520 lines (520 with data), 195.4 kB
{
"cells": [
{
"cell_type": "code",
"execution_count": 166,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "eI_d8C3_Tnyu",
"outputId": "19462f19-092a-4d4b-cad2-ef1f0e132ca4"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Time in seconds since beginning of run: 1696832550.219995\n",
"Mon Oct 9 06:22:30 2023\n"
]
}
],
"source": [
"# This cell is added by sphinx-gallery\n",
"# It can be customized to whatever you like\n",
"%matplotlib inline\n",
"# !pip install pennylane\n",
"\n",
"import time\n",
"seconds = time.time()\n",
"print(\"Time in seconds since beginning of run:\", seconds)\n",
"local_time = time.ctime(seconds)\n",
"print(local_time)"
]
},
{
"cell_type": "code",
"execution_count": 167,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 388
},
"id": "lScQSFsjTnyw",
"outputId": "e7052716-9029-494d-a27c-0cffba2ab801"
},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 400x400 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"import pennylane as qml\n",
"from pennylane import numpy as np\n",
"from pennylane.optimize import AdamOptimizer, GradientDescentOptimizer\n",
"\n",
"import matplotlib.pyplot as plt\n",
"\n",
"\n",
"# Set a random seed\n",
"np.random.seed(42)\n",
"\n",
"\n",
"# Make a dataset of points inside and outside of a circle\n",
"def circle(samples, center=[0.0, 0.0], radius=np.sqrt(2 / np.pi)):\n",
" \"\"\"\n",
" Generates a dataset of points with 1/0 labels inside a given radius.\n",
"\n",
" Args:\n",
" samples (int): number of samples to generate\n",
" center (tuple): center of the circle\n",
" radius (float: radius of the circle\n",
"\n",
" Returns:\n",
" Xvals (array[tuple]): coordinates of points\n",
" yvals (array[int]): classification labels\n",
" \"\"\"\n",
" Xvals, yvals = [], []\n",
"\n",
" for i in range(samples):\n",
" x = 2 * (np.random.rand(2)) - 1\n",
" y = 0\n",
" if np.linalg.norm(x - center) < radius:\n",
" y = 1\n",
" Xvals.append(x)\n",
" yvals.append(y)\n",
" return np.array(Xvals, requires_grad=False), np.array(yvals, requires_grad=False)\n",
"\n",
"\n",
"def plot_data(x, y, fig=None, ax=None):\n",
" \"\"\"\n",
" Plot data with red/blue values for a binary classification.\n",
"\n",
" Args:\n",
" x (array[tuple]): array of data points as tuples\n",
" y (array[int]): array of data points as tuples\n",
" \"\"\"\n",
" if fig == None:\n",
" fig, ax = plt.subplots(1, 1, figsize=(5, 5))\n",
" reds = y == 0\n",
" blues = y == 1\n",
" ax.scatter(x[reds, 0], x[reds, 1], c=\"red\", s=20, edgecolor=\"k\")\n",
" ax.scatter(x[blues, 0], x[blues, 1], c=\"blue\", s=20, edgecolor=\"k\")\n",
" ax.set_xlabel(\"$x_1$\")\n",
" ax.set_ylabel(\"$x_2$\")\n",
"\n",
"\n",
"Xdata, ydata = circle(500)\n",
"fig, ax = plt.subplots(1, 1, figsize=(4, 4))\n",
"plot_data(Xdata, ydata, fig=fig, ax=ax)\n",
"plt.show()\n",
"\n",
"\n",
"# Define output labels as quantum state vectors\n",
"def density_matrix(state):\n",
" \"\"\"Calculates the density matrix representation of a state.\n",
"\n",
" Args:\n",
" state (array[complex]): array representing a quantum state vector\n",
"\n",
" Returns:\n",
" dm: (array[complex]): array representing the density matrix\n",
" \"\"\"\n",
" return state * np.conj(state).T\n",
"\n",
"\n",
"label_0 = [[1], [0]]\n",
"label_1 = [[0], [1]]\n",
"state_labels = np.array([label_0, label_1], requires_grad=False)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "NqAg65FbTnyx"
},
"source": [
"Simple classifier with data reloading and fidelity loss\n",
"=======================================================\n"
]
},
{
"cell_type": "code",
"execution_count": 168,
"metadata": {
"id": "ZyKIWD9bTnyx"
},
"outputs": [],
"source": [
"dev = qml.device(\"lightning.qubit\", wires=1)\n",
"# Install any pennylane-plugin to run on some particular backend\n",
"\n",
"\n",
"@qml.qnode(dev, interface=\"autograd\")\n",
"def qcircuit(params, x, y):\n",
" \"\"\"A variational quantum circuit representing the Universal classifier.\n",
"\n",
" Args:\n",
" params (array[float]): array of parameters\n",
" x (array[float]): single input vector\n",
" y (array[float]): single output state density matrix\n",
"\n",
" Returns:\n",
" float: fidelity between output state and input\n",
" \"\"\"\n",
" for p in params:\n",
" qml.Rot(*x, wires=0)\n",
" qml.Rot(*p, wires=0)\n",
" return qml.expval(qml.Hermitian(y, wires=[0]))\n",
"\n",
"\n",
"def cost(params, x, y, state_labels=None):\n",
" \"\"\"Cost function to be minimized.\n",
"\n",
" Args:\n",
" params (array[float]): array of parameters\n",
" x (array[float]): 2-d array of input vectors\n",
" y (array[float]): 1-d array of targets\n",
" state_labels (array[float]): array of state representations for labels\n",
"\n",
" Returns:\n",
" float: loss value to be minimized\n",
" \"\"\"\n",
" # Compute prediction for each input in data batch\n",
" loss = 0.0\n",
" dm_labels = [density_matrix(s) for s in state_labels]\n",
" for i in range(len(x)):\n",
" f = qcircuit(params, x[i], dm_labels[y[i]])\n",
" loss = loss + (1 - f) ** 2\n",
" return loss / len(x)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "3Bz83H0xTnyx"
},
"source": [
"Utility functions for testing and creating batches\n",
"==================================================\n"
]
},
{
"cell_type": "code",
"execution_count": 169,
"metadata": {
"id": "i1-TLseuTnyx"
},
"outputs": [],
"source": [
"def test(params, x, y, state_labels=None):\n",
" \"\"\"\n",
" Tests on a given set of data.\n",
"\n",
" Args:\n",
" params (array[float]): array of parameters\n",
" x (array[float]): 2-d array of input vectors\n",
" y (array[float]): 1-d array of targets\n",
" state_labels (array[float]): 1-d array of state representations for labels\n",
"\n",
" Returns:\n",
" predicted (array([int]): predicted labels for test data\n",
" output_states (array[float]): output quantum states from the circuit\n",
" \"\"\"\n",
" fidelity_values = []\n",
" dm_labels = [density_matrix(s) for s in state_labels]\n",
" predicted = []\n",
"\n",
" for i in range(len(x)):\n",
" fidel_function = lambda y: qcircuit(params, x[i], y)\n",
" fidelities = [fidel_function(dm) for dm in dm_labels]\n",
" best_fidel = np.argmax(fidelities)\n",
"\n",
" predicted.append(best_fidel)\n",
" fidelity_values.append(fidelities)\n",
"\n",
" return np.array(predicted), np.array(fidelity_values)\n",
"\n",
"\n",
"def accuracy_score(y_true, y_pred):\n",
" \"\"\"Accuracy score.\n",
"\n",
" Args:\n",
" y_true (array[float]): 1-d array of targets\n",
" y_predicted (array[float]): 1-d array of predictions\n",
" state_labels (array[float]): 1-d array of state representations for labels\n",
"\n",
" Returns:\n",
" score (float): the fraction of correctly classified samples\n",
" \"\"\"\n",
" score = y_true == y_pred\n",
" return score.sum() / len(y_true)\n",
"\n",
"\n",
"def iterate_minibatches(inputs, targets, batch_size):\n",
" \"\"\"\n",
" A generator for batches of the input data\n",
"\n",
" Args:\n",
" inputs (array[float]): input data\n",
" targets (array[float]): targets\n",
"\n",
" Returns:\n",
" inputs (array[float]): one batch of input data of length `batch_size`\n",
" targets (array[float]): one batch of targets of length `batch_size`\n",
" \"\"\"\n",
" for start_idx in range(0, inputs.shape[0] - batch_size + 1, batch_size):\n",
" idxs = slice(start_idx, start_idx + batch_size)\n",
" yield inputs[idxs], targets[idxs]"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "B5s1nRL2Tnyy"
},
"source": [
"Train a quantum classifier on the circle dataset\n",
"================================================\n"
]
},
{
"cell_type": "code",
"execution_count": 170,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "NqJGMjbpTnyy",
"outputId": "e017ec5c-471b-4863-b472-b022c2bdf32c"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Epoch: 0 | Cost: 0.415535 | Train accuracy: 0.460000 | Test Accuracy: 0.448500\n",
"Epoch: 1 | Loss: 0.125441 | Train accuracy: 0.855000 | Test accuracy: 0.809000\n",
"Epoch: 2 | Loss: 0.158179 | Train accuracy: 0.725000 | Test accuracy: 0.691500\n",
"Epoch: 3 | Loss: 0.146359 | Train accuracy: 0.805000 | Test accuracy: 0.794500\n",
"Epoch: 4 | Loss: 0.131897 | Train accuracy: 0.770000 | Test accuracy: 0.763500\n",
"Epoch: 5 | Loss: 0.129102 | Train accuracy: 0.830000 | Test accuracy: 0.786000\n",
"Epoch: 6 | Loss: 0.132443 | Train accuracy: 0.805000 | Test accuracy: 0.807000\n",
"Epoch: 7 | Loss: 0.115615 | Train accuracy: 0.815000 | Test accuracy: 0.792000\n",
"Epoch: 8 | Loss: 0.117939 | Train accuracy: 0.865000 | Test accuracy: 0.824500\n",
"Epoch: 9 | Loss: 0.135877 | Train accuracy: 0.785000 | Test accuracy: 0.771500\n",
"Epoch: 10 | Loss: 0.108541 | Train accuracy: 0.880000 | Test accuracy: 0.844500\n"
]
}
],
"source": [
"# Generate training and test data\n",
"num_training = 200\n",
"num_test = 2000\n",
"\n",
"Xdata, y_train = circle(num_training)\n",
"X_train = np.hstack((Xdata, np.zeros((Xdata.shape[0], 1), requires_grad=False)))\n",
"\n",
"Xtest, y_test = circle(num_test)\n",
"X_test = np.hstack((Xtest, np.zeros((Xtest.shape[0], 1), requires_grad=False)))\n",
"\n",
"\n",
"# Train using Adam optimizer and evaluate the classifier\n",
"num_layers = 3\n",
"learning_rate = 0.62\n",
"epochs = 10\n",
"batch_size = 32\n",
"\n",
"opt = AdamOptimizer(learning_rate, beta1=0.9, beta2=0.999)\n",
"\n",
"# initialize random weights\n",
"params = np.random.uniform(size=(num_layers, 3), requires_grad=True)\n",
"\n",
"predicted_train, fidel_train = test(params, X_train, y_train, state_labels)\n",
"accuracy_train = accuracy_score(y_train, predicted_train)\n",
"\n",
"predicted_test, fidel_test = test(params, X_test, y_test, state_labels)\n",
"accuracy_test = accuracy_score(y_test, predicted_test)\n",
"\n",
"# save predictions with random weights for comparison\n",
"initial_predictions = predicted_test\n",
"\n",
"loss = cost(params, X_test, y_test, state_labels)\n",
"\n",
"print(\n",
" \"Epoch: {:2d} | Cost: {:3f} | Train accuracy: {:3f} | Test Accuracy: {:3f}\".format(\n",
" 0, loss, accuracy_train, accuracy_test\n",
" )\n",
")\n",
"\n",
"for it in range(epochs):\n",
" for Xbatch, ybatch in iterate_minibatches(X_train, y_train, batch_size=batch_size):\n",
" params, _, _, _ = opt.step(cost, params, Xbatch, ybatch, state_labels)\n",
"\n",
" predicted_train, fidel_train = test(params, X_train, y_train, state_labels)\n",
" accuracy_train = accuracy_score(y_train, predicted_train)\n",
" loss = cost(params, X_train, y_train, state_labels)\n",
"\n",
" predicted_test, fidel_test = test(params, X_test, y_test, state_labels)\n",
" accuracy_test = accuracy_score(y_test, predicted_test)\n",
" res = [it + 1, loss, accuracy_train, accuracy_test]\n",
" print(\n",
" \"Epoch: {:2d} | Loss: {:3f} | Train accuracy: {:3f} | Test accuracy: {:3f}\".format(\n",
" *res\n",
" )\n",
" )"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "YWspC-9BTnyy"
},
"source": [
"Results\n",
"=======\n"
]
},
{
"cell_type": "code",
"execution_count": 171,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 399
},
"id": "ZPszGYA3Tnyy",
"outputId": "fc7a5571-c1a4-4e74-add9-df69ecade42e"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Cost: 0.108541 | Train accuracy 0.880000 | Test Accuracy : 0.844500\n",
"Learned weights\n",
"Layer 0: [-0.15834625 1.10613644 -0.19950019]\n",
"Layer 1: [0.5521213 0.83936582 0.45552379]\n",
"Layer 2: [ 2.49297762 -1.18364848 0.32099704]\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1000x300 with 3 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"print(\n",
" \"Cost: {:3f} | Train accuracy {:3f} | Test Accuracy : {:3f}\".format(\n",
" loss, accuracy_train, accuracy_test\n",
" )\n",
")\n",
"\n",
"print(\"Learned weights\")\n",
"for i in range(num_layers):\n",
" print(\"Layer {}: {}\".format(i, params[i]))\n",
"\n",
"\n",
"fig, axes = plt.subplots(1, 3, figsize=(10, 3))\n",
"plot_data(X_test, initial_predictions, fig, axes[0])\n",
"plot_data(X_test, predicted_test, fig, axes[1])\n",
"plot_data(X_test, y_test, fig, axes[2])\n",
"axes[0].set_title(\"Predictions with random weights\")\n",
"axes[1].set_title(\"Predictions after training\")\n",
"axes[2].set_title(\"True test data\")\n",
"plt.tight_layout()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "sYQWz6IdTnyy"
},
"source": [
"References\n",
"==========\n",
"\n",
"\\[1\\] Pérez-Salinas, Adrián, et al. \\\"Data re-uploading for a universal\n",
"quantum classifier.\\\" arXiv preprint arXiv:1907.02085 (2019).\n",
"\n",
"\\[2\\] Kingma, Diederik P., and Ba, J. \\\"Adam: A method for stochastic\n",
"optimization.\\\" arXiv preprint arXiv:1412.6980 (2014).\n",
"\n",
"\\[3\\] Liu, Dong C., and Nocedal, J. \\\"On the limited memory BFGS method\n",
"for large scale optimization.\\\" Mathematical programming 45.1-3 (1989):\n",
"503-528.\n",
"\n",
"About the author\n",
"================\n"
]
},
{
"cell_type": "code",
"source": [
"seconds = time.time()\n",
"print(\"Time in seconds since end of run:\", seconds)\n",
"local_time = time.ctime(seconds)\n",
"print(local_time)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "8FGVwF_QUYza",
"outputId": "b66ad6f0-9716-4141-d6be-421b7b00f8ee"
},
"execution_count": 172,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Time in seconds since end of run: 1696832821.05739\n",
"Mon Oct 9 06:27:01 2023\n"
]
}
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.9.18"
},
"colab": {
"provenance": []
}
},
"nbformat": 4,
"nbformat_minor": 0
}