{ "cells": [ { "attachments": {}, "cell_type": "markdown", "id": "6f71ca5c", "metadata": {}, "source": [ "# Tutorial: Introductory Tutorial: A Beginner’s Guide to PINA\n", "\n", "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mathLab/PINA/blob/master/tutorials/tutorial17/tutorial.ipynb)\n", "\n", "

\n", " \"PINA\n", "

\n", "\n", "\n", "Welcome to **PINA**!\n", "\n", "PINA [1] is an open-source Python library designed for **Scientific Machine Learning (SciML)** tasks, particularly involving:\n", "\n", "- **Physics-Informed Neural Networks (PINNs)**\n", "- **Neural Operators (NOs)**\n", "- **Reduced Order Models (ROMs)**\n", "- **Graph Neural Networks (GNNs)**\n", "- ...\n", "\n", "Built on **PyTorch**, **PyTorch Lightning**, and **PyTorch Geometric**, it provides a **user-friendly, intuitive interface** for formulating and solving differential problems using neural networks.\n", "\n", "This tutorial offers a **step-by-step guide** to using PINA—starting from basic to advanced techniques—enabling users to tackle a broad spectrum of differential problems with minimal code.\n", "\n", "\n" ] }, { "cell_type": "markdown", "id": "3014129d", "metadata": {}, "source": [ "## The PINA Workflow \n", "\n", "

\n", " \"PINA\n", "

\n", "\n", "Solving a differential problem in **PINA** involves four main steps:\n", "\n", "1. ***Problem & Data***\n", " Define the mathematical problem and its physical constraints using PINA’s base classes: \n", " - `AbstractProblem`\n", " - `SpatialProblem`\n", " - `InverseProblem` \n", " - ...\n", "\n", " Then prepare inputs by discretizing the domain or importing numerical data. PINA provides essential tools like the `Conditions` class and the `pina.domain` module to facilitate domain sampling and ensure that the input data aligns with the problem's requirements.\n", "\n", "> **👉 We have a dedicated [tutorial](https://mathlab.github.io/PINA/tutorial16/tutorial.html) to teach how to build a Problem from scratch — have a look if you're interested!**\n", "\n", "2. ***Model Design*** \n", " Build neural network models as **PyTorch modules**. For graph-structured data, use **PyTorch Geometric** to build Graph Neural Networks. You can also import models from `pina.model` module!\n", "\n", "3. ***Solver Selection*** \n", " Choose and configure a solver to optimize your model. Options include:\n", " - **Supervised solvers**: `SupervisedSolver`, `ReducedOrderModelSolver`\n", " - **Physics-informed solvers**: `PINN` and (many) variants\n", " - **Generative solvers**: `GAROM` \n", " Solvers can be used out-of-the-box, extended, or fully customized.\n", "\n", "4. ***Training*** \n", " Train your model using the `Trainer` class (built on **PyTorch Lightning**), which enables scalable and efficient training with advanced features.\n", "\n", "\n", "By following these steps, PINA simplifies applying deep learning to scientific computing and differential problems.\n", "\n", "\n", "## A Simple Regression Problem in PINA\n", "We'll start with a simple regression problem [2] of approximating the following function with a Neural Net model $\\mathcal{M}_{\\theta}$:\n", "$$y = x^3 + \\epsilon, \\quad \\epsilon \\sim \\mathcal{N}(0, 9)$$ \n", "using only 20 samples: \n", "\n", "$$x_i \\sim \\mathcal{U}[-3, 3], \\; \\forall i \\in \\{1, \\dots, 20\\}$$\n", "\n", "Using PINA, we will:\n", "\n", "- Generate a synthetic dataset.\n", "- Implement a **Bayesian regressor**.\n", "- Use **Monte Carlo (MC) Dropout** for **Bayesian inference** and **uncertainty estimation**.\n", "\n", "This example highlights how PINA can be used for classic regression tasks with probabilistic modeling capabilities. Let's first import useful modules!" ] }, { "cell_type": "code", "execution_count": 1, "id": "0981f1e9", "metadata": {}, "outputs": [], "source": [ "## routine needed to run the notebook on Google Colab\n", "try:\n", " import google.colab\n", "\n", " IN_COLAB = True\n", "except:\n", " IN_COLAB = False\n", "if IN_COLAB:\n", " !pip install \"pina-mathlab[tutorial]\"\n", "\n", "import warnings\n", "import torch\n", "import matplotlib.pyplot as plt\n", "\n", "warnings.filterwarnings(\"ignore\")\n", "\n", "from pina import Condition, LabelTensor\n", "from pina.problem import AbstractProblem\n", "from pina.domain import EllipsoidDomain, Difference, CartesianDomain, Union" ] }, { "cell_type": "markdown", "id": "7b91de38", "metadata": {}, "source": [ "#### ***Problem & Data***\n", "\n", "We'll start by defining a `BayesianProblem` inheriting from `AbstractProblem` to handle input/output data. This is suitable when data is available. For other cases like PDEs without data, use:\n", "\n", "- `SpatialProblem` – for spatial variables\n", "- `TimeDependentProblem` – for temporal variables\n", "- `ParametricProblem` – for parametric inputs\n", "- `InverseProblem` – for parameter estimation from observations\n", " \n", "but we will see this more in depth in a while!" ] }, { "cell_type": "code", "execution_count": 2, "id": "014bbd86", "metadata": {}, "outputs": [], "source": [ "# (a) Data generation and plot\n", "domain = CartesianDomain({\"x\": [-3, 3]})\n", "x = domain.sample(n=20, mode=\"random\")\n", "y = LabelTensor(x.pow(3) + 3 * torch.randn_like(x), \"y\")\n", "\n", "\n", "# (b) PINA Problem formulation\n", "class BayesianProblem(AbstractProblem):\n", "\n", " output_variables = [\"y\"]\n", " input_variables = [\"x\"]\n", " conditions = {\"data\": Condition(input=x, target=y)}\n", "\n", "\n", "problem = BayesianProblem()\n", "\n", "# # (b) EXTRA!\n", "# # alternatively you can do the following which is easier\n", "# # uncomment to try it!\n", "# from pina.problem.zoo import SupervisedProblem\n", "# problem = SupervisedProblem(input_=x, output_=y)" ] }, { "cell_type": "markdown", "id": "b1b1e4c4", "metadata": {}, "source": [ "We highlight two very important features of PINA\n", "\n", "1. **`LabelTensor` Structure** \n", " - Alongside the standard `torch.Tensor`, PINA introduces the `LabelTensor` structure, which allows **string-based indexing**. \n", " - Ideal for managing and stacking tensors with different labels (e.g., `\"x\"`, `\"t\"`, `\"u\"`) for improved clarity and organization. \n", " - You can still use standard PyTorch tensors if needed.\n", "\n", "2. **`Condition` Object** \n", " - The `Condition` object enforces the **constraints** that the model $\\mathcal{M}_{\\theta}$ must satisfy, such as boundary or initial conditions. \n", " - It ensures that the model adheres to the specific requirements of the problem, making constraint handling more intuitive and streamlined." ] }, { "cell_type": "code", "execution_count": 3, "id": "6f25d3a6", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The Label Tensor object, a very short introduction... \n", "\n", "1: {'dof': ['a', 'b', 'c', 'd'], 'name': 1}\n", "\n", "tensor([[0.0906, 0.7385, 0.9804, 0.2950],\n", " [0.7645, 0.2285, 0.0513, 0.3863],\n", " [0.8320, 0.8914, 0.9107, 0.4953]]) \n", "\n", "Torch methods can be used, label_tensor.shape=torch.Size([3, 4])\n", "also label_tensor.requires_grad=False \n", "\n", "But we have labels as well, e.g. label_tensor.labels=['a', 'b', 'c', 'd']\n", "And we can slice with labels: \n", " label_tensor[\"a\"]=LabelTensor([[0.0906],\n", " [0.7645],\n", " [0.8320]])\n", "Similarly to: \n", " label_tensor[:, 0]=LabelTensor([[0.0906],\n", " [0.7645],\n", " [0.8320]])\n" ] } ], "source": [ "# EXTRA - on the use of LabelTensor\n", "\n", "# We define a 2D tensor, and we index with ['a', 'b', 'c', 'd'] its columns\n", "label_tensor = LabelTensor(torch.rand(3, 4), [\"a\", \"b\", \"c\", \"d\"])\n", "\n", "print(f\"The Label Tensor object, a very short introduction... \\n\")\n", "print(label_tensor, \"\\n\")\n", "print(f\"Torch methods can be used, {label_tensor.shape=}\")\n", "print(f\"also {label_tensor.requires_grad=} \\n\")\n", "print(f\"But we have labels as well, e.g. {label_tensor.labels=}\")\n", "print(f'And we can slice with labels: \\n {label_tensor[\"a\"]=}')\n", "print(f\"Similarly to: \\n {label_tensor[:, 0]=}\")" ] }, { "cell_type": "markdown", "id": "98cba096", "metadata": {}, "source": [ "#### ***Model Design***\n", "\n", "We will now solve the problem using a **simple PyTorch Neural Network** with **Dropout**, which we will implement from scratch following [2]. \n", "It's important to note that PINA provides a wide range of **state-of-the-art (SOTA)** architectures in the `pina.model` module, which you can explore further [here](https://mathlab.github.io/PINA/_rst/_code.html#models).\n", "\n", "#### ***Solver Selection***\n", "\n", "For this task, we will use a straightforward **supervised learning** approach by importing the `SupervisedSolver` from `pina.solvers`. The solver is responsible for defining the training strategy. \n", "\n", "The `SupervisedSolver` is designed to handle typical regression tasks effectively by minimizing the following loss function:\n", "$$\n", "\\mathcal{L}_{\\rm{problem}} = \\frac{1}{N}\\sum_{i=1}^N\n", "\\mathcal{L}(y_i - \\mathcal{M}_{\\theta}(x_i))\n", "$$\n", "where $\\mathcal{L}$ is the loss function, with the default being **Mean Squared Error (MSE)**:\n", "$$\n", "\\mathcal{L}(v) = \\| v \\|^2_2.\n", "$$\n", "\n", "#### **Training**\n", "\n", "Next, we will use the `Trainer` class to train the model. The `Trainer` class, based on **PyTorch Lightning**, offers many features that help:\n", "- **Improve model accuracy**\n", "- **Reduce training time and memory usage**\n", "- **Facilitate logging and visualization** \n", "\n", "The great work done by the PyTorch Lightning team ensures a streamlined training process." ] }, { "cell_type": "code", "execution_count": null, "id": "5388aaaa", "metadata": {}, "outputs": [], "source": [ "from pina.solver import SupervisedSolver\n", "from pina.trainer import Trainer\n", "\n", "\n", "# define problem & data (step 1)\n", "class BayesianModel(torch.nn.Module):\n", " def __init__(self):\n", " super().__init__()\n", " self.layers = torch.nn.Sequential(\n", " torch.nn.Linear(1, 100),\n", " torch.nn.ReLU(),\n", " torch.nn.Dropout(0.5),\n", " torch.nn.Linear(100, 1),\n", " )\n", "\n", " def forward(self, x):\n", " return self.layers(x)\n", "\n", "\n", "problem = BayesianProblem()\n", "\n", "# model design (step 2)\n", "model = BayesianModel()\n", "\n", "# solver selection (step 3)\n", "solver = SupervisedSolver(problem, model)\n", "\n", "# training (step 4)\n", "trainer = Trainer(solver=solver, max_epochs=2000, accelerator=\"cpu\")\n", "trainer.train()" ] }, { "cell_type": "markdown", "id": "5bf9b0d5", "metadata": {}, "source": [ "#### ***Model Training Complete! Now Visualize the Solutions***\n", "\n", "The model has been trained! Since we used **Dropout** during training, the model is probabilistic (Bayesian) [3]. This means that each time we evaluate the forward pass on the input points $x_i$, the results will differ due to the stochastic nature of Dropout.\n", "\n", "To visualize the model's predictions and uncertainty, we will:\n", "\n", "1. **Evaluate the Forward Pass**: Perform multiple forward passes to get different predictions for each input $x_i$.\n", "2. **Compute the Mean**: Calculate the average prediction $\\mu_\\theta$ across all forward passes.\n", "3. **Compute the Standard Deviation**: Calculate the variability of the predictions $\\sigma_\\theta$, which indicates the model's uncertainty.\n", "\n", "This allows us to understand not only the predicted values but also the confidence in those predictions." ] }, { "cell_type": "code", "execution_count": 5, "id": "f2555911", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "x_test = LabelTensor(torch.linspace(-4, 4, 100).reshape(-1, 1), \"x\")\n", "y_test = torch.stack([solver(x_test) for _ in range(1000)], dim=0)\n", "y_mean, y_std = y_test.mean(0).detach(), y_test.std(0).detach()\n", "# plot\n", "x_test = x_test.flatten()\n", "y_mean = y_mean.flatten()\n", "y_std = y_std.flatten()\n", "plt.plot(x_test, y_mean, label=r\"$\\mu_{\\theta}$\")\n", "plt.fill_between(\n", " x_test,\n", " y_mean - 3 * y_std,\n", " y_mean + 3 * y_std,\n", " alpha=0.3,\n", " label=r\"3$\\sigma_{\\theta}$\",\n", ")\n", "plt.plot(x_test, x_test.pow(3), label=\"true\")\n", "plt.scatter(x, y, label=\"train data\")\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "ea79c71d", "metadata": {}, "source": [ "## PINA for Physics-Informed Machine Learning\n", "\n", "In the previous section, we used PINA for **supervised learning**. However, one of its main strengths lies in **Physics-Informed Machine Learning (PIML)**, specifically through **Physics-Informed Neural Networks (PINNs)**.\n", "\n", "### What Are PINNs?\n", "\n", "PINNs are deep learning models that integrate the laws of physics directly into the training process. By incorporating **differential equations** and **boundary conditions** into the loss function, PINNs allow the modeling of complex physical systems while ensuring the predictions remain consistent with scientific laws.\n", "\n", "### Solving a 2D Poisson Problem\n", "\n", "In this section, we will solve a **2D Poisson problem** with **Dirichlet boundary conditions** on an **hourglass-shaped domain** using a simple PINN [4]. You can explore other PINN variants, e.g. [5] or [6] in PINA by visiting the [PINA solvers documentation](https://mathlab.github.io/PINA/_rst/_code.html#solvers). We aim to solve the following 2D Poisson problem:\n", "\n", "$$\n", "\\begin{cases}\n", "\\Delta u(x, y) = \\sin{(\\pi x)} \\sin{(\\pi y)} & \\text{in } D, \\\\\n", "u(x, y) = 0 & \\text{on } \\partial D \n", "\\end{cases}\n", "$$\n", "\n", "where $D$ is an **hourglass-shaped domain** defined as the difference between a **Cartesian domain** and two intersecting **ellipsoids**, and $\\partial D$ is the boundary of the domain.\n", "\n", "### Building Complex Domains\n", "\n", "PINA allows you to build complex geometries easily. It provides many built-in domain shapes and Boolean operators for combining them. For this problem, we will define the hourglass-shaped domain using the existing `CartesianDomain` and `EllipsoidDomain` classes, with Boolean operators like `Difference` and `Union`.\n", "\n", "> **👉 If you are interested in exploring the `domain` module in more detail, check out [this tutorial](https://mathlab.github.io/PINA/_rst/tutorials/tutorial6/tutorial.html).**\n" ] }, { "cell_type": "code", "execution_count": 6, "id": "02518706", "metadata": {}, "outputs": [], "source": [ "# (a) Building the interior of the hourglass-shaped domain\n", "cartesian = CartesianDomain({\"x\": [-3, 3], \"y\": [-3, 3]})\n", "ellipsoid_1 = EllipsoidDomain({\"x\": [-5, -1], \"y\": [-3, 3]})\n", "ellipsoid_2 = EllipsoidDomain({\"x\": [1, 5], \"y\": [-3, 3]})\n", "interior = Difference([cartesian, ellipsoid_1, ellipsoid_2])\n", "\n", "# (b) Building the boundary of the hourglass-shaped domain\n", "border_ellipsoid_1 = ellipsoid_1.partial()\n", "border_ellipsoid_2 = ellipsoid_2.partial()\n", "border_1 = CartesianDomain({\"x\": [-3, 3], \"y\": 3})\n", "border_2 = CartesianDomain({\"x\": [-3, 3], \"y\": -3})\n", "ex_1 = CartesianDomain({\"x\": [-5, -3], \"y\": [-3, 3]})\n", "ex_2 = CartesianDomain({\"x\": [3, 5], \"y\": [-3, 3]})\n", "border_ells = Union([border_ellipsoid_1, border_ellipsoid_2])\n", "border = Union(\n", " [\n", " border_1,\n", " border_2,\n", " Difference(\n", " [Union([border_ellipsoid_1, border_ellipsoid_2]), ex_1, ex_2]\n", " ),\n", " ]\n", ")\n", "\n", "# (c) Sample the domains\n", "interior_samples = interior.sample(n=1000, mode=\"random\")\n", "border_samples = border.sample(n=1000, mode=\"random\")" ] }, { "cell_type": "markdown", "id": "b0da3d52", "metadata": {}, "source": [ "#### Plotting the domain\n", "\n", "Nice! Now that we have built the domain, let's try to plot it" ] }, { "cell_type": "code", "execution_count": 7, "id": "47459922", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(8, 4))\n", "plt.subplot(1, 2, 1)\n", "plt.scatter(\n", " interior_samples.extract(\"x\"),\n", " interior_samples.extract(\"y\"),\n", " c=\"blue\",\n", " alpha=0.5,\n", ")\n", "plt.title(\"Hourglass Interior\")\n", "plt.subplot(1, 2, 2)\n", "plt.scatter(\n", " border_samples.extract(\"x\"),\n", " border_samples.extract(\"y\"),\n", " c=\"blue\",\n", " alpha=0.5,\n", ")\n", "plt.title(\"Hourglass Border\")\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "4d2e59a9", "metadata": {}, "source": [ "#### Writing the Poisson Problem Class\n", "\n", "Very good! Now we will implement the problem class for the 2D Poisson problem. Unlike the previous examples, where we inherited from `AbstractProblem`, for this problem, we will inherit from the `SpatialProblem` class. \n", "\n", "The reason for this is that the Poisson problem involves **spatial variables** as input, so we use `SpatialProblem` to handle such cases.\n", "\n", "This will allow us to define the problem with spatial dependencies and set up the neural network model accordingly." ] }, { "cell_type": "code", "execution_count": 8, "id": "e1eb5a09", "metadata": {}, "outputs": [], "source": [ "from pina.problem import SpatialProblem\n", "from pina.operator import laplacian\n", "from pina.equation import FixedValue, Equation\n", "\n", "\n", "def poisson_equation(input_, output_):\n", " force_term = torch.sin(input_.extract([\"x\"]) * torch.pi) * torch.sin(\n", " input_.extract([\"y\"]) * torch.pi\n", " )\n", " laplacian_u = laplacian(output_, input_, components=[\"u\"], d=[\"x\", \"y\"])\n", " return laplacian_u - force_term\n", "\n", "\n", "class Poisson(SpatialProblem):\n", " # define output_variables and spatial_domain\n", " output_variables = [\"u\"]\n", " spatial_domain = Union([interior, border])\n", " # define the domains\n", " domains = {\"border\": border, \"interior\": interior}\n", " # define the conditions\n", " conditions = {\n", " \"border\": Condition(domain=\"border\", equation=FixedValue(0.0)),\n", " \"interior\": Condition(\n", " domain=\"interior\", equation=Equation(poisson_equation)\n", " ),\n", " }\n", "\n", "\n", "poisson_problem = Poisson()" ] }, { "cell_type": "markdown", "id": "f49a8307", "metadata": {}, "source": [ "As you can see, writing the problem class for a differential equation in PINA is straightforward! The main differences are:\n", "\n", "- We inherit from **`SpatialProblem`** instead of `AbstractProblem` to account for spatial variables.\n", "- We use **`domain`** and **`equation`** inside the `Condition` to define the problem.\n", "\n", "The `Equation` class can be very useful for creating modular problem classes. If you're interested, check out [this tutorial](https://mathlab.github.io/PINA/_rst/tutorial12/tutorial.html) for more details. There's also a dedicated [tutorial](https://mathlab.github.io/PINA/_rst/tutorial16/tutorial.html) for building custom problems!\n", "\n", "Once the problem class is set, we need to **sample the domain** to obtain the data. PINA will automatically handle this, and if you forget to sample, an error will be raised before training begins 😉." ] }, { "cell_type": "code", "execution_count": 9, "id": "a95bb250", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Points are not automatically sampled, you can see this by:\n", " poisson_problem.are_all_domains_discretised=False\n", "\n", "But you can easily sample by running .discretise_domain:\n", " poisson_problem.are_all_domains_discretised=True\n" ] } ], "source": [ "print(\"Points are not automatically sampled, you can see this by:\")\n", "print(f\" {poisson_problem.are_all_domains_discretised=}\\n\")\n", "print(\"But you can easily sample by running .discretise_domain:\")\n", "poisson_problem.discretise_domain(n=1000, domains=[\"interior\"])\n", "poisson_problem.discretise_domain(n=100, domains=[\"border\"])\n", "print(f\" {poisson_problem.are_all_domains_discretised=}\")" ] }, { "cell_type": "markdown", "id": "a2c7b406", "metadata": {}, "source": [ "### Building the Model\n", "\n", "After setting the problem and sampling the domain, the next step is to **build the model** $\\mathcal{M}_{\\theta}$.\n", "\n", "For this, we will use the custom PINA models available [here](https://mathlab.github.io/PINA/_rst/_code.html#models). Specifically, we will use a **feed-forward neural network** by importing the `FeedForward` class.\n", "\n", "This neural network takes the **coordinates** (in this case `['x', 'y']`) as input and outputs the unknown field of the Poisson problem. \n", "\n", "In this tutorial, the neural network is composed of 2 hidden layers, each with 120 neurons and tanh activation." ] }, { "cell_type": "code", "execution_count": 10, "id": "b893232b", "metadata": {}, "outputs": [], "source": [ "from pina.model import FeedForward\n", "\n", "model = FeedForward(\n", " func=torch.nn.Tanh,\n", " layers=[120] * 2,\n", " output_dimensions=len(poisson_problem.output_variables),\n", " input_dimensions=len(poisson_problem.input_variables),\n", ")" ] }, { "cell_type": "markdown", "id": "37b09ea9", "metadata": {}, "source": [ "### Solver Selection\n", "\n", "The thir part of the PINA pipeline involves using a **Solver**.\n", "\n", "In this tutorial, we will use the **classical PINN** solver. However, many other variants are also available and we invite to try them!\n", "\n", "#### Loss Function in PINA\n", "\n", "The loss function in the **classical PINN** is defined as follows:\n", "\n", "$$\\theta_{\\rm{best}}=\\min_{\\theta}\\mathcal{L}_{\\rm{problem}}(\\theta), \\quad \\mathcal{L}_{\\rm{problem}}(\\theta)= \\frac{1}{N_{D}}\\sum_{i=1}^N\n", "\\mathcal{L}(\\Delta\\mathcal{M}_{\\theta}(\\mathbf{x}_i, \\mathbf{y}_i) - \\sin(\\pi x_i)\\sin(\\pi y_i)) +\n", "\\frac{1}{N}\\sum_{i=1}^N\n", "\\mathcal{L}(\\mathcal{M}_{\\theta}(\\mathbf{x}_i, \\mathbf{y}_i))$$\n", "\n", "This loss consists of:\n", "1. The **differential equation residual**: Ensures the model satisfies the Poisson equation.\n", "2. The **boundary condition**: Ensures the model satisfies the Dirichlet boundary condition.\n", "\n", "### Training\n", "\n", "For the last part of the pipeline we need a `Trainer`. We will train the model for **1000 epochs** using the default optimizer parameters. These parameters can be adjusted as needed. For more details, check the solvers documentation [here](https://mathlab.github.io/PINA/_rst/_code.html#solvers).\n", "\n", "To track metrics during training, we use the **`MetricTracker`** class.\n", "\n", "> **👉 Want to know more about `Trainer` and how to boost PINA performance, check out [this tutorial](https://mathlab.github.io/PINA/_rst/tutorials/tutorial11/tutorial.html).**" ] }, { "cell_type": "code", "execution_count": null, "id": "0f135cc4", "metadata": {}, "outputs": [], "source": [ "from pina.solver import PINN\n", "from pina.callback import MetricTracker\n", "\n", "# define the solver\n", "solver = PINN(poisson_problem, model)\n", "\n", "# define trainer\n", "trainer = Trainer(\n", " solver,\n", " max_epochs=1500,\n", " callbacks=[MetricTracker()],\n", " accelerator=\"cpu\",\n", " enable_model_summary=False,\n", ")\n", "\n", "# train\n", "trainer.train()" ] }, { "cell_type": "markdown", "id": "a3d9fc51", "metadata": {}, "source": [ "Done! We can plot the solution and its residual" ] }, { "cell_type": "code", "execution_count": 12, "id": "dea7acf4", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# sample points in the domain. remember to set requires_grad!\n", "pts = poisson_problem.spatial_domain.sample(1000).requires_grad_(True)\n", "# compute the solution\n", "solution = solver(pts)\n", "# compute the residual in the interior\n", "equation = poisson_problem.conditions[\"interior\"].equation\n", "residual = solver.compute_residual(pts, equation)\n", "# simple plot\n", "with torch.no_grad():\n", " plt.subplot(1, 2, 1)\n", " plt.scatter(\n", " pts.extract(\"x\").flatten(),\n", " pts.extract(\"y\").flatten(),\n", " c=solution.extract(\"u\").flatten(),\n", " )\n", " plt.colorbar()\n", " plt.title(\"Solution\")\n", " plt.subplot(1, 2, 2)\n", " plt.scatter(\n", " pts.extract(\"x\").flatten(),\n", " pts.extract(\"y\").flatten(),\n", " c=residual.flatten(),\n", " )\n", " plt.colorbar()\n", " plt.tight_layout()\n", " plt.title(\"Residual\")" ] }, { "cell_type": "markdown", "id": "487c1d47", "metadata": {}, "source": [ "## What's Next?\n", "\n", "Congratulations on completing the introductory tutorial of **PINA**! Now that you have a solid foundation, here are a few directions you can explore:\n", "\n", "1. **Explore Advanced Solvers**: Dive into more advanced solvers like **SAPINN** or **RBAPINN** and experiment with different variations of Physics-Informed Neural Networks.\n", "2. **Apply PINA to New Problems**: Try solving other types of differential equations or explore inverse problems and parametric problems using the PINA framework.\n", "3. **Optimize Model Performance**: Use the `Trainer` class to enhance model performance by exploring features like dynamic learning rates, early stopping, and model checkpoints.\n", "\n", "4. **...and many more!** — There are countless directions to further explore, from testing on different problems to refining the model architecture!\n", "\n", "For more resources and tutorials, check out the [PINA Documentation](https://mathlab.github.io/PINA/).\n", "\n", "\n", "### References\n", "\n", "[1] *Coscia, Dario, et al. \"Physics-informed neural networks for advanced modeling.\" Journal of Open Source Software, 2023.*\n", "\n", "[2] *Hernández-Lobato, José Miguel, and Ryan Adams. \"Probabilistic backpropagation for scalable learning of bayesian neural networks.\" International conference on machine learning, 2015.*\n", "\n", "[3] *Gal, Yarin, and Zoubin Ghahramani. \"Dropout as a bayesian approximation: Representing model uncertainty in deep learning.\" International conference on machine learning, 2016.*\n", "\n", "[4] *Raissi, Maziar, Paris Perdikaris, and George E. Karniadakis. \"Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations.\" Journal of Computational Physics, 2019.*\n", "\n", "[5] *McClenny, Levi D., and Ulisses M. Braga-Neto. \"Self-adaptive physics-informed neural networks.\" Journal of Computational Physics, 2023.*\n", "\n", "[6] *Anagnostopoulos, Sokratis J., et al. \"Residual-based attention in physics-informed neural networks.\" Computer Methods in Applied Mechanics and Engineering, 2024.*" ] } ], "metadata": { "kernelspec": { "display_name": "deep", "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": "3.12.11" } }, "nbformat": 4, "nbformat_minor": 5 }