|
2 | 2 | "cells": [ |
3 | 3 | { |
4 | 4 | "cell_type": "code", |
5 | | - "execution_count": 1, |
| 5 | + "execution_count": null, |
6 | 6 | "metadata": { |
7 | 7 | "colab": {}, |
8 | 8 | "colab_type": "code", |
|
15 | 15 | }, |
16 | 16 | { |
17 | 17 | "cell_type": "code", |
18 | | - "execution_count": 2, |
| 18 | + "execution_count": null, |
19 | 19 | "metadata": { |
20 | 20 | "cellView": "form", |
21 | 21 | "colab": {}, |
|
116 | 116 | "metadata": {}, |
117 | 117 | "outputs": [], |
118 | 118 | "source": [ |
119 | | - "!pip install -U tensorflow-addons" |
| 119 | + "!pip install -U tensorflow-addons\n", |
| 120 | + "!pip install nltk sklearn" |
120 | 121 | ] |
121 | 122 | }, |
122 | 123 | { |
|
132 | 133 | "#download data\n", |
133 | 134 | "print(\"Downloading Dataset:\")\n", |
134 | 135 | "!wget --quiet http://www.manythings.org/anki/deu-eng.zip\n", |
135 | | - "!unzip deu-eng.zip" |
| 136 | + "!unzip -o deu-eng.zip" |
136 | 137 | ] |
137 | 138 | }, |
138 | 139 | { |
|
159 | 160 | "import itertools\n", |
160 | 161 | "from pickle import load\n", |
161 | 162 | "from tensorflow.keras.utils import to_categorical\n", |
162 | | - "from keras.utils.vis_utils import plot_model\n", |
| 163 | + "from tensorflow.keras.utils import plot_model\n", |
163 | 164 | "from tensorflow.keras.models import Sequential\n", |
164 | 165 | "from tensorflow.keras.layers import LSTM\n", |
165 | 166 | "from tensorflow.keras.layers import Dense\n", |
166 | 167 | "from tensorflow.keras.layers import Embedding\n", |
167 | 168 | "from pickle import load\n", |
168 | 169 | "import random\n", |
169 | 170 | "import tensorflow as tf\n", |
170 | | - "from keras.models import load_model\n", |
| 171 | + "from tensorflow.keras.models import load_model\n", |
171 | 172 | "from nltk.translate.bleu_score import corpus_bleu\n", |
172 | 173 | "from sklearn.model_selection import train_test_split\n", |
173 | 174 | "import tensorflow_addons as tfa" |
|
187 | 188 | }, |
188 | 189 | { |
189 | 190 | "cell_type": "code", |
190 | | - "execution_count": 2, |
| 191 | + "execution_count": null, |
191 | 192 | "metadata": { |
192 | 193 | "colab": {}, |
193 | 194 | "colab_type": "code", |
|
366 | 367 | }, |
367 | 368 | { |
368 | 369 | "cell_type": "code", |
369 | | - "execution_count": 4, |
| 370 | + "execution_count": null, |
370 | 371 | "metadata": { |
371 | 372 | "colab": {}, |
372 | 373 | "colab_type": "code", |
|
389 | 390 | }, |
390 | 391 | { |
391 | 392 | "cell_type": "code", |
392 | | - "execution_count": 5, |
| 393 | + "execution_count": null, |
393 | 394 | "metadata": { |
394 | 395 | "colab": {}, |
395 | 396 | "colab_type": "code", |
|
414 | 415 | }, |
415 | 416 | { |
416 | 417 | "cell_type": "code", |
417 | | - "execution_count": 6, |
| 418 | + "execution_count": null, |
418 | 419 | "metadata": { |
419 | 420 | "colab": {}, |
420 | 421 | "colab_type": "code", |
|
479 | 480 | }, |
480 | 481 | { |
481 | 482 | "cell_type": "code", |
482 | | - "execution_count": 8, |
| 483 | + "execution_count": null, |
483 | 484 | "metadata": { |
484 | 485 | "colab": {}, |
485 | 486 | "colab_type": "code", |
|
546 | 547 | }, |
547 | 548 | { |
548 | 549 | "cell_type": "code", |
549 | | - "execution_count": 10, |
| 550 | + "execution_count": null, |
550 | 551 | "metadata": { |
551 | 552 | "colab": {}, |
552 | 553 | "colab_type": "code", |
|
615 | 616 | }, |
616 | 617 | { |
617 | 618 | "cell_type": "code", |
618 | | - "execution_count": 11, |
| 619 | + "execution_count": null, |
619 | 620 | "metadata": { |
620 | 621 | "colab": {}, |
621 | 622 | "colab_type": "code", |
|
821 | 822 | }, |
822 | 823 | "kernelspec": { |
823 | 824 | "display_name": "Python 3", |
| 825 | + "language": "python", |
824 | 826 | "name": "python3" |
825 | 827 | } |
826 | 828 | }, |
|
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