From dfcb494225c16a9e29b0211da0af5c04189b4db4 Mon Sep 17 00:00:00 2001 From: paul-loedige Date: Sat, 21 Jan 2023 16:55:43 +0900 Subject: [PATCH] finished code --- README.md | 2 - Week_12_Assignment.ipynb | 444 +++++++++++++++++++++++++++++++++++++++ 2 files changed, 444 insertions(+), 2 deletions(-) delete mode 100644 README.md create mode 100644 Week_12_Assignment.ipynb diff --git a/README.md b/README.md deleted file mode 100644 index 4816688..0000000 --- a/README.md +++ /dev/null @@ -1,2 +0,0 @@ -# Week_12_Assignment - diff --git a/Week_12_Assignment.ipynb b/Week_12_Assignment.ipynb new file mode 100644 index 0000000..a56633c --- /dev/null +++ b/Week_12_Assignment.ipynb @@ -0,0 +1,444 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Intelligent World Informatics LectureV: Assignment Week 12\n", + "- Author: Paul Lödige (ploedige@g.ecc.u-tokyo.ac.jp)\n", + "- Student ID: 37-229753" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Assignment\n", + "- Similar to previous homework, experiment with the code \n", + " (e.g. adding more LSTM layers, Dense layer, dropouts, or changing batch_size, dropouts percentage, etc)\n", + " - Feel free to use the same or different dataset\n", + "- Take screenshots of the code and the result\n", + " - Put them into a single PDF file, and upload it to ITC-LMS" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Code\n", + "### Import libraries" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2023-01-21 16:44:16.036543: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA\n", + "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n", + "2023-01-21 16:44:16.325069: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory\n", + "2023-01-21 16:44:16.325090: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.\n", + "2023-01-21 16:44:17.336248: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory\n", + "2023-01-21 16:44:17.336314: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory\n", + "2023-01-21 16:44:17.336321: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.\n" + ] + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "from tensorflow.keras import datasets, layers, models\n", + "import tkinter.messagebox # for notifications" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Load Dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# define dataset\n", + "mnist = datasets.mnist\n", + "# split into training and test data\n", + "(x_train, y_train),(x_test, y_test) = mnist.load_data()\n", + "# normalize data\n", + "x_train, x_test = x_train / 255.0, x_test / 255.0\n" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Confirm Data" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + 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NNQH/kSEp/l3kv8x80XvmOY1NaV+QPnx6uvfM3/7Z+pT2NTZvuPfMN35b7T1Tcu973jPILVwJAQDMECEAgBkiBAAwQ4QAAGaIEADADBECAJghQgAAM0QIAGCGCAEAzBAhAIAZIgQAMEOEAABmuIFprnH+I33qS2lXc/I7vWdWvDDJe+Yrm/3Xl9fe7T0jSf8w53bvmcLFH3nPLL/j77xnqkYc8Z7Z3VPsPSNJf3ZsvvfMqP86MqV9YXDjSggAYIYIAQDMeEWotrZWU6ZMUSgUUlFRke655x6dOHEiaRvnnNasWaOSkhLl5+eroqJCx48fT+uiAQC5wStCjY2NWrp0qQ4fPqz6+nr19vaqsrJSPT09iW3WrVun9evXq66uTk1NTYpEIrr77rvV3Z3av9EDAHKX1wcTXn311aSvN2/erKKiIh05ckSzZ8+Wc04bNmzQqlWrtGjRIknSli1bVFxcrO3bt+vRRx9N38oBAFnvpt4T6urqkiQVFhZKklpaWtTe3q7KysrENsFgUHPmzNGhQ4eu+XvE43HFYrGkBwBgcEg5Qs451dTUaObMmRo/frwkqb29XZJUXJz8sdDi4uLEa59XW1urcDiceJSWlqa6JABAlkk5QsuWLdO7776rF1988arXAoFA0tfOuaueu2LlypXq6upKPFpbW1NdEgAgy6T0zarLly/X7t27dfDgQY0ePTrxfCQSkXT5iigajSae7+jouOrq6IpgMKhgMJjKMgAAWc7rSsg5p2XLlmnnzp3av3+/ysvLk14vLy9XJBJRfX194rkLFy6osbFRM2bMSM+KAQA5w+tKaOnSpdq+fbteeeUVhUKhxPs84XBY+fn5CgQCWrFihdauXasxY8ZozJgxWrt2rUaMGKEHH3wwI38AAED28orQpk2bJEkVFRVJz2/evFlLliyRJD311FM6f/68Hn/8cX388ceaOnWqXnvtNYVCobQsGACQOwLOuRRueZk5sVhM4XBYFVqoYYE86+VknbN/Pt175tDqn2VgJenz5me3ec80xyMp7evh8KmU5m6FH52Z5T3z6qE/SWlfY354OKU5QJJ63UU16BV1dXWpoKCg3225dxwAwAwRAgCYIUIAADNECABghggBAMwQIQCAGSIEADBDhAAAZogQAMAMEQIAmCFCAAAzRAgAYIYIAQDMpPSTVTFwFTd0eM/8xaP+d96WpP8UeSulOV+zb7vgPTPztlPpX8h1HI37/13ugcY/954Z+/AR75kx4m7YGNi4EgIAmCFCAAAzRAgAYIYIAQDMECEAgBkiBAAwQ4QAAGaIEADADBECAJghQgAAM0QIAGCGCAEAzHAD0xxz6X/9b++Z5j/9ckr7umv5cu+Z9/7VX6e0r1vlzr2Pe8/8s42fes+MPep/M1IgF3ElBAAwQ4QAAGaIEADADBECAJghQgAAM0QIAGCGCAEAzBAhAIAZIgQAMEOEAABmiBAAwAwRAgCYCTjnnPUi/rFYLKZwOKwKLdSwQJ71cgAAnnrdRTXoFXV1damgoKDfbbkSAgCYIUIAADNECABghggBAMwQIQCAGSIEADBDhAAAZogQAMAMEQIAmCFCAAAzRAgAYIYIAQDMECEAgBkiBAAwQ4QAAGa8IlRbW6spU6YoFAqpqKhI99xzj06cOJG0zZIlSxQIBJIe06ZNS+uiAQC5wStCjY2NWrp0qQ4fPqz6+nr19vaqsrJSPT09SdvNnz9fbW1ticfevXvTumgAQG4Y5rPxq6++mvT15s2bVVRUpCNHjmj27NmJ54PBoCKRSHpWCADIWTf1nlBXV5ckqbCwMOn5hoYGFRUVaezYsXrkkUfU0dFx3d8jHo8rFoslPQAAg0PKEXLOqaamRjNnztT48eMTz1dVVWnbtm3av3+/nn32WTU1NWnevHmKx+PX/H1qa2sVDocTj9LS0lSXBADIMgHnnEtlcOnSpdqzZ4/efPNNjR49+rrbtbW1qaysTC+99JIWLVp01evxeDwpULFYTKWlparQQg0L5KWyNACAoV53UQ16RV1dXSooKOh3W6/3hK5Yvny5du/erYMHD/YbIEmKRqMqKytTc3PzNV8PBoMKBoOpLAMAkOW8IuSc0/Lly/Xyyy+roaFB5eXlN5zp7OxUa2urotFoyosEAOQmr/eEli5dql//+tfavn27QqGQ2tvb1d7ervPnz0uSzp07pyeffFJvvfWWTp06pYaGBi1YsECjRo3Svffem5E/AAAge3ldCW3atEmSVFFRkfT85s2btWTJEg0dOlTHjh3T1q1b9cknnygajWru3LnasWOHQqFQ2hYNAMgN3v8c15/8/Hzt27fvphYEABg8uHccAMAMEQIAmCFCAAAzRAgAYIYIAQDMECEAgBkiBAAwQ4QAAGaIEADADBECAJghQgAAM0QIAGCGCAEAzBAhAIAZIgQAMEOEAABmiBAAwAwRAgCYIUIAADNECABghggBAMwQIQCAGSIEADBDhAAAZogQAMDMMOsFfJ5zTpLUq4uSM14MAMBbry5K+v//Pe/PgItQd3e3JOlN7TVeCQDgZnR3dyscDve7TcB9kVTdQn19fTpz5oxCoZACgUDSa7FYTKWlpWptbVVBQYHRCu1xHC7jOFzGcbiM43DZQDgOzjl1d3erpKREQ4b0/67PgLsSGjJkiEaPHt3vNgUFBYP6JLuC43AZx+EyjsNlHIfLrI/Dja6AruCDCQAAM0QIAGAmqyIUDAa1evVqBYNB66WY4jhcxnG4jONwGcfhsmw7DgPugwkAgMEjq66EAAC5hQgBAMwQIQCAGSIEADCTVRHauHGjysvLddttt2nSpEl64403rJd0S61Zs0aBQCDpEYlErJeVcQcPHtSCBQtUUlKiQCCgXbt2Jb3unNOaNWtUUlKi/Px8VVRU6Pjx4zaLzaAbHYclS5ZcdX5MmzbNZrEZUltbqylTpigUCqmoqEj33HOPTpw4kbTNYDgfvshxyJbzIWsitGPHDq1YsUKrVq3S0aNHNWvWLFVVVen06dPWS7ulxo0bp7a2tsTj2LFj1kvKuJ6eHk2cOFF1dXXXfH3dunVav3696urq1NTUpEgkorvvvjtxH8JccaPjIEnz589POj/27s2tezA2NjZq6dKlOnz4sOrr69Xb26vKykr19PQkthkM58MXOQ5SlpwPLkt885vfdI899ljSc3feeaf78Y9/bLSiW2/16tVu4sSJ1sswJcm9/PLLia/7+vpcJBJxzzzzTOK5zz77zIXDYffzn//cYIW3xuePg3POVVdXu4ULF5qsx0pHR4eT5BobG51zg/d8+PxxcC57zoesuBK6cOGCjhw5osrKyqTnKysrdejQIaNV2WhublZJSYnKy8t1//336+TJk9ZLMtXS0qL29vakcyMYDGrOnDmD7tyQpIaGBhUVFWns2LF65JFH1NHRYb2kjOrq6pIkFRYWShq858Pnj8MV2XA+ZEWEzp49q0uXLqm4uDjp+eLiYrW3txut6tabOnWqtm7dqn379un5559Xe3u7ZsyYoc7OTuulmbnyv/9gPzckqaqqStu2bdP+/fv17LPPqqmpSfPmzVM8HrdeWkY451RTU6OZM2dq/Pjxkgbn+XCt4yBlz/kw4O6i3Z/P/2gH59xVz+WyqqqqxK8nTJig6dOn6ytf+Yq2bNmimpoaw5XZG+znhiQtXrw48evx48dr8uTJKisr0549e7Ro0SLDlWXGsmXL9O677+rNN9+86rXBdD5c7zhky/mQFVdCo0aN0tChQ6/6m0xHR8dVf+MZTEaOHKkJEyaoubnZeilmrnw6kHPjatFoVGVlZTl5fixfvly7d+/WgQMHkn70y2A7H653HK5loJ4PWRGh4cOHa9KkSaqvr096vr6+XjNmzDBalb14PK73339f0WjUeilmysvLFYlEks6NCxcuqLGxcVCfG5LU2dmp1tbWnDo/nHNatmyZdu7cqf3796u8vDzp9cFyPtzoOFzLgD0fDD8U4eWll15yeXl57pe//KV777333IoVK9zIkSPdqVOnrJd2yzzxxBOuoaHBnTx50h0+fNh95zvfcaFQKOePQXd3tzt69Kg7evSok+TWr1/vjh496j788EPnnHPPPPOMC4fDbufOne7YsWPugQcecNFo1MViMeOVp1d/x6G7u9s98cQT7tChQ66lpcUdOHDATZ8+3X3pS1/KqePwgx/8wIXDYdfQ0ODa2toSj08//TSxzWA4H250HLLpfMiaCDnn3HPPPefKysrc8OHD3Te+8Y2kjyMOBosXL3bRaNTl5eW5kpISt2jRInf8+HHrZWXcgQMHnKSrHtXV1c65yx/LXb16tYtEIi4YDLrZs2e7Y8eO2S46A/o7Dp9++qmrrKx0t99+u8vLy3N33HGHq66udqdPn7Zedlpd688vyW3evDmxzWA4H250HLLpfOBHOQAAzGTFe0IAgNxEhAAAZogQAMAMEQIAmCFCAAAzRAgAYIYIAQDMECEAgBkiBAAwQ4QAAGaIEADADBECAJj5v4ccDVKOJlNOAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.imshow(x_train[1])\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Configurations\n", + "The following is a list of the neural network configurations that will be compared:" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "configs = {}" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2023-01-21 16:44:19.266912: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory\n", + "2023-01-21 16:44:19.267191: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)\n", + "2023-01-21 16:44:19.267220: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (paul-laptop): /proc/driver/nvidia/version does not exist\n", + "2023-01-21 16:44:19.267499: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA\n", + "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n" + ] + } + ], + "source": [ + "configs['with SimpleRNN (lecture example)'] = {\n", + " 'model': models.Sequential([\n", + " layers.SimpleRNN(64, input_shape=(28, 28), activation='relu'),\n", + " layers.Dense(10, activation='softmax')\n", + " ]),\n", + " 'optimizer': 'adam',\n", + " 'loss': 'sparse_categorical_crossentropy',\n", + " 'metrics': ['accuracy'],\n", + " 'epochs': 5,\n", + " 'batch_size': 64\n", + " }" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "configs['with LSTM (lecture example)'] = {\n", + " 'model': models.Sequential([\n", + " layers.LSTM(64, input_shape=(28, 28), activation='relu'),\n", + " layers.Dense(10, activation='softmax')\n", + " ]),\n", + " 'optimizer': 'adam',\n", + " 'loss': 'sparse_categorical_crossentropy',\n", + " 'metrics': ['accuracy'],\n", + " 'epochs': 5,\n", + " 'batch_size': 64\n", + " }" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "configs['Custom 1'] = {\n", + " 'model': models.Sequential([\n", + " layers.LSTM(64, input_shape=(28, 28), activation='relu', return_sequences=True),\n", + " layers.LSTM(64, activation='relu', dropout=0.1, recurrent_dropout=0.1, return_sequences=True),\n", + " layers.LSTM(64, activation='relu', dropout=0.1, recurrent_dropout=0.1, return_sequences=True),\n", + " layers.LSTM(64, activation='relu', dropout=0.1, recurrent_dropout=0.1, return_sequences=True),\n", + " layers.LSTM(64, activation='relu', dropout=0.1, recurrent_dropout=0.1),\n", + " layers.Dense(32, activation='relu'),\n", + " layers.Dropout(rate=0.1),\n", + " layers.Dense(10, activation='softmax')\n", + " ]),\n", + " 'optimizer': 'adam',\n", + " 'loss': 'sparse_categorical_crossentropy',\n", + " 'metrics': ['accuracy'],\n", + " 'epochs': 5,\n", + " 'batch_size': 64\n", + " }" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "configs['Custom 2'] = {\n", + " 'model': models.Sequential([\n", + " layers.LSTM(64, input_shape=(28, 28), activation='relu', return_sequences=True),\n", + " layers.LSTM(64, activation='relu', dropout=0.2, recurrent_dropout=0.2),\n", + " layers.Dense(32, activation='relu'),\n", + " layers.Dense(32, activation='relu'),\n", + " layers.Dense(32, activation='relu'),\n", + " layers.Dropout(rate=0.1),\n", + " layers.Dense(10, activation='softmax')\n", + " ]),\n", + " 'optimizer': 'adam',\n", + " 'loss': 'sparse_categorical_crossentropy',\n", + " 'metrics': ['accuracy'],\n", + " 'epochs': 5,\n", + " 'batch_size': 64\n", + " }" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "configs['Custom 3'] = {\n", + " 'model': models.Sequential([\n", + " layers.LSTM(64, input_shape=(28, 28), activation='relu', return_sequences=True),\n", + " layers.LSTM(64, activation='relu', dropout=0.2, recurrent_dropout=0.2),\n", + " layers.Dense(32, activation='relu'),\n", + " layers.Dropout(rate=0.2),\n", + " layers.Dense(10, activation='softmax')\n", + " ]),\n", + " 'optimizer': 'adam',\n", + " 'loss': 'sparse_categorical_crossentropy',\n", + " 'metrics': ['accuracy'],\n", + " 'epochs': 5,\n", + " 'batch_size': 64\n", + " }" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "configs['Custom 4'] = {\n", + " 'model': models.Sequential([\n", + " layers.LSTM(64, input_shape=(28, 28), activation='relu'),\n", + " layers.Dense(32, activation='relu'),\n", + " layers.Dropout(rate=0.2),\n", + " layers.Dense(10, activation='softmax')\n", + " ]),\n", + " 'optimizer': 'adam',\n", + " 'loss': 'sparse_categorical_crossentropy',\n", + " 'metrics': ['accuracy'],\n", + " 'epochs': 5,\n", + " 'batch_size': 64\n", + " }" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Compile the Models" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "for config in configs.values():\n", + " if 'history' not in config.keys():\n", + " config['model'].compile(\n", + " optimizer=config['optimizer'],\n", + " loss=config['loss'],\n", + " metrics=config['metrics']\n", + " )" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Train and Evaluate the Models" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Now training model \"with SimpleRNN (lecture example)\"\n", + "Now training model \"with LSTM (lecture example)\"\n", + "Now training model \"Custom 1\"\n", + "Now training model \"Custom 2\"\n", + "Now training model \"Custom 3\"\n", + "Now training model \"Custom 4\"\n" + ] + } + ], + "source": [ + "try:\n", + " for config_name, config in configs.items():\n", + " if 'history' in config.keys():\n", + " print(f'Already trained model \"{config_name}\"')\n", + " else:\n", + " print(f'Now training model \"{config_name}\"')\n", + " config['history'] = config['model'].fit(x_train, y_train, epochs=config['epochs'], validation_data=(x_test, y_test), batch_size=config['batch_size'], verbose=0)\n", + "except:\n", + " tkinter.messagebox.showerror(\"ERROR\", \"ERROR\")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Plot the accuracy" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10,5))\n", + "for config_name, config in configs.items():\n", + " plt.plot(config['history'].history['accuracy'], label=config_name)\n", + "plt.xlabel('Epoch')\n", + "plt.ylabel('Accuracy')\n", + "plt.ylim([0.75, 1])\n", + "plt.legend(loc='lower right')\n", + "plt.title(\"Accuracy\")\n", + "plt.show()\n", + "\n", + "plt.figure(figsize=(10,5))\n", + "for config_name, config in configs.items():\n", + " plt.plot(config['history'].history['val_accuracy'], label=config_name)\n", + "plt.xlabel('Epoch')\n", + "plt.ylabel('Accuracy')\n", + "plt.ylim([0.8, 1])\n", + "plt.legend(loc='lower right')\n", + "plt.title(\"Validation Accuracy\")\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Notify when done" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'ok'" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "tkinter.messagebox.showinfo(\"DONE\", \"DONE\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "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": "3.10.9" + }, + "orig_nbformat": 4, + "vscode": { + "interpreter": { + "hash": "767d51c1340bd893661ea55ea3124f6de3c7a262a8b4abca0554b478b1e2ff90" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +}