{ "cells": [ { "cell_type": "markdown", "id": "brilliant-cross", "metadata": {}, "source": [ "# Quantum Neural Networks\n", "\n", "## Overview\n", "This notebook demonstrates different quantum neural network (QNN) implementations provided in `qiskit-machine-learning`, and how they can be integrated into basic quantum machine learning (QML) workflows.\n", "\n", "The tutorial is structured as follows:\n", "\n", "1. [Introduction](#1.-Introduction)\n", "2. [How to Instantiate QNNs](#2.-How-to-Instantiate-QNNs)\n", "3. [How to Run a Forward Pass](#3.-How-to-Run-a-Forward-Pass)\n", "4. [How to Run a Backward Pass](#4.-How-to-Run-a-Backward-Pass)\n", "5. [Advanced Functionality](#5.-Advanced-Functionality)\n", "6. [Conclusion](#6.-Conclusion)" ] }, { "attachments": { "new_qnn-3.jpg": { "image/jpeg": "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" } }, "cell_type": "markdown", "id": "efb9083a", "metadata": {}, "source": [ "## 1. Introduction\n", "\n", "### 1.1. Quantum vs. Classical Neural Networks\n", "\n", "Classical neural networks are algorithmic models inspired by the human brain that can be trained to recognize patterns in data and learn to solve complex problems. They are based on a series of interconnected nodes, or *neurons*, organized in a layered structure, with parameters that can be learned by applying machine or deep learning training strategies.\n", "\n", "The motivation behind quantum machine learning (QML) is to integrate notions from quantum computing and classical machine learning to open the way for new and improved learning schemes. QNNs apply this generic principle by combining classical neural networks and parametrized quantum circuits. Because they lie at an intersection between two fields, QNNs can be viewed from two perspectives:\n", "\n", "- From a **machine learning perspective**, QNNs are, once again, algorithmic models that can be trained to find hidden patterns in data in a similar manner to their classical counterparts. These models can **load** classical data (**inputs**) into a quantum state, and later **process** it with quantum gates parametrized by **trainable weights**. Figure 1 shows a generic QNN example including the data loading and processing steps. The output from measuring this state can then be plugged into a loss function to train the weights through backpropagation.\n", "\n", "- From a **quantum computing perspective**, QNNs are quantum algorithms based on parametrized quantum circuits that can be trained in a variational manner using classical optimizers. These circuits contain a **feature map** (with input parameters) and an **ansatz** (with trainable weights), as seen in Figure 1.\n", "\n", "![new_qnn-3.jpg](attachment:new_qnn-3.jpg)\n", "\n", "\n", "*Figure 1. Generic quantum neural network (QNN) structure.*" ] }, { "cell_type": "markdown", "id": "f47d2070", "metadata": {}, "source": [ "As you can see, these two perspectives are complementary, and do not necessarily rely on strict definitions of concepts such as \"quantum neuron\" or what constitutes a QNN's \"layer\".\n", "\n", "### 1.2. Implementation in `qiskit-machine-learning`\n", "\n", "The QNNs in `qiskit-machine-learning` are meant as application-agnostic computational units that can be used for different use cases, and their setup will depend on the application they are needed for. The module contains an interface for the QNNs and two specific implementations:\n", "\n", "1. [NeuralNetwork](https://qiskit.org/ecosystem/machine-learning/stubs/qiskit_machine_learning.neural_networks.NeuralNetwork.html): The interface for neural networks. This is an abstract class all QNNs inherit from.\n", "2. [EstimatorQNN](https://qiskit.org/ecosystem/machine-learning/stubs/qiskit_machine_learning.neural_networks.EstimatorQNN.html): A network based on the evaluation of quantum mechanical observables.\n", "3. [SamplerQNN](https://qiskit.org/ecosystem/machine-learning/locale/fr_FR/stubs/qiskit_machine_learning.neural_networks.SamplerQNN.html): A network based on the samples resulting from measuring a quantum circuit.\n", "\n", "\n", "These implementations are based on the [qiskit primitives](https://qiskit.org/documentation/apidoc/primitives.html). The primitives are the entry point to run QNNs on either a simulator or real quantum hardware. Each implementation, `EstimatorQNN` and `SamplerQNN`, takes in an optional instance of its corresponding primitive, which can be any subclass of `BaseEstimator` and `BaseSampler`, respectively.\n", "\n", "The `qiskit.primitives` module provides a reference implementation for the `Sampler` and `Estimator` classes to run statevector simulations. By default, if no instance is passed to a QNN class, an instance of the corresponding reference primitive (`Sampler` or `Estimator`) is created automatically by the network.\n", "For more information about primitives please refer to the [primitives documentation](https://qiskit.org/documentation/apidoc/primitives.html).\n", "\n", "The `NeuralNetwork` class is the interface for all QNNs available in `qiskit-machine-learning`.\n", "It exposes a forward and a backward pass that take data samples and trainable weights as input.\n", "\n", "It's important to note that `NeuralNetwork`s are \"stateless\". They do not contain any training capabilities (these are pushed to the actual algorithms or applications: [classifiers](https://qiskit.org/ecosystem/machine-learning/apidocs/qiskit_machine_learning.algorithms.html#classifiers), [regressors](https://qiskit.org/ecosystem/machine-learning/apidocs/qiskit_machine_learning.algorithms.html#regressors), etc), nor do they store the values for trainable weights." ] }, { "cell_type": "markdown", "id": "ba316207", "metadata": {}, "source": [ "***\n", "\n", "Let's now look into specific examples for the two `NeuralNetwork` implementations. But first, let's set the algorithmic seed to ensure that the results don't change between runs." ] }, { "cell_type": "code", "execution_count": 25, "id": "annual-engine", "metadata": {}, "outputs": [], "source": [ "from qiskit_algorithms.utils import algorithm_globals\n", "\n", "algorithm_globals.random_seed = 42" ] }, { "cell_type": "markdown", "id": "billion-uniform", "metadata": {}, "source": [ "## 2. How to Instantiate QNNs\n", "\n", "### 2.1. `EstimatorQNN`\n", "\n", "The `EstimatorQNN` takes in a parametrized quantum circuit as input, as well as an optional quantum mechanical observable, and outputs expectation value computations for the forward pass. The `EstimatorQNN` also accepts lists of observables to construct more complex QNNs.\n", "\n", "Let's see an `EstimatorQNN` in action with a simple example. We start by constructing the parametrized circuit. This quantum circuit has two parameters, one represents a QNN input and the other represents a trainable weight:" ] }, { "cell_type": "code", "execution_count": 26, "id": "popular-artwork", "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from qiskit.circuit import Parameter\n", "from qiskit import QuantumCircuit\n", "\n", "params1 = [Parameter(\"input1\"), Parameter(\"weight1\")]\n", "qc1 = QuantumCircuit(1)\n", "qc1.h(0)\n", "qc1.ry(params1[0], 0)\n", "qc1.rx(params1[1], 0)\n", "qc1.draw(\"mpl\")" ] }, { "cell_type": "markdown", "id": "crucial-aquatic", "metadata": {}, "source": [ "We can now create an observable to define the expectation value computation. If not set, then the `EstimatorQNN` will automatically create the default observable $Z^{\\otimes n}$. Here, $n$ is the number of qubits of the quantum circuit.\n", "\n", "In this example, we will change things up and use the $Y^{\\otimes n}$ observable:" ] }, { "cell_type": "code", "execution_count": 27, "id": "encouraging-magnitude", "metadata": {}, "outputs": [], "source": [ "from qiskit.quantum_info import SparsePauliOp\n", "\n", "observable1 = SparsePauliOp.from_list([(\"Y\" * qc1.num_qubits, 1)])" ] }, { "cell_type": "markdown", "id": "dd1fb7ea", "metadata": {}, "source": [ "Together with the quantum circuit defined above, and the observable we have created, the `EstimatorQNN` constructor takes in the following keyword arguments:\n", "\n", "- `estimator`: optional primitive instance\n", "- `input_params`: list of quantum circuit parameters that should be treated as \"network inputs\"\n", "- `weight_params`: list of quantum circuit parameters that should be treated as \"network weights\"\n", "\n", "In this example, we previously decided that the first parameter of `params1` should be the input, while the second should be the weight. As we are performing a local statevector simulation, we will not set the `estimator` parameter; the network will create an instance of the reference `Estimator` primitive for us. If we needed to access cloud resources or `Aer` simulators, we would have to define the respective `Estimator` instances and pass them to the `EstimatorQNN`." ] }, { "cell_type": "code", "execution_count": 28, "id": "italian-clear", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from qiskit_machine_learning.neural_networks import EstimatorQNN\n", "\n", "estimator_qnn = EstimatorQNN(\n", " circuit=qc1, observables=observable1, input_params=[params1[0]], weight_params=[params1[1]]\n", ")\n", "estimator_qnn" ] }, { "cell_type": "markdown", "id": "16ecacdb", "metadata": {}, "source": [ "We'll see how to use the QNN in the following sections, but before that, let's check out the `SamplerQNN` class." ] }, { "cell_type": "markdown", "id": "f1ac3811", "metadata": {}, "source": [ "### 2.2. `SamplerQNN`\n", "\n", "The `SamplerQNN` is instantiated in a similar way to the `EstimatorQNN`, but because it directly consumes samples from measuring the quantum circuit, it does not require a custom observable.\n", "\n", "These output samples are interpreted by default as the probabilities of measuring the integer index corresponding to a bitstring. However, the `SamplerQNN` also allows us to specify an `interpret` function to post-process the samples. This function should be defined so that it takes a measured integer (from a bitstring) and maps it to a new value, i.e. non-negative integer.\n", "\n", "**(!)** It's important to note that if a custom `interpret` function is defined, the `output_shape` cannot be inferred by the network, and **needs to be provided explicitly**.\n", "\n", "**(!)** It's also important to keep in mind that if no `interpret` function is used, the dimension of the probability vector will scale exponentially with the number of qubits. With a custom `interpret` function, this scaling can change. If, for instance, an index is mapped to the parity of the corresponding bitstring, i.e., to 0 or 1, the result will be a probability vector of length 2 independently of the number of qubits." ] }, { "cell_type": "markdown", "id": "82cc2353", "metadata": {}, "source": [ "Let's create a different quantum circuit for the `SamplerQNN`. In this case, we will have two input parameters and four trainable weights that parametrize a two-local circuit." ] }, { "cell_type": "code", "execution_count": 29, "id": "acceptable-standing", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "input parameters: ['input[0]', 'input[1]']\n", "weight parameters: ['weight[0]', 'weight[1]', 'weight[2]', 'weight[3]']\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from qiskit.circuit import ParameterVector\n", "\n", "inputs2 = ParameterVector(\"input\", 2)\n", "weights2 = ParameterVector(\"weight\", 4)\n", "print(f\"input parameters: {[str(item) for item in inputs2.params]}\")\n", "print(f\"weight parameters: {[str(item) for item in weights2.params]}\")\n", "\n", "qc2 = QuantumCircuit(2)\n", "qc2.ry(inputs2[0], 0)\n", "qc2.ry(inputs2[1], 1)\n", "qc2.cx(0, 1)\n", "qc2.ry(weights2[0], 0)\n", "qc2.ry(weights2[1], 1)\n", "qc2.cx(0, 1)\n", "qc2.ry(weights2[2], 0)\n", "qc2.ry(weights2[3], 1)\n", "\n", "qc2.draw(output=\"mpl\")" ] }, { "cell_type": "markdown", "id": "1e86defb", "metadata": {}, "source": [ "Similarly to the `EstimatorQNN`, we must specify inputs and weights when instantiating the `SamplerQNN`. In this case, the keyword arguments will be:\n", "- `sampler`: optional primitive instance\n", "- `input_params`: list of quantum circuit parameters that should be treated as \"network inputs\"\n", "- `weight_params`: list of quantum circuit parameters that should be treated as \"network weights\"\n", "\n", "Please note that, once again, we are choosing not to set the `Sampler` instance to the QNN and relying on the default." ] }, { "cell_type": "code", "execution_count": 30, "id": "5c007d10", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from qiskit_machine_learning.neural_networks import SamplerQNN\n", "\n", "sampler_qnn = SamplerQNN(circuit=qc2, input_params=inputs2, weight_params=weights2)\n", "sampler_qnn" ] }, { "cell_type": "markdown", "id": "e8c56e76", "metadata": {}, "source": [ "In addition to the basic arguments shown above, the `SamplerQNN` accepts three more settings: `input_gradients`, `interpret`, and `output_shape`. These will be introduced in sections 4 and 5." ] }, { "cell_type": "markdown", "id": "0ac89b99", "metadata": {}, "source": [ "## 3. How to Run a Forward Pass" ] }, { "cell_type": "markdown", "id": "8589abbd", "metadata": {}, "source": [ "### 3.1. Set-Up\n", "In a real setting, the inputs would be defined by the dataset, and the weights would be defined by the training algorithm or as part of a pre-trained model. However, for the sake of this tutorial, we will specify random sets of input and weights of the right dimension:" ] }, { "cell_type": "markdown", "id": "2698406f", "metadata": {}, "source": [ "#### 3.1.1. `EstimatorQNN` Example" ] }, { "cell_type": "code", "execution_count": 31, "id": "beneficial-summary", "metadata": {}, "outputs": [], "source": [ "estimator_qnn_input = algorithm_globals.random.random(estimator_qnn.num_inputs)\n", "estimator_qnn_weights = algorithm_globals.random.random(estimator_qnn.num_weights)" ] }, { "cell_type": "code", "execution_count": 32, "id": "4d5c27e2", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of input features for EstimatorQNN: 1 \n", "Input: [0.77395605]\n", "Number of trainable weights for EstimatorQNN: 1 \n", "Weights: [0.43887844]\n" ] } ], "source": [ "print(\n", " f\"Number of input features for EstimatorQNN: {estimator_qnn.num_inputs} \\nInput: {estimator_qnn_input}\"\n", ")\n", "print(\n", " f\"Number of trainable weights for EstimatorQNN: {estimator_qnn.num_weights} \\nWeights: {estimator_qnn_weights}\"\n", ")" ] }, { "cell_type": "markdown", "id": "81d07341", "metadata": {}, "source": [ "#### 3.1.2. `SamplerQNN` Example" ] }, { "cell_type": "code", "execution_count": 33, "id": "a0fd6253", "metadata": { "scrolled": true }, "outputs": [], "source": [ "sampler_qnn_input = algorithm_globals.random.random(sampler_qnn.num_inputs)\n", "sampler_qnn_weights = algorithm_globals.random.random(sampler_qnn.num_weights)" ] }, { "cell_type": "code", "execution_count": 34, "id": "a008cebc", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of input features for SamplerQNN: 2 \n", "Input: [0.85859792 0.69736803]\n", "Number of trainable weights for SamplerQNN: 4 \n", "Weights: [0.09417735 0.97562235 0.7611397 0.78606431]\n" ] } ], "source": [ "print(\n", " f\"Number of input features for SamplerQNN: {sampler_qnn.num_inputs} \\nInput: {sampler_qnn_input}\"\n", ")\n", "print(\n", " f\"Number of trainable weights for SamplerQNN: {sampler_qnn.num_weights} \\nWeights: {sampler_qnn_weights}\"\n", ")" ] }, { "cell_type": "markdown", "id": "7f1500df", "metadata": {}, "source": [ "Once we have the inputs and the weights, let's see the results for batched and non-batched passes." ] }, { "cell_type": "markdown", "id": "de7e7302", "metadata": {}, "source": [ "### 3.2. Non-batched Forward Pass" ] }, { "cell_type": "markdown", "id": "52c5fcc5", "metadata": {}, "source": [ "#### 3.2.1. `EstimatorQNN` Example" ] }, { "cell_type": "markdown", "id": "7fba01a3", "metadata": {}, "source": [ "For the `EstimatorQNN`, the expected output shape for the forward pass is `(1, num_qubits * num_observables)` where `1` in our case is the number of samples:" ] }, { "cell_type": "code", "execution_count": 35, "id": "54bed89e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Forward pass result for EstimatorQNN: [[0.2970094]]. \n", "Shape: (1, 1)\n" ] } ], "source": [ "estimator_qnn_forward = estimator_qnn.forward(estimator_qnn_input, estimator_qnn_weights)\n", "\n", "print(\n", " f\"Forward pass result for EstimatorQNN: {estimator_qnn_forward}. \\nShape: {estimator_qnn_forward.shape}\"\n", ")" ] }, { "cell_type": "markdown", "id": "4ea4f85e", "metadata": {}, "source": [ "#### 3.2.2. `SamplerQNN` Example" ] }, { "cell_type": "markdown", "id": "94473b35", "metadata": {}, "source": [ "For the `SamplerQNN` (without a custom interpret function), the expected output shape for the forward pass is `(1, 2**num_qubits)`. With a custom interpret function, the output shape will be `(1, output_shape)`, where `1` in our case is the number of samples:" ] }, { "cell_type": "code", "execution_count": 36, "id": "cb847a75", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Forward pass result for SamplerQNN: [[0.01826527 0.25735654 0.5267981 0.19758009]]. \n", "Shape: (1, 4)\n" ] } ], "source": [ "sampler_qnn_forward = sampler_qnn.forward(sampler_qnn_input, sampler_qnn_weights)\n", "\n", "print(\n", " f\"Forward pass result for SamplerQNN: {sampler_qnn_forward}. \\nShape: {sampler_qnn_forward.shape}\"\n", ")" ] }, { "cell_type": "markdown", "id": "1c843c95", "metadata": {}, "source": [ "### 3.3. Batched Forward Pass" ] }, { "cell_type": "markdown", "id": "9c51e2fc", "metadata": {}, "source": [ "#### 3.3.1. `EstimatorQNN` Example" ] }, { "cell_type": "markdown", "id": "3612ff46", "metadata": {}, "source": [ "For the `EstimatorQNN`, the expected output shape for the forward pass is `(batch_size, num_qubits * num_observables)`:" ] }, { "cell_type": "code", "execution_count": 37, "id": "2629892e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Forward pass result for EstimatorQNN: [[0.2970094]\n", " [0.2970094]]. \n", "Shape: (2, 1)\n" ] } ], "source": [ "estimator_qnn_forward_batched = estimator_qnn.forward(\n", " [estimator_qnn_input, estimator_qnn_input], estimator_qnn_weights\n", ")\n", "\n", "print(\n", " f\"Forward pass result for EstimatorQNN: {estimator_qnn_forward_batched}. \\nShape: {estimator_qnn_forward_batched.shape}\"\n", ")" ] }, { "cell_type": "markdown", "id": "acb7b0a7", "metadata": {}, "source": [ "#### 3.3.2. `SamplerQNN` Example" ] }, { "cell_type": "markdown", "id": "48f7b7bb", "metadata": {}, "source": [ "For the `SamplerQNN` (without custom interpret function), the expected output shape for the forward pass is `(batch_size, 2**num_qubits)`. With a custom interpret function, the output shape will be `(batch_size, output_shape)`." ] }, { "cell_type": "code", "execution_count": 38, "id": "29eb2151", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Forward pass result for SamplerQNN: [[0.01826527 0.25735654 0.5267981 0.19758009]\n", " [0.01826527 0.25735654 0.5267981 0.19758009]]. \n", "Shape: (2, 4)\n" ] } ], "source": [ "sampler_qnn_forward_batched = sampler_qnn.forward(\n", " [sampler_qnn_input, sampler_qnn_input], sampler_qnn_weights\n", ")\n", "\n", "print(\n", " f\"Forward pass result for SamplerQNN: {sampler_qnn_forward_batched}. \\nShape: {sampler_qnn_forward_batched.shape}\"\n", ")" ] }, { "cell_type": "markdown", "id": "171b8ee1", "metadata": {}, "source": [ "## 4. How to Run a Backward Pass\n", "\n", "Let's take advantage of the inputs and weights defined above to show how the backward pass works. This pass returns a tuple `(input_gradients, weight_gradients)`. By default, the backward pass will only calculate gradients with respect to the weight parameters.\n", "\n", "If you want to enable gradients with respect to the input parameters, you should set the following flag during the QNN instantiation:\n", "\n", "```python\n", "qnn = ...QNN(..., input_gradients=True)\n", "```\n", "\n", "Please remember that input gradients are **required** for the use of `TorchConnector` for PyTorch integration." ] }, { "cell_type": "markdown", "id": "e5b90338", "metadata": {}, "source": [ "### 4.1. Backward Pass without Input Gradients" ] }, { "cell_type": "markdown", "id": "fe1a6c32", "metadata": {}, "source": [ "#### 4.1.1. `EstimatorQNN` Example" ] }, { "cell_type": "markdown", "id": "387c9700", "metadata": {}, "source": [ "For the `EstimatorQNN`, the expected output shape for the weight gradients is `(batch_size, num_qubits * num_observables, num_weights)`:" ] }, { "cell_type": "code", "execution_count": 39, "id": "entitled-reaction", "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Input gradients for EstimatorQNN: None. \n", "Shape: None\n", "Weight gradients for EstimatorQNN: [[[0.63272767]]]. \n", "Shape: (1, 1, 1)\n" ] } ], "source": [ "estimator_qnn_input_grad, estimator_qnn_weight_grad = estimator_qnn.backward(\n", " estimator_qnn_input, estimator_qnn_weights\n", ")\n", "\n", "print(\n", " f\"Input gradients for EstimatorQNN: {estimator_qnn_input_grad}. \\nShape: {estimator_qnn_input_grad}\"\n", ")\n", "print(\n", " f\"Weight gradients for EstimatorQNN: {estimator_qnn_weight_grad}. \\nShape: {estimator_qnn_weight_grad.shape}\"\n", ")" ] }, { "cell_type": "markdown", "id": "6d5feb04", "metadata": {}, "source": [ "#### 4.1.2. `SamplerQNN` Example" ] }, { "cell_type": "markdown", "id": "bebaa404", "metadata": {}, "source": [ "For the `SamplerQNN` (without custom interpret function), the expected output shape for the forward pass is `(batch_size, 2**num_qubits, num_weights)`. With a custom interpret function, the output shape will be `(batch_size, output_shape, num_weights)`.:" ] }, { "cell_type": "code", "execution_count": 40, "id": "eefacefe", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Input gradients for SamplerQNN: None. \n", "Shape: None\n", "Weight gradients for SamplerQNN: [[[ 0.00606238 -0.1124595 -0.06856156 -0.09809236]\n", " [ 0.21167414 -0.09069775 0.06856156 -0.22549618]\n", " [-0.48846674 0.32499215 -0.32262178 0.09809236]\n", " [ 0.27073021 -0.12183491 0.32262178 0.22549618]]]. \n", "Shape: (1, 4, 4)\n" ] } ], "source": [ "sampler_qnn_input_grad, sampler_qnn_weight_grad = sampler_qnn.backward(\n", " sampler_qnn_input, sampler_qnn_weights\n", ")\n", "\n", "print(\n", " f\"Input gradients for SamplerQNN: {sampler_qnn_input_grad}. \\nShape: {sampler_qnn_input_grad}\"\n", ")\n", "print(\n", " f\"Weight gradients for SamplerQNN: {sampler_qnn_weight_grad}. \\nShape: {sampler_qnn_weight_grad.shape}\"\n", ")" ] }, { "cell_type": "markdown", "id": "74d28a00", "metadata": {}, "source": [ "### 4.2. Backward Pass with Input Gradients\n", "\n", "Let's enable the `input_gradients` to show what the expected output sizes are for this option." ] }, { "cell_type": "code", "execution_count": 41, "id": "9ccc4641", "metadata": {}, "outputs": [], "source": [ "estimator_qnn.input_gradients = True\n", "sampler_qnn.input_gradients = True" ] }, { "cell_type": "markdown", "id": "f5d2cd57", "metadata": {}, "source": [ "#### 4.2.1. `EstimatorQNN` Example" ] }, { "cell_type": "markdown", "id": "9d1ebc80", "metadata": {}, "source": [ "For the `EstimatorQNN`, the expected output shape for the input gradients is `(batch_size, num_qubits * num_observables, num_inputs)`:" ] }, { "cell_type": "code", "execution_count": 42, "id": "4332f42b", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Input gradients for EstimatorQNN: [[[0.3038852]]]. \n", "Shape: (1, 1, 1)\n", "Weight gradients for EstimatorQNN: [[[0.63272767]]]. \n", "Shape: (1, 1, 1)\n" ] } ], "source": [ "estimator_qnn_input_grad, estimator_qnn_weight_grad = estimator_qnn.backward(\n", " estimator_qnn_input, estimator_qnn_weights\n", ")\n", "\n", "print(\n", " f\"Input gradients for EstimatorQNN: {estimator_qnn_input_grad}. \\nShape: {estimator_qnn_input_grad.shape}\"\n", ")\n", "print(\n", " f\"Weight gradients for EstimatorQNN: {estimator_qnn_weight_grad}. \\nShape: {estimator_qnn_weight_grad.shape}\"\n", ")" ] }, { "cell_type": "markdown", "id": "d3e50ff8", "metadata": {}, "source": [ "#### 4.2.2. `SamplerQNN` Example" ] }, { "cell_type": "markdown", "id": "b76da18a", "metadata": {}, "source": [ "For the `SamplerQNN` (without custom interpret function), the expected output shape for the input gradients is `(batch_size, 2**num_qubits, num_inputs)`. With a custom interpret function, the output shape will be `(batch_size, output_shape, num_inputs)`." ] }, { "cell_type": "code", "execution_count": 43, "id": "3339f869", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Input gradients for SamplerQNN: [[[-0.05844702 -0.10621091]\n", " [ 0.38798796 -0.19544083]\n", " [-0.34561132 0.09459601]\n", " [ 0.01607038 0.20705573]]]. \n", "Shape: (1, 4, 2)\n", "Weight gradients for SamplerQNN: [[[ 0.00606238 -0.1124595 -0.06856156 -0.09809236]\n", " [ 0.21167414 -0.09069775 0.06856156 -0.22549618]\n", " [-0.48846674 0.32499215 -0.32262178 0.09809236]\n", " [ 0.27073021 -0.12183491 0.32262178 0.22549618]]]. \n", "Shape: (1, 4, 4)\n" ] } ], "source": [ "sampler_qnn_input_grad, sampler_qnn_weight_grad = sampler_qnn.backward(\n", " sampler_qnn_input, sampler_qnn_weights\n", ")\n", "\n", "print(\n", " f\"Input gradients for SamplerQNN: {sampler_qnn_input_grad}. \\nShape: {sampler_qnn_input_grad.shape}\"\n", ")\n", "print(\n", " f\"Weight gradients for SamplerQNN: {sampler_qnn_weight_grad}. \\nShape: {sampler_qnn_weight_grad.shape}\"\n", ")" ] }, { "cell_type": "markdown", "id": "45871b6d", "metadata": {}, "source": [ "## 5. Advanced Functionality" ] }, { "cell_type": "markdown", "id": "4e1fb829", "metadata": {}, "source": [ "### 5.1. `EstimatorQNN` with Multiple Observables" ] }, { "cell_type": "markdown", "id": "18c86fd7", "metadata": {}, "source": [ "The `EstimatorQNN` allows to pass lists of observables for more complex QNN architectures. For example (note the change in output shape):" ] }, { "cell_type": "code", "execution_count": 44, "id": "34e1e2f0", "metadata": {}, "outputs": [], "source": [ "observable2 = SparsePauliOp.from_list([(\"Z\" * qc1.num_qubits, 1)])\n", "\n", "estimator_qnn2 = EstimatorQNN(\n", " circuit=qc1,\n", " observables=[observable1, observable2],\n", " input_params=[params1[0]],\n", " weight_params=[params1[1]],\n", ")" ] }, { "cell_type": "code", "execution_count": 45, "id": "e801632d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Forward output for EstimatorQNN1: (1, 1)\n", "Forward output for EstimatorQNN2: (1, 2)\n", "Backward output for EstimatorQNN1: (1, 1, 1)\n", "Backward output for EstimatorQNN2: (1, 2, 1)\n" ] } ], "source": [ "estimator_qnn_forward2 = estimator_qnn2.forward(estimator_qnn_input, estimator_qnn_weights)\n", "estimator_qnn_input_grad2, estimator_qnn_weight_grad2 = estimator_qnn2.backward(\n", " estimator_qnn_input, estimator_qnn_weights\n", ")\n", "\n", "print(f\"Forward output for EstimatorQNN1: {estimator_qnn_forward.shape}\")\n", "print(f\"Forward output for EstimatorQNN2: {estimator_qnn_forward2.shape}\")\n", "print(f\"Backward output for EstimatorQNN1: {estimator_qnn_weight_grad.shape}\")\n", "print(f\"Backward output for EstimatorQNN2: {estimator_qnn_weight_grad2.shape}\")" ] }, { "cell_type": "markdown", "id": "788ec9f1", "metadata": {}, "source": [ "### 5.2. `SamplerQNN` with custom `interpret`" ] }, { "cell_type": "markdown", "id": "378ef3ba", "metadata": {}, "source": [ "One common `interpret` method for `SamplerQNN` is the `parity` function, which allows it to perform binary classification. As explained in the instantiation section, using interpret functions will modify the output shape of the forward and backward passes. In the case of the parity interpret function, `output_shape` is fixed to `2`. Therefore, the expected forward and weight gradient shapes are `(batch_size, 2)` and `(batch_size, 2, num_weights)`, respectively:" ] }, { "cell_type": "code", "execution_count": 46, "id": "eed68d1a", "metadata": {}, "outputs": [], "source": [ "parity = lambda x: \"{:b}\".format(x).count(\"1\") % 2\n", "output_shape = 2 # parity = 0, 1\n", "\n", "sampler_qnn2 = SamplerQNN(\n", " circuit=qc2,\n", " input_params=inputs2,\n", " weight_params=weights2,\n", " interpret=parity,\n", " output_shape=output_shape,\n", ")" ] }, { "cell_type": "code", "execution_count": 47, "id": "c2888195", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Forward output for SamplerQNN1: (1, 4)\n", "Forward output for SamplerQNN2: (1, 2)\n", "Backward output for SamplerQNN1: (1, 4, 4)\n", "Backward output for SamplerQNN2: (1, 2, 4)\n" ] } ], "source": [ "sampler_qnn_forward2 = sampler_qnn2.forward(sampler_qnn_input, sampler_qnn_weights)\n", "sampler_qnn_input_grad2, sampler_qnn_weight_grad2 = sampler_qnn2.backward(\n", " sampler_qnn_input, sampler_qnn_weights\n", ")\n", "\n", "print(f\"Forward output for SamplerQNN1: {sampler_qnn_forward.shape}\")\n", "print(f\"Forward output for SamplerQNN2: {sampler_qnn_forward2.shape}\")\n", "print(f\"Backward output for SamplerQNN1: {sampler_qnn_weight_grad.shape}\")\n", "print(f\"Backward output for SamplerQNN2: {sampler_qnn_weight_grad2.shape}\")" ] }, { "cell_type": "markdown", "id": "66117e82", "metadata": {}, "source": [ "## 6. Conclusion\n", "\n", "In this tutorial, we introduced the two neural networks classes provided by `qiskit-machine-learning`, namely the `EstimatorQNN` and `SamplerQNN`, which extend the base `NeuralNetwork` class. We provided some theoretical background, the key steps for QNN initialization, basic use in forward and backward passes, and advanced functionality.\n", "\n", "We now encourage you to play around with the problem setup and see how different circuit sizes, input, and weight parameter lengths influence the output shapes.\n", "\n" ] }, { "cell_type": "code", "execution_count": 48, "id": "appointed-shirt", "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "text/html": [ "

Version Information

Qiskit SoftwareVersion
qiskit-terra0.22.3
qiskit-machine-learning0.6.0
System information
Python version3.9.15
Python compilerClang 14.0.6
Python buildmain, Nov 24 2022 08:29:02
OSDarwin
CPUs8
Memory (Gb)64.0
Mon Jan 23 11:57:49 2023 CET
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "

This code is a part of Qiskit

© Copyright IBM 2017, 2023.

This code is licensed under the Apache License, Version 2.0. You may
obtain a copy of this license in the LICENSE.txt file in the root directory
of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.

Any modifications or derivative works of this code must retain this
copyright notice, and modified files need to carry a notice indicating
that they have been altered from the originals.

" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import qiskit.tools.jupyter\n", "\n", "%qiskit_version_table\n", "%qiskit_copyright" ] } ], "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": "3.8.13" } }, "nbformat": 4, "nbformat_minor": 5 }