{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Image Classification using EmuCore\n", "#### Device: EmuCore\n", "\n", "\n", "## Introduction\n", "\n", "In what follows, We present an image classification model built using using QCi's EmuCore technology. \n", "\n", "The dataset consists of 70,000 images of handwritten digits 0-9; 60,000 samples are used for training and the remaining 10,000 images are kept for testing. Each sample is a 28 x 28 pixel image.\n", "\n", "The images are serialized in one of the two spatial directions and sent through EmuCore. The output is an enriched dataset which is then used to train a simple linear model." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Get train and test datasets\n", "\n", "We use the **mnist** package from __tensorflow__ to import training data. " ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "x_train shape: (60000, 28, 28)\n", "x_test shape: (10000, 28, 28)\n", "y_train shape: (60000,)\n", "y_test shape: (10000,)\n" ] } ], "source": [ "from tensorflow.keras.datasets import mnist\n", "\n", "(x_train, y_train), (x_test, y_test) = mnist.load_data()\n", "\n", "print(\"x_train shape:\", x_train.shape)\n", "print(\"x_test shape:\", x_test.shape)\n", "\n", "print(\"y_train shape:\", y_train.shape)\n", "print(\"y_test shape:\", y_test.shape)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Plot some of the samples\n", "\n", "We plot the first few images in training data," ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "plt.figure(figsize = (9,9))\n", "\n", "for i in range(9):\n", " plt.subplot(330 + 1 + i)\n", " plt.imshow(x_train[i], cmap=plt.get_cmap(\"gray\"))\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And in the testing data," ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize = (9,9))\n", "\n", "for i in range(9):\n", " plt.subplot(330 + 1 + i)\n", " plt.imshow(x_train[i], cmap=plt.get_cmap(\"plasma\"))\n", " \n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Normalize data\n", "\n", "As each image is 28 by 28 pixels, each sample in the data consists of a 28 by 28 matrix. The elements of the matrix are integers between 0 and 255, each representing one of the 256 colors. We can normalize values to a 0-1 range. This normalization improves the behavior of the reservoir." ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [], "source": [ "x_train = x_train.astype('float32')\n", "x_test = x_test.astype('float32')\n", "x_train = x_train / 255.0\n", "x_test = x_test / 255.0" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Flatten data\n", "\n", "We should now **flatten** in one of the two spatial directions. We have tested with both directions and the results are nearly identical." ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Flat x_train shape: (60000, 784)\n", "Flat x_test shape: (10000, 784)\n" ] } ], "source": [ "#x_train = np.swapaxes(x_train, 1, 2)\n", "#x_test = np.swapaxes(x_test, 1, 2)\n", "\n", "x_train_flat = x_train.reshape((x_train.shape[0], 28 * 28))\n", "x_test_flat = x_test.reshape((x_test.shape[0], 28 * 28))\n", "\n", "print(\"Flat x_train shape:\", x_train_flat.shape)\n", "print(\"Flat x_test shape:\", x_test_flat.shape)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can plot the first few flattened samples," ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize = (9,9))\n", "\n", "for i in range(9):\n", " plt.subplot(330 + 1 + i)\n", " plt.plot(x_train_flat[i].reshape(784,1))\n", " \n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Run the dataset through EmuCore\n", "\n", "We now push the flattened training and testing data through the reservoir." ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Training response shape: (60000, 2500)\n", "Testing response shape: (10000, 2500)\n" ] } ], "source": [ "from emucore_direct.client import EmuCoreClient\n", "\n", "IP_ADDR = \"172.22.19.49\" \n", "VBIAS = 0.31\n", "GAIN = 0.72\n", "NUM_NODES = 2500\n", "NUM_TAPS = 2500\n", "FEATURE_SCALING = 0.1\n", "DENSITY = 1.0\n", "\n", "# Instantiate an EmuCore instance\n", "client = EmuCoreClient(ip_addr=IP_ADDR)\n", "\n", "# A a lock id and reset the device\n", "lock_id, start, end = client.wait_for_lock()\n", "client.reservoir_reset(lock_id=lock_id)\n", "\n", "# Configure\n", "client.rc_config(\n", " lock_id=lock_id,\n", " vbias=VBIAS,\n", " gain=GAIN,\n", " num_nodes=NUM_NODES,\n", " num_taps=NUM_TAPS\n", ")\n", "\n", "# Push data through reservoir\n", "resp_train, train_max_scale_val, train_wgts = client.process_all_data(\n", " input_data=x_train_flat,\n", " num_nodes=NUM_NODES,\n", " density=DENSITY,\n", " feature_scaling=FEATURE_SCALING,\n", " lock_id=lock_id,\n", ")\n", "\n", "resp_test, test_max_scale_val, test_wgts = client.process_all_data(\n", " input_data=x_test_flat,\n", " num_nodes=NUM_NODES,\n", " density=DENSITY,\n", " feature_scaling=FEATURE_SCALING,\n", " lock_id=lock_id,\n", ")\n", "\n", "# Release the lock\n", "client.release_lock(lock_id=lock_id)\n", "\n", "print(\"Training response shape:\", resp_train.shape)\n", "print(\"Testing response shape:\", resp_test.shape)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Build a linear model\n", "\n", "We should now build a linear model based on the responses from the reservoir. As each label (from 0 to 9) represents a category of digits, the labels are converted to categorical values; each label is converted to an array with one element set to 1 and the other elements set to -1.\n", "\n", "For example, the label \"1\" is converted to,\n", "\n", "$[-1, 1, -1, -1, -1, -1, -1, -1, -1, -1]$\n", "\n", "and the label \"5\" is converted to,\n", "\n", "$[-1, -1, -1, -1, -1, 1, -1, -1, -1, -1]$" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Categorical y_train.shape: (60000, 10)\n", "Categorical y_test.shape: (10000, 10)\n" ] } ], "source": [ "import numpy as np\n", "\n", "def to_categorical(y, num_classes=None, dtype=\"float32\"):\n", "\n", " y = np.array(y, dtype=\"int\")\n", " input_shape = y.shape\n", "\n", " # Shrink the last dimension if the shape is (..., 1).\n", " if input_shape and input_shape[-1] == 1 and len(input_shape) > 1:\n", " input_shape = tuple(input_shape[:-1])\n", "\n", " y = y.reshape(-1)\n", " if not num_classes:\n", " num_classes = np.max(y) + 1\n", " \n", " n = y.shape[0]\n", " categorical = np.zeros((n, num_classes), dtype=dtype)\n", " categorical[np.arange(n), y] = 1\n", " output_shape = input_shape + (num_classes,)\n", " categorical = np.reshape(categorical, output_shape)\n", " \n", " return categorical\n", "\n", "y_train_cat = []\n", "for digit in y_train:\n", " cat_digit = 2 * to_categorical(digit, num_classes=10) - 1\n", " y_train_cat.append(cat_digit)\n", " \n", "y_train_cat = np.array(y_train_cat)\n", "\n", "y_test_cat = []\n", "for digit in y_test:\n", " cat_digit = 2 * to_categorical(digit, num_classes=10) - 1\n", " y_test_cat.append(cat_digit)\n", " \n", "y_test_cat = np.array(y_test_cat)\n", "\n", "print(\"Categorical y_train.shape:\", y_train_cat.shape)\n", "print(\"Categorical y_test.shape:\", y_test_cat.shape)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Train a linear model\n", "\n", "We can now build a simple linear model," ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "R2 = 0.6806182222229208\n" ] } ], "source": [ "from sklearn.linear_model import LinearRegression\n", "\n", "model = LinearRegression(fit_intercept=True)\n", "\n", "model.fit(resp_train, y_train_cat)\n", "\n", "print(\"R2 = \", model.score(resp_train, y_train_cat))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Calculate classification success rates\n", "\n", "We can calculate the success rates of classifier on training and testing data," ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Success rate on train data: 0.919\n", "Success rate on test data: 0.903\n" ] } ], "source": [ "from sklearn.metrics import accuracy_score\n", "\n", "y_train_prd = model.predict(resp_train)\n", "y_test_prd = model.predict(resp_test)\n", "\n", "def from_categorical(y_cat):\n", " y = []\n", " for i in range(y_cat.shape[0]):\n", " y.append(np.argmax(y_cat[i]))\n", " \n", " return np.array(y)\n", " \n", "y_train_prd = from_categorical(y_train_prd)\n", "y_test_prd = from_categorical(y_test_prd)\n", "\n", "print(\n", " \"Success rate on train data: %0.3f\" % (\n", " accuracy_score(y_train, y_train_prd)\n", " )\n", ")\n", " \n", "print(\n", " \"Success rate on test data: %0.3f\" % (\n", " accuracy_score(y_test, y_test_prd)\n", " )\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Conclusion\n", "QCi's EmuCore reservoir technoloy was used to build an image classification model using the MNIST digit dataset. In this approach, images are flattened in one of the two spatial dimensions and are passed through EmuCore. A linear model is then trained using the output of EmuCore. The classification model yields a success rate of about 91\\% on both training and testing data. " ] } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.10.7" } }, "nbformat": 4, "nbformat_minor": 4 }