{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "682fef9a", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import matplotlib as mpl\n", "from matplotlib import pyplot as plt" ] }, { "cell_type": "markdown", "id": "75cc3c1d", "metadata": {}, "source": [ "# Dense Layers\n", "\n", "Exponential LR Decay: 0.98\n", "\n", "100 Epochs\n", "\n", "## Index\n", "0. fc layers\n", "1. nodes per layer\n", "2. top-1 accuracy\n", "3. top-5 accuracy\n", "4. last val loss\n", "5. last val accuracy" ] }, { "cell_type": "code", "execution_count": 2, "id": "85cb4e35", "metadata": {}, "outputs": [], "source": [ "fc_results = np.array([\n", " [1, 256, 52.44, 79.86, 2.49, 57.66],\n", " [1, 512, 49.29, 73.93, 2.95, 53.25],\n", " [1, 1024, 40.7, 68.38, 3.66, 45.22],\n", " [1, 2048, 32.12, 58.93, 4.66, 35.72],\n", " [1, 4096, 24.03, 46.76, 5.61, 27.94],\n", " [1, 8192, 19.70, 41.01, 6.42, 23.96],\n", " \n", " [2, 256, 54.48, 81.22, 1.86, 57.11],\n", " [2, 512, 56.64, 82.46, 1.94, 60.23],\n", " [2, 1024, 56.39, 81.53, 2.08, 60.91],\n", " [2, 2048, 51.39, 79.00, 2.38, 56.74],\n", " [2, 4096, 44.41, 71.83, 3.04, 47.61], # DEFAULT ALEXNET\n", " [2, 8192, 37.74, 64.36, 3.60, 42.40],\n", " \n", " [3, 256, 0.8, 2.1, 5.29, 0.55],\n", " [3, 512, 30.7, 65.16, 2.57, 30.82],\n", " [3, 1024, 48.36, 76.65, 2.30, 49.88],\n", " [3, 2048, 54.11, 80.48, 2.38, 58.21],\n", " [3, 4096, 54.48, 82.09, 2.39, 57.17],\n", " [3, 8192, 50.71, 78.57, 2.55, 55.88],\n", " \n", " [4, 256, 0.8, 2.29, 5.29, 0.55],\n", " [4, 512, 0.8, 2.1, 5.29, 0.55],\n", " [4, 1024, 0.8, 2.1, 5.29, 0.55],\n", " [4, 2048, 25.45, 60.9, 2.84, 28.55],\n", " [4, 4096, 41.14, 73.81, 2.81, 46.32],\n", " [4, 8192, 49.85, 77.58, 2.97, 53.92]\n", "])\n", "\n", "fc_0_results = [0, 196, 28.91, 54.05, 6.52, 33.21]\n", "\n", "layers = [1, 2, 3, 4]\n", "nodes = [256, 512, 1024, 2048, 4096, 8192]\n", "\n", "fc_matrix = np.zeros((len(layers), len(nodes)))\n", "for i in fc_results:\n", " fc_matrix[layers.index(i[0]), nodes.index(i[1])] = i[2]" ] }, { "cell_type": "code", "execution_count": 9, "id": "0fd9f416", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "X, Y = np.meshgrid(layers, nodes)\n", "\n", "# fig = plt.figure(figsize=(8, 5))\n", "fig = plt.figure()\n", "ax = plt.axes(projection='3d')\n", "\n", "surf = ax.plot_surface(X, Y, fc_matrix.T, cmap='viridis')\n", "\n", "ax.set_title('Accuracy with Different MLP Configurations')\n", "ax.set_xlabel('Fully Connected Layers')\n", "ax.set_ylabel('Nodes Per Layer')\n", "ax.set_zlabel('Top-1 % Test Accuracy')\n", "\n", "ax.view_init(60, -130)\n", "fig.colorbar(surf, shrink=0.3, aspect=6)\n", "\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 11, "id": "dc9d04b1", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# plt.plot([196], fc_0_results[2], 'x-', label=f'0 Layers')\n", "\n", "for i in layers:\n", " plt.plot(nodes, fc_matrix[i-1, :], 'x-', label=f'{i} Layers')\n", "\n", "plt.annotate('Standard\\nAlexNet', \n", " (4096, fc_matrix[layers.index(2), nodes.index(4096)]),\n", " textcoords=\"offset points\",\n", " xytext=(40, 10),\n", " ha='center',\n", " arrowprops={'arrowstyle': 'simple'}\n", " )\n", " \n", "plt.title('Accuracy for Varied Dense Layers')\n", "plt.xlabel('Nodes Per Layer')\n", "plt.ylabel('Top-1 % Test Accuracy')\n", "\n", "plt.grid()\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "340c4eb8", "metadata": {}, "source": [ "# Convolutional Non-Linearity\n", "\n", "Exponential LR Decay: 0.98\n", "\n", "100 Epochs\n", "\n", "Taking conovlutional layers and distributing the standard number of filters into separate conv layers with ReLu nonlinearity\n", "\n", "## Index\n", "0. convolutional layer\n", "1. number of divisions\n", "2. top-1 accuracy\n", "3. top-5 accuracy\n", "4. last val loss\n", "5. last val accuracy" ] }, { "cell_type": "code", "execution_count": 10, "id": "3426107c", "metadata": {}, "outputs": [], "source": [ "conv_nonlin_results = np.array([\n", "# [1, 1, 44.41, 71.83, 3.04, 47.61], # STANDARD ALEXNET\n", "# [1, 2],\n", "# [1, 4],\n", " \n", " [4, 1, 44.41, 71.83, 3.04, 47.61], # STANDARD ALEXNET\n", " [4, 2, 42.31, 71.96, 3.07, 49.75],\n", " [4, 4, 0.8, 2.47, 5.29, 0.55],\n", " \n", " [5, 1, 44.41, 71.83, 3.04, 47.61], # STANDARD ALEXNET\n", " [5, 2, 46.08, 73.87, 3.00, 49.20],\n", " [5, 4, 0.8, 2.47, 5.29, 0.55]\n", "])\n", "\n", "nonlin_layers = [4, 5]\n", "nonlin_div = [1, 2, 4]\n", "\n", "conv_nonlin_matrix = np.zeros((len(nonlin_layers), len(nonlin_div)))\n", "for i in conv_nonlin_results:\n", " conv_nonlin_matrix[nonlin_layers.index(i[0]), nonlin_div.index(i[1])] = i[2]" ] }, { "cell_type": "code", "execution_count": 11, "id": "d7457e0e", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "for idx, i in enumerate(nonlin_layers):\n", " plt.plot(nonlin_div, conv_nonlin_matrix[idx, :], 'x-', label=f'Layer {i}')\n", "\n", "plt.title('Accuracy for Varied Convolutional Non-Linearity')\n", "plt.xlabel('Layer Divisor')\n", "plt.ylabel('Top-1 % Test Accuracy')\n", "\n", "plt.grid()\n", "plt.legend()\n", "plt.show()" ] }, { "source": [ "# Convolutional Kernel Size\n", "\n", "Exponential LR Decay: 0.98\n", "\n", "100 Epochs\n", "\n", "## Index\n", "0. convolutional layer\n", "1. kernel size\n", "2. top-1 accuracy\n", "3. top-5 accuracy\n", "4. last val loss\n", "5. last val accuracy" ], "cell_type": "markdown", "metadata": {} }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "kernel_results = np.array([\n", " [1, 3, 37.06, 64.73, 3.38, 44.36],\n", " [1, 7, 44.72, 71.16, 3.00, 48.96],\n", " [1, 11, 44.41, 71.83, 3.04, 47.61], # DEFAULT ALEXNET\n", " [1, 15, 43.17, 71.59, 3.09, 47.55],\n", "\n", " [2, 3, 41.63, 67.63, 3.24, 45.53],\n", " [2, 5, 44.41, 71.83, 3.04, 47.61], # DEFAULT ALEXNET\n", " [2, 7, 45.15, 72.21, 2.97, 50.49],\n", " [2, 9, 43.61, 71.34, 3.10, 47.37],\n", " [2, 11, 39.35, 65.6, 3.36, 44.98],\n", "\n", " [3, 3, 44.41, 71.83, 3.04, 47.61], # DEFAULT ALEXNET\n", " [3, 5],\n", " [3, 7],\n", " [3, 9],\n", " [3, 11],\n", "])" ] } ], "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": "3.9.2" } }, "nbformat": 4, "nbformat_minor": 5 }