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Final class updates
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-5
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‎examples/keras-perf/cnn.py

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config.img_height = 28
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config.epochs = 4
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(X_train, y_train), (X_test, y_test) = tf.keras.datasets.mnist.load_data()
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(X_train, y_train), (X_test, y_test) = tf.keras.datasets.cifar10.load_data()
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X_train = X_train.astype('float32')
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X_train /= 255.
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X_test = X_test.astype('float32')
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X_test /= 255.
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# reshape input data
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X_train = X_train.reshape(
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X_train.shape[0], config.img_width, config.img_height, 1)
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X_test = X_test.reshape(
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X_test.shape[0], config.img_width, config.img_height, 1)
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# X_train = X_train.reshape(
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# X_train.shape[0], config.img_width, config.img_height, 1)
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# X_test = X_test.reshape(
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# X_test.shape[0], config.img_width, config.img_height, 1)
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# one hot encode outputs
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y_train = tf.keras.utils.to_categorical(y_train)

‎examples/lstm/imdb-classifier/imdb.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"from tensorflow.keras.datasets import imdb\n",
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"(X_train, y_train), (X_test, y_test) = imdb.load_data(num_words=1000)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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" 32]"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"X_train[0]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"<START> this film was just brilliant casting <UNK> <UNK> story direction <UNK> really <UNK> the part they played and you could just imagine being there robert <UNK> is an amazing actor and now the same being director <UNK> father came from the same <UNK> <UNK> as myself so i loved the fact there was a real <UNK> with this film the <UNK> <UNK> throughout the film were great it was just brilliant so much that i <UNK> the film as soon as it was released for <UNK> and would recommend it to everyone to watch and the <UNK> <UNK> was amazing really <UNK> at the end it was so sad and you know what they say if you <UNK> at a film it must have been good and this definitely was also <UNK> to the two little <UNK> that played the <UNK> of <UNK> and paul they were just brilliant children are often left out of the <UNK> <UNK> i think because the stars that play them all <UNK> up are such a big <UNK> for the whole film but these children are amazing and should be <UNK> for what they have done don't you think the whole story was so <UNK> because it was true and was <UNK> life after all that was <UNK> with us all\n"
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]
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}
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],
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"source": [
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"INDEX_FROM=3\n",
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"word_to_id = imdb.get_word_index()\n",
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"word_to_id = {k:(v+INDEX_FROM) for k,v in word_to_id.items()}\n",
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"word_to_id[\"<PAD>\"] = 0\n",
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"word_to_id[\"<START>\"] = 1\n",
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"word_to_id[\"<UNK>\"] = 2\n",
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"\n",
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"id_to_word = {value:key for key,value in word_to_id.items()}\n",
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"print(' '.join(id_to_word[id] for id in X_train[0] ))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

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