{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# FTE/BTE Experiment for food-101\n", "\n", "The progressive learning package utilizes representation ensembling algorithms to sequentially learn a representation for each task and ensemble both old and new representations for all future decisions. \n", "\n", "Here, a representation ensembling algorithm based on decision forests (SynF) demonstrates forward and backward knowledge transfer of tasks on the food-101 dataset. The original dataset can be found at https://data.vision.ee.ethz.ch/cvl/datasets_extra/food-101/static/bossard_eccv14_food-101.pdf and https://www.tensorflow.org/datasets/catalog/food101.\n", "\n", "### Import necessary packages and modules" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import os\n", "import matplotlib.pyplot as plt\n", "from multiprocessing import Pool\n", "import seaborn as sns\n", "from matplotlib import rcParams\n", "\n", "rcParams.update({\"figure.autolayout\": True})" ] }, { "attachments": { "FTE_BTE%20Set-up%20for%20food-101.PNG": { "image/png": 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" } }, "cell_type": "markdown", "metadata": {}, "source": [ "### Experimental Set-up\n", "\n", "food-101 has 101 classes of food with 1000 images each. For the purposes of this experiment, only 100 of those classes are used. The dataset is split into 10 tasks with 10 classes each. \n", "\n", "Each class is then split into 10 batches of 100 images each. Every time the experiment is repeated, the batch used as the test set is shifted.\n", "\n", "The remaining 900 images in each class are further split into 10 batches containing 90 images each. Every time the experiment is repeated, the batch used for training each task is shifted. Originally, the first 90 images from each class are used for training, then the second 90 images from each class, third 90 images, and so on.\n", "\n", "With 10 batches of test sets and 10 batches of training sets, the number of permutations comes out to 100, so the final errors are averaged across 100 trials and then used to calculate FTE and BTE\n", "\n", "![FTE_BTE%20Set-up%20for%20food-101.PNG](attachment:FTE_BTE%20Set-up%20for%20food-101.PNG)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### food-101 Data Generation\n", "\n", "The food-101 dataset was downloaded and preprocessed (images were padded and resized) by running the algorithms found in https://github.com/neurodata/LLF_tidy_images. This sectipn of the notebook serves to take those processed images and convert them into numpy arrays that can be read and used by the progressive learning algorithms." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Load data set\n", "data_dir = \"food-101_dataset/images/\" # replace with the path name for wherever the downloaded food-101 images have been stored\n", "foods_sorted = sorted(os.listdir(data_dir))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Start reading the image data into numpy arrays. Only the first 100 out of the 101 sorted food classes will be used in order to make it easier to split up the samples into tasks later on.\n", "\n", "This process of initializing each x data array with some images and then concatenating to get the next batch of 10000 images is repeated 10 times, resulting in 10 numpy arrays each containing all the images from 10 of the food-101 classes." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "dict_x = {}\n", "for k in range(10):\n", " # Initialize data_x* with the first image in the first class, then concatenate to acquire all images from the first class\n", " food_class = os.listdir(os.path.join(data_dir, foods_sorted[10 * k]))\n", " data_xk = [plt.imread(os.path.join(data_dir, foods_sorted[10 * k], food_class[0]))]\n", "\n", " for i in range(1, 1000):\n", " data_xk = np.concatenate(\n", " [\n", " data_xk,\n", " [\n", " (\n", " plt.imread(\n", " os.path.join(data_dir, foods_sorted[10 * k], food_class[i])\n", " )\n", " )\n", " ],\n", " ]\n", " )\n", "\n", " # Add to the initialized data_x* array until it contains all images from the 10 classes\n", " # Concatenating more than 10000 images per batch increases the run time by a lot\n", " for j in range(((k * 10) + 1), (10 * (k + 1))):\n", " food_class = os.listdir(os.path.join(data_dir, foods_sorted[j]))\n", " for i in range(0, 1000):\n", " data_xk = np.concatenate(\n", " [\n", " data_xk,\n", " [\n", " (\n", " plt.imread(\n", " os.path.join(data_dir, foods_sorted[j], food_class[i])\n", " )\n", " )\n", " ],\n", " ]\n", " )\n", "\n", " dict_x[\"data_x\" + str(k + 1)] = data_xk" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Combine individual numpy arrays for x data for each batch of 10 classes all into one big numpy array\n", "data_x = np.concatenate([dict_x[\"data_x1\"], dict_x[\"data_x2\"], dict_x[\"data_x3\"]])\n", "data_x = np.concatenate([data_x, dict_x[\"data_x4\"], dict_x[\"data_x5\"]])\n", "data_x = np.concatenate([data_x, dict_x[\"data_x6\"], dict_x[\"data_x7\"]])\n", "data_x = np.concatenate([data_x, dict_x[\"data_x8\"], dict_x[\"data_x9\"]])\n", "data_x = np.concatenate([data_x, dict_x[\"data_x10\"]])" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Create y data containing 100 class labels\n", "data_y = np.full((1000), 0, dtype=int)\n", "for i in range(1, 100):\n", " data_y = np.concatenate([data_y, np.full((1000), i, dtype=int)])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Train the model and perform validation\n", "\n", "`which_task`: The task number for which BTE should be calculated\n", "\n", "#### run_parallel_exp: \n", "Wrapper method for the `run_bte_exp` function which declares and trains the model, and performs validation with respect to the test data to compute the error of the model at a particular iteration" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from functions.fte_bte_food101_functions import run_fte_bte_exp\n", "\n", "fte = []\n", "bte = []\n", "te = []\n", "accuracies = []\n", "\n", "for which_task in range(1, 11):\n", "\n", " def run_parallel_exp(shift):\n", "\n", " df_list = run_fte_bte_exp(data_x, data_y, which_task, shift=shift)\n", "\n", " return df_list\n", "\n", " shifts = np.arange(0, 10, 1)\n", " acc = []\n", "\n", " with Pool(8) as p:\n", " # Paralell processing to run the experiment using a different batch for the test set each time\n", " acc.append(p.map(run_parallel_exp, shifts))\n", "\n", " # Average forward transfer accuracies accross all permutations of testing and training batches for each task\n", " acc_x = []\n", " acc_y = []\n", " acc_z = []\n", " for z in range(which_task):\n", " for y in range(10):\n", " for x in range(10):\n", " acc_x.append(acc[0][x][y][\"task_accuracy\"][z])\n", " acc_y.append(np.mean(acc_x))\n", " acc_x = []\n", " acc_z.append(np.mean(acc_y))\n", " acc_y = []\n", "\n", " # Calculate and store FTE\n", " fte.append((1 - acc_z[0]) / (1 - acc_z[-1]))\n", "\n", " # Average backward transfer accuracies accross all permutations of testing and training batches for each task\n", " acc_x = []\n", " acc_y = []\n", " acc_z = []\n", " for z in range((which_task - 1), 10):\n", " for y in range(10):\n", " for x in range(10):\n", " acc_x.append(acc[0][x][y][\"task_accuracy\"][z])\n", " acc_y.append(np.mean(acc_x))\n", " acc_x = []\n", " acc_z.append(np.mean(acc_y))\n", " acc_y = []\n", "\n", " # Calculate and store accuracies, BTE, and TE\n", " accuracies.append(acc_z)\n", " calc_bte = (1 - acc_z[0]) / ([1 - a for a in acc_z])\n", " bte.append(calc_bte)\n", " te.append([fte[(which_task - 1)] * a for a in calc_bte])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Calculating FTE, BTE, TE, and Accuracy\n", "\n", "The forward transfer efficiency of $f$ for task $t$ given $n$ samples is \n", "$$FTE_n^t (f) := \\mathbb{E} [R^t (f(D_n^{t}) )] / \\mathbb{E} [R^t (f(D_n^{ 1$. Intuitively, this means that the progressive learner has used data associated with past tasks to improve performance on task $t$. \n", "\n", "The backward transfer efficiency of $f$ for task $t$ given $n$ samples is \n", "$$BTE_n^t (f) := \\mathbb{E} [R^t (f(D_n^{ 1$. Intuitively, this means that the progressive learner has used data associated with new tasks to improve performance on previous tasks. \n", "\n", "The transfer efficiency of $f$ for task $t$ given $n$ samples is \n", "$$TE_n^t (f) := \\mathbb{E} [R^t (f(D_n^{t}) )] / \\mathbb{E} [R^t (f(D_n))]$$\n", "\n", "We say an algorithm has transfer learned for task $t$ with data $D_n$ if and only if $TE_n^t(f) > 1$." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Plotting FTE, BTE, TE, and Accuracy\n", "Run cell to generate a figure containing 4 plots of the forward transfer efficiency, backward transfer efficiency, transfer efficiency, and accuracy of the SynF algorithm. " ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.set()\n", "\n", "n_tasks = 10\n", "clr = [\"#e41a1c\", \"#a65628\", \"#377eb8\", \"#4daf4a\", \"#984ea3\", \"#ff7f00\", \"#CCCC00\"]\n", "# c = sns.color_palette(clr, n_colors=len(clr))\n", "\n", "fontsize = 22\n", "ticksize = 20\n", "\n", "# Plot FTE\n", "\n", "fig, ax = plt.subplots(2, 2, figsize=(16, 11.5))\n", "# fig.suptitle('ntrees = '+str(ntrees),fontsize=25)\n", "ax[0][0].plot(\n", " np.arange(1, n_tasks + 1), fte, c=\"red\", marker=\".\", markersize=14, linewidth=3\n", ")\n", "ax[0][0].hlines(1, 1, n_tasks, colors=\"grey\", linestyles=\"dashed\", linewidth=1.5)\n", "ax[0][0].tick_params(labelsize=ticksize)\n", "ax[0][0].set_xlabel(\"Number of tasks seen\", fontsize=fontsize)\n", "ax[0][0].set_ylabel(\"FTE\", fontsize=fontsize)\n", "\n", "# Plot BTE\n", "\n", "for i in range(n_tasks):\n", "\n", " et = np.asarray(bte[i])\n", "\n", " ns = np.arange(i + 1, n_tasks + 1)\n", " ax[0][1].plot(ns, et, c=\"red\", linewidth=2.6)\n", "\n", "ax[0][1].set_xlabel(\"Number of tasks seen\", fontsize=fontsize)\n", "ax[0][1].set_ylabel(\"BTE\", fontsize=fontsize)\n", "# ax[0][1].set_xticks(np.arange(1,10))\n", "ax[0][1].tick_params(labelsize=ticksize)\n", "ax[0][1].hlines(1, 1, n_tasks, colors=\"grey\", linestyles=\"dashed\", linewidth=1.5)\n", "\n", "# Plot TE\n", "\n", "for i in range(n_tasks):\n", "\n", " et = np.asarray(te[i])\n", "\n", " ns = np.arange(i + 1, n_tasks + 1)\n", " ax[1][0].plot(ns, et, c=\"red\", linewidth=2.6)\n", "\n", "ax[1][0].set_xlabel(\"Number of tasks seen\", fontsize=fontsize)\n", "ax[1][0].set_ylabel(\"Transfer Efficiency\", fontsize=fontsize)\n", "# ax[1][0].set_xticks(np.arange(1,10))\n", "ax[1][0].tick_params(labelsize=ticksize)\n", "ax[1][0].hlines(1, 1, n_tasks, colors=\"grey\", linestyles=\"dashed\", linewidth=1.5)\n", "\n", "# Plot accuracy\n", "\n", "for i in range(n_tasks):\n", " acc_p = np.asarray(accuracies[i])\n", " ns = np.arange(i + 1, n_tasks + 1)\n", "\n", " ax[1][1].plot(ns, acc_p, c=\"red\", linewidth=2.6)\n", "\n", "# ax[1][1].legend(loc='center left', bbox_to_anchor=(1, 0.5), fontsize=22)\n", "ax[1][1].set_xlabel(\"Number of tasks seen\", fontsize=fontsize)\n", "ax[1][1].set_ylabel(\"Accuracy\", fontsize=fontsize)\n", "ax[1][1].tick_params(labelsize=ticksize)" ] } ], "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": "3.8.5" } }, "nbformat": 4, "nbformat_minor": 2 }