mirror of
https://github.com/ArthurDanjou/ArtStudies.git
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619 lines
330 KiB
Plaintext
619 lines
330 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Séance 3 - Compléments\n",
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"\n",
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"Dans cette séance nous travaillerons avec le dataset d'images [CIFAR10](https://keras.io/api/datasets/cifar10/) qui correspond à des petites images en couleurs. Notre objectif est de construire un réseau de neurones convolutionnel capable d'identifier chacun des dix types en exploitant quelque-unes des nouvelles méthodes décrites en cours.\n",
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"\n",
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"## Exploration des données\n",
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"\n",
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"Commençons par importer les données."
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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": 100,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import pandas as pd\n",
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"\n",
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"%matplotlib inline\n",
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"import matplotlib.pyplot as plt\n",
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"import seaborn as sns\n",
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"\n",
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"sns.set(style=\"whitegrid\")\n",
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"\n",
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"from tensorflow import keras\n",
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"\n",
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"(X_train, y_train), (X_valid, y_valid) = keras.datasets.cifar10.load_data()\n",
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"\n",
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"label_map = {\n",
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" 0: \"airplane\",\n",
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" 1: \"automobile\",\n",
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" 2: \"bird\",\n",
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" 3: \"cat\",\n",
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" 4: \"deer\",\n",
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" 5: \"dog\",\n",
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" 6: \"frog\",\n",
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" 7: \"horse\",\n",
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" 8: \"ship\",\n",
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" 9: \"truck \",\n",
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"}\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Regardons la structure d'*y_train* avec son premier élément."
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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": 101,
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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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"[6]\n"
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]
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}
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],
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"source": [
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"print(y_train[0])"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Au lieu d'avoir un entier, nous avons un array. Pour pouvoir travailler, nous allons devoir modifier la structure de *y_train* et *y_valid*. Il faudrait passer d'un vecteur de taille $n$ à une matrice de type one-hot encoding de taille $(n, 10)$.\n",
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"\n",
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"**Consigne** : À l'aide de la fonction [`to_categorical`](https://keras.io/2.16/api/utils/python_utils/#tocategorical-function), modifier *y_train* et *y_valid*."
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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": 102,
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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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"[0. 0. 0. 0. 0. 0. 1. 0. 0. 0.]\n"
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]
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}
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],
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"source": [
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"y_train = keras.utils.to_categorical(y_train, num_classes=10)\n",
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"y_valid = keras.utils.to_categorical(y_valid, num_classes=10)\n",
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"\n",
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"print(y_train[0])"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Consigne** : Afficher plusieurs images du dataset d'entraînement aléatoirement. On pourra utiliser la fonction [`imshow`](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.imshow.html) et le dictionnaire."
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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": 103,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 1000x1000 with 25 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.figure(figsize=(10, 10))\n",
|
|
"for i in range(25):\n",
|
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" plt.subplot(5, 5, i + 1)\n",
|
|
" plt.xticks([])\n",
|
|
" plt.yticks([])\n",
|
|
" plt.grid(False)\n",
|
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" plt.imshow(X_train[i])\n",
|
|
" plt.xlabel(label_map[np.argmax(y_train[i])])\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"**Consigne** : Standardiser les données en utilisant la classe [`StandardScaler`](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.StandardScaler.html). On commencera par applatir les images en utilisant la méthode [`reshape`](https://numpy.org/doc/stable/reference/generated/numpy.reshape.html), puis on applique le pré-processing et on termine par reformer la matrice. Attention à bien respecter les dimensions d'origines de l'image."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 104,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"(50000, 32, 32, 3)\n",
|
|
"(10000, 32, 32, 3)\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"from sklearn.preprocessing import StandardScaler\n",
|
|
"\n",
|
|
"X_train_reshaped = X_train.reshape(-1, 32 * 32 * 3)\n",
|
|
"X_valid_reshaped = X_valid.reshape(-1, 32 * 32 * 3)\n",
|
|
"\n",
|
|
"scaler = StandardScaler()\n",
|
|
"X_train_scaled = scaler.fit_transform(X_train_reshaped).reshape(-1, 32, 32, 3)\n",
|
|
"X_valid_scaled = scaler.transform(X_valid_reshaped).reshape(-1, 32, 32, 3)\n",
|
|
"\n",
|
|
"X_train = X_train_scaled.astype(np.float32)\n",
|
|
"X_valid = X_valid_scaled.astype(np.float32)\n",
|
|
"\n",
|
|
"print(X_train.shape)\n",
|
|
"print(X_valid.shape)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Modélisation\n",
|
|
"\n",
|
|
"On souhaite visualiser les différentes courbes d'apprentissages obtenues par différent optimizer. Pour pouvoir le faire, nous allons devoir choisir les optimizers à comparer et lancer l'entraîner de plusieurs modèles. Commençons par définir une architecture avec une fonction de sorte à pouvoir simplement générer des modèles lors de la comparaisons entre les optimizers.\n",
|
|
"\n",
|
|
"**Consigne** : Définir une fonction `get_model` qui ne prend pas de paramètre et qui renvoie un modèle convolutionnel de moins de 200k paramètres en utilisant des couches de régularisations au choix."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 105,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_28\"</span>\n",
|
|
"</pre>\n"
|
|
],
|
|
"text/plain": [
|
|
"\u001b[1mModel: \"sequential_28\"\u001b[0m\n"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
|
|
"┃<span style=\"font-weight: bold\"> Layer (type) </span>┃<span style=\"font-weight: bold\"> Output Shape </span>┃<span style=\"font-weight: bold\"> Param # </span>┃\n",
|
|
"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
|
|
"│ batch_normalization_61 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">3</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">12</span> │\n",
|
|
"│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>) │ │ │\n",
|
|
"├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
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"│ conv2d_33 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">30</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">30</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">22</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">616</span> │\n",
|
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"├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
|
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"│ batch_normalization_62 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">30</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">30</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">22</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">88</span> │\n",
|
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"│ (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">BatchNormalization</span>) │ │ │\n",
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"├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
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"│ flatten_28 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Flatten</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">19800</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
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"├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
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"│ dense_31 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">10</span>) │ <span style=\"color: #00af00; text-decoration-color: #00af00\">198,010</span> │\n",
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"└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
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"</pre>\n"
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],
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"┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
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"┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
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"┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
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"│ batch_normalization_61 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m32\u001b[0m, \u001b[38;5;34m3\u001b[0m) │ \u001b[38;5;34m12\u001b[0m │\n",
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"│ (\u001b[38;5;33mBatchNormalization\u001b[0m) │ │ │\n",
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"├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
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"│ conv2d_33 (\u001b[38;5;33mConv2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m30\u001b[0m, \u001b[38;5;34m30\u001b[0m, \u001b[38;5;34m22\u001b[0m) │ \u001b[38;5;34m616\u001b[0m │\n",
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"├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
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"│ batch_normalization_62 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m30\u001b[0m, \u001b[38;5;34m30\u001b[0m, \u001b[38;5;34m22\u001b[0m) │ \u001b[38;5;34m88\u001b[0m │\n",
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"│ (\u001b[38;5;33mBatchNormalization\u001b[0m) │ │ │\n",
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"├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
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"│ flatten_28 (\u001b[38;5;33mFlatten\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m19800\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n",
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"├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
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"│ dense_31 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m10\u001b[0m) │ \u001b[38;5;34m198,010\u001b[0m │\n",
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"└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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"data": {
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">198,726</span> (776.27 KB)\n",
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"</pre>\n"
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],
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"\u001b[1m Total params: \u001b[0m\u001b[38;5;34m198,726\u001b[0m (776.27 KB)\n"
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]
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},
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">198,676</span> (776.08 KB)\n",
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"</pre>\n"
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"\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m198,676\u001b[0m (776.08 KB)\n"
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]
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"<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">50</span> (200.00 B)\n",
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"</pre>\n"
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],
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"\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m50\u001b[0m (200.00 B)\n"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
|
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"def get_model() -> keras.Model:\n",
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" model = keras.Sequential(\n",
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" [\n",
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" keras.layers.InputLayer(shape=(32, 32, 3)),\n",
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" keras.layers.BatchNormalization(),\n",
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" keras.layers.Conv2D(\n",
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" filters=22, kernel_size=3, activation=\"relu\"\n",
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" ),\n",
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" keras.layers.BatchNormalization(),\n",
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" keras.layers.Flatten(),\n",
|
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" keras.layers.Dense(10, activation=\"softmax\"),\n",
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" ]\n",
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" )\n",
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"\n",
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" return model\n",
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"\n",
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"model = get_model()\n",
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"model.compile(\n",
|
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" optimizer=\"adam\", loss=\"categorical_crossentropy\", metrics=[\"accuracy\"]\n",
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")\n",
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"model.summary()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
|
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"Nous avons modifié la structure de *y_train* et *y_valid*, nous devons adapter la fonction de perte à optimiser en conséquence. Cette fois on considérera la fonction de perte [`CategoricalCrossentropy`](https://keras.io/api/losses/probabilistic_losses/#categoricalcrossentropy-class) au lieu de [`SparseCategoricalCrossentropy`](https://keras.io/api/losses/probabilistic_losses/#sparsecategoricalcrossentropy-class) que l'on utilisait jusqu'à présent.\n",
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"\n",
|
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"**Consigne** : Définir une fonction `compile_train` qui prend en paramètre:\n",
|
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"* *optimizer_function* : l'instanciation de la classe de l'optimizer\n",
|
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"* *learning_rate* : le learning rate associé à l'optimizer\n",
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"* Et des [kwargs](https://book.pythontips.com/en/latest/args_and_kwargs.html)\n",
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"\n",
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"La fonction renvoie l'historique d'apprentissage du modèle définit par la fonction `get_model`. La fonction doit compiler le modèle avec l'optimizer définit en paramètre et l'entraîner avec les paramètres définit dans les kwargs."
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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": 106,
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"metadata": {},
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"outputs": [],
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"source": [
|
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"def compile_train(optimizer_function: str, learning_rate: float, **kwargs) -> keras.callbacks.History:\n",
|
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" model = get_model()\n",
|
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" optimizer = optimizer_function(learning_rate=learning_rate)\n",
|
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" model.compile(\n",
|
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" optimizer=optimizer,\n",
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" loss=\"categorical_crossentropy\",\n",
|
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" metrics=[\"accuracy\"],\n",
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" )\n",
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"\n",
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" history = model.fit(\n",
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" X_train,\n",
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" y_train,\n",
|
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" validation_data=(X_valid, y_valid),\n",
|
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" **kwargs,\n",
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" )\n",
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"\n",
|
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" return history"
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]
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},
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{
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"cell_type": "markdown",
|
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"metadata": {},
|
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"source": [
|
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"**Consigne** : Valider le bon fonctionnement de la fonction `compile_train` sur quelques époques."
|
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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": 107,
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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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"Epoch 1/5\n",
|
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"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 10ms/step - accuracy: 0.4699 - loss: 1.9874 - val_accuracy: 0.5507 - val_loss: 1.3598\n",
|
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"Epoch 2/5\n",
|
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"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 10ms/step - accuracy: 0.6308 - loss: 1.0889 - val_accuracy: 0.5818 - val_loss: 1.2457\n",
|
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"Epoch 3/5\n",
|
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"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 10ms/step - accuracy: 0.6901 - loss: 0.8998 - val_accuracy: 0.5852 - val_loss: 1.2750\n",
|
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"Epoch 4/5\n",
|
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"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 10ms/step - accuracy: 0.7228 - loss: 0.7992 - val_accuracy: 0.5827 - val_loss: 1.3171\n",
|
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"Epoch 5/5\n",
|
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"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 10ms/step - accuracy: 0.7521 - loss: 0.7165 - val_accuracy: 0.5840 - val_loss: 1.4040\n"
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]
|
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}
|
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],
|
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"source": [
|
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"epochs=5\n",
|
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"batch_size=64\n",
|
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"history_adam = compile_train(keras.optimizers.Adam, learning_rate=0.001, epochs=epochs, batch_size=batch_size)"
|
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]
|
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},
|
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{
|
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"cell_type": "markdown",
|
|
"metadata": {},
|
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"source": [
|
|
"Pour s'affranchir un peu de l'aléatoire, nous proposons de lancer trois fois les différents schéma d'optimisation pour les comparer. La légende sera composée du nom de l'optimizer et la valeur du learning rate sélectionnée. La classe [`optimizer`](https://keras.io/api/optimizers/#optimizer-class) de Keras permet d'obtenir ces informations comme suit:"
|
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]
|
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},
|
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{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
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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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"Epoch 1/20\n",
|
|
"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 10ms/step - accuracy: 0.3976 - loss: 1.7441 - val_accuracy: 0.4561 - val_loss: 1.5517\n",
|
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"Epoch 2/20\n",
|
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"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 9ms/step - accuracy: 0.5012 - loss: 1.4300 - val_accuracy: 0.4861 - val_loss: 1.4430\n",
|
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"Epoch 3/20\n",
|
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"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 9ms/step - accuracy: 0.5393 - loss: 1.3120 - val_accuracy: 0.5182 - val_loss: 1.3558\n",
|
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"Epoch 4/20\n",
|
|
"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 9ms/step - accuracy: 0.5643 - loss: 1.2424 - val_accuracy: 0.5276 - val_loss: 1.3330\n",
|
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"Epoch 5/20\n",
|
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"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 9ms/step - accuracy: 0.5821 - loss: 1.1924 - val_accuracy: 0.5417 - val_loss: 1.2986\n",
|
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"Epoch 6/20\n",
|
|
"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 9ms/step - accuracy: 0.6001 - loss: 1.1472 - val_accuracy: 0.5488 - val_loss: 1.2816\n",
|
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"Epoch 7/20\n",
|
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"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 9ms/step - accuracy: 0.6136 - loss: 1.1104 - val_accuracy: 0.5412 - val_loss: 1.2849\n",
|
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"Epoch 8/20\n",
|
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"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 9ms/step - accuracy: 0.6268 - loss: 1.0763 - val_accuracy: 0.5497 - val_loss: 1.2994\n",
|
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"Epoch 9/20\n",
|
|
"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 9ms/step - accuracy: 0.6388 - loss: 1.0446 - val_accuracy: 0.5646 - val_loss: 1.2380\n",
|
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"Epoch 10/20\n",
|
|
"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 9ms/step - accuracy: 0.6502 - loss: 1.0139 - val_accuracy: 0.5711 - val_loss: 1.2461\n",
|
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"Epoch 11/20\n",
|
|
"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 9ms/step - accuracy: 0.6593 - loss: 0.9879 - val_accuracy: 0.5662 - val_loss: 1.2473\n",
|
|
"Epoch 12/20\n",
|
|
"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 9ms/step - accuracy: 0.6699 - loss: 0.9612 - val_accuracy: 0.5635 - val_loss: 1.2665\n",
|
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"Epoch 13/20\n",
|
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"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 9ms/step - accuracy: 0.6793 - loss: 0.9401 - val_accuracy: 0.5835 - val_loss: 1.1972\n",
|
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"Epoch 14/20\n",
|
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"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 10ms/step - accuracy: 0.6886 - loss: 0.9142 - val_accuracy: 0.5853 - val_loss: 1.1988\n",
|
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"Epoch 15/20\n",
|
|
"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 11ms/step - accuracy: 0.6927 - loss: 0.8935 - val_accuracy: 0.5851 - val_loss: 1.1988\n",
|
|
"Epoch 16/20\n",
|
|
"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 9ms/step - accuracy: 0.7011 - loss: 0.8743 - val_accuracy: 0.5886 - val_loss: 1.1869\n",
|
|
"Epoch 17/20\n",
|
|
"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 10ms/step - accuracy: 0.7087 - loss: 0.8534 - val_accuracy: 0.5907 - val_loss: 1.1876\n",
|
|
"Epoch 18/20\n",
|
|
"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 9ms/step - accuracy: 0.7167 - loss: 0.8351 - val_accuracy: 0.5947 - val_loss: 1.1968\n",
|
|
"Epoch 19/20\n",
|
|
"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 9ms/step - accuracy: 0.7233 - loss: 0.8172 - val_accuracy: 0.5918 - val_loss: 1.2110\n",
|
|
"Epoch 20/20\n",
|
|
"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 9ms/step - accuracy: 0.7291 - loss: 0.8025 - val_accuracy: 0.5947 - val_loss: 1.1795\n",
|
|
"Epoch 1/20\n",
|
|
"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 10ms/step - accuracy: 0.4545 - loss: 2.0899 - val_accuracy: 0.4783 - val_loss: 1.5931\n",
|
|
"Epoch 2/20\n",
|
|
"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 9ms/step - accuracy: 0.6080 - loss: 1.1881 - val_accuracy: 0.5289 - val_loss: 1.4473\n",
|
|
"Epoch 3/20\n",
|
|
"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 10ms/step - accuracy: 0.6821 - loss: 0.9430 - val_accuracy: 0.5797 - val_loss: 1.3671\n",
|
|
"Epoch 4/20\n",
|
|
"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 12ms/step - accuracy: 0.7320 - loss: 0.7998 - val_accuracy: 0.5861 - val_loss: 1.3690\n",
|
|
"Epoch 5/20\n",
|
|
"\u001b[1m782/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 15ms/step - accuracy: 0.7675 - loss: 0.6918 - val_accuracy: 0.5718 - val_loss: 1.5073\n",
|
|
"Epoch 6/20\n",
|
|
"\u001b[1m779/782\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 12ms/step - accuracy: 0.8107 - loss: 0.5657"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"learning_rate = 0.001\n",
|
|
"epochs = 20\n",
|
|
"batch_size = 64\n",
|
|
"optimizers = [\n",
|
|
" keras.optimizers.SGD,\n",
|
|
" keras.optimizers.RMSprop,\n",
|
|
" keras.optimizers.Adam,\n",
|
|
"]\n",
|
|
"\n",
|
|
"histories = []\n",
|
|
"for optimizer in optimizers:\n",
|
|
" history = compile_train(\n",
|
|
" optimizer, learning_rate=learning_rate, epochs=epochs, batch_size=batch_size\n",
|
|
" )\n",
|
|
" name = optimizer.__name__\n",
|
|
" label = f\"{name} (lr={learning_rate:.06})\"\n",
|
|
" histories.append({\"label\": label, \"history\": history})"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 119,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 1000x1000 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.figure(figsize=(10, 10))\n",
|
|
"colors = sns.color_palette(\"husl\", len(histories))\n",
|
|
"for i, record in enumerate(histories):\n",
|
|
" label = record[\"label\"]\n",
|
|
" history = record[\"history\"]\n",
|
|
"\n",
|
|
" loss = history.history[\"loss\"]\n",
|
|
" val_loss = history.history[\"val_loss\"]\n",
|
|
"\n",
|
|
" mean_train = np.mean(loss)\n",
|
|
" std_train = np.std(loss)\n",
|
|
" mean_val = np.mean(val_loss)\n",
|
|
" std_val = np.std(val_loss)\n",
|
|
"\n",
|
|
" plt.plot(history.history[\"loss\"], label=label, color=colors[i], alpha=0.4)\n",
|
|
" plt.fill_between(\n",
|
|
" range(len(loss)),\n",
|
|
" np.array(loss) - np.array(std_train),\n",
|
|
" np.array(loss) + np.array(std_train),\n",
|
|
" color=colors[i],\n",
|
|
" alpha=0.1,\n",
|
|
" )\n",
|
|
" plt.plot(history.history[\"val_loss\"], linestyle=\"--\", color=colors[i], linewidth=3)\n",
|
|
" plt.fill_between(\n",
|
|
" range(len(val_loss)),\n",
|
|
" np.array(val_loss) - np.array(std_val),\n",
|
|
" np.array(val_loss) + np.array(std_val),\n",
|
|
" color=colors[i],\n",
|
|
" alpha=0.1,\n",
|
|
" )\n",
|
|
"plt.title(\"Validation Loss by Optimizer\")\n",
|
|
"plt.xlabel(\"Epochs\")\n",
|
|
"plt.ylabel(\"Validation Loss\")\n",
|
|
"plt.legend()\n",
|
|
"plt.show()\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"**Consigne** : Écrire une boucle d'entraînement qui va stocker dans une liste les courbes d'apprentissage. Chaque élément de la liste correspondra à un dictionnaire avec pour clé:\n",
|
|
"* *type*: le nom de l'optimizer\n",
|
|
"* *history*: l'historique d'apprentissage"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"Il faut maintenant visualiser les résultats. Commençons par préparer les données.\n",
|
|
"\n",
|
|
"**Consigne** : Définir une fonction `agregate_result` qui prend en paramètre:\n",
|
|
"* *results*: le dictionnaire de résultat, au format décrit précédemment\n",
|
|
"* *network_type*: chaîne de caractère identifiant le type de réseau\n",
|
|
"* *metric_name*: le nom de la métrique d'intérêt\n",
|
|
"\n",
|
|
"La fonction renverra deux matrices de tailles (nombre de comparaisons, nombre d'époque) : une pour le dataset d'entraînement et une pour le dataset de validation. On concatène donc les différentes courbes d'apprentissage."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"**Consigne** : Visualiser les courbes d'apprentissage en faisant apparaître des intervals de confiance. On prendra exemple sur la fonction `show_results` du TP précédent. Commenter."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Pour continuer\n",
|
|
"\n",
|
|
"Choisir une ou plusieurs pistes de recherche parmi les suivantes. Il est possible de choisir une autre direction, mais elle doit être validé auparavant.\n",
|
|
"\n",
|
|
"1. Nous avons utilisé un learning rate fixe et dans le cours nous avons parlé d'échéancier. Comparer les deux approches, puis se poser la question de l'importance (ou non) d'un phase de warmup.\n",
|
|
"2. Le [`Dropout`](https://keras.io/api/layers/regularization_layers/dropout/) permet de régulariser un réseau de neurones. Comparer un réseau avec et sans dropout, puis se poser la question de l'importance de la magnitude et du placement d'une couche dropout."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "studies",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.13.3"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|