532 lines (532 with data), 211.7 kB
{
"cells": [
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "eI_d8C3_Tnyu",
"outputId": "690a11c1-599f-44b0-db88-ed5a7292b1b0"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Time in seconds since beginning of run: 1696874946.7993512\n",
"Mon Oct 9 18:09:06 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": 10,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 388
},
"id": "lScQSFsjTnyw",
"outputId": "c7342693-3585-4389-9941-b60c173040cb"
},
"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": 11,
"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": 12,
"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": 13,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "NqJGMjbpTnyy",
"outputId": "1b1ae4f6-bc01-458a-e83a-9b43c7bad01d"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Epoch: 0 | Cost: 0.432906 | Train accuracy: 0.437150 | Test Accuracy: 0.436600\n",
"Epoch: 1 | Loss: 0.137655 | Train accuracy: 0.789750 | Test accuracy: 0.790385\n",
"Epoch: 2 | Loss: 0.133815 | Train accuracy: 0.811950 | Test accuracy: 0.813110\n",
"Epoch: 3 | Loss: 0.133554 | Train accuracy: 0.814000 | Test accuracy: 0.815350\n",
"Epoch: 4 | Loss: 0.132577 | Train accuracy: 0.814300 | Test accuracy: 0.815630\n",
"Epoch: 5 | Loss: 0.131819 | Train accuracy: 0.812950 | Test accuracy: 0.814990\n",
"Epoch: 6 | Loss: 0.132018 | Train accuracy: 0.811000 | Test accuracy: 0.813140\n",
"Epoch: 7 | Loss: 0.132240 | Train accuracy: 0.810950 | Test accuracy: 0.812960\n",
"Epoch: 8 | Loss: 0.132322 | Train accuracy: 0.810900 | Test accuracy: 0.813035\n",
"Epoch: 9 | Loss: 0.132379 | Train accuracy: 0.810750 | Test accuracy: 0.813040\n",
"Epoch: 10 | Loss: 0.132397 | Train accuracy: 0.810850 | Test accuracy: 0.813050\n"
]
}
],
"source": [
"# Generate training and test data\n",
"num_training = 20000\n",
"num_test = 200000\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 = 0.48\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": 14,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 399
},
"id": "ZPszGYA3Tnyy",
"outputId": "a48e5481-41b0-481d-e606-008855f84a87"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Cost: 0.132397 | Train accuracy 0.810850 | Test Accuracy : 0.813050\n",
"Learned weights\n",
"Layer 0: [-0.47066371 1.38638534 0.12151584]\n",
"Layer 1: [-1.92712429 0.22904365 0.39878692]\n",
"Layer 2: [0.91544545 1.61403136 0.51966469]\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": {
"id": "8FGVwF_QUYza",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"outputId": "86f78281-e6ef-43ab-eada-678ca8a57ee4"
},
"execution_count": 15,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Time in seconds since end of run: 1696901138.0821452\n",
"Tue Oct 10 01:25:38 2023\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"from google.colab import runtime\n",
"runtime.unassign()"
],
"metadata": {
"id": "_bhu6bcJOBH4"
},
"execution_count": null,
"outputs": []
}
],
"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
}