From e26f0769e1bf2006e4646d297ea9517460660611 Mon Sep 17 00:00:00 2001 From: ShivaniRajput11 Date: Wed, 12 Jul 2023 21:17:50 +0530 Subject: [PATCH] Tutorial for data reuploading classifier Signed-off-by: Shivani Rajput --- .../13_data_reuploading_classifier.ipynb | 904 ++++++++++++++++++ 1 file changed, 904 insertions(+) create mode 100644 docs/tutorials/13_data_reuploading_classifier.ipynb diff --git a/docs/tutorials/13_data_reuploading_classifier.ipynb b/docs/tutorials/13_data_reuploading_classifier.ipynb new file mode 100644 index 000000000..4583c52b1 --- /dev/null +++ b/docs/tutorials/13_data_reuploading_classifier.ipynb @@ -0,0 +1,904 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "53ffe049", + "metadata": {}, + "source": [ + "# TUTORIAL" + ] + }, + { + "cell_type": "markdown", + "id": "eef044f6", + "metadata": {}, + "source": [ + "# Implement Date-reuploading classifier in Qiskit Machine Learning" + ] + }, + { + "cell_type": "markdown", + "id": "ce94fac5", + "metadata": {}, + "source": [ + "## 1. Introduction " + ] + }, + { + "cell_type": "markdown", + "id": "65ea6a63", + "metadata": {}, + "source": [ + "The data re-uploading , \"**re-uploading**\" refers to the process of repeatedly encoding the input data into the quantum state. The input data is re-uploaded into the quantum circuit at multiple layers or stages of the network. \n", + "\n" + ] + }, + { + "attachments": { + "Screenshot%20%28144%29.png": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "id": "23b97c63", + "metadata": {}, + "source": [ + "\n", + "![Screenshot%20%28144%29.png](attachment:Screenshot%20%28144%29.png)\n", + "\n", + "**Figure 1**: *Simplified working schemes of a neural network and a single-qubit quantum classifier with data re-uploading. Image taken from the reference ([1](https://arxiv.org/abs/1907.02085))*\n" + ] + }, + { + "cell_type": "markdown", + "id": "5d635534", + "metadata": {}, + "source": [ + "## 2. Encoding the Data" + ] + }, + { + "cell_type": "markdown", + "id": "04d2931c", + "metadata": {}, + "source": [ + "A product of free single-qubit unitaries can be written with another single-qubit unitary \n", + "\n", + "**$U(\\vec{\\varphi}_1) \\ldots U(\\vec{\\varphi}_n) \\equiv U(\\vec{\\varphi})$**\n", + "\n", + "But , it is insufficient to carry out any non-trivial task\n", + "\n", + "So we need to adopt technique called **data re-uploading**. If we add some fixed parameter dependency, the operation becomes flexible and data-depedent.\n", + "\n", + "**$U(\\vec{\\varphi}, \\vec{x}) \\equiv U(\\vec{\\varphi}_N)U(\\vec{x}) \\ldots U(\\vec{\\varphi}_1)U(\\vec{x})$**\n" + ] + }, + { + "cell_type": "markdown", + "id": "6b278464", + "metadata": {}, + "source": [ + "## 3. Data Reuploading Layers" + ] + }, + { + "cell_type": "markdown", + "id": "d32ab714", + "metadata": {}, + "source": [ + "### Single Qubit Classifier" + ] + }, + { + "attachments": { + "Screenshot%20%28146%29.png": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "id": "63a19f23", + "metadata": {}, + "source": [ + "![Screenshot%20%28146%29.png](attachment:Screenshot%20%28146%29.png)\n", + "**Figure 2**: *Single-qubit classifier with data re-uploading.The quantum circuit is divided into layer gates L(i),which constitutes the classifier building blocks.In the upper circuit, each of these layers is composed of a U ($\\vec{x}$) gate,which uploads the data,and a parametrized unitary gate U ($\\vec{Φ}$). Image taken from the reference ([1](https://arxiv.org/abs/1907.02085))*" + ] + }, + { + "cell_type": "markdown", + "id": "9609a140", + "metadata": {}, + "source": [ + "**Layers**\n", + "\n", + "The final classification of patterns will come from the results of measurements on $|\\psi\\rangle$. We need to introduce the concept of processing layer as the combination of \n", + "\n", + "$\\boxed{ L(i) \\equiv U(\\vec{\\varphi}_i)U(\\vec{x})} $\n", + "\n", + "This will equivalent to the below structure:\n", + "\n", + "**$\\boxed{U(\\vec{\\varphi}, \\vec{x}) = L(N) L(N-1) \\ldots L(2)L(1)}$**\n", + "\n", + "\n", + "Then,a layer would only need a single rotation to introduce data and tunable parameters,$L(i) = U(\\vec{\\phi}, \\vec{x})$.In addition,each data point can be uploaded with some weight **$ w_i$**.\n", + "\n", + "**$ L(i) = U(\\vec{\\phi}, \\vec{x})$** -----> **U($\\vec{\\theta}_i $ + $\\vec{w}$ $\\cdot$ $\\vec{x}$)**\n", + "\n", + "$\\boxed{L(i) = U(\\vec{\\theta}^{(k)}_i + \\vec{w}^{(k)}_i\\cdot \\vec{x}^{(k)})....... U(\\vec{\\theta}^{(1)}_i + \\vec{w}^{(1)}_i \\cdot \\vec{x}^{(1)})}$\n", + "\n", + "$U(\\theta) = R_x(\\theta_x)R_y(\\theta_y)R_z(\\theta_z) \\vec{\\theta}$\n", + "\n", + "where $\\theta = (\\theta_x, \\theta_y, \\theta_z) \\vec{w}$, $w = (w_x, w_y, w_z)$, $\\vec{x}$ represents the input data, $N$ represents the number of layers." + ] + }, + { + "cell_type": "markdown", + "id": "b446dda9", + "metadata": {}, + "source": [ + "### Multi Qubit Quantum Classifier" + ] + }, + { + "cell_type": "markdown", + "id": "410d2bfe", + "metadata": {}, + "source": [ + "We need to introduce **entanglement** (therefore, more qubits) to eventually prove any quantum advantage." + ] + }, + { + "attachments": { + "Screenshot%20%28148%29.png": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "id": "31848083", + "metadata": {}, + "source": [ + "![Screenshot%20%28148%29.png](attachment:Screenshot%20%28148%29.png)\n", + "**Figure 3** : *Two-qubit quantum classifier circuit without entanglement(topcircuit)and with entanglement(bottom circuit).Here, each layer includes a rotation with data reuploading in both qubits plus a CZgate if there is entanglement.The exception is the last layer,which does not have any CZ gate associated to it.Image taken from the reference ([1](https://arxiv.org/abs/1907.02085))*" + ] + }, + { + "cell_type": "markdown", + "id": "e05aeaa7", + "metadata": {}, + "source": [ + "Structure:\n", + "\n", + "**$\\boxed {U(\\vec{\\phi}, \\vec{x}) = L(N) \\ E \\ L(N-1) \\ E \\ \\ldots \\, E \\ L(2) \\ E \\ L(1)}$**\n", + "\n", + "NOTE: *Linear Entanglement*\n" + ] + }, + { + "cell_type": "markdown", + "id": "9532ab95", + "metadata": {}, + "source": [ + "## 4.Training/Optimization\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "17d277cb", + "metadata": {}, + "source": [ + "**Training** and **Optimization** of the quantum circuit require careful consideration of the framework and integration with Qiskit Machine Learning's Quantum Neural Network (`QNN`) implementation. In this scenario, `PyTorch` is chosen as the training framework, and it is integrated with Qiskit using the `TorchConnector` feature.\n", + "\n", + "By utilizing `PyTorch`, we can leverage its extensive functionality to train and optimize the quantum circuit effectively.\n", + "\n", + "Qiskit Machine Learning offers the `EstimatorQNN` and `SamplerQNN` components, specifically designed for working with quantum neural networks. \n", + "\n", + "The `TorchConnector` feature in `Qiskit` serves as a bridge between `PyTorch` and `Qiskit`, facilitating the integration process. It allows us to use `PyTorch` as the underlying framework for **training** and **optimization** while taking advantage of the `QNN` implementation provided by **Qiskit Machine Learning**. \n" + ] + }, + { + "cell_type": "markdown", + "id": "2d393cbe", + "metadata": {}, + "source": [ + "--------------------------------------------------------------------------------------------------------------------------------" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "6a0ee78e", + "metadata": {}, + "outputs": [], + "source": [ + "from qiskit.circuit import QuantumCircuit, ParameterVector\n", + "from qiskit.utils import algorithm_globals\n", + "from qiskit.circuit import Parameter\n", + "from qiskit.circuit.library import RealAmplitudes, ZZFeatureMap, TwoLocal\n", + "from qiskit_machine_learning.neural_networks import SamplerQNN, EstimatorQNN\n", + "from qiskit_machine_learning.connectors import TorchConnector\n", + "\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from torch import Tensor\n", + "from torch.nn import Linear, CrossEntropyLoss, MSELoss\n", + "from torch.optim import LBFGS" + ] + }, + { + "cell_type": "markdown", + "id": "f13adf51", + "metadata": {}, + "source": [ + "--------------------------------------------------------------------------------------------------------------------------------" + ] + }, + { + "cell_type": "markdown", + "id": "4a6bb92e", + "metadata": {}, + "source": [ + "### Set up" + ] + }, + { + "cell_type": "markdown", + "id": "f88f44fe", + "metadata": {}, + "source": [ + "The code provided defines a class called `DataReuploading` which represents a quantum circuit ansatz, and contains **rotational** and **entanglement** layers alternatively.The constructor takes three parameters: `num_qubits`, `num_features`, and `num_layers`.\n", + "\n", + "The number of features (`num_features`) is rounded up to the nearest multiple of 3 . This ensures that the number of features is divisible by 3, which is a requirement for the **rotational** gate layer.\n", + "\n", + "Two ParameterVector objects are created: `self.parameters` and `self.input_params`. \n", + "\n", + "`self.parameters` represents the *trainable* parameters of the circuit. \n", + "\n", + "`self.input_params` represents the *input* parameters of the circuit.\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "f9bacd89", + "metadata": {}, + "outputs": [], + "source": [ + "class DataReuploading():\n", + " \"\"\"\n", + " Create the Data Reuploading Classifier ansatz.\n", + "\n", + " \n", + " \"\"\"\n", + "\n", + " def __init__(\n", + " self,\n", + " num_qubits: int = None,\n", + " num_features: int = None,\n", + " num_layers: int = None\n", + " ):\n", + " \"\"\"\n", + " Args:\n", + " num_qubits: The number of qubits.\n", + " num_features: The number of input features (the dimension of the input data).\n", + " num_layers: The number of layers (N).\n", + " Returns:\n", + " ansatz: A QuantumCircuit object.\n", + " \"\"\"\n", + "\n", + " self._num_qubits = num_qubits\n", + " # rounding up the number of features to the nearest integer number that is multiples of 3\n", + " self._num_features = int(np.ceil(num_features/3)*3)\n", + " self._num_layers = num_layers\n", + "\n", + " self.parameters = ParameterVector(name=\"θ\", length=2*self._num_qubits*self._num_features*self._num_layers)\n", + " self.input_params = ParameterVector(name=\"x\", length=self._num_features)\n", + "\n", + " qc = QuantumCircuit(self._num_qubits)\n", + " for l in range(self._num_layers):\n", + " for k in range(int(np.ceil(num_features/3))):\n", + " for q in range(self._num_qubits):\n", + " qc.compose(self.rotational_gate_layer(self._num_qubits, q, self.parameters[l*self._num_qubits*int(np.ceil(num_features/3))*2*3 + q*int(np.ceil(num_features/3))*2*3 + k*2*3 : l*self._num_qubits*int(np.ceil(num_features/3))*2*3 + q*int(np.ceil(num_features/3))*2*3 + k*2*3 + 2*3], self.input_params[k*3 : k*3+3]), inplace=True)\n", + "\n", + " qc.barrier()\n", + " \n", + " # if it's not the last layer, add the entanglement\n", + " if (l+1) != self._num_layers and self._num_qubits != 1:\n", + " qc.compose(self.entanglement_layer(self._num_qubits), inplace=True)\n", + " qc.barrier()\n", + "\n", + " self.circuit = qc\n", + " \n", + " \n", + " def rotational_gate_layer(\n", + " self,\n", + " num_qubits: int = None,\n", + " qubit_id: int = None,\n", + " trainable_params : ParameterVector = None,\n", + " input_params : ParameterVector = None\n", + " ):\n", + " circuit_block = QuantumCircuit(num_qubits)\n", + " circuit_block.rx(trainable_params[0] + trainable_params[3]*input_params[0], qubit_id)\n", + " circuit_block.ry(trainable_params[1] + trainable_params[4]*input_params[1], qubit_id)\n", + " circuit_block.rz(trainable_params[2] + trainable_params[5]*input_params[2], qubit_id)\n", + "\n", + " return circuit_block\n", + " def entanglement_layer(\n", + " self,\n", + " num_qubits: int = None\n", + " ):\n", + " circuit_block = QuantumCircuit(num_qubits)\n", + "\n", + " # Apply CZ gates between adjacent qubits linearly\n", + " for i in range(num_qubits - 1):\n", + " circuit_block.cz(i, i + 1)\n", + "\n", + "\n", + " return circuit_block\n", + " \n", + "\n", + " @property\n", + " def num_qubits(self) -> int:\n", + " \"\"\"Returns the number of qubits used by the ansatz.\"\"\"\n", + " return self._num_qubits\n", + "\n", + " @property\n", + " def num_features(self) -> int:\n", + " \"\"\"Returns the number of features of the input data accepted by the ansatz.\"\"\"\n", + " return self._num_features\n", + "\n", + " @property\n", + " def num_layers(self) -> int:\n", + " \"\"\"Returns the number of layers used by the ansatz.\"\"\"\n", + " return self._num_layers\n", + " \n", + "\n", + " \n", + "\n", + "\n", + " \n", + " \n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "7aada146", + "metadata": {}, + "source": [ + "# Dataset Generation" + ] + }, + { + "cell_type": "markdown", + "id": "9e0ae843", + "metadata": {}, + "source": [ + "Generating and visualizing the circle pattern datasets using sklearn datasets([here](https://scikit-learn.org/stable/datasets/sample_generators.html)) and can be used for further analysis for machine learning models. \n", + "\n", + "*note:noise parameter 0.0*" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "96d6005d", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from sklearn.datasets import make_circles\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# Generate a dataset with a circle pattern\n", + "X_circle, y_circle = make_circles(n_samples=200, noise=0.0, factor=0.5)\n", + "\n", + "# Plot the circle pattern\n", + "plt.scatter(X_circle[:, 0], X_circle[:, 1], c=y_circle)\n", + "plt.title('Circle Pattern')\n", + "plt.show()\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "c31ec532", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(torch.Size([160, 3]),\n", + " torch.Size([160, 1]),\n", + " torch.Size([40, 3]),\n", + " torch.Size([40, 1]),\n", + " torch.Size([160]))" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# zero padding\n", + "\n", + "X_circle = np.pad(X_circle, ((0, 0), (0, 1)))\n", + "\n", + "# convert to torch Tensors\n", + "\n", + "X_circle = Tensor(X_circle)\n", + "y_circle = Tensor(y_circle).reshape(len(y_circle), 1)\n", + "\n", + "\n", + "\n", + "# Train-Test split\n", + "from sklearn.model_selection import train_test_split\n", + "\n", + "X_train, X_test, y_train, y_test = train_test_split(X_circle, y_circle, test_size=0.2, random_state=42)\n", + "\n", + "\n", + "y_train01 = Tensor(y_train).reshape(len(y_train))\n", + "X_train.shape, y_train.shape, X_test.shape, y_test.shape , y_train01.shape " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7c112063", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "7c7c2bbd", + "metadata": {}, + "source": [ + "## Let's check how well the prepared DataReuploading class is working." + ] + }, + { + "cell_type": "markdown", + "id": "5a067e38", + "metadata": {}, + "source": [ + "*Example: let's take the `num_qubits` and `num_features` **2** and the `num_layers` **9** and passed these three parameters to the constructed `DataReuploading` class*.\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "9ad62fb6", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "DRC = DataReuploading(num_qubits=2, num_features=2, num_layers = 9)\n", + "DRC.circuit.draw('mpl')\n", + " " + ] + }, + { + "cell_type": "markdown", + "id": "30ada363", + "metadata": {}, + "source": [ + "--------------------------------------------------------------------------------------------------------------------------------" + ] + }, + { + "cell_type": "markdown", + "id": "bed59806", + "metadata": {}, + "source": [ + "# Classification with Estimator QNN / Sampler QNN and pytorch" + ] + }, + { + "cell_type": "markdown", + "id": "42f0811a", + "metadata": {}, + "source": [ + "*Integration with QNN implementation of Qiskit Machine Learning (`EstimatorQNN` and `SamplerQNN`)*\n", + "\n", + "*Used `TorchConnector` feature of Qiskit.Connects a Qiskit (Quantum) Neural Network to `PyTorch`.*" + ] + }, + { + "cell_type": "markdown", + "id": "c7eb13fa", + "metadata": {}, + "source": [ + "**Estimator QNN**" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "25b742fb", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "tensor([0.6147], grad_fn=<_TorchNNFunctionBackward>)" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Setup QNN\n", + "qnn1 = EstimatorQNN(\n", + " circuit=DRC.circuit, input_params=DRC.input_params, weight_params=DRC.parameters\n", + ")\n", + "\n", + "# Set up PyTorch module\n", + "model1 = TorchConnector(qnn1)\n", + " \n", + "\n", + "# Test with a single input\n", + "model1(X_train[0, :])\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "2daee66c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "49.51571273803711\n", + "36.08623123168945\n", + "24.9346866607666\n", + "26.76576805114746\n", + "12.875452995300293\n", + "10.740562438964844\n", + "7.955015182495117\n", + "6.020380973815918\n", + "4.713078498840332\n", + "3.9996087551116943\n", + "3.3921408653259277\n", + "2.8623194694519043\n", + "2.5865378379821777\n", + "2.2231757640838623\n", + "1.5752922296524048\n", + "1.9049632549285889\n", + "1.116324543952942\n", + "1.0402249097824097\n", + "0.9560691118240356\n", + "0.8304160833358765\n" + ] + }, + { + "data": { + "text/plain": [ + "tensor(49.5157, grad_fn=)" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "# Define optimizer and loss\n", + "optimizer = LBFGS(model1.parameters())\n", + "f_loss = MSELoss(reduction=\"sum\")\n", + "\n", + "# Start training\n", + "model1.train() # set model to training mode\n", + "\n", + "\n", + "# Note from (https://pytorch.org/docs/stable/optim.html):\n", + "# Some optimization algorithms such as LBFGS need to\n", + "# reevaluate the function multiple times, so you have to\n", + "# pass in a closure that allows them to recompute your model.\n", + "# The closure should clear the gradients, compute the loss,\n", + "# and return it.\n", + "def closure():\n", + " optimizer.zero_grad() # Initialize/clear gradients\n", + " loss = f_loss(model1(X_train), y_train) # Evaluate loss function\n", + " loss.backward() # Backward pass\n", + " print(loss.item()) # Print loss\n", + " return loss\n", + "\n", + "\n", + "# Run optimizer step4\n", + "optimizer.step(closure)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "9f8d1801", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 0.875\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Evaluate model and compute accuracy\n", + "y_predict = []\n", + "for x, y_target in zip(X_test, y_test):\n", + " output = model1(Tensor(x))\n", + " y_predict += [np.sign(output.detach().numpy())[0]]\n", + "\n", + "print(\"Accuracy:\", sum(y_predict == y_test.numpy().reshape(-1,)*2-1) / len(y_test))\n", + "\n", + "# Plot results\n", + "# red == wrongly classified\n", + "for x, y_target, y_p in zip(X_test, y_test.numpy().reshape(-1,)*2-1, y_predict):\n", + " if y_target == 1:\n", + " plt.plot(x[0], x[1], \"bo\")\n", + " else:\n", + " plt.plot(x[0], x[1], \"go\")\n", + " if y_target != y_p:\n", + " plt.scatter(x[0], x[1], s=200, facecolors=\"none\", edgecolors=\"r\", linewidths=2)\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e265a7a7", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "252eb896", + "metadata": {}, + "source": [ + "**Sampler QNN**" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "a2cd26b7", + "metadata": {}, + "outputs": [], + "source": [ + "y_train01 = y_train01.long() " + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "bcfc134f", + "metadata": {}, + "outputs": [], + "source": [ + "qnn2 = SamplerQNN(\n", + " circuit=DRC.circuit, input_params=DRC.input_params, weight_params=DRC.parameters\n", + " \n", + ")\n", + "model2 = TorchConnector(qnn2)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "04e9683d", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1.4023065567016602\n", + "1.36484694480896\n", + "1.4456677436828613\n", + "1.4079097509384155\n", + "1.319462537765503\n", + "1.362990140914917\n", + "1.2540619373321533\n", + "1.2891684770584106\n", + "1.1489008665084839\n", + "1.1184463500976562\n", + "1.081809401512146\n", + "1.0144281387329102\n", + "0.9817455410957336\n", + "0.9635218381881714\n", + "0.9541428685188293\n", + "0.9275864362716675\n", + "0.9190753102302551\n", + "0.9020005464553833\n", + "0.8918275833129883\n", + "0.8830900192260742\n" + ] + } + ], + "source": [ + "# Define model, optimizer, and loss\n", + "optimizer = LBFGS(model2.parameters())\n", + "f_loss = CrossEntropyLoss() # Our output will be in the [0,1] range\n", + "\n", + "# Start training\n", + "model2.train()\n", + "\n", + "# Define LBFGS closure method (explained in previous section)\n", + "def closure():\n", + " optimizer.zero_grad(set_to_none=True) # Initialize gradient\n", + " loss = f_loss(model2(X_train), y_train01) # Calculate loss\n", + " loss.backward() # Backward pass\n", + "\n", + " print(loss.item()) # Print loss\n", + " return loss\n", + "\n", + "\n", + "# Run optimizer (LBFGS requires closure)\n", + "optimizer.step(closure);" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "942949e5", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy: 0.525\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Evaluate model and compute accuracy\n", + "y_predict = []\n", + "for x, y_target in zip(X_test, y_test):\n", + " output = model2(Tensor(x))\n", + " y_predict += [np.sign(output.detach().numpy())[0]]\n", + "\n", + "print(\"Accuracy:\", sum(y_predict == y_test.numpy().reshape(-1,)*2-1) / len(y_test))\n", + "\n", + "# Plot results\n", + "# red == wrongly classified\n", + "for x, y_target, y_p in zip(X_test, y_test.numpy().reshape(-1,)*2-1, y_predict):\n", + " if y_target == 1:\n", + " plt.plot(x[0], x[1], \"bo\")\n", + " else:\n", + " plt.plot(x[0], x[1], \"go\")\n", + " if y_target != y_p:\n", + " plt.scatter(x[0], x[1], s=200, facecolors=\"none\", edgecolors=\"r\", linewidths=2)\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "0ce493cf", + "metadata": {}, + "source": [ + "--------------------------------------------------------------------------------------------------------------------------------" + ] + }, + { + "cell_type": "markdown", + "id": "b4751f6e", + "metadata": {}, + "source": [ + "# Reference" + ] + }, + { + "cell_type": "markdown", + "id": "bfafdf4c", + "metadata": {}, + "source": [ + "**[1]** *PĂ©rez-Salinas et al.Data re-uploading for a universal quantum classsifier,(2019)[https://arxiv.org/abs/1907.02085]*\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "0dfdd91b", + "metadata": {}, + "source": [ + "# Conclusion" + ] + }, + { + "cell_type": "markdown", + "id": "b4ffd2b3", + "metadata": {}, + "source": [ + "In this tutorial, we prepared a Data re-uploading(ansatz) class, which uses a quantum circuit with a series of data re-uploading and processing layers. Unlike the conventional quantum circuit of quantum neural network, it has multiple layers of re-uploading input data. We implemented the data re-uploading quantum neural network in Qiskit Machine Learning.\n", + "\n", + "We now encourage you to play around and see how different numbers of `qubits`, `features`, and `layers` parameters and evaluate the performance of the model with different datasets." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "73ae762f", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "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": "3.9.13" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}