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"\u001b[0;32m~/Developement/accetuation/prepare_data.py\u001b[0m in \u001b[0;36mget_ensemble_location_predictions\u001b[0;34m(input_words, letter_location_model, syllable_location_model, syllabled_letters_location_model, letter_location_co_model, syllable_location_co_model, syllabled_letters_location_co_model, dictionary, max_word, max_num_vowels, vowels, accented_vowels, feature_dictionary, syllable_dictionary)\u001b[0m\n\u001b[1;32m 1465\u001b[0m \u001b[0mletter_location_co_predictions\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mletter_location_co_model\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict_generator\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgenerator\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mbatch_size\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1466\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1467\u001b[0;31m \u001b[0mletter_location_co_predictions\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreverse_predictions\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mletter_location_co_predictions\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minput_words\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvowels\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1468\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1469\u001b[0m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mData\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m's'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshuffle_all_inputs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconvert_multext\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreverse_inputs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m~/Developement/accetuation/prepare_data.py\u001b[0m in \u001b[0;36mget_ensemble_location_predictions\u001b[0;34m(input_words, letter_location_model, syllable_location_model, syllabled_letters_location_model, letter_location_co_model, syllable_location_co_model, syllabled_letters_location_co_model, dictionary, max_word, max_num_vowels, vowels, accented_vowels, feature_dictionary, syllable_dictionary)\u001b[0m\n\u001b[1;32m 1465\u001b[0m \u001b[0mletter_location_co_predictions\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mletter_location_co_model\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict_generator\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgenerator\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mbatch_size\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1466\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1467\u001b[0;31m \u001b[0mletter_location_co_predictions\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreverse_predictions\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mletter_location_co_predictions\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minput_words\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvowels\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1468\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1469\u001b[0m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mData\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m's'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshuffle_all_inputs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconvert_multext\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreverse_inputs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m~/Developement/accetuation/prepare_data.py\u001b[0m in \u001b[0;36mreverse_predictions\u001b[0;34m(self, predictions, words, vowels)\u001b[0m\n\u001b[1;32m 1503\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1504\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mword_len\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1505\u001b[0;31m \u001b[0mnew_predictions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mpredictions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mword_len\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0;36m1\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1506\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1507\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mnew_predictions\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m~/Developement/accetuation/prepare_data.py\u001b[0m in \u001b[0;36mreverse_predictions\u001b[0;34m(self, predictions, words, vowels)\u001b[0m\n\u001b[1;32m 1503\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1504\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mword_len\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1505\u001b[0;31m \u001b[0mnew_predictions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mpredictions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mword_len\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0;36m1\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1506\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1507\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mnew_predictions\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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