979 ]
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0.022098841 0.008615616 0.009687239 0.012540554 0.013420544
0.016871113 0.013982384 0.0050038984 0.0061929864 0.017607428
0.02213756 0.030760888 0.051660728 0.040596966 0.009957591
0.009624806 0.008910387 0.031811476 0.048867352 0.022865683
0.013254005 0.010757168 0.011077567 0.019045329 0.057793505
0.05124263 0.05358418 0.045082226 0.0124639785]
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0.05124262 0.05358421 0.04508223 0.01246398 ]
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0.022098847 0.008615616 0.009687241 0.012540558 0.01342055
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0.022137564 0.030760895 0.051660698 0.040596966 0.009957594
0.009624805 0.008910391 0.031811498 0.048867352 0.022865681
0.013254007 0.010757171 0.011077571 0.019045332 0.057793543
0.051242635 0.0535842 0.045082234 0.012463984 ]
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0.007844044 0.00728861 0.018129295 0.016580645 0.042555828
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0.016871117 0.013982381 0.0050038993 0.0061929845 0.01760743
0.022137554 0.030760888 0.0516607 0.040596966 0.009957596
0.009624806 0.008910388 0.031811494 0.048867363 0.022865688
0.013254008 0.010757172 0.01107757 0.019045338 0.057793517
0.051242627 0.053584192 0.045082226 0.012463981 ]
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0.014842662 0.024159461 0.03624352 0.041397214 0.026511839
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0.016871117 0.0139823835 0.0050038993 0.0061929845 0.017607426
0.022137564 0.030760892 0.05166071 0.040596962 0.009957593
0.009624808 0.008910388 0.031811498 0.04886736 0.022865675
0.013254006 0.010757169 0.01107757 0.019045332 0.057793487
0.051242612 0.0535842 0.045082245 0.012463983 ]
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0.013254005 0.010757169 0.011077568 0.019045334 0.057793494
0.05124263 0.053584192 0.04508224 0.012463983 ]
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0.022098852 0.008615619 0.009687241 0.012540556 0.01342055
0.016871117 0.013982384 0.0050038993 0.0061929845 0.01760743
0.022137566 0.030760895 0.0516607 0.040596984 0.009957595
0.009624808 0.008910389 0.031811494 0.048867345 0.022865683
0.013254008 0.010757171 0.011077569 0.019045334 0.057793517
0.051242642 0.053584192 0.045082226 0.012463984 ]
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0.014842664 0.02415945 0.036243536 0.041397214 0.02651184
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0.016871117 0.013982384 0.0050038993 0.0061929845 0.017607432
0.022137558 0.030760903 0.051660717 0.040596966 0.009957593
0.009624806 0.008910387 0.031811483 0.048867352 0.022865683
0.0132540045 0.010757169 0.011077569 0.019045334 0.057793517
0.051242612 0.053584203 0.045082226 0.012463981 ]
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0.01987151 0.0056504956 0.0058947206 0.010722294 0.011110017
0.014842664 0.024159456 0.036243524 0.041397225 0.026511835
0.022098847 0.008615617 0.00968724 0.012540559 0.013420547
0.016871119 0.013982384 0.0050038984 0.0061929864 0.017607432
0.022137566 0.030760895 0.051660728 0.040596973 0.009957594
0.009624809 0.008910391 0.031811494 0.048867352 0.02286568
0.013254008 0.010757171 0.011077571 0.019045334 0.057793505
0.051242642 0.053584203 0.045082238 0.012463983 ]
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0.007844043 0.0072886087 0.018129295 0.016580645 0.042555828
0.01987151 0.0056504956 0.0058947187 0.010722295 0.011110018
0.014842664 0.024159458 0.036243524 0.041397225 0.02651184
0.022098852 0.008615618 0.009687239 0.012540556 0.013420546
0.016871117 0.013982384 0.0050038993 0.0061929845 0.017607432
0.022137554 0.030760895 0.051660687 0.040596955 0.009957595
0.009624806 0.008910388 0.031811498 0.048867352 0.022865677
0.0132540045 0.010757171 0.01107757 0.019045334 0.057793517
0.051242627 0.053584214 0.045082226 0.012463982 ]
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0.007844044 0.007288608 0.018129287 0.016580647 0.04255583
0.019871512 0.0056504966 0.005894719 0.010722293 0.011110019
0.014842665 0.024159452 0.036243528 0.04139723 0.026511831
0.022098854 0.008615617 0.009687239 0.012540557 0.013420548
0.016871115 0.013982383 0.005003899 0.0061929855 0.017607432
0.022137562 0.030760892 0.05166068 0.04059697 0.009957594
0.009624807 0.008910389 0.031811487 0.048867334 0.022865681
0.013254006 0.01075717 0.01107757 0.01904533 0.057793524
0.051242646 0.05358421 0.04508223 0.012463981 ]]

Does this mean that the model does not learn the difference between words and only gets a single visual attention vector for each sentence? Does this problem also appear in the original paper code?

Thank you very much!