From 37f71788029be2c85de767d83a9fc7adadc7649c Mon Sep 17 00:00:00 2001 From: Bruno Jacob Date: Mon, 9 Sep 2024 16:15:04 -0700 Subject: [PATCH 1/6] multi-fidelity kan class and example --- examples/KANs/README.md | 25 + .../KANs/p1_fbkan_vs_kan_noise_data_1d.ipynb | 681 +++++++++++ .../KANs/p2_fbkan_vs_kan_noise_data_2d.ipynb | 728 +++++++++++ examples/KANs/p3_mfkan_example_1d.ipynb | 1075 +++++++++++++++++ src/neuromancer/loggers.py | 48 +- src/neuromancer/modules/blocks.py | 304 +++-- src/neuromancer/modules/functions.py | 44 + src/neuromancer/trainer.py | 6 + 8 files changed, 2833 insertions(+), 78 deletions(-) create mode 100644 examples/KANs/README.md create mode 100644 examples/KANs/p1_fbkan_vs_kan_noise_data_1d.ipynb create mode 100644 examples/KANs/p2_fbkan_vs_kan_noise_data_2d.ipynb create mode 100644 examples/KANs/p3_mfkan_example_1d.ipynb diff --git a/examples/KANs/README.md b/examples/KANs/README.md new file mode 100644 index 00000000..350798a4 --- /dev/null +++ b/examples/KANs/README.md @@ -0,0 +1,25 @@ +# Kolmogorov-Arnold Networks in Neuromancer + +This directory contains interactive examples that can serve as a step-by-step tutorial +showcasing the capabilities of Kolmogorov-Arnold Networks (KANs), finite basis KANs (FBKANs) and multi-fidelity KANs (MFKANs) in Neuromancer. + +Examples of learning from multiscale, noisy data with KANs and FBKANs: ++ Open In Colab Part 1: A comparison of KANs and FBKANs in learning a 1D multiscale function with noise ++ Open In Colab Part 2: A comparison of KANs and FBKANs in learning a 2D multiscale function with noise + +Examples of learning multi-fidelity data with MFKANs: ++ Open In Colab Part 3: A comparison of KANs and MFKANs in learning a 1D jump function with abundant, low-fidelity data and sparse, high-fidelity data + + +## Kolmogorov-Arnold Networks (KANs) +Based on the Kolmogorov-Arnold representation theorem, KANs offer an alternative architecture: where traditional neural networks utilize fixed activation functions, KANs employ learnable activation functions on the edges of the network, replacing linear weight parameters with parametrized spline functions. This fundamental shift sometimes enhances model interpretability and improves computational efficiency and accuracy [1]. KANs are available on Neuromancer via `blocks.KANBlock`, which leverages the efficient-kan implementation of [2]. Moreover, users can leverage the finite basis KANs (FBKANs), a domain decomposition method for KANs proposed by Howard et al. (2024)[3] by simply setting the `num_domains` argument in `blocks.KANBlock`. + +### References + +[1] [Liu, Ziming, et al. (2024). KAN: Kolmogorov-Arnold Networks.](https://arxiv.org/abs/2404.19756) + +[2] https://github.com/Blealtan/efficient-kan + +[3] [Howard, Amanda A., et al. (2024) Finite basis Kolmogorov-Arnold networks: domain decomposition for data-diven and physics-informed problems.](https://arxiv.org/abs/2406.19662) + +[4] Howard, Amanda A., et al. (2024) Multi-fidelity Kolmogorov-Arnold networks. diff --git a/examples/KANs/p1_fbkan_vs_kan_noise_data_1d.ipynb b/examples/KANs/p1_fbkan_vs_kan_noise_data_1d.ipynb new file mode 100644 index 00000000..8f67bd24 --- /dev/null +++ b/examples/KANs/p1_fbkan_vs_kan_noise_data_1d.ipynb @@ -0,0 +1,681 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "f907d42f-9f66-49eb-83dd-c3bd911279d8", + "metadata": {}, + "source": [ + "# Finite Basis Kolmogorov-Arnold Networks (FBKANs) in Neuromancer\n", + "\n", + "This tutorial demonstrates the use of Finite Basis Kolmogorov-Arnold Networks (FBKANs) for learning noisy data via domain decomposition.\n", + "\n", + "### References\n", + "\n", + "[1] [Liu, Ziming, et al. (2024). KAN: Kolmogorov-Arnold Networks.](https://arxiv.org/abs/2404.19756)\n", + "\n", + "[2] https://github.com/Blealtan/efficient-kan\n", + "\n", + "[3] [Howard, Amanda A., et al. (2024) Finite basis Kolmogorov-Arnold networks: domain decomposition for data-diven and physics-informed problems.](https://arxiv.org/abs/2406.19662)\n" + ] + }, + { + "cell_type": "markdown", + "id": "434eddd1-f45d-4ad2-a36e-59f67c6e1f47", + "metadata": {}, + "source": [ + "### Install Neuromancer\n", + "(Note: You can skip this step if running locally.)\n", + "(Note 2: Colab might ask you to restart your session after installing Neuromancer. Simply restart it when prompted.)" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "20e257c6-efb3-4e4a-9c06-4dfc270bc8ba", + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "\n", + "# Check if the neuromancer directory already exists\n", + "if not os.path.isdir('neuromancer'):\n", + " # Clone the specific branch of the repository\n", + " !git clone --branch feature/fbkans https://github.com/pnnl/neuromancer.git\n", + "\n", + "# Navigate to the repository directory\n", + "%cd neuromancer\n", + "\n", + "# Install the repository with the required extras\n", + "!pip install -e .[docs,tests,examples]\n" + ] + }, + { + "cell_type": "markdown", + "id": "0767c18e-4d26-4814-aaf4-42b2767cf0d1", + "metadata": {}, + "source": [ + "### Import dependencies" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "42e56a8c-8890-4d5f-808a-a95094b1767b", + "metadata": {}, + "outputs": [], + "source": [ + "import torch\n", + "import numpy as np\n", + "import torch.nn as nn\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from neuromancer.dataset import DictDataset\n", + "from neuromancer.modules import blocks\n", + "from neuromancer.system import Node, System\n", + "from neuromancer.constraint import variable\n", + "from neuromancer.loss import PenaltyLoss\n", + "from neuromancer.problem import Problem\n", + "from neuromancer.trainer import Trainer\n", + "from neuromancer.callbacks import Callback\n", + "from neuromancer.loggers import LossLogger\n", + "\n", + "from torch.utils.data import DataLoader\n", + "\n", + "import time\n" + ] + }, + { + "cell_type": "markdown", + "id": "7bf98ff1-29fd-4861-851d-9d2d8600e77d", + "metadata": {}, + "source": [ + "### Configure device and RNG seed" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "042a7f49-9184-4eb9-a5ea-44ba5c7d4a1e", + "metadata": {}, + "outputs": [], + "source": [ + "#Set default dtype to float32\n", + "torch.set_default_dtype(torch.float)\n", + "#PyTorch random number generator\n", + "torch.manual_seed(1234)\n", + "# Random number generators in other libraries\n", + "np.random.seed(1234)\n", + "# Device configuration\n", + "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')" + ] + }, + { + "cell_type": "markdown", + "id": "3534ae8a-a7b0-4662-a8e8-e221611863cb", + "metadata": {}, + "source": [ + "### Generate data\n", + "\n", + "We will use the function below to generate data from the function:\n", + "\n", + "$$\n", + "f(x) = \\exp\\left[\\sin\\left(4 \\pi x^2\\right)\\right],\n", + "$$\n", + "\n", + "where $x \\in [0,2]$. To simulate noise in the training data, random Gaussian noise with a standard deviation of 0.1 is added to the training labels." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "6357144a-cf71-457e-90b4-6d3f71068593", + "metadata": {}, + "outputs": [], + "source": [ + "def create_dataset(f,\n", + " n_var=2,\n", + " ranges = [0,1],\n", + " train_num=1000, \n", + " test_num=1000,\n", + " normalize_input=False,\n", + " normalize_label=False,\n", + " device='cpu',\n", + " seed=0):\n", + " '''\n", + " create dataset\n", + " \n", + " Args:\n", + " -----\n", + " f : function\n", + " the symbolic formula used to create the synthetic dataset\n", + " ranges : list or np.array; shape (2,) or (n_var, 2)\n", + " the range of input v|ariables. Default: [-1,1].\n", + " train_num : int\n", + " the number of training samples. Default: 1000.\n", + " test_num : int\n", + " the number of test samples. Default: 1000.\n", + " normalize_input : bool\n", + " If True, apply normalization to inputs. Default: False.\n", + " normalize_label : bool\n", + " If True, apply normalization to labels. Default: False.\n", + " device : str\n", + " device. Default: 'cpu'.\n", + " seed : int\n", + " random seed. Default: 0.\n", + " \n", + " Returns:\n", + " --------\n", + " dataset : dic\n", + " Train/test inputs/labels are dataset['train_input'], dataset['train_label'],\n", + " dataset['test_input'], dataset['test_label']\n", + " \n", + " Example\n", + " -------\n", + " >>> f = lambda x: torch.exp(torch.sin(torch.pi*x[:,[0]]) + x[:,[1]]**2)\n", + " >>> dataset = create_dataset(f, n_var=2, train_num=100)\n", + " >>> dataset['train_input'].shape\n", + " torch.Size([100, 2])\n", + " '''\n", + "\n", + " np.random.seed(seed)\n", + " torch.manual_seed(seed)\n", + "\n", + " if len(np.array(ranges).shape) == 1:\n", + " ranges = np.array(ranges * n_var).reshape(n_var,2)\n", + " else:\n", + " ranges = np.array(ranges)\n", + " \n", + " train_input = torch.zeros(train_num, n_var)\n", + " test_input = torch.zeros(test_num, n_var)\n", + " for i in range(n_var):\n", + " train_input[:,i] = torch.rand(train_num,)*(ranges[i,1]-ranges[i,0])+ranges[i,0]\n", + " test_input[:,i] = torch.rand(test_num,)*(ranges[i,1]-ranges[i,0])+ranges[i,0]\n", + " \n", + " train_label = f(train_input)\n", + " test_label = f(test_input)\n", + " \n", + " def normalize(data, mean, std):\n", + " return (data-mean)/std\n", + " \n", + " if normalize_input == True:\n", + " mean_input = torch.mean(train_input, dim=0, keepdim=True)\n", + " std_input = torch.std(train_input, dim=0, keepdim=True)\n", + " train_input = normalize(train_input, mean_input, std_input)\n", + " test_input = normalize(test_input, mean_input, std_input)\n", + " \n", + " if normalize_label == True:\n", + " mean_label = torch.mean(train_label, dim=0, keepdim=True)\n", + " std_label = torch.std(train_label, dim=0, keepdim=True)\n", + " train_label = normalize(train_label, mean_label, std_label)\n", + " test_label = normalize(test_label, mean_label, std_label)\n", + "\n", + " dataset = {}\n", + " dataset['train_input'] = train_input.to(device)\n", + " dataset['test_input'] = test_input.to(device)\n", + "\n", + " dataset['train_label'] = train_label.to(device)\n", + " dataset['test_label'] = test_label.to(device)\n", + "\n", + " return dataset\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "57cac4d3-8c43-4a5b-9e62-d4080c6ab74b", + "metadata": {}, + "outputs": [], + "source": [ + "# Function to sample from\n", + "f = lambda x: torch.exp((torch.sin(4*torch.pi*(x[:,[0]]**2))))\n", + "\n", + "# Create dataset\n", + "dataset = create_dataset(f, n_var=1, ranges=[0,2], train_num=400, test_num=1000, device=device)\n", + "\n", + "# Extract data directly as PyTorch tensors\n", + "X_train = dataset['train_input']\n", + "X_test = dataset['test_input']\n", + "y_train = dataset['train_label']\n", + "y_test = dataset['test_label']\n", + "y_clean = y_train.clone()\n", + "\n", + "# Add noise to y_train\n", + "y_train += 0.1 * torch.randn_like(y_train)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "73b7776d-8541-4aed-aeed-c8a87cefce02", + "metadata": {}, + "outputs": [], + "source": [ + "# Wrap data into Neuromancer DictDatasets\n", + "train_data = DictDataset({'x': dataset['train_input'].to(device), 'y':dataset['train_label'].to(device)}, name='train')\n", + "dev_data = DictDataset({'x': dataset['test_input'].to(device), 'y':dataset['test_label'].to(device)}, name='dev')\n", + "\n", + "# Create torch dataloaders with DictDatasets\n", + "batch_size = train_data.datadict['x'].shape[0]\n", + "train_loader = torch.utils.data.DataLoader(train_data, batch_size=batch_size,\n", + " collate_fn=train_data.collate_fn,\n", + " shuffle=False)\n", + "dev_loader = torch.utils.data.DataLoader(dev_data, batch_size=batch_size,\n", + " collate_fn=dev_data.collate_fn,\n", + " shuffle=False)" + ] + }, + { + "cell_type": "markdown", + "id": "71525382-b70b-40a9-97e3-0d7a345dc920", + "metadata": {}, + "source": [ + "### Create KAN blocks in Neuromancer" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "a8a962ce-4d79-4d0c-9789-308da815a813", + "metadata": {}, + "outputs": [], + "source": [ + "# Neural nets to solve the PDE problem\n", + "net_fbkan = blocks.KANBlock(insize=1,\n", + " outsize=1,\n", + " hsizes=[5], # hidden width\n", + " num_domains=10, # number of domains for domain decomposition\n", + " grid_sizes=[5], # grid size for KAN\n", + " spline_order=3, # spline order\n", + " grid_range=[0,2]\n", + " ).to(device)\n", + "\n", + "\n", + "net_kan = blocks.KANBlock(insize=1,\n", + " outsize=1,\n", + " hsizes=[5], # hidden width\n", + " num_domains=1, # number of domains\n", + " grid_sizes=[5], # grid size for KAN\n", + " spline_order=3, # spline order\n", + " grid_range=[0,2]\n", + " ).to(device)\n", + "\n", + "# Symbolic wrapper of the neural nets\n", + "neural_net_wrapper_fbkan = Node(net_fbkan, ['x'], ['y_hat'], name='net_wrapper_fbkan')\n", + "neural_net_wrapper_kan = Node(net_kan, ['x'], ['y_hat'], name='net_wrapper_kan')\n" + ] + }, + { + "cell_type": "markdown", + "id": "6b71c82e-3c4d-4a0b-9e79-301470c79042", + "metadata": {}, + "source": [ + "### Define symbolic variables and losses" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "4aad78b1-3632-4a83-b557-1bbc61dc092f", + "metadata": {}, + "outputs": [], + "source": [ + "# Define symbolic variables in Neuromancer\n", + "# Note: y = f(x)\n", + "x = variable('x')\n", + "y = variable('y')\n", + "y_hat = variable('y_hat')\n", + "\n", + "loss_data_fbkan = (y == y_hat)^2\n", + "loss_data_fbkan.name = \"ref_loss_fbkan\"\n", + "\n", + "loss_data_kan = (y == y_hat)^2\n", + "loss_data_kan.name = \"ref_loss_kan\"\n", + "\n", + "loss_fbkan = PenaltyLoss(objectives=[loss_data_fbkan], constraints=[])\n", + "loss_kan = PenaltyLoss(objectives=[loss_data_kan], constraints=[])\n" + ] + }, + { + "cell_type": "markdown", + "id": "9af5ad88-a719-4da0-b75c-b5fe2ac6b41b", + "metadata": {}, + "source": [ + "### Construct the Neuromancer Problem objects and train" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "2311c265-c15a-49a6-b89f-f24359ebf061", + "metadata": {}, + "outputs": [], + "source": [ + "# Construct the optimization problems\n", + "problem_fbkan = Problem(nodes=[neural_net_wrapper_fbkan], # list of nodes (neural nets) to be optimized\n", + " loss=loss_fbkan, # data loss\n", + " grad_inference=True # argument for allowing computation of gradients at the inference time\n", + " )\n", + "\n", + "problem_kan = Problem(nodes=[neural_net_wrapper_kan], # list of nodes (neural nets) to be optimized\n", + " loss=loss_kan, # data loss\n", + " grad_inference=True # argument for allowing computation of gradients at the inference time\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "70b7b8c8-0f27-419a-b510-9dde18b91bcd", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "None\n", + "None\n", + "Number of parameters: 1000\n", + "Number of parameters: 100\n" + ] + } + ], + "source": [ + "# Parameters for training\n", + "num_epochs = 2000\n", + "epoch_verbose = 50\n", + "\n", + "# Initial learning rate\n", + "init_lr = 1e-2\n", + "\n", + "# Create loggers\n", + "logger_fbkan = LossLogger(args=None, savedir='test_fbkan', verbosity=epoch_verbose, stdout=['train_loss','dev_loss'])\n", + "logger_kan = LossLogger(args=None, savedir='test_kan', verbosity=epoch_verbose, stdout=['train_loss', 'dev_loss'])\n", + "\n", + "# Create trainers\n", + "trainer_fbkan = Trainer(\n", + " problem_fbkan.to(device),\n", + " train_data=train_loader,\n", + " dev_data=dev_loader,\n", + " optimizer= torch.optim.Adam(problem_fbkan.parameters(), lr=init_lr),\n", + " epoch_verbose=epoch_verbose,\n", + " logger=logger_fbkan,\n", + " epochs=num_epochs,\n", + " train_metric='train_loss',\n", + " eval_metric='dev_loss',\n", + " dev_metric='dev_loss',\n", + " warmup=num_epochs,\n", + " device=device\n", + ")\n", + "\n", + "trainer_kan = Trainer(\n", + " problem_kan.to(device),\n", + " train_data=train_loader,\n", + " dev_data=dev_loader,\n", + " optimizer= torch.optim.Adam(problem_kan.parameters(), lr=init_lr),\n", + " epoch_verbose=epoch_verbose,\n", + " logger=logger_kan,\n", + " epochs=num_epochs,\n", + " train_metric='train_loss',\n", + " eval_metric='dev_loss',\n", + " dev_metric='dev_loss',\n", + " warmup=num_epochs,\n", + " device=device\n", + ")\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "b34f7799-ea6c-4e49-80c3-9bad203b990c", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "epoch: 0\ttrain_loss: 2.72812\tdev_loss: 2.43958\teltime: 0.05157\n", + "epoch: 50\ttrain_loss: 0.69293\tdev_loss: 0.67429\teltime: 0.42308\n", + "epoch: 100\ttrain_loss: 0.63379\tdev_loss: 0.61552\teltime: 0.73360\n", + "epoch: 150\ttrain_loss: 0.54580\tdev_loss: 0.51654\teltime: 1.07527\n", + "epoch: 200\ttrain_loss: 0.47687\tdev_loss: 0.47113\teltime: 1.34512\n", + "epoch: 250\ttrain_loss: 0.43037\tdev_loss: 0.42795\teltime: 1.61852\n", + "epoch: 300\ttrain_loss: 0.34899\tdev_loss: 0.35744\teltime: 1.88319\n", + "epoch: 350\ttrain_loss: 0.25711\tdev_loss: 0.23473\teltime: 2.14741\n", + "epoch: 400\ttrain_loss: 0.14942\tdev_loss: 0.14594\teltime: 2.44503\n", + "epoch: 450\ttrain_loss: 0.11961\tdev_loss: 0.12998\teltime: 2.70329\n", + "epoch: 500\ttrain_loss: 0.09109\tdev_loss: 0.10154\teltime: 2.97068\n", + "epoch: 550\ttrain_loss: 0.07658\tdev_loss: 0.08560\teltime: 3.22704\n", + "epoch: 600\ttrain_loss: 0.06664\tdev_loss: 0.07253\teltime: 3.51260\n", + "epoch: 650\ttrain_loss: 0.05640\tdev_loss: 0.05513\teltime: 3.87460\n", + "epoch: 700\ttrain_loss: 0.04705\tdev_loss: 0.04137\teltime: 4.19259\n", + "epoch: 750\ttrain_loss: 0.04238\tdev_loss: 0.03520\teltime: 4.47007\n", + "epoch: 800\ttrain_loss: 0.03987\tdev_loss: 0.03232\teltime: 4.74716\n", + "epoch: 850\ttrain_loss: 0.03827\tdev_loss: 0.03111\teltime: 5.02860\n", + "epoch: 900\ttrain_loss: 0.03728\tdev_loss: 0.02889\teltime: 5.31432\n", + "epoch: 950\ttrain_loss: 0.03610\tdev_loss: 0.02898\teltime: 5.59623\n", + "epoch: 1000\ttrain_loss: 0.03513\tdev_loss: 0.02761\teltime: 5.87246\n", + "epoch: 1050\ttrain_loss: 0.03446\tdev_loss: 0.02677\teltime: 6.15345\n", + "epoch: 1100\ttrain_loss: 0.03388\tdev_loss: 0.02668\teltime: 6.43407\n", + "epoch: 1150\ttrain_loss: 0.03337\tdev_loss: 0.02574\teltime: 6.70995\n", + "epoch: 1200\ttrain_loss: 0.03304\tdev_loss: 0.02603\teltime: 6.98823\n", + "epoch: 1250\ttrain_loss: 0.03244\tdev_loss: 0.02476\teltime: 7.34500\n", + "epoch: 1300\ttrain_loss: 0.03218\tdev_loss: 0.02411\teltime: 7.62287\n", + "epoch: 1350\ttrain_loss: 0.03155\tdev_loss: 0.02389\teltime: 7.90124\n", + "epoch: 1400\ttrain_loss: 0.03133\tdev_loss: 0.02322\teltime: 8.18068\n", + "epoch: 1450\ttrain_loss: 0.03073\tdev_loss: 0.02298\teltime: 8.45253\n", + "epoch: 1500\ttrain_loss: 0.03036\tdev_loss: 0.02269\teltime: 8.73061\n", + "epoch: 1550\ttrain_loss: 0.03000\tdev_loss: 0.02222\teltime: 9.00461\n", + "epoch: 1600\ttrain_loss: 0.02968\tdev_loss: 0.02175\teltime: 9.28038\n", + "epoch: 1650\ttrain_loss: 0.02937\tdev_loss: 0.02159\teltime: 9.55810\n", + "epoch: 1700\ttrain_loss: 0.02909\tdev_loss: 0.02136\teltime: 9.83871\n", + "epoch: 1750\ttrain_loss: 0.02882\tdev_loss: 0.02089\teltime: 10.11503\n", + "epoch: 1800\ttrain_loss: 0.02878\tdev_loss: 0.02110\teltime: 10.46439\n", + "epoch: 1850\ttrain_loss: 0.02832\tdev_loss: 0.02026\teltime: 10.73900\n", + "epoch: 1900\ttrain_loss: 0.02810\tdev_loss: 0.02030\teltime: 11.02328\n", + "epoch: 1950\ttrain_loss: 0.02774\tdev_loss: 0.01975\teltime: 11.31012\n", + "Elapsed time = 11.598954916000366\n" + ] + } + ], + "source": [ + "# Train KAN\n", + "start_time = time.time()\n", + "\n", + "best_model_kan = trainer_kan.train()\n", + "problem_kan.load_state_dict(best_model_kan)\n", + "trained_model_kan = problem_kan.nodes[0]\n", + "y_test_pred_kan = trained_model_kan(dev_data.datadict)['y_hat'].cpu().detach().numpy()\n", + "\n", + "print(f'Elapsed time = {time.time()-start_time}')" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "b0bfce74-25c9-4d1d-8b61-b43a8d854749", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "epoch: 0\ttrain_loss: 2.78375\tdev_loss: 2.51061\teltime: 11.64286\n", + "epoch: 50\ttrain_loss: 0.59925\tdev_loss: 0.55923\teltime: 13.27524\n", + "epoch: 100\ttrain_loss: 0.31653\tdev_loss: 0.32432\teltime: 14.93617\n", + "epoch: 150\ttrain_loss: 0.18461\tdev_loss: 0.19397\teltime: 16.54737\n", + "epoch: 200\ttrain_loss: 0.05953\tdev_loss: 0.05293\teltime: 18.13060\n", + "epoch: 250\ttrain_loss: 0.01788\tdev_loss: 0.01243\teltime: 19.72843\n", + "epoch: 300\ttrain_loss: 0.01205\tdev_loss: 0.00835\teltime: 21.41892\n", + "epoch: 350\ttrain_loss: 0.01116\tdev_loss: 0.00787\teltime: 22.90162\n", + "epoch: 400\ttrain_loss: 0.01051\tdev_loss: 0.00744\teltime: 24.45135\n", + "epoch: 450\ttrain_loss: 0.00984\tdev_loss: 0.00729\teltime: 26.03485\n", + "epoch: 500\ttrain_loss: 0.00911\tdev_loss: 0.00694\teltime: 27.55288\n", + "epoch: 550\ttrain_loss: 0.00861\tdev_loss: 0.00687\teltime: 29.07457\n", + "epoch: 600\ttrain_loss: 0.00827\tdev_loss: 0.00673\teltime: 30.54862\n", + "epoch: 650\ttrain_loss: 0.00812\tdev_loss: 0.00672\teltime: 32.27572\n", + "epoch: 700\ttrain_loss: 0.00808\tdev_loss: 0.00694\teltime: 33.77082\n", + "epoch: 750\ttrain_loss: 0.00803\tdev_loss: 0.00689\teltime: 35.23642\n", + "epoch: 800\ttrain_loss: 0.00803\tdev_loss: 0.00683\teltime: 36.65269\n", + "epoch: 850\ttrain_loss: 0.00800\tdev_loss: 0.00683\teltime: 38.12384\n", + "epoch: 900\ttrain_loss: 0.00802\tdev_loss: 0.00701\teltime: 39.54441\n", + "epoch: 950\ttrain_loss: 0.00798\tdev_loss: 0.00677\teltime: 40.93773\n", + "epoch: 1000\ttrain_loss: 0.00797\tdev_loss: 0.00676\teltime: 42.33790\n", + "epoch: 1050\ttrain_loss: 0.00796\tdev_loss: 0.00670\teltime: 43.80358\n", + "epoch: 1100\ttrain_loss: 0.00794\tdev_loss: 0.00663\teltime: 45.30647\n", + "epoch: 1150\ttrain_loss: 0.00793\tdev_loss: 0.00659\teltime: 46.74806\n", + "epoch: 1200\ttrain_loss: 0.00793\tdev_loss: 0.00665\teltime: 48.19932\n", + "epoch: 1250\ttrain_loss: 0.00791\tdev_loss: 0.00650\teltime: 49.66190\n", + "epoch: 1300\ttrain_loss: 0.00790\tdev_loss: 0.00636\teltime: 51.07035\n", + "epoch: 1350\ttrain_loss: 0.00789\tdev_loss: 0.00636\teltime: 52.43710\n", + "epoch: 1400\ttrain_loss: 0.00788\tdev_loss: 0.00638\teltime: 53.90273\n", + "epoch: 1450\ttrain_loss: 0.00800\tdev_loss: 0.00702\teltime: 55.32491\n", + "epoch: 1500\ttrain_loss: 0.00785\tdev_loss: 0.00636\teltime: 56.77368\n", + "epoch: 1550\ttrain_loss: 0.00785\tdev_loss: 0.00612\teltime: 58.20147\n", + "epoch: 1600\ttrain_loss: 0.00790\tdev_loss: 0.00617\teltime: 59.74119\n", + "epoch: 1650\ttrain_loss: 0.00782\tdev_loss: 0.00627\teltime: 61.22715\n", + "epoch: 1700\ttrain_loss: 0.00785\tdev_loss: 0.00673\teltime: 62.64858\n", + "epoch: 1750\ttrain_loss: 0.00780\tdev_loss: 0.00628\teltime: 64.08438\n", + "epoch: 1800\ttrain_loss: 0.00780\tdev_loss: 0.00614\teltime: 65.60982\n", + "epoch: 1850\ttrain_loss: 0.00778\tdev_loss: 0.00619\teltime: 67.04397\n", + "epoch: 1900\ttrain_loss: 0.00777\tdev_loss: 0.00625\teltime: 68.50112\n", + "epoch: 1950\ttrain_loss: 0.00777\tdev_loss: 0.00625\teltime: 69.89413\n", + "Elapsed time = 59.75298190116882\n" + ] + } + ], + "source": [ + "# Train FBKAN\n", + "start_time = time.time()\n", + "\n", + "best_model_fbkan = trainer_fbkan.train()\n", + "problem_fbkan.load_state_dict(best_model_fbkan)\n", + "trained_model_fbkan = problem_fbkan.nodes[0]\n", + "y_test_pred_fbkan = trained_model_fbkan(dev_data.datadict)['y_hat'].cpu().detach().numpy()\n", + "print(f'Elapsed time = {time.time()-start_time}')" + ] + }, + { + "cell_type": "markdown", + "id": "25cf6286-90db-43f6-a051-6778ba74bd1b", + "metadata": {}, + "source": [ + "### Plot results" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "21e0ce18-123f-40eb-bad8-0e72d17fa76b", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plotting\n", + "fig, ax = plt.subplots(2, 2, figsize=(16, 9))\n", + "losses_fbkan = trainer_fbkan.logger.get_losses()\n", + "losses_kan = trainer_kan.logger.get_losses()\n", + "sorted_indices = np.argsort(X_test[:, 0].numpy(), axis=0)\n", + "X_test_sorted = X_test[sorted_indices]\n", + "y_test_sorted = y_test[sorted_indices]\n", + "y_test_pred_fbkan_sorted = y_test_pred_fbkan[sorted_indices]\n", + "y_test_pred_kan_sorted = y_test_pred_kan[sorted_indices]\n", + "\n", + "# Plotting losses vs epochs with log scale on y-axis\n", + "epochs = range(1, len(losses_fbkan['train'])*epoch_verbose+1, epoch_verbose)\n", + "\n", + "# Sorting the training data for plotting noisy data and clean function\n", + "inds = np.argsort(X_train[:, 0].numpy(), axis=0)\n", + "X_train_sorted = X_train[inds]\n", + "y_train_sorted = y_train[inds]\n", + "\n", + "# Plotting noisy data and clean function\n", + "ax[0, 0].scatter(X_train_sorted[:, 0], y_train_sorted[:, 0], label='Noisy data', alpha=0.6)\n", + "ax[0, 0].plot(X_test_sorted[:, 0], y_test_sorted[:, 0], 'k', label='Actual', linewidth=2)\n", + "ax[0, 0].set_xlim([0, 2])\n", + "ax[0, 0].set_xlabel('x', fontsize=14)\n", + "ax[0, 0].set_ylabel(r'f(x)', fontsize=14)\n", + "ax[0, 0].legend(fontsize=12, ncol=1)\n", + "ax[0, 0].tick_params(labelsize=14)\n", + "\n", + "# Plotting loss vs epochs\n", + "ax[0, 1].plot(epochs, losses_kan['train'], label='KAN Training Loss')\n", + "ax[0, 1].plot(epochs, losses_kan['dev'], label='KAN Dev Loss')\n", + "ax[0, 1].plot(epochs, losses_fbkan['train'], label='FBKAN Training Loss')\n", + "ax[0, 1].plot(epochs, losses_fbkan['dev'], label='FBKAN Dev Loss')\n", + "ax[0, 1].set_xlabel('Epochs', fontsize=14)\n", + "ax[0, 1].set_ylabel('Loss (log scale)', fontsize=14)\n", + "ax[0, 1].set_yscale('log')\n", + "ax[0, 1].legend(fontsize=12, ncol=1)\n", + "ax[0, 1].tick_params(labelsize=14)\n", + "\n", + "# Plotting predictions vs true values\n", + "ax[1, 0].scatter(y_test_sorted, y_test_pred_kan_sorted, label='KAN', alpha=0.6, color='#f28e2b')\n", + "ax[1, 0].scatter(y_test_sorted, y_test_pred_fbkan_sorted, label='FBKAN', alpha=0.6, color='#4e79a7')\n", + "ax[1, 0].plot([y_test_sorted.min(), y_test_sorted.max()], [y_test_sorted.min(), y_test_sorted.max()], 'k--', lw=2, label='Ideal Fit')\n", + "ax[1, 0].set_xlim([y_test_sorted.min(), y_test_sorted.max()])\n", + "ax[1, 0].set_ylim([y_test_sorted.min(), y_test_sorted.max() + 0.25])\n", + "ax[1, 0].set_xlabel('True values', fontsize=14)\n", + "ax[1, 0].set_ylabel('Predictions', fontsize=14)\n", + "ax[1, 0].legend(fontsize=12, ncol=1)\n", + "ax[1, 0].tick_params(labelsize=14)\n", + "\n", + "# Plotting function approximation\n", + "ax[1, 1].plot(X_test_sorted[:, 0], y_test_sorted[:, 0], 'k-', label='Actual', linewidth=2)\n", + "ax[1, 1].plot(X_test_sorted[:, 0], y_test_pred_kan_sorted[:, 0], '--', color='#f28e2b', label='KAN', linewidth=2)\n", + "ax[1, 1].plot(X_test_sorted[:, 0], y_test_pred_fbkan_sorted[:, 0], '--', color='#4e79a7', label='FBKAN', linewidth=2)\n", + "ax[1, 1].set_xlim([0, 2])\n", + "ax[1, 1].legend(fontsize=12, ncol=1)\n", + "ax[1, 1].tick_params(labelsize=14)\n", + "ax[1, 1].set_xlabel('$x$', fontsize=14)\n", + "ax[1, 1].set_ylabel('$f(x)$', fontsize=14)\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "93f404e5-47f5-4586-9169-ced2bb5b26ae", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "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": "3.10.0" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/examples/KANs/p2_fbkan_vs_kan_noise_data_2d.ipynb b/examples/KANs/p2_fbkan_vs_kan_noise_data_2d.ipynb new file mode 100644 index 00000000..3c377969 --- /dev/null +++ b/examples/KANs/p2_fbkan_vs_kan_noise_data_2d.ipynb @@ -0,0 +1,728 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "5d6766e5-46e3-4d27-b654-10164b85b280", + "metadata": {}, + "source": [ + "# Finite Basis Kolmogorov-Arnold Networks (FBKANs) in Neuromancer\n", + "\n", + "This tutorial demonstrates the use of Finite Basis Kolmogorov-Arnold Networks (FBKANs) for learning noisy data via domain decomposition.\n", + "\n", + "### References\n", + "\n", + "[1] [Liu, Ziming, et al. (2024). KAN: Kolmogorov-Arnold Networks.](https://arxiv.org/abs/2404.19756)\n", + "\n", + "[2] https://github.com/Blealtan/efficient-kan\n", + "\n", + "[3] [Howard, Amanda A., et al. (2024) Finite basis Kolmogorov-Arnold networks: domain decomposition for data-diven and physics-informed problems.](https://arxiv.org/abs/2406.19662)\n" + ] + }, + { + "cell_type": "markdown", + "id": "84265625-5e66-44e2-8e63-fa9db1f7358f", + "metadata": {}, + "source": [ + "### Install Neuromancer\n", + "(Note: You can skip this step if running locally.)\n", + "(Note 2: Colab might ask you to restart your session after installing Neuromancer. Simply restart it when prompted.)" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "778a7341-cb19-4cee-9e79-ca3ed5dbc45d", + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "\n", + "# Check if the neuromancer directory already exists\n", + "if not os.path.isdir('neuromancer'):\n", + " # Clone the specific branch of the repository\n", + " !git clone --branch feature/fbkans https://github.com/pnnl/neuromancer.git\n", + "\n", + "# Navigate to the repository directory\n", + "%cd neuromancer\n", + "\n", + "# Install the repository with the required extras\n", + "!pip install -e .[docs,tests,examples]\n" + ] + }, + { + "cell_type": "markdown", + "id": "0767c18e-4d26-4814-aaf4-42b2767cf0d1", + "metadata": {}, + "source": [ + "### Import dependencies" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "42e56a8c-8890-4d5f-808a-a95094b1767b", + "metadata": {}, + "outputs": [], + "source": [ + "import torch\n", + "import numpy as np\n", + "import torch.nn as nn\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from neuromancer.dataset import DictDataset\n", + "from neuromancer.modules import blocks\n", + "from neuromancer.system import Node, System\n", + "from neuromancer.constraint import variable\n", + "from neuromancer.loss import PenaltyLoss\n", + "from neuromancer.problem import Problem\n", + "from neuromancer.trainer import Trainer\n", + "from neuromancer.callbacks import Callback\n", + "from neuromancer.loggers import LossLogger\n" + ] + }, + { + "cell_type": "markdown", + "id": "7bf98ff1-29fd-4861-851d-9d2d8600e77d", + "metadata": {}, + "source": [ + "### Configure device and RNG seed" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "042a7f49-9184-4eb9-a5ea-44ba5c7d4a1e", + "metadata": {}, + "outputs": [], + "source": [ + "#Set default dtype to float32\n", + "torch.set_default_dtype(torch.float)\n", + "#PyTorch random number generator\n", + "torch.manual_seed(1234)\n", + "# Random number generators in other libraries\n", + "np.random.seed(1234)\n", + "# Device configuration\n", + "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')" + ] + }, + { + "cell_type": "markdown", + "id": "3534ae8a-a7b0-4662-a8e8-e221611863cb", + "metadata": {}, + "source": [ + "### Generate data\n", + "\n", + "We will use the function below to generate data from the function:\n", + "\n", + "$$\n", + "f(x) = \\sin(4 \\pi x^2) \\sin(6 \\pi y^2)\n", + "$$\n", + "\n", + "where $x, y \\in [0,1]^2$. To simulate noise in the training data, random Gaussian noise with a standard deviation of 0.05 is added to the training labels.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "6357144a-cf71-457e-90b4-6d3f71068593", + "metadata": {}, + "outputs": [], + "source": [ + "def create_dataset(f, \n", + " n_var=2, \n", + " ranges = [0,1],\n", + " train_num=1000, \n", + " test_num=1000,\n", + " normalize_input=False,\n", + " normalize_label=False,\n", + " device='cpu',\n", + " seed=0):\n", + " '''\n", + " create dataset\n", + " \n", + " Args:\n", + " -----\n", + " f : function\n", + " the symbolic formula used to create the synthetic dataset\n", + " ranges : list or np.array; shape (2,) or (n_var, 2)\n", + " the range of input variables. Default: [-1,1].\n", + " train_num : int\n", + " the number of training samples. Default: 1000.\n", + " test_num : int\n", + " the number of test samples. Default: 1000.\n", + " normalize_input : bool\n", + " If True, apply normalization to inputs. Default: False.\n", + " normalize_label : bool\n", + " If True, apply normalization to labels. Default: False.\n", + " device : str\n", + " device. Default: 'cpu'.\n", + " seed : int\n", + " random seed. Default: 0.\n", + " \n", + " Returns:\n", + " --------\n", + " dataset : dic\n", + " Train/test inputs/labels are dataset['train_input'], dataset['train_label'],\n", + " dataset['test_input'], dataset['test_label']\n", + " \n", + " Example\n", + " -------\n", + " >>> f = lambda x: torch.exp(torch.sin(torch.pi*x[:,[0]]) + x[:,[1]]**2)\n", + " >>> dataset = create_dataset(f, n_var=2, train_num=100)\n", + " >>> dataset['train_input'].shape\n", + " torch.Size([100, 2])\n", + " '''\n", + "\n", + " np.random.seed(seed)\n", + " torch.manual_seed(seed)\n", + "\n", + " if len(np.array(ranges).shape) == 1:\n", + " ranges = np.array(ranges * n_var).reshape(n_var,2)\n", + " else:\n", + " ranges = np.array(ranges)\n", + " \n", + " train_input = torch.zeros(train_num, n_var)\n", + " test_input = torch.zeros(test_num, n_var)\n", + " for i in range(n_var):\n", + " train_input[:,i] = torch.rand(train_num,)*(ranges[i,1]-ranges[i,0])+ranges[i,0]\n", + " test_input[:,i] = torch.rand(test_num,)*(ranges[i,1]-ranges[i,0])+ranges[i,0]\n", + " \n", + " \n", + " train_label = f(train_input)\n", + " test_label = f(test_input)\n", + " \n", + " \n", + " def normalize(data, mean, std):\n", + " return (data-mean)/std\n", + " sd\n", + " if normalize_input == True:\n", + " mean_input = torch.mean(train_input, dim=0, keepdim=True)\n", + " std_input = torch.std(train_input, dim=0, keepdim=True)\n", + " train_input = normalize(train_input, mean_input, std_input)\n", + " test_input = normalize(test_input, mean_input, std_input)\n", + " \n", + " if normalize_label == True:\n", + " mean_label = torch.mean(train_label, dim=0, keepdim=True)\n", + " std_label = torch.std(train_label, dim=0, keepdim=True)\n", + " train_label = normalize(train_label, mean_label, std_label)\n", + " test_label = normalize(test_label, mean_label, std_label)\n", + "\n", + " dataset = {}\n", + " dataset['train_input'] = train_input.to(device)\n", + " dataset['test_input'] = test_input.to(device)\n", + "\n", + " dataset['train_label'] = train_label.to(device)\n", + " dataset['test_label'] = test_label.to(device)\n", + "\n", + " return dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "57cac4d3-8c43-4a5b-9e62-d4080c6ab74b", + "metadata": {}, + "outputs": [], + "source": [ + "# Function to sample from\n", + "f = lambda x: ((torch.sin(4*torch.pi*(x[:,[0]]**2))))*((torch.sin(6*torch.pi*(x[:,[1]]**2))))\n", + "\n", + "# Create dataset\n", + "dataset = create_dataset(f, n_var=2, train_num=1000, test_num=1000)\n", + "\n", + "# Extract data directly as PyTorch tensors\n", + "X_train = dataset['train_input']\n", + "X_test = dataset['test_input']\n", + "y_train = dataset['train_label']\n", + "y_test = dataset['test_label']\n", + "y_clean = y_train.clone()\n", + "\n", + "# Add 5% noise to the training data labels\n", + "y_train += 0.05 * torch.randn(y_train.shape)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "73b7776d-8541-4aed-aeed-c8a87cefce02", + "metadata": {}, + "outputs": [], + "source": [ + "# DictDatasets\n", + "train_data = DictDataset({'X': dataset['train_input'].to(device), 'z':dataset['train_label'].to(device)}, name='train')\n", + "dev_data = DictDataset({'X': dataset['test_input'].to(device), 'z':dataset['test_label'].to(device)}, name='dev')\n", + "\n", + "# torch dataloaders\n", + "batch_size = train_data.datadict['X'].shape[0]\n", + "train_loader = torch.utils.data.DataLoader(train_data, batch_size=batch_size,\n", + " collate_fn=train_data.collate_fn,\n", + " shuffle=False)\n", + "dev_loader = torch.utils.data.DataLoader(dev_data, batch_size=batch_size,\n", + " collate_fn=dev_data.collate_fn,\n", + " shuffle=False)" + ] + }, + { + "cell_type": "markdown", + "id": "71525382-b70b-40a9-97e3-0d7a345dc920", + "metadata": {}, + "source": [ + "### Create KAN blocks in Neuromancer" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "a8a962ce-4d79-4d0c-9789-308da815a813", + "metadata": {}, + "outputs": [], + "source": [ + "# Neural nets to solve the PDE problem\n", + "\n", + "net_fbkan = blocks.KANBlock(insize=2,outsize=1, hsizes=[5], num_domains=4, grid_sizes=[5],\n", + " spline_order=3, grid_eps=0.02, scale_base=1.0).to(device)\n", + "\n", + "net_kan = blocks.KANBlock(insize=2,outsize=1, hsizes=[5], num_domains=1, grid_sizes=[5],\n", + " spline_order=3, grid_eps=0.02, scale_base=1.0).to(device)\n", + "\n", + "# Symbolic wrapper of the neural nets\n", + "neural_net_wrapper_fbkan = Node(net_fbkan, ['X'], ['z_hat'], name='net_wrapper_fbkan')\n", + "neural_net_wrapper_kan = Node(net_kan, ['X'], ['z_hat'], name='net_wrapper_kan')\n" + ] + }, + { + "cell_type": "markdown", + "id": "6b71c82e-3c4d-4a0b-9e79-301470c79042", + "metadata": {}, + "source": [ + "### Define symbolic variables and losses" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "4aad78b1-3632-4a83-b557-1bbc61dc092f", + "metadata": {}, + "outputs": [], + "source": [ + "# Define symbolic variables in Neuromancer\n", + "# Note: y = f(x)\n", + "x = variable('X')[:,[0]]\n", + "y = variable('X')[:,[1]]\n", + "z = variable('z')\n", + "z_hat = variable('z_hat')\n", + "\n", + "scaling = 1.\n", + "\n", + "loss_data_fbkan = scaling*(z == z_hat)^2\n", + "loss_data_fbkan.name = \"ref_loss_fbkan\"\n", + "\n", + "loss_data_kan = scaling*(z == z_hat)^2\n", + "loss_data_kan.name = \"ref_loss_kan\"\n", + "\n", + "loss_fbkan = PenaltyLoss(objectives=[loss_data_fbkan], constraints=[])\n", + "loss_kan = PenaltyLoss(objectives=[loss_data_kan], constraints=[])\n" + ] + }, + { + "cell_type": "markdown", + "id": "9af5ad88-a719-4da0-b75c-b5fe2ac6b41b", + "metadata": {}, + "source": [ + "### Construct the Neuromancer Problem objects and train" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "2311c265-c15a-49a6-b89f-f24359ebf061", + "metadata": {}, + "outputs": [], + "source": [ + "# Construct the optimization problems\n", + "problem_fbkan = Problem(nodes=[neural_net_wrapper_fbkan], # list of nodes (neural nets) to be optimized\n", + " loss=loss_fbkan, # data loss\n", + " grad_inference=True # argument for allowing computation of gradients at the inference time\n", + " )\n", + "\n", + "problem_kan = Problem(nodes=[neural_net_wrapper_kan], # list of nodes (neural nets) to be optimized\n", + " loss=loss_kan, # data loss\n", + " grad_inference=True # argument for allowing computation of gradients at the inference time\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "70b7b8c8-0f27-419a-b510-9dde18b91bcd", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "None\n", + "None\n", + "Number of parameters: 600\n", + "Number of parameters: 150\n" + ] + } + ], + "source": [ + "# Parameters for training\n", + "num_epochs = 1001\n", + "epoch_verbose = 50\n", + "\n", + "# Initial learning rate\n", + "init_lr = 0.02\n", + "\n", + "# Create loggers\n", + "logger_fbkan = LossLogger(args=None, savedir='test_fbkan', verbosity=epoch_verbose, stdout=['train_loss','dev_loss'])\n", + "logger_kan = LossLogger(args=None, savedir='test_kan', verbosity=epoch_verbose, stdout=['train_loss', 'dev_loss'])\n", + "\n", + "# Create trainers\n", + "trainer_fbkan = Trainer(\n", + " problem_fbkan.to(device),\n", + " train_data=train_loader,\n", + " dev_data=dev_loader,\n", + " optimizer= torch.optim.Adam(problem_fbkan.parameters(), lr=init_lr),#schedule_fbkan.optimizer,\n", + " epoch_verbose=epoch_verbose,\n", + " logger=logger_fbkan,\n", + " epochs=num_epochs,\n", + " train_metric='train_loss',\n", + " eval_metric='dev_loss',\n", + " dev_metric='dev_loss',\n", + " warmup=num_epochs,\n", + " device=device\n", + ")\n", + "\n", + "trainer_kan = Trainer(\n", + " problem_kan.to(device),\n", + " train_data=train_loader,\n", + " dev_data=dev_loader,\n", + " optimizer= torch.optim.Adam(problem_kan.parameters(), lr=init_lr),#schedule_kan.optimizer,\n", + " epoch_verbose=epoch_verbose,\n", + " logger=logger_kan,\n", + " epochs=num_epochs,\n", + " train_metric='train_loss',\n", + " eval_metric='dev_loss',\n", + " dev_metric='dev_loss',\n", + " warmup=num_epochs,\n", + " device=device\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "b0bfce74-25c9-4d1d-8b61-b43a8d854749", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "epoch: 0\ttrain_loss: 0.19858\tdev_loss: 0.18781\teltime: 0.04408\n", + "epoch: 50\ttrain_loss: 0.12017\tdev_loss: 0.11974\teltime: 0.98760\n", + "epoch: 100\ttrain_loss: 0.03547\tdev_loss: 0.04448\teltime: 1.88288\n", + "epoch: 150\ttrain_loss: 0.01443\tdev_loss: 0.01751\teltime: 2.69070\n", + "epoch: 200\ttrain_loss: 0.01119\tdev_loss: 0.01346\teltime: 3.48212\n", + "epoch: 250\ttrain_loss: 0.00829\tdev_loss: 0.00942\teltime: 4.28909\n", + "epoch: 300\ttrain_loss: 0.00721\tdev_loss: 0.00813\teltime: 5.13658\n", + "epoch: 350\ttrain_loss: 0.00956\tdev_loss: 0.00810\teltime: 5.89438\n", + "epoch: 400\ttrain_loss: 0.00555\tdev_loss: 0.00580\teltime: 6.76285\n", + "epoch: 450\ttrain_loss: 0.00501\tdev_loss: 0.00493\teltime: 7.56369\n", + "epoch: 500\ttrain_loss: 0.00445\tdev_loss: 0.00428\teltime: 8.55607\n", + "epoch: 550\ttrain_loss: 0.00413\tdev_loss: 0.00444\teltime: 9.78196\n", + "epoch: 600\ttrain_loss: 0.00534\tdev_loss: 0.00503\teltime: 10.75619\n", + "epoch: 650\ttrain_loss: 0.00339\tdev_loss: 0.00344\teltime: 11.84819\n", + "epoch: 700\ttrain_loss: 0.00299\tdev_loss: 0.00280\teltime: 12.94066\n", + "epoch: 750\ttrain_loss: 0.00307\tdev_loss: 0.00257\teltime: 14.01460\n", + "epoch: 800\ttrain_loss: 0.00279\tdev_loss: 0.00238\teltime: 15.07571\n", + "epoch: 850\ttrain_loss: 0.00280\tdev_loss: 0.00239\teltime: 16.25827\n", + "epoch: 900\ttrain_loss: 0.00482\tdev_loss: 0.00311\teltime: 17.41800\n", + "epoch: 950\ttrain_loss: 0.00264\tdev_loss: 0.00213\teltime: 18.54224\n", + "epoch: 1000\ttrain_loss: 0.00259\tdev_loss: 0.00205\teltime: 19.57284\n" + ] + } + ], + "source": [ + "# Train FBKAN\n", + "best_model_fbkan = trainer_fbkan.train()\n", + "problem_fbkan.load_state_dict(best_model_fbkan)\n", + "trained_model_fbkan = problem_fbkan.nodes[0]\n", + "z_test_pred_fbkan = trained_model_fbkan(dev_data.datadict)['z_hat'].cpu().detach().numpy()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "b34f7799-ea6c-4e49-80c3-9bad203b990c", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "epoch: 0\ttrain_loss: 0.20121\tdev_loss: 0.19113\teltime: 19.64045\n", + "epoch: 50\ttrain_loss: 0.16842\tdev_loss: 0.16688\teltime: 20.06003\n", + "epoch: 100\ttrain_loss: 0.14238\tdev_loss: 0.14534\teltime: 20.53543\n", + "epoch: 150\ttrain_loss: 0.11018\tdev_loss: 0.11803\teltime: 20.97161\n", + "epoch: 200\ttrain_loss: 0.07499\tdev_loss: 0.08277\teltime: 21.44121\n", + "epoch: 250\ttrain_loss: 0.06059\tdev_loss: 0.06680\teltime: 21.91846\n", + "epoch: 300\ttrain_loss: 0.05511\tdev_loss: 0.06288\teltime: 22.31885\n", + "epoch: 350\ttrain_loss: 0.05344\tdev_loss: 0.06120\teltime: 22.70428\n", + "epoch: 400\ttrain_loss: 0.05226\tdev_loss: 0.05941\teltime: 23.09720\n", + "epoch: 450\ttrain_loss: 0.05113\tdev_loss: 0.05787\teltime: 23.51434\n", + "epoch: 500\ttrain_loss: 0.04937\tdev_loss: 0.05685\teltime: 24.02329\n", + "epoch: 550\ttrain_loss: 0.04648\tdev_loss: 0.05583\teltime: 24.45336\n", + "epoch: 600\ttrain_loss: 0.04318\tdev_loss: 0.04911\teltime: 24.96189\n", + "epoch: 650\ttrain_loss: 0.04042\tdev_loss: 0.04821\teltime: 25.38162\n", + "epoch: 700\ttrain_loss: 0.03868\tdev_loss: 0.04386\teltime: 25.88007\n", + "epoch: 750\ttrain_loss: 0.03666\tdev_loss: 0.04242\teltime: 26.37139\n", + "epoch: 800\ttrain_loss: 0.03454\tdev_loss: 0.03878\teltime: 26.78114\n", + "epoch: 850\ttrain_loss: 0.03277\tdev_loss: 0.03831\teltime: 27.16932\n", + "epoch: 900\ttrain_loss: 0.03190\tdev_loss: 0.03761\teltime: 27.55376\n", + "epoch: 950\ttrain_loss: 0.03140\tdev_loss: 0.03736\teltime: 28.00943\n", + "epoch: 1000\ttrain_loss: 0.03165\tdev_loss: 0.03805\teltime: 28.40723\n" + ] + } + ], + "source": [ + "# Train KAN\n", + "best_model_kan = trainer_kan.train()\n", + "problem_kan.load_state_dict(best_model_kan)\n", + "trained_model_kan = problem_kan.nodes[0]\n", + "z_test_pred_kan = trained_model_kan(dev_data.datadict)['z_hat'].cpu().detach().numpy()\n" + ] + }, + { + "cell_type": "markdown", + "id": "5c57bae0-bd69-4b65-9012-e850e02b8a47", + "metadata": {}, + "source": [ + "### Plot results" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "21e0ce18-123f-40eb-bad8-0e72d17fa76b", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plotting results\n", + "\n", + "# Get the losses from the trainers\n", + "losses_fbkan = trainer_fbkan.logger.get_losses()\n", + "losses_kan = trainer_kan.logger.get_losses()\n", + "\n", + "# # Sort the test data for plotting\n", + "sorted_indices = np.argsort(X_test[:, 0].detach().numpy(), axis=0)\n", + "X_test_sorted = X_test[sorted_indices].detach().numpy()\n", + "z_test_sorted = y_test[sorted_indices].detach().numpy()\n", + "z_test_pred_fbkan_sorted = z_test_pred_fbkan[sorted_indices]\n", + "z_test_pred_kan_sorted = z_test_pred_kan[sorted_indices]\n", + "\n", + "# Plotting results\n", + "fig, ax = plt.subplots(1, 2, figsize=(12, 6))\n", + "\n", + "epochs = range(1, len(losses_fbkan['train'])*epoch_verbose+1, epoch_verbose)\n", + "\n", + "ax[0].plot(epochs, losses_kan['train'], label='KAN Loss', color='#4e79a7')\n", + "ax[0].plot(epochs, losses_fbkan['train'], label='FBKAN Loss', color='#59a14f')\n", + "ax[0].set_xlabel('Epochs', fontsize=20)\n", + "ax[0].set_ylabel('Loss', fontsize=20)\n", + "ax[0].set_yscale('log') # Set y-axis to logarithmic scale\n", + "ax[0].legend(fontsize=12, ncol=1)\n", + "ax[0].tick_params(labelsize=16)\n", + "\n", + "ax[1].scatter(z_test_sorted, z_test_pred_kan_sorted, label='KAN', alpha=0.6, color='#4e79a7')\n", + "ax[1].scatter(z_test_sorted, z_test_pred_fbkan_sorted, label='FBKAN', alpha=0.6, color='#59a14f')\n", + "ax[1].plot([z_test_sorted.min(), z_test_sorted.max()], [z_test_sorted.min(), z_test_sorted.max()], 'k--', lw=2, label='Ideal Fit')\n", + "ax[1].set_xlim([z_test_sorted.min(), z_test_sorted.max()])\n", + "ax[1].set_ylim([z_test_sorted.min() - 0.25, z_test_sorted.max() + 0.25])\n", + "ax[1].set_xlabel('True values', fontsize=20)\n", + "ax[1].set_ylabel('Predictions', fontsize=20)\n", + "ax[1].legend(fontsize=12, ncol=1)\n", + "ax[1].tick_params(labelsize=16)\n", + "\n", + "plt.tight_layout()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "f6cffe66-071a-4a97-947b-838a586e2dd9", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "MSE KAN = 0.19136252999305725\n", + "MSE FBKAN = 0.010615437291562557\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Create meshgrid\n", + "xx = np.linspace(0., 1., 100)\n", + "yy = np.linspace(0., 1., 100)\n", + "XX, YY = np.meshgrid(xx, yy)\n", + "\n", + "# Create input tensor for the meshgrid points\n", + "X_mesh = torch.tensor(np.column_stack((XX.ravel(), YY.ravel())), dtype=torch.float32).to(device)\n", + "\n", + "# Create DictDataset for meshgrid points\n", + "mesh_data = DictDataset({'X': X_mesh, 'z': torch.zeros(X_mesh.shape[0], 1)}, name='mesh')\n", + "\n", + "# Perform inference\n", + "with torch.no_grad():\n", + " z_mesh_pred_fbkan = trained_model_fbkan(mesh_data.datadict)['z_hat'].cpu().numpy()\n", + " z_mesh_pred_kan = trained_model_kan(mesh_data.datadict)['z_hat'].cpu().numpy()\n", + "\n", + "# Reshape predictions to match meshgrid\n", + "z_mesh_pred_fbkan_reshaped = z_mesh_pred_fbkan.reshape(XX.shape)\n", + "z_mesh_pred_kan_reshaped = z_mesh_pred_kan.reshape(XX.shape)\n", + "\n", + "# Create true values for comparison (using the original function f)\n", + "y_mesh_true = f(X_mesh).cpu().numpy().reshape(XX.shape)\n", + "\n", + "# Calculate errors\n", + "error_kan = np.abs(z_mesh_pred_kan_reshaped - y_mesh_true)\n", + "error_fbkan = np.abs(z_mesh_pred_fbkan_reshaped - y_mesh_true)\n", + "\n", + "# Create the plots\n", + "fig, ax = plt.subplots(2, 3, figsize=(15, 8))\n", + "\n", + "minc = -1.\n", + "maxc = 1.\n", + "\n", + "cmap = plt.get_cmap('viridis')\n", + "\n", + "# Plotting exact values with isocontour lines\n", + "p = ax[0, 0].pcolor(XX, YY, y_mesh_true, vmin=minc, vmax=maxc, cmap=cmap)\n", + "fig.colorbar(p, ax=ax[0, 0])\n", + "ax[0, 0].contour(XX, YY, y_mesh_true, colors='k', linewidths=0.5)\n", + "ax[0, 0].set_xlim([XX.min(), XX.max()])\n", + "ax[0, 0].set_ylim([YY.min(), YY.max()])\n", + "ax[0, 0].set_xlabel('$x$', fontsize=12)\n", + "ax[0, 0].set_ylabel('$y$', fontsize=12)\n", + "ax[0, 0].tick_params(labelsize=12)\n", + "ax[0, 0].set_title('Exact', fontsize=12)\n", + "ax[0, 0].set_aspect('equal')\n", + "\n", + "# Plotting KAN predictions with isocontour lines\n", + "p = ax[0, 1].pcolor(XX, YY, z_mesh_pred_kan_reshaped, vmin=minc, vmax=maxc, cmap=cmap)\n", + "fig.colorbar(p, ax=ax[0, 1])\n", + "ax[0, 1].contour(XX, YY, z_mesh_pred_kan_reshaped, colors='k', linewidths=0.5)\n", + "ax[0, 1].set_xlim([XX.min(), XX.max()])\n", + "ax[0, 1].set_ylim([YY.min(), YY.max()])\n", + "ax[0, 1].tick_params(labelsize=12)\n", + "ax[0, 1].set_title('KAN', fontsize=12)\n", + "ax[0, 1].set_aspect('equal')\n", + "\n", + "# Plotting FBKAN predictions with isocontour lines\n", + "p = ax[1, 1].pcolor(XX, YY, z_mesh_pred_fbkan_reshaped, vmin=minc, vmax=maxc, cmap=cmap)\n", + "fig.colorbar(p, ax=ax[1, 1])\n", + "ax[1, 1].contour(XX, YY, z_mesh_pred_fbkan_reshaped, colors='k', linewidths=0.5)\n", + "ax[1, 1].set_xlim([XX.min(), XX.max()])\n", + "ax[1, 1].set_ylim([YY.min(), YY.max()])\n", + "ax[1, 1].tick_params(labelsize=12)\n", + "ax[1, 1].set_title('FBKAN', fontsize=12)\n", + "ax[1, 1].set_aspect('equal')\n", + "\n", + "# Plotting KAN error without isocontour lines\n", + "p = ax[0, 2].pcolor(XX, YY, error_kan, cmap=cmap)\n", + "fig.colorbar(p, ax=ax[0, 2])\n", + "ax[0, 2].set_xlim([XX.min(), XX.max()])\n", + "ax[0, 2].set_ylim([YY.min(), YY.max()])\n", + "ax[0, 2].tick_params(labelsize=12)\n", + "ax[0, 2].set_title('KAN absolute error', fontsize=12)\n", + "ax[0, 2].set_aspect('equal')\n", + "\n", + "# Plotting FBKAN error without isocontour lines\n", + "p = ax[1, 2].pcolor(XX, YY, error_fbkan, cmap=cmap)\n", + "fig.colorbar(p, ax=ax[1, 2])\n", + "ax[1, 2].set_xlim([XX.min(), XX.max()])\n", + "ax[1, 2].set_ylim([YY.min(), YY.max()])\n", + "ax[1, 2].tick_params(labelsize=12)\n", + "ax[1, 2].set_title('FBKAN absolute error', fontsize=12)\n", + "ax[1, 2].set_aspect('equal')\n", + "\n", + "# Plot error comparison along the y-axis\n", + "x_mid_index = XX.shape[0] // 2 # Get the middle index along the y-axis\n", + "ax[1, 0].plot(yy, y_mesh_true[x_mid_index, :], '-k', label='Exact')\n", + "ax[1, 0].plot(yy, z_mesh_pred_kan_reshaped[x_mid_index, :], 'og', label='KAN')\n", + "ax[1, 0].plot(yy, z_mesh_pred_fbkan_reshaped[x_mid_index, :],'sb', label='FBKAN')\n", + "ax[1, 0].set_xlabel('$y$', fontsize=12)\n", + "ax[1, 0].set_ylabel('$f(x,y)$', fontsize=12)\n", + "ax[1, 0].legend()\n", + "ax[1, 0].set_title('Comparison along vertical centerline', fontsize=12)\n", + "ax[1, 0].grid()\n", + "\n", + "print(f'MSE KAN = {np.mean((y_test.cpu().numpy() - z_test_pred_kan)**2) / np.mean(y_test.cpu().numpy()**2)}')\n", + "print(f'MSE FBKAN = {np.mean((y_test.cpu().numpy() - z_test_pred_fbkan)**2) / np.mean(y_test.cpu().numpy()**2)}')\n", + "\n", + "plt.tight_layout()\n", + "plt.show()\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "eebcbf71-2155-4d9b-b9ab-fb013437f37e", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "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": "3.10.0" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/examples/KANs/p3_mfkan_example_1d.ipynb b/examples/KANs/p3_mfkan_example_1d.ipynb new file mode 100644 index 00000000..977b0d3c --- /dev/null +++ b/examples/KANs/p3_mfkan_example_1d.ipynb @@ -0,0 +1,1075 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "zPjMocS6JIUz" + }, + "source": [ + "# Multi-Fidelity Kolmogorov-Arnold Networks (MFKANs) in Neuromancer\n", + "\n", + "This tutorial demonstrates the use of Multi-Fidelity Kolmogorov-Arnold Networks (MFKANs) for learning functions from high and low-fidelity data sources.\n", + "\n", + "\n", + "\n", + "\n", + "### References\n", + "\n", + "[1] [Liu, Ziming, et al. (2024). KAN: Kolmogorov-Arnold Networks.](https://arxiv.org/abs/2404.19756)\n", + "\n", + "[2] https://github.com/Blealtan/efficient-kan\n", + "\n", + "[3] [Howard, Amanda A., et al. (2024) Multifidelity KANs.]\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Y61YA90-WIZ1" + }, + "source": [ + "### Install Neuromancer\n", + "(Note: You can skip this step if running locally.)\n", + "(Note 2: Colab might ask you to restart your session after installing Neuromancer. Simply restart it when prompted.)" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000 + }, + "id": "WZrPCr9GWEAJ", + "outputId": "d0ff6dfe-de2a-4675-a36c-e2a7fce486d9" + }, + "outputs": [], + "source": [ + "import os\n", + "\n", + "# Check if the neuromancer directory already exists\n", + "if not os.path.isdir('neuromancer'):\n", + " # Clone the specific branch of the repository\n", + " !git clone --branch feature/mfkans https://github.com/pnnl/neuromancer.git\n", + "\n", + "# Navigate to the repository directory\n", + "%cd neuromancer\n", + "\n", + "# Install the repository with the required extras\n", + "!pip install -e .[docs,tests,examples]\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "6k0-63d0JIU1" + }, + "source": [ + "### Import dependencies" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "id": "OdYMzuSDi7Js" + }, + "outputs": [], + "source": [ + "import torch\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "\n", + "from neuromancer.dataset import DictDataset\n", + "from neuromancer.modules import blocks\n", + "from neuromancer.system import Node, System\n", + "from neuromancer.constraint import variable\n", + "from neuromancer.loss import PenaltyLoss\n", + "from neuromancer.problem import Problem\n", + "from neuromancer.trainer import Trainer\n", + "from neuromancer.loggers import LossLogger\n", + "\n", + "# filter some user warnings from torch broadcast\n", + "import warnings\n", + "warnings.filterwarnings(\"ignore\")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Configure device and RNG seed" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "id": "4-D966haJIU1" + }, + "outputs": [], + "source": [ + "# Set default dtype to float32\n", + "torch.set_default_dtype(torch.float)\n", + "#PyTorch random number generator\n", + "torch.manual_seed(1234)\n", + "# Random number generators in other libraries\n", + "np.random.seed(1234)\n", + "# Device configuration\n", + "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Generate data\n", + "\n", + "We will use the following jump function with a linear correlation. In this example we have sparse, high-fidelity data, which is not sufficient to capture the jump. \n", + "$$\n", + " y_L(x) = \\begin{cases} \n", + " 0.1\\left[0.5(6x-2)^2 \\sin(12x-4) + 10(x-0.5)-5\\right] & x \\leq 0.5 \\\\\n", + " 0.1\\left[0.5(6x-2)^2 \\sin(12x-4) + 10(x-0.5)-2\\right] & x > 0.5 \n", + " \\end{cases}\n", + "$$\n", + "$$\n", + "\n", + "y_H(x) = 2y_L(x) -2x + 2\n", + "$$\n", + "\n", + "for $ x \\in [0, 1].$ We take $ N_{LF}= 51 $ low-fidelity data points evenly distributed in $[0,1]$ and $ N_{HF} = 5 $ high-fidelity data points evenly spaced in $[0.1, 0.93]$. \n", + "\n", + "We also generate $N_{full} = 200$ data points to test low, high and multi-fidelity models.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# Define the low-fidelity and high-fidelity functions\n", + "def yL(x):\n", + " y = torch.where(x < 0.5,\n", + " 0.5*(6*x-2)**2 * torch.sin(12*x-4) + 10*(x-0.5)-5,\n", + " 3 + 0.5*(6*x-2)**2 * torch.sin(12*x-4) + 10*(x-0.5)-5)\n", + " return y / 10\n", + "\n", + "def yH(x):\n", + " return 2*(yL(x)) - 2*x + 2\n", + "\n", + "\n", + "# Generate three datasets: low-fidelity \n", + "x_data_LF = torch.linspace(0, 1, 51).reshape(-1, 1)\n", + "y_data_LF = yL(x_data_LF)\n", + "\n", + "x_data_HF = torch.linspace(.1, .93, 5).reshape(-1, 1)\n", + "y_data_HF = yH(x_data_HF)\n", + "\n", + "x_data_full = torch.linspace(0, 1, 200).reshape(-1, 1)\n", + "y_data_full = yH(x_data_full)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# We will leverage Neuromancer's DictDataset to wrap the different datasets, giving them names\n", + "train_data_LF = DictDataset({'x': x_data_LF.to(device), 'y': y_data_LF.to(device)}, name='train_LF')\n", + "train_data_HF = DictDataset({'x': x_data_HF.to(device), 'y': y_data_HF.to(device)}, name='train_HF')\n", + "data_full = DictDataset({'x': x_data_full.to(device), 'y': y_data_full.to(device)}, name='data_full')\n", + "\n", + "# Here we leverage Torch's DataLoader class, that can use Neuromancer's DictDataset directly\n", + "batch_size_LF = train_data_LF.datadict['x'].shape[0]\n", + "batch_size_HF = train_data_HF.datadict['x'].shape[0]\n", + "batch_size_full = data_full.datadict['x'].shape[0]\n", + "\n", + "train_loader_LF = torch.utils.data.DataLoader(train_data_LF, batch_size=batch_size_LF,\n", + " collate_fn=train_data_LF.collate_fn,\n", + " shuffle=False)\n", + "\n", + "train_loader_HF = torch.utils.data.DataLoader(train_data_HF, batch_size=batch_size_HF,\n", + " collate_fn=train_data_HF.collate_fn,\n", + " shuffle=False)\n", + "\n", + "\n", + "data_loader_full = torch.utils.data.DataLoader(data_full, batch_size=batch_size_full,\n", + " collate_fn=data_full.collate_fn,\n", + " shuffle=False)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Part 1: Create a single-fidelity KAN and train on low-fidelity data" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# Define the low-fidelity KAN model\n", + "kan_LF = blocks.KANBlock(\n", + " insize=1, # Input size\n", + " outsize=1, # Output size\n", + " hsizes=[5], # KAN shape is [insize, hsizes, outsize]\n", + " grid_sizes=[5], # Grid size. Note: Neuromancer currently only support single-grid\n", + " spline_order=3, # 3rd order splines\n", + " grid_range=[0, 1], # Range for grid normalization \n", + " base_activation=torch.nn.Sigmoid, # Basis function\n", + ").to(device)\n", + "\n", + "\n", + "# Symbolic wrapper of the LF KAN\n", + "kan_wrapper_LF = Node(kan_LF, ['x'], ['y_hat'], name='wrapper_LF')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Define symbolic variables and losses for low-fidelity KAN" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# Define symbolic variables for LF model\n", + "x_LF = variable('x')\n", + "y_LF = variable('y')\n", + "y_hat_LF = variable('y_hat')\n", + "\n", + "# Define losses\n", + "loss_data_LF = (y_LF == y_hat_LF)^2\n", + "loss_data_LF.name = \"ref_loss_LF\"\n", + "\n", + "# Create loss function\n", + "loss_LF = PenaltyLoss(objectives=[loss_data_LF], constraints=[])\n", + "\n", + "# Construct the optimization problem\n", + "problem_LF = Problem(nodes=[kan_wrapper_LF], loss=loss_LF, grad_inference=True)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Train the model defined by the `problem_LF`\n", + "\n", + "Here we train a single-fidelity KAN with low-fidelity data alone." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of parameters: 100\n", + "epoch: 0\ttrain_LF_loss: 0.28923\teltime: 0.02929\n", + "epoch: 100\ttrain_LF_loss: 0.02990\teltime: 0.16434\n", + "epoch: 200\ttrain_LF_loss: 0.00099\teltime: 0.29818\n", + "epoch: 300\ttrain_LF_loss: 0.00057\teltime: 0.43077\n", + "epoch: 400\ttrain_LF_loss: 0.00040\teltime: 0.56490\n", + "epoch: 500\ttrain_LF_loss: 0.00030\teltime: 0.69451\n", + "epoch: 600\ttrain_LF_loss: 0.00023\teltime: 0.82519\n", + "epoch: 700\ttrain_LF_loss: 0.00017\teltime: 0.95411\n", + "epoch: 800\ttrain_LF_loss: 0.00012\teltime: 1.08317\n", + "epoch: 900\ttrain_LF_loss: 0.00008\teltime: 1.21211\n", + "epoch: 1000\ttrain_LF_loss: 0.00005\teltime: 1.34099\n", + "epoch: 1100\ttrain_LF_loss: 0.00003\teltime: 1.47295\n", + "epoch: 1200\ttrain_LF_loss: 0.00002\teltime: 1.60520\n", + "epoch: 1300\ttrain_LF_loss: 0.00001\teltime: 1.73394\n", + "epoch: 1400\ttrain_LF_loss: 0.00001\teltime: 1.86303\n", + "epoch: 1500\ttrain_LF_loss: 0.00001\teltime: 1.99600\n", + "epoch: 1600\ttrain_LF_loss: 0.00001\teltime: 2.12536\n", + "epoch: 1700\ttrain_LF_loss: 0.00000\teltime: 2.24995\n", + "epoch: 1800\ttrain_LF_loss: 0.00000\teltime: 2.37797\n", + "epoch: 1900\ttrain_LF_loss: 0.00000\teltime: 2.50702\n", + "epoch: 2000\ttrain_LF_loss: 0.00000\teltime: 2.63460\n", + "epoch: 2100\ttrain_LF_loss: 0.00000\teltime: 2.76854\n", + "epoch: 2200\ttrain_LF_loss: 0.00000\teltime: 2.89938\n", + "epoch: 2300\ttrain_LF_loss: 0.00000\teltime: 3.02265\n", + "epoch: 2400\ttrain_LF_loss: 0.00000\teltime: 3.15452\n", + "epoch: 2500\ttrain_LF_loss: 0.00000\teltime: 3.27297\n", + "epoch: 2600\ttrain_LF_loss: 0.00000\teltime: 3.40348\n", + "epoch: 2700\ttrain_LF_loss: 0.00000\teltime: 3.52100\n", + "epoch: 2800\ttrain_LF_loss: 0.00000\teltime: 3.64977\n", + "epoch: 2900\ttrain_LF_loss: 0.00000\teltime: 3.77446\n", + "epoch: 3000\ttrain_LF_loss: 0.00000\teltime: 3.89494\n", + "epoch: 3100\ttrain_LF_loss: 0.00000\teltime: 4.02866\n", + "epoch: 3200\ttrain_LF_loss: 0.00000\teltime: 4.15645\n", + "epoch: 3300\ttrain_LF_loss: 0.00000\teltime: 4.27763\n", + "epoch: 3400\ttrain_LF_loss: 0.00001\teltime: 4.40387\n", + "epoch: 3500\ttrain_LF_loss: 0.00000\teltime: 4.52443\n", + "epoch: 3600\ttrain_LF_loss: 0.00000\teltime: 4.65828\n", + "epoch: 3700\ttrain_LF_loss: 0.00000\teltime: 4.78050\n", + "epoch: 3800\ttrain_LF_loss: 0.00000\teltime: 4.90837\n", + "epoch: 3900\ttrain_LF_loss: 0.00000\teltime: 5.04141\n", + "epoch: 4000\ttrain_LF_loss: 0.00000\teltime: 5.15972\n", + "epoch: 4100\ttrain_LF_loss: 0.00000\teltime: 5.28684\n", + "epoch: 4200\ttrain_LF_loss: 0.00000\teltime: 5.41620\n", + "epoch: 4300\ttrain_LF_loss: 0.00000\teltime: 5.53584\n", + "epoch: 4400\ttrain_LF_loss: 0.00000\teltime: 5.66481\n", + "epoch: 4500\ttrain_LF_loss: 0.00001\teltime: 5.78742\n", + "epoch: 4600\ttrain_LF_loss: 0.00000\teltime: 5.90449\n", + "epoch: 4700\ttrain_LF_loss: 0.00000\teltime: 6.03360\n", + "epoch: 4800\ttrain_LF_loss: 0.00000\teltime: 6.15129\n", + "epoch: 4900\ttrain_LF_loss: 0.00000\teltime: 6.27380\n", + "epoch: 5000\ttrain_LF_loss: 0.00000\teltime: 6.40276\n", + "epoch: 5100\ttrain_LF_loss: 0.00000\teltime: 6.51812\n", + "epoch: 5200\ttrain_LF_loss: 0.00000\teltime: 6.64508\n", + "epoch: 5300\ttrain_LF_loss: 0.00000\teltime: 6.76892\n", + "epoch: 5400\ttrain_LF_loss: 0.00000\teltime: 6.89108\n", + "epoch: 5500\ttrain_LF_loss: 0.00000\teltime: 7.02495\n", + "epoch: 5600\ttrain_LF_loss: 0.00000\teltime: 7.14651\n", + "epoch: 5700\ttrain_LF_loss: 0.00000\teltime: 7.27781\n", + "epoch: 5800\ttrain_LF_loss: 0.00000\teltime: 7.41108\n", + "epoch: 5900\ttrain_LF_loss: 0.00000\teltime: 7.52457\n", + "epoch: 6000\ttrain_LF_loss: 0.00000\teltime: 7.64994\n", + "epoch: 6100\ttrain_LF_loss: 0.00004\teltime: 7.77374\n", + "epoch: 6200\ttrain_LF_loss: 0.00000\teltime: 7.88996\n", + "epoch: 6300\ttrain_LF_loss: 0.00000\teltime: 8.01677\n", + "epoch: 6400\ttrain_LF_loss: 0.00000\teltime: 8.13552\n", + "epoch: 6500\ttrain_LF_loss: 0.00000\teltime: 8.25520\n", + "epoch: 6600\ttrain_LF_loss: 0.00000\teltime: 8.38427\n", + "epoch: 6700\ttrain_LF_loss: 0.00000\teltime: 8.49959\n", + "epoch: 6800\ttrain_LF_loss: 0.00000\teltime: 8.62357\n", + "epoch: 6900\ttrain_LF_loss: 0.00000\teltime: 8.74854\n", + "epoch: 7000\ttrain_LF_loss: 0.00000\teltime: 8.86946\n", + "epoch: 7100\ttrain_LF_loss: 0.00000\teltime: 9.00702\n", + "epoch: 7200\ttrain_LF_loss: 0.00000\teltime: 9.12624\n", + "epoch: 7300\ttrain_LF_loss: 0.00000\teltime: 9.24753\n", + "epoch: 7400\ttrain_LF_loss: 0.00000\teltime: 9.36985\n", + "epoch: 7500\ttrain_LF_loss: 0.00000\teltime: 9.48475\n", + "epoch: 7600\ttrain_LF_loss: 0.00000\teltime: 9.61265\n", + "epoch: 7700\ttrain_LF_loss: 0.00000\teltime: 9.72883\n", + "epoch: 7800\ttrain_LF_loss: 0.00000\teltime: 9.85056\n", + "epoch: 7900\ttrain_LF_loss: 0.00000\teltime: 9.97873\n", + "epoch: 8000\ttrain_LF_loss: 0.00000\teltime: 10.09357\n", + "epoch: 8100\ttrain_LF_loss: 0.00000\teltime: 10.21628\n", + "epoch: 8200\ttrain_LF_loss: 0.00000\teltime: 10.34431\n", + "epoch: 8300\ttrain_LF_loss: 0.00000\teltime: 10.46160\n", + "epoch: 8400\ttrain_LF_loss: 0.00000\teltime: 10.58424\n", + "epoch: 8500\ttrain_LF_loss: 0.00000\teltime: 10.70324\n", + "epoch: 8600\ttrain_LF_loss: 0.00000\teltime: 10.81873\n", + "epoch: 8700\ttrain_LF_loss: 0.00000\teltime: 10.95177\n", + "epoch: 8800\ttrain_LF_loss: 0.00000\teltime: 11.06928\n", + "epoch: 8900\ttrain_LF_loss: 0.00000\teltime: 11.19095\n", + "epoch: 9000\ttrain_LF_loss: 0.00001\teltime: 11.31503\n", + "epoch: 9100\ttrain_LF_loss: 0.00000\teltime: 11.43006\n", + "epoch: 9200\ttrain_LF_loss: 0.00000\teltime: 11.55888\n", + "epoch: 9300\ttrain_LF_loss: 0.00000\teltime: 11.67542\n", + "epoch: 9400\ttrain_LF_loss: 0.00000\teltime: 11.79353\n", + "epoch: 9500\ttrain_LF_loss: 0.00000\teltime: 11.92035\n", + "epoch: 9600\ttrain_LF_loss: 0.00000\teltime: 12.03579\n", + "epoch: 9700\ttrain_LF_loss: 0.00000\teltime: 12.16444\n", + "epoch: 9800\ttrain_LF_loss: 0.00000\teltime: 12.28807\n", + "epoch: 9900\ttrain_LF_loss: 0.00000\teltime: 12.40648\n" + ] + } + ], + "source": [ + "# Create trainer for LF model\n", + "init_lr =0.005\n", + "epoch_verbose_lf = 100\n", + "num_epochs_lf=10000\n", + "logger_LF = LossLogger(args=None, savedir='test_LF', verbosity=epoch_verbose_lf, stdout=['train_LF_loss'])\n", + "\n", + "\n", + "trainer_LF = Trainer(\n", + " problem_LF.to(device),\n", + " train_data=train_loader_LF,\n", + " dev_data=train_loader_LF,\n", + " optimizer= torch.optim.Adam(problem_LF.parameters(), lr=init_lr),\n", + " epoch_verbose=epoch_verbose_lf,\n", + " logger=logger_LF,\n", + " epochs=num_epochs_lf,\n", + " train_metric='train_LF_loss',\n", + " eval_metric='train_LF_loss',\n", + " dev_metric='train_LF_loss',\n", + " warmup=num_epochs_lf,\n", + " device=device\n", + ")\n", + "\n", + "\n", + "# Train LF model\n", + "best_model_LF = trainer_LF.train()\n", + "problem_LF.load_state_dict(best_model_LF)\n", + "trained_model_LF = problem_LF.nodes[0]\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Part 2: Create a single-fidelity KAN and train on high-fidelity data" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "# Define the high-fidelity KAN model\n", + "kan_HF = blocks.KANBlock(\n", + " insize=1, # Input size\n", + " outsize=1, # Output size\n", + " hsizes=[5], # KAN shape is [insize, hsizes, outsize]\n", + " grid_sizes=[5], # Grid size. Note: Neuromancer currently only support single-grid\n", + " spline_order=3, # 3rd order splines\n", + " grid_range=[0, 1], # Range for grid normalization \n", + " base_activation=torch.nn.Sigmoid, # Basis function\n", + ").to(device)\n", + "\n", + "# Symbolic wrapper of the HF KAN\n", + "kan_wrapper_HF = Node(kan_HF, ['x'], ['y_hat'], name='wrapper_HF')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Define symbolic variables and losses for high-fidelity KAN" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "# Define symbolic variables for HF model\n", + "x_HF = variable('x')\n", + "y_HF = variable('y')\n", + "y_hat_HF = variable('y_hat')\n", + "\n", + "# Define losses\n", + "loss_data_HF = (y_HF == y_hat_HF)^2\n", + "loss_data_HF.name = \"ref_loss_HF\"\n", + "\n", + "# Create loss function\n", + "loss_HF = PenaltyLoss(objectives=[loss_data_HF], constraints=[])\n", + "\n", + "# Construct the HF optimization problem\n", + "problem_HF = Problem(nodes=[kan_wrapper_HF], loss=loss_HF, grad_inference=True)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Train the model defined by the `problem_HF`\n", + "\n", + "Here we train a single-fidelity KAN with the high-fidelity data alone." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of parameters: 100\n", + "epoch: 0\ttrain_HF_loss: 0.61907\teltime: 0.00270\n", + "epoch: 100\ttrain_HF_loss: 0.00110\teltime: 0.11428\n", + "epoch: 200\ttrain_HF_loss: 0.00000\teltime: 0.21474\n", + "epoch: 300\ttrain_HF_loss: 0.00000\teltime: 0.31609\n", + "epoch: 400\ttrain_HF_loss: 0.00000\teltime: 0.41249\n", + "epoch: 500\ttrain_HF_loss: 0.00000\teltime: 0.50663\n", + "epoch: 600\ttrain_HF_loss: 0.00000\teltime: 0.60414\n", + "epoch: 700\ttrain_HF_loss: 0.00000\teltime: 0.70197\n", + "epoch: 800\ttrain_HF_loss: 0.00000\teltime: 0.79531\n", + "epoch: 900\ttrain_HF_loss: 0.00000\teltime: 0.89208\n", + "epoch: 1000\ttrain_HF_loss: 0.00000\teltime: 0.98970\n", + "epoch: 1100\ttrain_HF_loss: 0.00000\teltime: 1.08312\n", + "epoch: 1200\ttrain_HF_loss: 0.00000\teltime: 1.18582\n", + "epoch: 1300\ttrain_HF_loss: 0.00000\teltime: 1.28156\n", + "epoch: 1400\ttrain_HF_loss: 0.00000\teltime: 1.37587\n", + "epoch: 1500\ttrain_HF_loss: 0.00000\teltime: 1.47076\n", + "epoch: 1600\ttrain_HF_loss: 0.00000\teltime: 1.56531\n", + "epoch: 1700\ttrain_HF_loss: 0.00000\teltime: 1.66175\n", + "epoch: 1800\ttrain_HF_loss: 0.00000\teltime: 1.75759\n", + "epoch: 1900\ttrain_HF_loss: 0.00000\teltime: 1.85336\n", + "epoch: 2000\ttrain_HF_loss: 0.00000\teltime: 1.94770\n", + "epoch: 2100\ttrain_HF_loss: 0.00000\teltime: 2.04235\n", + "epoch: 2200\ttrain_HF_loss: 0.00000\teltime: 2.13705\n", + "epoch: 2300\ttrain_HF_loss: 0.00000\teltime: 2.23081\n", + "epoch: 2400\ttrain_HF_loss: 0.00000\teltime: 2.32509\n", + "epoch: 2500\ttrain_HF_loss: 0.00000\teltime: 2.41951\n", + "epoch: 2600\ttrain_HF_loss: 0.00000\teltime: 2.51318\n", + "epoch: 2700\ttrain_HF_loss: 0.00000\teltime: 2.60754\n", + "epoch: 2800\ttrain_HF_loss: 0.00000\teltime: 2.70216\n", + "epoch: 2900\ttrain_HF_loss: 0.00000\teltime: 2.80034\n", + "epoch: 3000\ttrain_HF_loss: 0.00000\teltime: 2.89345\n", + "epoch: 3100\ttrain_HF_loss: 0.00000\teltime: 2.98654\n", + "epoch: 3200\ttrain_HF_loss: 0.00000\teltime: 3.08214\n", + "epoch: 3300\ttrain_HF_loss: 0.00000\teltime: 3.17693\n", + "epoch: 3400\ttrain_HF_loss: 0.00000\teltime: 3.27147\n", + "epoch: 3500\ttrain_HF_loss: 0.00000\teltime: 3.36933\n", + "epoch: 3600\ttrain_HF_loss: 0.00000\teltime: 3.46336\n", + "epoch: 3700\ttrain_HF_loss: 0.00000\teltime: 3.55791\n", + "epoch: 3800\ttrain_HF_loss: 0.00000\teltime: 3.65166\n", + "epoch: 3900\ttrain_HF_loss: 0.00000\teltime: 3.74749\n", + "epoch: 4000\ttrain_HF_loss: 0.00000\teltime: 3.84320\n", + "epoch: 4100\ttrain_HF_loss: 0.00000\teltime: 3.94093\n", + "epoch: 4200\ttrain_HF_loss: 0.00000\teltime: 4.03516\n", + "epoch: 4300\ttrain_HF_loss: 0.00000\teltime: 4.12984\n", + "epoch: 4400\ttrain_HF_loss: 0.00000\teltime: 4.22490\n", + "epoch: 4500\ttrain_HF_loss: 0.00000\teltime: 4.32297\n", + "epoch: 4600\ttrain_HF_loss: 0.00000\teltime: 4.42150\n", + "epoch: 4700\ttrain_HF_loss: 0.00000\teltime: 4.51528\n", + "epoch: 4800\ttrain_HF_loss: 0.00000\teltime: 4.60860\n", + "epoch: 4900\ttrain_HF_loss: 0.00000\teltime: 4.70197\n", + "epoch: 5000\ttrain_HF_loss: 0.00000\teltime: 4.79649\n", + "epoch: 5100\ttrain_HF_loss: 0.00000\teltime: 4.88983\n", + "epoch: 5200\ttrain_HF_loss: 0.00000\teltime: 4.98333\n", + "epoch: 5300\ttrain_HF_loss: 0.00000\teltime: 5.07733\n", + "epoch: 5400\ttrain_HF_loss: 0.00000\teltime: 5.17497\n", + "epoch: 5500\ttrain_HF_loss: 0.00000\teltime: 5.27349\n", + "epoch: 5600\ttrain_HF_loss: 0.00000\teltime: 5.39752\n", + "epoch: 5700\ttrain_HF_loss: 0.00000\teltime: 5.49568\n", + "epoch: 5800\ttrain_HF_loss: 0.00000\teltime: 5.59400\n", + "epoch: 5900\ttrain_HF_loss: 0.00000\teltime: 5.68871\n", + "epoch: 6000\ttrain_HF_loss: 0.00000\teltime: 5.78636\n", + "epoch: 6100\ttrain_HF_loss: 0.00000\teltime: 5.88455\n", + "epoch: 6200\ttrain_HF_loss: 0.00000\teltime: 5.98716\n", + "epoch: 6300\ttrain_HF_loss: 0.00000\teltime: 6.08131\n", + "epoch: 6400\ttrain_HF_loss: 0.00000\teltime: 6.17586\n", + "epoch: 6500\ttrain_HF_loss: 0.00000\teltime: 6.26988\n", + "epoch: 6600\ttrain_HF_loss: 0.00000\teltime: 6.36429\n", + "epoch: 6700\ttrain_HF_loss: 0.00000\teltime: 6.45828\n", + "epoch: 6800\ttrain_HF_loss: 0.00000\teltime: 6.55292\n", + "epoch: 6900\ttrain_HF_loss: 0.00000\teltime: 6.65106\n", + "epoch: 7000\ttrain_HF_loss: 0.00000\teltime: 6.74928\n", + "epoch: 7100\ttrain_HF_loss: 0.00000\teltime: 6.84368\n", + "epoch: 7200\ttrain_HF_loss: 0.00000\teltime: 6.94149\n", + "epoch: 7300\ttrain_HF_loss: 0.00000\teltime: 7.03986\n", + "epoch: 7400\ttrain_HF_loss: 0.00000\teltime: 7.13431\n", + "epoch: 7500\ttrain_HF_loss: 0.00000\teltime: 7.23205\n", + "epoch: 7600\ttrain_HF_loss: 0.00000\teltime: 7.33030\n", + "epoch: 7700\ttrain_HF_loss: 0.00000\teltime: 7.42895\n", + "epoch: 7800\ttrain_HF_loss: 0.00000\teltime: 7.52235\n", + "epoch: 7900\ttrain_HF_loss: 0.00000\teltime: 7.61578\n", + "epoch: 8000\ttrain_HF_loss: 0.00000\teltime: 7.71529\n", + "epoch: 8100\ttrain_HF_loss: 0.00000\teltime: 7.80847\n", + "epoch: 8200\ttrain_HF_loss: 0.00000\teltime: 7.90207\n", + "epoch: 8300\ttrain_HF_loss: 0.00000\teltime: 7.99743\n", + "epoch: 8400\ttrain_HF_loss: 0.00000\teltime: 8.09520\n", + "epoch: 8500\ttrain_HF_loss: 0.00000\teltime: 8.19344\n", + "epoch: 8600\ttrain_HF_loss: 0.00000\teltime: 8.28717\n", + "epoch: 8700\ttrain_HF_loss: 0.00000\teltime: 8.38186\n", + "epoch: 8800\ttrain_HF_loss: 0.00000\teltime: 8.47689\n", + "epoch: 8900\ttrain_HF_loss: 0.00000\teltime: 8.57462\n", + "epoch: 9000\ttrain_HF_loss: 0.00000\teltime: 8.66765\n", + "epoch: 9100\ttrain_HF_loss: 0.00000\teltime: 8.76147\n", + "epoch: 9200\ttrain_HF_loss: 0.00000\teltime: 8.85646\n", + "epoch: 9300\ttrain_HF_loss: 0.00000\teltime: 8.94994\n", + "epoch: 9400\ttrain_HF_loss: 0.00000\teltime: 9.04368\n", + "epoch: 9500\ttrain_HF_loss: 0.00000\teltime: 9.14018\n", + "epoch: 9600\ttrain_HF_loss: 0.00000\teltime: 9.23563\n", + "epoch: 9700\ttrain_HF_loss: 0.00000\teltime: 9.33089\n", + "epoch: 9800\ttrain_HF_loss: 0.00000\teltime: 9.43206\n", + "epoch: 9900\ttrain_HF_loss: 0.00000\teltime: 9.52504\n" + ] + } + ], + "source": [ + "# Create trainer for HF model\n", + "init_lr =0.005\n", + "epoch_verbose_hf = 100\n", + "num_epochs_hf=10000\n", + "logger_HF = LossLogger(args=None, savedir='test_HF', verbosity=epoch_verbose_hf, stdout=['train_HF_loss'])\n", + "\n", + "trainer_HF = Trainer(\n", + " problem_HF.to(device),\n", + " train_data=train_loader_HF,\n", + " dev_data=train_loader_HF,\n", + " optimizer= torch.optim.Adam(problem_HF.parameters(), lr=init_lr),\n", + " epoch_verbose=epoch_verbose_hf,\n", + " logger=logger_HF,\n", + " epochs=num_epochs_hf,\n", + " train_metric='train_HF_loss',\n", + " eval_metric='train_HF_loss',\n", + " dev_metric='train_HF_loss',\n", + " warmup=num_epochs_hf,\n", + " device=device\n", + ")\n", + "\n", + "# Train HF model\n", + "best_model_HF = trainer_HF.train()\n", + "problem_HF.load_state_dict(best_model_HF)\n", + "trained_model_HF = problem_HF.nodes[0]\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Part 3: Create a multi-fidelity KAN\n", + "\n", + "This network leverages the low-fidelity model and the high-fidelity data." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "# Define the multi-fidelity KAN model\n", + "\n", + "# Here we use Neuromancer's MultiFidelityKAN block. The syntax is very similar to KANBlock!\n", + "kan_MF = blocks.MultiFidelityKAN(\n", + " sfkan=kan_LF, # A trained, low-fidelity model\n", + " insize=1, # Input size\n", + " outsize=1, # Output size\n", + " hsizes=[5], # Nonlinear KAN shape: [insize, hsizes, outsize]. Shape of linear KAN is always [insize, outsize].\n", + " grid_sizes=[4], # Grid size. Note: Neuromancer currently only support single-grid\n", + " spline_order=2, # 2nd order splines\n", + " grid_range=[0, 1], # Range for grid normalization \n", + " alpha_init=0.1, # Initial value of learnable weight alpha, used in the convex combination of linear and nonlinear nets.\n", + " base_activation=torch.nn.Sigmoid, # Basis function\n", + ").to(device)\n", + "\n", + "# Symbolic wrapper of the MF KAN\n", + "kan_wrapper_MF = Node(kan_MF, ['x'], ['y_hat'], name='kan_wrapper_MF')\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Define symbolic variables and losses for multi-fidelity KAN" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "# Define symbolic variables for MF model\n", + "x_MF = variable('x')\n", + "y_MF = variable('y')\n", + "y_hat_MF = variable('y_hat')\n", + "\n", + "# Define losses\n", + "loss_data_MF = (y_MF == y_hat_MF)^2\n", + "loss_data_MF.name = \"ref_loss_MF\"\n", + "\n", + "# Create loss function\n", + "loss_MF = PenaltyLoss(objectives=[loss_data_MF], constraints=[])\n", + "\n", + "# Construct the MF optimization problem\n", + "problem_MF = Problem(nodes=[kan_wrapper_MF], loss=loss_MF, grad_inference=True)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Train the model defined by the `problem_MF`\n", + "\n", + "Here we train a multi-fidelity KAN using a low-fidelity, pre-trained model and high-fidelity, sparse data." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of parameters: 131\n", + "epoch: 0\ttrain_HF_loss: 0.49794\teltime: 0.00381\n", + "epoch: 100\ttrain_HF_loss: 0.05398\teltime: 0.19552\n", + "epoch: 200\ttrain_HF_loss: 0.04039\teltime: 0.39655\n", + "epoch: 300\ttrain_HF_loss: 0.01642\teltime: 0.58579\n", + "epoch: 400\ttrain_HF_loss: 0.00703\teltime: 0.77287\n", + "epoch: 500\ttrain_HF_loss: 0.00391\teltime: 0.95766\n", + "epoch: 600\ttrain_HF_loss: 0.00253\teltime: 1.14821\n", + "epoch: 700\ttrain_HF_loss: 0.00177\teltime: 1.32636\n", + "epoch: 800\ttrain_HF_loss: 0.00129\teltime: 1.50102\n", + "epoch: 900\ttrain_HF_loss: 0.00099\teltime: 1.68525\n", + "epoch: 1000\ttrain_HF_loss: 0.00079\teltime: 1.87304\n", + "epoch: 1100\ttrain_HF_loss: 0.00064\teltime: 2.04949\n", + "epoch: 1200\ttrain_HF_loss: 0.00055\teltime: 2.21655\n", + "epoch: 1300\ttrain_HF_loss: 0.00044\teltime: 2.40254\n", + "epoch: 1400\ttrain_HF_loss: 0.00037\teltime: 2.59020\n", + "epoch: 1500\ttrain_HF_loss: 0.00030\teltime: 2.76811\n", + "epoch: 1600\ttrain_HF_loss: 0.00024\teltime: 2.96144\n", + "epoch: 1700\ttrain_HF_loss: 0.00020\teltime: 3.13274\n", + "epoch: 1800\ttrain_HF_loss: 0.00016\teltime: 3.31163\n", + "epoch: 1900\ttrain_HF_loss: 0.00013\teltime: 3.49370\n", + "epoch: 2000\ttrain_HF_loss: 0.00011\teltime: 3.66585\n", + "epoch: 2100\ttrain_HF_loss: 0.00009\teltime: 3.83847\n", + "epoch: 2200\ttrain_HF_loss: 0.00007\teltime: 4.01240\n", + "epoch: 2300\ttrain_HF_loss: 0.00005\teltime: 4.18102\n", + "epoch: 2400\ttrain_HF_loss: 0.00004\teltime: 4.34899\n", + "epoch: 2500\ttrain_HF_loss: 0.00003\teltime: 4.52197\n", + "epoch: 2600\ttrain_HF_loss: 0.00004\teltime: 4.69354\n", + "epoch: 2700\ttrain_HF_loss: 0.00001\teltime: 4.87159\n", + "epoch: 2800\ttrain_HF_loss: 0.00001\teltime: 5.03473\n", + "epoch: 2900\ttrain_HF_loss: 0.00006\teltime: 5.21688\n", + "epoch: 3000\ttrain_HF_loss: 0.00000\teltime: 5.38323\n", + "epoch: 3100\ttrain_HF_loss: 0.00001\teltime: 5.55701\n", + "epoch: 3200\ttrain_HF_loss: 0.00000\teltime: 5.73750\n", + "epoch: 3300\ttrain_HF_loss: 0.00000\teltime: 5.89653\n", + "epoch: 3400\ttrain_HF_loss: 0.00000\teltime: 6.07450\n", + "epoch: 3500\ttrain_HF_loss: 0.00000\teltime: 6.23402\n", + "epoch: 3600\ttrain_HF_loss: 0.00004\teltime: 6.40454\n", + "epoch: 3700\ttrain_HF_loss: 0.00000\teltime: 6.56518\n", + "epoch: 3800\ttrain_HF_loss: 0.00001\teltime: 6.73146\n", + "epoch: 3900\ttrain_HF_loss: 0.00000\teltime: 6.88974\n", + "epoch: 4000\ttrain_HF_loss: 0.00000\teltime: 7.04982\n", + "epoch: 4100\ttrain_HF_loss: 0.00000\teltime: 7.20961\n", + "epoch: 4200\ttrain_HF_loss: 0.00000\teltime: 7.36634\n", + "epoch: 4300\ttrain_HF_loss: 0.00000\teltime: 7.52261\n", + "epoch: 4400\ttrain_HF_loss: 0.00000\teltime: 7.68976\n", + "epoch: 4500\ttrain_HF_loss: 0.00000\teltime: 7.84454\n", + "epoch: 4600\ttrain_HF_loss: 0.00000\teltime: 8.00179\n", + "epoch: 4700\ttrain_HF_loss: 0.00000\teltime: 8.16284\n", + "epoch: 4800\ttrain_HF_loss: 0.00000\teltime: 8.32455\n", + "epoch: 4900\ttrain_HF_loss: 0.00000\teltime: 8.48521\n", + "epoch: 5000\ttrain_HF_loss: 0.00000\teltime: 8.64290\n", + "epoch: 5100\ttrain_HF_loss: 0.00002\teltime: 8.80497\n", + "epoch: 5200\ttrain_HF_loss: 0.00000\teltime: 8.96105\n", + "epoch: 5300\ttrain_HF_loss: 0.00006\teltime: 9.11873\n", + "epoch: 5400\ttrain_HF_loss: 0.00000\teltime: 9.27524\n", + "epoch: 5500\ttrain_HF_loss: 0.00002\teltime: 9.43070\n", + "epoch: 5600\ttrain_HF_loss: 0.00000\teltime: 9.58733\n", + "epoch: 5700\ttrain_HF_loss: 0.00000\teltime: 9.74352\n", + "epoch: 5800\ttrain_HF_loss: 0.00000\teltime: 9.90043\n", + "epoch: 5900\ttrain_HF_loss: 0.00000\teltime: 10.06250\n", + "epoch: 6000\ttrain_HF_loss: 0.00000\teltime: 10.21906\n", + "epoch: 6100\ttrain_HF_loss: 0.00000\teltime: 10.38037\n", + "epoch: 6200\ttrain_HF_loss: 0.00033\teltime: 10.54589\n", + "epoch: 6300\ttrain_HF_loss: 0.00000\teltime: 10.70106\n", + "epoch: 6400\ttrain_HF_loss: 0.00000\teltime: 10.85539\n", + "epoch: 6500\ttrain_HF_loss: 0.00000\teltime: 11.01700\n", + "epoch: 6600\ttrain_HF_loss: 0.00000\teltime: 11.17345\n", + "epoch: 6700\ttrain_HF_loss: 0.00000\teltime: 11.33450\n", + "epoch: 6800\ttrain_HF_loss: 0.00000\teltime: 11.49212\n", + "epoch: 6900\ttrain_HF_loss: 0.00000\teltime: 11.64926\n", + "epoch: 7000\ttrain_HF_loss: 0.00003\teltime: 11.80785\n", + "epoch: 7100\ttrain_HF_loss: 0.00000\teltime: 11.97048\n", + "epoch: 7200\ttrain_HF_loss: 0.00010\teltime: 12.13281\n", + "epoch: 7300\ttrain_HF_loss: 0.00000\teltime: 12.28854\n", + "epoch: 7400\ttrain_HF_loss: 0.00000\teltime: 12.44568\n", + "epoch: 7500\ttrain_HF_loss: 0.00000\teltime: 12.60751\n", + "epoch: 7600\ttrain_HF_loss: 0.00000\teltime: 12.76965\n", + "epoch: 7700\ttrain_HF_loss: 0.00005\teltime: 12.92561\n", + "epoch: 7800\ttrain_HF_loss: 0.00000\teltime: 13.08260\n", + "epoch: 7900\ttrain_HF_loss: 0.00000\teltime: 13.24395\n", + "epoch: 8000\ttrain_HF_loss: 0.00000\teltime: 13.40610\n", + "epoch: 8100\ttrain_HF_loss: 0.00000\teltime: 13.56460\n", + "epoch: 8200\ttrain_HF_loss: 0.00000\teltime: 13.74919\n", + "epoch: 8300\ttrain_HF_loss: 0.00000\teltime: 13.90511\n", + "epoch: 8400\ttrain_HF_loss: 0.00000\teltime: 14.07140\n", + "epoch: 8500\ttrain_HF_loss: 0.00009\teltime: 14.25007\n", + "epoch: 8600\ttrain_HF_loss: 0.00000\teltime: 14.40581\n", + "epoch: 8700\ttrain_HF_loss: 0.00000\teltime: 14.58163\n", + "epoch: 8800\ttrain_HF_loss: 0.00000\teltime: 14.73713\n", + "epoch: 8900\ttrain_HF_loss: 0.00000\teltime: 14.90421\n", + "epoch: 9000\ttrain_HF_loss: 0.00000\teltime: 15.08326\n", + "epoch: 9100\ttrain_HF_loss: 0.00000\teltime: 15.23869\n", + "epoch: 9200\ttrain_HF_loss: 0.00000\teltime: 15.40918\n", + "epoch: 9300\ttrain_HF_loss: 0.00000\teltime: 15.56601\n", + "epoch: 9400\ttrain_HF_loss: 0.00000\teltime: 15.73261\n", + "epoch: 9500\ttrain_HF_loss: 0.00001\teltime: 15.89992\n", + "epoch: 9600\ttrain_HF_loss: 0.00000\teltime: 16.05665\n", + "epoch: 9700\ttrain_HF_loss: 0.00000\teltime: 16.23551\n", + "epoch: 9800\ttrain_HF_loss: 0.00000\teltime: 16.39111\n", + "epoch: 9900\ttrain_HF_loss: 0.00000\teltime: 16.56118\n", + "epoch: 10000\ttrain_HF_loss: 0.00000\teltime: 16.72418\n", + "epoch: 10100\ttrain_HF_loss: 0.00000\teltime: 16.88834\n", + "epoch: 10200\ttrain_HF_loss: 0.00010\teltime: 17.07175\n", + "epoch: 10300\ttrain_HF_loss: 0.00000\teltime: 17.22786\n", + "epoch: 10400\ttrain_HF_loss: 0.00000\teltime: 17.38862\n", + "epoch: 10500\ttrain_HF_loss: 0.00002\teltime: 17.57103\n", + "epoch: 10600\ttrain_HF_loss: 0.00000\teltime: 17.72851\n", + "epoch: 10700\ttrain_HF_loss: 0.00000\teltime: 17.90562\n", + "epoch: 10800\ttrain_HF_loss: 0.00000\teltime: 18.06861\n", + "epoch: 10900\ttrain_HF_loss: 0.00000\teltime: 18.22485\n", + "epoch: 11000\ttrain_HF_loss: 0.00000\teltime: 18.41453\n", + "epoch: 11100\ttrain_HF_loss: 0.00000\teltime: 18.57161\n", + "epoch: 11200\ttrain_HF_loss: 0.00000\teltime: 18.73530\n", + "epoch: 11300\ttrain_HF_loss: 0.00000\teltime: 18.91516\n", + "epoch: 11400\ttrain_HF_loss: 0.00000\teltime: 19.07042\n", + "epoch: 11500\ttrain_HF_loss: 0.00000\teltime: 19.24921\n", + "epoch: 11600\ttrain_HF_loss: 0.00000\teltime: 19.41372\n", + "epoch: 11700\ttrain_HF_loss: 0.00000\teltime: 19.57605\n", + "epoch: 11800\ttrain_HF_loss: 0.00002\teltime: 19.75235\n", + "epoch: 11900\ttrain_HF_loss: 0.00000\teltime: 19.90924\n", + "epoch: 12000\ttrain_HF_loss: 0.00000\teltime: 20.08444\n", + "epoch: 12100\ttrain_HF_loss: 0.00000\teltime: 20.23792\n", + "epoch: 12200\ttrain_HF_loss: 0.00000\teltime: 20.41586\n", + "epoch: 12300\ttrain_HF_loss: 0.00000\teltime: 20.57516\n", + "epoch: 12400\ttrain_HF_loss: 0.00000\teltime: 20.72894\n", + "epoch: 12500\ttrain_HF_loss: 0.00013\teltime: 20.90862\n", + "epoch: 12600\ttrain_HF_loss: 0.00000\teltime: 21.06517\n", + "epoch: 12700\ttrain_HF_loss: 0.00000\teltime: 21.23664\n", + "epoch: 12800\ttrain_HF_loss: 0.00000\teltime: 21.39672\n", + "epoch: 12900\ttrain_HF_loss: 0.00000\teltime: 21.55203\n", + "epoch: 13000\ttrain_HF_loss: 0.00003\teltime: 21.73418\n", + "epoch: 13100\ttrain_HF_loss: 0.00000\teltime: 21.88853\n", + "epoch: 13200\ttrain_HF_loss: 0.00000\teltime: 22.05885\n", + "epoch: 13300\ttrain_HF_loss: 0.00003\teltime: 22.23299\n", + "epoch: 13400\ttrain_HF_loss: 0.00000\teltime: 22.39175\n", + "epoch: 13500\ttrain_HF_loss: 0.00000\teltime: 22.56750\n", + "epoch: 13600\ttrain_HF_loss: 0.00000\teltime: 22.72309\n", + "epoch: 13700\ttrain_HF_loss: 0.00000\teltime: 22.89708\n", + "epoch: 13800\ttrain_HF_loss: 0.00001\teltime: 23.07607\n", + "epoch: 13900\ttrain_HF_loss: 0.00000\teltime: 23.23045\n", + "epoch: 14000\ttrain_HF_loss: 0.00000\teltime: 23.39921\n", + "epoch: 14100\ttrain_HF_loss: 0.00012\teltime: 23.57696\n", + "epoch: 14200\ttrain_HF_loss: 0.00000\teltime: 23.73401\n", + "epoch: 14300\ttrain_HF_loss: 0.00000\teltime: 23.91380\n", + "epoch: 14400\ttrain_HF_loss: 0.00001\teltime: 24.09190\n", + "epoch: 14500\ttrain_HF_loss: 0.00000\teltime: 24.24850\n", + "epoch: 14600\ttrain_HF_loss: 0.00000\teltime: 24.43149\n", + "epoch: 14700\ttrain_HF_loss: 0.00000\teltime: 24.59704\n", + "epoch: 14800\ttrain_HF_loss: 0.00000\teltime: 24.76679\n", + "epoch: 14900\ttrain_HF_loss: 0.00000\teltime: 24.94718\n", + "epoch: 15000\ttrain_HF_loss: 0.00000\teltime: 25.11051\n", + "epoch: 15100\ttrain_HF_loss: 0.00000\teltime: 25.28891\n", + "epoch: 15200\ttrain_HF_loss: 0.00000\teltime: 25.45364\n", + "epoch: 15300\ttrain_HF_loss: 0.00000\teltime: 25.61920\n", + "epoch: 15400\ttrain_HF_loss: 0.00000\teltime: 25.80002\n", + "epoch: 15500\ttrain_HF_loss: 0.00000\teltime: 25.97354\n", + "epoch: 15600\ttrain_HF_loss: 0.00000\teltime: 26.12965\n", + "epoch: 15700\ttrain_HF_loss: 0.00000\teltime: 26.31680\n", + "epoch: 15800\ttrain_HF_loss: 0.00000\teltime: 26.48590\n", + "epoch: 15900\ttrain_HF_loss: 0.00000\teltime: 26.65200\n", + "epoch: 16000\ttrain_HF_loss: 0.00000\teltime: 26.83328\n", + "epoch: 16100\ttrain_HF_loss: 0.00000\teltime: 27.00038\n", + "epoch: 16200\ttrain_HF_loss: 0.00000\teltime: 27.16980\n", + "epoch: 16300\ttrain_HF_loss: 0.00000\teltime: 27.34440\n", + "epoch: 16400\ttrain_HF_loss: 0.00000\teltime: 27.50882\n", + "epoch: 16500\ttrain_HF_loss: 0.00000\teltime: 27.68831\n", + "epoch: 16600\ttrain_HF_loss: 0.00000\teltime: 27.85227\n", + "epoch: 16700\ttrain_HF_loss: 0.00000\teltime: 28.02868\n", + "epoch: 16800\ttrain_HF_loss: 0.00000\teltime: 28.18373\n", + "epoch: 16900\ttrain_HF_loss: 0.00000\teltime: 28.36474\n", + "epoch: 17000\ttrain_HF_loss: 0.00000\teltime: 28.52010\n", + "epoch: 17100\ttrain_HF_loss: 0.00000\teltime: 28.69638\n", + "epoch: 17200\ttrain_HF_loss: 0.00000\teltime: 28.85627\n", + "epoch: 17300\ttrain_HF_loss: 0.00000\teltime: 29.02591\n", + "epoch: 17400\ttrain_HF_loss: 0.00000\teltime: 29.18715\n", + "epoch: 17500\ttrain_HF_loss: 0.00000\teltime: 29.35103\n", + "epoch: 17600\ttrain_HF_loss: 0.00000\teltime: 29.51298\n", + "epoch: 17700\ttrain_HF_loss: 0.00000\teltime: 29.68411\n", + "epoch: 17800\ttrain_HF_loss: 0.00000\teltime: 29.85166\n", + "epoch: 17900\ttrain_HF_loss: 0.00000\teltime: 30.01409\n", + "epoch: 18000\ttrain_HF_loss: 0.00001\teltime: 30.18576\n", + "epoch: 18100\ttrain_HF_loss: 0.00000\teltime: 30.35149\n", + "epoch: 18200\ttrain_HF_loss: 0.00004\teltime: 30.52633\n", + "epoch: 18300\ttrain_HF_loss: 0.00000\teltime: 30.68439\n", + "epoch: 18400\ttrain_HF_loss: 0.00000\teltime: 30.86006\n", + "epoch: 18500\ttrain_HF_loss: 0.00000\teltime: 31.03315\n", + "epoch: 18600\ttrain_HF_loss: 0.00000\teltime: 31.23712\n", + "epoch: 18700\ttrain_HF_loss: 0.00000\teltime: 31.42047\n", + "epoch: 18800\ttrain_HF_loss: 0.00000\teltime: 31.57658\n", + "epoch: 18900\ttrain_HF_loss: 0.00000\teltime: 31.75771\n", + "epoch: 19000\ttrain_HF_loss: 0.00000\teltime: 31.92166\n", + "epoch: 19100\ttrain_HF_loss: 0.00012\teltime: 32.09438\n", + "epoch: 19200\ttrain_HF_loss: 0.00000\teltime: 32.25546\n", + "epoch: 19300\ttrain_HF_loss: 0.00000\teltime: 32.43944\n", + "epoch: 19400\ttrain_HF_loss: 0.00000\teltime: 32.59608\n", + "epoch: 19500\ttrain_HF_loss: 0.00014\teltime: 32.76947\n", + "epoch: 19600\ttrain_HF_loss: 0.00000\teltime: 32.93512\n", + "epoch: 19700\ttrain_HF_loss: 0.00000\teltime: 33.10188\n", + "epoch: 19800\ttrain_HF_loss: 0.00000\teltime: 33.25940\n", + "epoch: 19900\ttrain_HF_loss: 0.00000\teltime: 33.42611\n" + ] + } + ], + "source": [ + "# Create trainer for MF model\n", + "num_epochs_mf = 20000\n", + "epoch_verbose_mf = 100\n", + "logger_MF = LossLogger(args=None, savedir='test_HF', verbosity=epoch_verbose_mf, stdout=['train_HF_loss'])\n", + "\n", + "\n", + "trainer_MF = Trainer(\n", + " problem_MF.to(device),\n", + " train_data=train_loader_HF,\n", + " dev_data=train_loader_HF,\n", + " optimizer=torch.optim.Adam(problem_MF.parameters(), lr=init_lr),\n", + " epoch_verbose=epoch_verbose_mf,\n", + " logger=logger_MF,\n", + " epochs=num_epochs_mf,\n", + " train_metric='train_HF_loss',\n", + " eval_metric='train_HF_loss',\n", + " dev_metric='train_HF_loss',\n", + " warmup=num_epochs_mf,\n", + " device=device\n", + ")\n", + "\n", + "# Train MF model\n", + "best_model_MF = trainer_MF.train()\n", + "problem_MF.load_state_dict(best_model_MF)\n", + "trained_model_MF = problem_MF.nodes[0]\n" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "alpha_0 = Parameter containing:\n", + "tensor(0.3903, requires_grad=True)\n" + ] + } + ], + "source": [ + "# Print value of final parameter alpha\n", + "for idx,alpha in enumerate(kan_MF.alpha):\n", + " print(f\"alpha_{idx} = {alpha}\")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plot results" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Make predictions\n", + "preds_HF = trained_model_HF(data_full.datadict)['y_hat'].cpu().detach().numpy() # high-fidelity predictions of full data\n", + "preds_LF = trained_model_LF(train_data_LF.datadict)['y_hat'].cpu().detach().numpy() # low-fidelity predictions of low-fidelity data\n", + "preds_MF = trained_model_MF(data_full.datadict)['y_hat'].cpu().detach().numpy() # multi-fidelity predictions of full data\n", + "\n", + "# Create subplots\n", + "fig, axs = plt.subplots(2, 2, figsize=(16, 8), constrained_layout=True)\n", + "\n", + "# Plot a): Sampled data and reference functions\n", + "axs[0, 0].scatter(x_data_LF.numpy(), y_data_LF.numpy(), c=\"#4e79a7\", label='LF data', alpha=0.8)\n", + "axs[0, 0].scatter(x_data_HF.numpy(), y_data_HF.numpy(), c=\"#59a14f\", label='HF data', alpha=0.8)\n", + "axs[0, 0].plot(x_data_LF.numpy(), yL(x_data_LF).numpy(), \"#4e79a7\", label='LF', alpha=0.8)\n", + "axs[0, 0].plot(x_data_LF.numpy(), yH(x_data_LF).numpy(), \"#59a14f\", label='HF', alpha=0.8)\n", + "axs[0, 0].set_xlim(0,1)\n", + "axs[0, 0].set_xlabel('x', fontsize=14)\n", + "axs[0, 0].set_ylabel('f(x)', fontsize=14)\n", + "axs[0, 0].legend(fontsize=10)\n", + "\n", + "# Plot b): Evolution of losses vs epochs\n", + "losses_LF = trainer_LF.logger.get_losses()\n", + "losses_HF = trainer_HF.logger.get_losses()\n", + "losses_MF = trainer_MF.logger.get_losses()\n", + "epoch_losses_LF = range(1, len(losses_LF['train'])*epoch_verbose_lf+1, epoch_verbose_lf)\n", + "epoch_losses_HF = range(1, len(losses_HF['train'])*epoch_verbose_hf+1, epoch_verbose_hf)\n", + "epoch_losses_MF = range(1, len(losses_MF['train'])*epoch_verbose_mf+1, epoch_verbose_mf)\n", + "\n", + "axs[0, 1].plot(epoch_losses_LF,losses_LF['train'], label='LF', color='#59a14f')\n", + "axs[0, 1].plot(epoch_losses_HF,losses_HF['train'], label='HF', linestyle='dotted', color='#4e79a7')\n", + "axs[0, 1].plot(epoch_losses_MF,losses_MF['train'], label='MF', color='#e15759') \n", + "axs[0, 1].set_xlabel('Epochs', fontsize=14)\n", + "axs[0, 1].set_ylabel('Loss', fontsize=14)\n", + "axs[0, 1].set_yscale('log')\n", + "axs[0, 1].set_ylim(1e-16)\n", + "axs[0, 1].legend(fontsize=10)\n", + "\n", + "# Plot c): LF predictions vs reference data\n", + "axs[1, 0].plot(x_data_LF.numpy(), yL(x_data_LF).numpy(), '#4e79a7', label='LF ref.', alpha=0.9)\n", + "axs[1, 0].plot(x_data_LF.numpy(), preds_LF, 'k--', label='LF pred.', linewidth=2)\n", + "axs[1, 0].set_xlim(0,1)\n", + "axs[1, 0].set_xlabel('x', fontsize=14)\n", + "axs[1, 0].set_ylabel('f(x)', fontsize=14)\n", + "axs[1, 0].legend(fontsize=10)\n", + "\n", + "# Plot d): MF vs HF predictions and reference\n", + "axs[1,1].scatter(x_data_HF.numpy(), y_data_HF.numpy(), c=\"#59a14f\", label='HF data', alpha=0.7, s=50)\n", + "axs[1,1].plot(x_data_full.numpy(), y_data_full.numpy(), '#59a14f', label='HF ref.', alpha=0.8, linewidth=2) # HF ref.\n", + "axs[1,1].plot(x_data_full.numpy(), preds_MF, '--b', label='MF', alpha=0.8, linewidth=2) # Predictions of MF model on full data\n", + "axs[1,1].plot(x_data_full.numpy(), preds_HF, '#e15759', linestyle='dotted', label='HF only', alpha=0.8, linewidth=2) # Predictions of HF model on full data\n", + "axs[1, 1].set_xlim(0,1)\n", + "axs[1, 1].set_xlabel('x', fontsize=14)\n", + "axs[1, 1].set_ylabel('f(x)', fontsize=14)\n", + "axs[1, 1].legend(fontsize=10)\n", + "\n", + "plt.tight_layout()\n", + "plt.show()\n", + "\n", + "# Optional: save your plot\n", + "# plt.savefig('MF_LF_Results_Inference_Neuromancer.png', dpi=300, bbox_inches='tight')\n", + "\n" + ] + } + ], + "metadata": { + "accelerator": "GPU", + "colab": { + "collapsed_sections": [ + "Y61YA90-WIZ1", + "UoqCzgLSp61M", + "i0j73GoH86-m", + "pOe9yRvxjakj" + ], + "machine_shape": "hm", + "name": "4.DiffusionEquation.ipynb", + "provenance": [] + }, + "kernelspec": { + "display_name": ".venv", + "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": "3.10.0" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/src/neuromancer/loggers.py b/src/neuromancer/loggers.py index c8d65363..0a5d2b57 100644 --- a/src/neuromancer/loggers.py +++ b/src/neuromancer/loggers.py @@ -29,11 +29,10 @@ def __init__(self, args=None, savedir='test', verbosity=10, self.start_time = time.time() self.step = 0 self.args = args - self.log_parameters() def log_parameters(self): """ - Pring experiment parameters to stdout + Print experiment parameters to stdout :param args: (Namespace) returned by argparse.ArgumentParser.parse_args() """ @@ -86,6 +85,51 @@ def clean_up(self): pass +class LossLogger(BasicLogger): + def __init__(self, args=None, savedir='test', verbosity=10, + stdout=('nstep_dev_loss', 'loop_dev_loss', 'best_loop_dev_loss', + 'nstep_dev_ref_loss', 'loop_dev_ref_loss')): + super().__init__(args, savedir, verbosity, stdout) + self.losses = {'train': [], 'dev': [], 'test': []} # Initialize losses dictionary + + def log_metrics(self, output, step=None): + """ + Print metrics to stdout and store loss values. + + :param output: (dict {str: tensor}) Will only record 0d tensors (scalars) + :param step: (int) Epoch of training + """ + if step is None: + step = self.step + else: + self.step = step + if step % self.verbosity == 0: + elapsed_time = time.time() - self.start_time + entries = [f'epoch: {step}'] + for k, v in output.items(): + try: + if k in self.stdout: + entries.append(f'{k}: {v.item():.5f}') + # Collect the loss values based on type + if 'loss' in k.lower(): + if 'train' in k.lower(): + self.losses['train'].append(v.item()) + elif 'dev' in k.lower(): + self.losses['dev'].append(v.item()) + elif 'test' in k.lower(): + self.losses['test'].append(v.item()) + except (ValueError, AttributeError) as e: + pass + entries.append(f'eltime: {elapsed_time: .5f}') + print('\t'.join([e for e in entries if 'reg_error' not in e])) + + def get_losses(self): + """ + Returns a dictionary of recorded loss values for train, dev, and test. + """ + return {k: v for k, v in self.losses.items() if v} + + class MLFlowLogger(BasicLogger): def __init__(self, args=None, savedir='test', verbosity=1, id=None, stdout=('nstep_dev_loss', 'loop_dev_loss', 'best_loop_dev_loss', diff --git a/src/neuromancer/modules/blocks.py b/src/neuromancer/modules/blocks.py index c7f5b24d..fb080b57 100644 --- a/src/neuromancer/modules/blocks.py +++ b/src/neuromancer/modules/blocks.py @@ -13,7 +13,7 @@ import neuromancer.slim as slim import neuromancer.modules.rnn as rnn from neuromancer.modules.activations import soft_exp, SoftExponential, SmoothedReLU -from neuromancer.modules.functions import bounds_clamp, bounds_scaling +from neuromancer.modules.functions import bounds_clamp, bounds_scaling, w_jl @@ -122,6 +122,7 @@ def _apply_fn(x): model.apply(_apply_fn) + class MLP(Block): """ Multi-Layer Perceptron consistent with blocks interface @@ -175,7 +176,6 @@ def block_eval(self, x): x = nlin(lin(x)) return x - class KANLinear(torch.nn.Module): """ KANLinear module based on the efficient implementation of Kolmogorov-Arnold Network. @@ -341,65 +341,60 @@ def forward(self, x: torch.Tensor): return base_output + spline_output @torch.no_grad() - def update_grid(self, x: torch.Tensor, margin=0.01): - assert x.dim() == 2 and x.size(1) == self.in_features - batch = x.size(0) - - splines = self.b_splines(x) # (batch, in, coeff) - splines = splines.permute(1, 0, 2) # (in, batch, coeff) - orig_coeff = self.scaled_spline_weight # (out, in, coeff) - orig_coeff = orig_coeff.permute(1, 2, 0) # (in, coeff, out) - unreduced_spline_output = torch.bmm(splines, orig_coeff) # (in, batch, out) - unreduced_spline_output = unreduced_spline_output.permute( - 1, 0, 2 - ) # (batch, in, out) - - # sort each channel individually to collect data distribution - x_sorted = torch.sort(x, dim=0)[0] - grid_adaptive = x_sorted[ - torch.linspace( - 0, batch - 1, self.grid_size + 1, dtype=torch.int64, device=x.device - ) - ] - - uniform_step = (x_sorted[-1] - x_sorted[0] + 2 * margin) / self.grid_size - grid_uniform = ( - torch.arange( - self.grid_size + 1, dtype=torch.float32, device=x.device - ).unsqueeze(1) - * uniform_step - + x_sorted[0] - - margin - ) - - grid = self.grid_eps * grid_uniform + (1 - self.grid_eps) * grid_adaptive - grid = torch.concatenate( - [ - grid[:1] - - uniform_step - * torch.arange(self.spline_order, 0, -1, device=x.device).unsqueeze(1), - grid, - grid[-1:] - + uniform_step - * torch.arange(1, self.spline_order + 1, device=x.device).unsqueeze(1), - ], - dim=0, - ) - - self.grid.copy_(grid.T) - self.spline_weight.data.copy_(self.curve2coeff(x, unreduced_spline_output)) + def update_grid(self, _x, margin=0.01): + for _,x in _x.items(): + if torch.is_tensor(x): + if x.dim() == 2 and x.size(1) == self.in_features: + batch = x.size(0) + splines = self.b_splines(x) # (batch, in, coeff) + splines = splines.permute(1, 0, 2) # (in, batch, coeff) + orig_coeff = self.scaled_spline_weight # (out, in, coeff) + orig_coeff = orig_coeff.permute(1, 2, 0) # (in, coeff, out) + unreduced_spline_output = torch.bmm(splines, orig_coeff) # (in, batch, out) + unreduced_spline_output = unreduced_spline_output.permute(1, 0, 2) # (batch, in, out) + + # sort each channel individually to collect data distribution + x_sorted = torch.sort(x, dim=0)[0] + grid_adaptive = x_sorted[torch.linspace(0, batch - 1, self.grid_size + 1, dtype=torch.int64, device=x.device)] + + uniform_step = (x_sorted[-1] - x_sorted[0] + 2 * margin) / self.grid_size + grid_uniform = ( + torch.arange( + self.grid_size + 1, dtype=torch.float32, device=x.device + ).unsqueeze(1) + * uniform_step + + x_sorted[0] + - margin + ) + + grid = self.grid_eps * grid_uniform + (1 - self.grid_eps) * grid_adaptive + grid = torch.concatenate( + [ + grid[:1] + - uniform_step + * torch.arange(self.spline_order, 0, -1, device=x.device).unsqueeze(1), + grid, + grid[-1:] + + uniform_step + * torch.arange(1, self.spline_order + 1, device=x.device).unsqueeze(1), + ], + dim=0, + ) + + self.grid.copy_(grid.T) + self.spline_weight.data.copy_(self.curve2coeff(x, unreduced_spline_output)) def regularization_loss(self, regularize_activation=1.0, regularize_entropy=1.0): """ Approximate, memory-efficient implementation of the regularization loss. """ - l1_fake = self.spline_weight.abs().mean(-1) + l1_fake = (self.spline_weight.abs()**2).mean(-1) regularization_loss_activation = l1_fake.sum() p = l1_fake / regularization_loss_activation - regularization_loss_entropy = -torch.sum(p * p.log()) + #regularization_loss_entropy = -torch.sum(p * p.log()) return ( regularize_activation * regularization_loss_activation - + regularize_entropy * regularization_loss_entropy + #+ regularize_entropy * regularization_loss_entropy ) @@ -454,16 +449,16 @@ def regularization_loss(self, regularize_activation=1.0, regularize_entropy=1.0) layer.regularization_loss(regularize_activation, regularize_entropy) for layer in self.layers ) - + class KANBlock(Block): def __init__( self, insize, outsize, - num_layers=1, - hidden_size=None, - grid_size=5, + hsizes=[64], + num_domains=1, + grid_sizes=[5], spline_order=3, scale_noise=0.1, scale_base=1.0, @@ -472,22 +467,165 @@ def __init__( base_activation=torch.nn.SiLU, grid_eps=0.02, grid_range=[-1, 1], + grid_updates=None, + verbose=False, ): super().__init__() self.in_features = insize self.out_features = outsize + self.num_domains = num_domains + self.spline_order = spline_order + self.kan_layers = nn.ModuleList() + for _ in range(num_domains): + layers = nn.ModuleList() + layer_sizes = [insize] + hsizes + [outsize] + for in_features, out_features in zip(layer_sizes[:-1], layer_sizes[1:]): + layers.append( + KANLinear( + in_features, + out_features, + grid_size=grid_sizes[0], + spline_order=spline_order, + scale_noise=scale_noise, + scale_base=scale_base, + scale_spline=scale_spline, + enable_standalone_scale_spline=enable_standalone_scale_spline, + base_activation=base_activation, + grid_eps=grid_eps, + grid_range=grid_range, + ) + ) + self.kan_layers.append(layers) - if hidden_size is None: - hidden_size = outsize + self.grid_sizes = grid_sizes + self.grid_updates = grid_updates or [] + self.current_grid_index = 0 + self.verbose = verbose - layer_sizes = [insize] + [hidden_size] * (num_layers - 1) + [outsize] - for in_features, out_features in zip(layer_sizes[:-1], layer_sizes[1:]): - self.kan_layers.append( - KANLinear( - in_features, - out_features, - grid_size=grid_size, + def block_eval(self, x): + if self.num_domains == 1: + for layer in self.kan_layers[0]: + x = layer(x) + return x + else: + w = w_jl(x, self.num_domains) + + x_domain_outputs = torch.zeros(x.shape[0], self.num_domains, self.out_features, device=x.device) + + for i, domain_layers in enumerate(self.kan_layers): + x_domain = x + for layer in domain_layers: + x_domain = layer(x_domain) + x_domain_outputs[:, i, :] = x_domain + + x_final = torch.sum(w.unsqueeze(-1) * x_domain_outputs, dim=1) + + return x_final + + + + def regularization_loss(self, regularize_activation=0.1, regularize_entropy=1.0): + return sum( + layer.regularization_loss(regularize_activation, regularize_entropy) + for domain_layers in self.kan_layers + for layer in domain_layers + ) + + def update_grid(self, x, margin=0.01): + if isinstance(x, dict): + x = next(iter(x.values())) + + for domain_layers in self.kan_layers: + for layer in domain_layers: + layer.update_grid(x, margin=margin) + + def update_epoch(self, epoch, x): + if self.current_grid_index < len(self.grid_updates) and epoch >= self.grid_updates[self.current_grid_index]: + new_grid_size = self.grid_sizes[self.current_grid_index] + if self.verbose: + print(f"Updating grid size to {new_grid_size} at epoch {epoch}") + + for domain_layers in self.kan_layers: + for layer in domain_layers: + layer.grid_size = new_grid_size + layer.reset_parameters() # Reinitialize parameters with new grid size + layer.update_grid(x) # Update the grid with the current batch + self.current_grid_index += 1 + + + +class MultiFidelityKAN(Block): + """ + Multi-Fidelity Kolmogorov-Arnold Network (KAN) with KANBlock. + Takes a pre-trained single-fidelity KAN as input. + """ + def __init__( + self, + sfkan, + insize, + outsize, + hsizes=[64], + num_stacked_blocks=1, + num_domains=1, + grid_sizes=[5], + spline_order=3, + scale_noise=0.1, + scale_base=1.0, + scale_spline=1.0, + enable_standalone_scale_spline=True, + base_activation=torch.nn.SiLU, + grid_eps=0.02, + grid_range=[-1, 1], + grid_updates=None, + alpha_init=0.1, + verbose=False + ): + super().__init__() + self.sfkan = sfkan # Pre-trained single-fidelity KAN + # Freeze the parameters of the low-fidelity model + for param in self.sfkan.parameters(): + param.requires_grad = False + + self.in_features = insize + self.out_features = outsize + self.num_stacked_blocks = num_stacked_blocks + self.num_domains = num_domains + self.verbose = verbose + + self.alpha = nn.ParameterList([nn.Parameter(torch.tensor(alpha_init)) for _ in range(num_stacked_blocks)]) + + # Multi-fidelity layers + self.linear_layers = nn.ModuleList() + self.nonlinear_layers = nn.ModuleList() + + for _ in range(num_stacked_blocks): + self.linear_layers.append( + KANBlock( + insize=insize + outsize, + outsize=outsize, + hsizes=[], + num_domains=num_domains, + grid_sizes=[2], + spline_order=1, + scale_noise=scale_noise, + scale_base=0., + scale_spline=scale_spline, + enable_standalone_scale_spline=enable_standalone_scale_spline, + base_activation=nn.Identity, + grid_eps=1.0, + grid_range=grid_range, + grid_updates=grid_updates, + verbose=verbose + ) + ) + self.nonlinear_layers.append( + KANBlock( + insize=insize + outsize, + outsize=outsize, + hsizes=hsizes, + num_domains=num_domains, + grid_sizes=grid_sizes, spline_order=spline_order, scale_noise=scale_noise, scale_base=scale_base, @@ -496,23 +634,37 @@ def __init__( base_activation=base_activation, grid_eps=grid_eps, grid_range=grid_range, + grid_updates=grid_updates, + verbose=verbose ) ) def block_eval(self, x): - for layer in self.kan_layers: - x = layer(x) - return x + # First layer (pre-trained single-fidelity KAN) + out = self.sfkan.block_eval(x).detach() + + # Subsequent layers (multi-fidelity) + for i in range(self.num_stacked_blocks): + linear_out = self.linear_layers[i].block_eval(torch.cat([x, out], dim=1)) + nonlinear_out = self.nonlinear_layers[i].block_eval(torch.cat([x, out], dim=1)) + out = torch.abs(self.alpha[i]) * nonlinear_out + (1 - torch.abs(self.alpha[i])) * linear_out + return out - def regularization_loss(self, regularize_activation=1.0, regularize_entropy=1.0): - return sum( - layer.regularization_loss(regularize_activation, regularize_entropy) - for layer in self.kan_layers - ) + def regularization_loss(self, regularize_activation=1.0, regularize_entropy=0.0): + loss = 0.0 + for linear_layer, nonlinear_layer in zip(self.linear_layers, self.nonlinear_layers): + loss += linear_layer.regularization_loss(regularize_activation, regularize_entropy) + loss += nonlinear_layer.regularization_loss(regularize_activation, regularize_entropy) + return loss + + def update_grid(self, x, margin=0.01): + for linear_layer, nonlinear_layer in zip(self.linear_layers, self.nonlinear_layers): + linear_layer.update_grid(x, margin=margin) + nonlinear_layer.update_grid(torch.cat([x, self.sfkan.block_eval(x)], dim=1), margin=margin) + + def get_alpha_loss(self): + return sum(10.*torch.pow(alpha, 2) for alpha in self.alpha) - def update_grid(self, x: torch.Tensor, margin=0.01): - for layer in self.kan_layers: - layer.update_grid(x, margin=margin) class MLP_bounds(MLP): diff --git a/src/neuromancer/modules/functions.py b/src/neuromancer/modules/functions.py index fb9fecf7..fd2c68dc 100644 --- a/src/neuromancer/modules/functions.py +++ b/src/neuromancer/modules/functions.py @@ -4,6 +4,7 @@ """ import torch +import numpy as np def bounds_scaling(x, xmin, xmax, scaling=1.): """ @@ -33,6 +34,49 @@ def bounds_clamp(x, xmin=None, xmax=None): return x +def w_jl(x, num_domains, delta=1.9): + """ + Window functions for finite-basis domain decomposition. + :param: x: domain coordinates. + :param: num_domains: number of domains. Must be a magic square number. + :param: delta: overlapping ratio between window functions. + :return w: partition of unit window functions. + """ + eps = 1e-12 # Small epsilon to prevent division by zero + + def w_jl_i(x_i, n_domains, x_min, x_max): + jvec = torch.arange(n_domains, device=x_i.device) + 1 + muvec = x_min + (jvec - 1) * (x_max - x_min) / (n_domains - 1) + muvec = muvec.unsqueeze(0).expand(x_i.shape[0], n_domains) + u = x_i.repeat(1, n_domains) + sigma = (x_max - x_min) * (delta / 2.0) / (n_domains - 1) + + z = (u - muvec) / (sigma + eps) + w_jl = ((1 + torch.cos(np.pi * z)) / 2) ** 2 + w_jl = torch.where(torch.abs(z) < 1, w_jl, torch.zeros_like(w_jl)) + return w_jl + + n_dims = x.shape[1] + if n_dims == 1: + x_min, x_max = x.min(), x.max() + w = w_jl_i(x, num_domains, x_min, x_max) + elif n_dims == 2: + n_per_dim = int(np.sqrt(num_domains)) + if n_per_dim ** 2 != num_domains: + raise ValueError("num_domains must be a perfect square for 2D inputs.") + x_min_x, x_max_x = x[:, 0].min(), x[:, 0].max() + x_min_y, x_max_y = x[:, 1].min(), x[:, 1].max() + w1 = w_jl_i(x[:, 0:1], n_per_dim, x_min_x, x_max_x) + w2 = w_jl_i(x[:, 1:2], n_per_dim, x_min_y, x_max_y) # Corrected slice + w = torch.einsum('bi,bj->bij', w1, w2).reshape(x.shape[0], -1) + if w.shape[1] > num_domains: + w = w[:, :num_domains] # Trim if necessary + else: + raise ValueError("Only 1D and 2D inputs are currently supported") + + s = torch.sum(w, dim=1, keepdim=True) + return w / (s + eps) + functions = { "bounds_scaling": bounds_scaling, "bounds_clamp": bounds_clamp, diff --git a/src/neuromancer/trainer.py b/src/neuromancer/trainer.py index de81d081..396c6ff6 100644 --- a/src/neuromancer/trainer.py +++ b/src/neuromancer/trainer.py @@ -16,6 +16,7 @@ from neuromancer.callbacks import Callback from neuromancer.problem import LitProblem from neuromancer.dataset import LitDataModule +from neuromancer.modules.blocks import MultiFidelityKAN from lightning.pytorch.callbacks import ModelCheckpoint from lightning.pytorch.callbacks.early_stopping import EarlyStopping @@ -250,6 +251,11 @@ def train(self): alpha_loss = node.callable.get_alpha_loss() output[self.train_metric] += alpha_loss + for node in self.model.nodes: + if isinstance(node.callable, MultiFidelityKAN): + kan_reg_loss = node.callable.regularization_loss() + output[self.train_metric] += kan_reg_loss + self.optimizer.zero_grad() output[self.train_metric].backward() torch.nn.utils.clip_grad_norm_(self.model.parameters(), self.clip) From 7e30f0b9a62b060189ee8d7f9fdff8ed7243f6f3 Mon Sep 17 00:00:00 2001 From: Bruno Jacob Date: Mon, 9 Sep 2024 16:22:06 -0700 Subject: [PATCH 2/6] updating README of examples/KANs --- examples/KANs/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/KANs/README.md b/examples/KANs/README.md index 350798a4..e75b51e8 100644 --- a/examples/KANs/README.md +++ b/examples/KANs/README.md @@ -12,7 +12,7 @@ Examples of learning multi-fidelity data with MFKANs: ## Kolmogorov-Arnold Networks (KANs) -Based on the Kolmogorov-Arnold representation theorem, KANs offer an alternative architecture: where traditional neural networks utilize fixed activation functions, KANs employ learnable activation functions on the edges of the network, replacing linear weight parameters with parametrized spline functions. This fundamental shift sometimes enhances model interpretability and improves computational efficiency and accuracy [1]. KANs are available on Neuromancer via `blocks.KANBlock`, which leverages the efficient-kan implementation of [2]. Moreover, users can leverage the finite basis KANs (FBKANs), a domain decomposition method for KANs proposed by Howard et al. (2024)[3] by simply setting the `num_domains` argument in `blocks.KANBlock`. +Based on the Kolmogorov-Arnold representation theorem, KANs offer an alternative architecture: where traditional neural networks utilize fixed activation functions, KANs employ learnable activation functions on the edges of the network, replacing linear weight parameters with parametrized spline functions. This fundamental shift sometimes enhances model interpretability and improves computational efficiency and accuracy [1]. KANs are available on Neuromancer via `blocks.KANBlock`, which leverages the efficient-kan implementation of [2]. Moreover, users can leverage the finite basis KANs (FBKANs), a domain decomposition method for KANs proposed by Howard et al. (2024)[3] by simply setting the `num_domains` argument in `blocks.KANBlock`. Users can also leverage multi-fidelity KANs (MFKANs) via `blocks.MultiFidelityKAN`. ### References From d635074dcf06b3237951f678df0cb7dad1fe0ecb Mon Sep 17 00:00:00 2001 From: Bruno Jacob Date: Mon, 9 Sep 2024 16:27:46 -0700 Subject: [PATCH 3/6] fixing markdown of equations --- examples/KANs/p3_mfkan_example_1d.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/KANs/p3_mfkan_example_1d.ipynb b/examples/KANs/p3_mfkan_example_1d.ipynb index 977b0d3c..16a7b1fd 100644 --- a/examples/KANs/p3_mfkan_example_1d.ipynb +++ b/examples/KANs/p3_mfkan_example_1d.ipynb @@ -133,8 +133,8 @@ " 0.1\\left[0.5(6x-2)^2 \\sin(12x-4) + 10(x-0.5)-2\\right] & x > 0.5 \n", " \\end{cases}\n", "$$\n", - "$$\n", "\n", + "$$\n", "y_H(x) = 2y_L(x) -2x + 2\n", "$$\n", "\n", From a4248a22423f3a239c47c4fd9b9748233be195c0 Mon Sep 17 00:00:00 2001 From: Bruno Jacob Date: Mon, 9 Sep 2024 16:33:52 -0700 Subject: [PATCH 4/6] fixing metadata tag so that name is displayed correctly on Colab --- examples/KANs/p3_mfkan_example_1d.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/KANs/p3_mfkan_example_1d.ipynb b/examples/KANs/p3_mfkan_example_1d.ipynb index 16a7b1fd..6173dcb1 100644 --- a/examples/KANs/p3_mfkan_example_1d.ipynb +++ b/examples/KANs/p3_mfkan_example_1d.ipynb @@ -1049,7 +1049,7 @@ "pOe9yRvxjakj" ], "machine_shape": "hm", - "name": "4.DiffusionEquation.ipynb", + "name": "p3_mfkan_example_1d.ipynb", "provenance": [] }, "kernelspec": { From de0ea14caff26f177092ff0d6636c06766e4ebfe Mon Sep 17 00:00:00 2001 From: Bruno Jacob Date: Tue, 3 Dec 2024 17:41:38 -0800 Subject: [PATCH 5/6] TLC of KAN p3 example; fixing markdown notation bugs in p1 and p2 as well --- .../KANs/p1_fbkan_vs_kan_noise_data_1d.ipynb | 8 +- .../KANs/p2_fbkan_vs_kan_noise_data_2d.ipynb | 8 +- examples/KANs/p3_mfkan_example_1d.ipynb | 978 ++++++++---------- examples/figs/mfkan_diagram.png | Bin 0 -> 653157 bytes src/neuromancer/modules/blocks.py | 46 +- src/neuromancer/modules/functions.py | 14 +- 6 files changed, 448 insertions(+), 606 deletions(-) create mode 100644 examples/figs/mfkan_diagram.png diff --git a/examples/KANs/p1_fbkan_vs_kan_noise_data_1d.ipynb b/examples/KANs/p1_fbkan_vs_kan_noise_data_1d.ipynb index f9b7a24c..4a147f76 100644 --- a/examples/KANs/p1_fbkan_vs_kan_noise_data_1d.ipynb +++ b/examples/KANs/p1_fbkan_vs_kan_noise_data_1d.ipynb @@ -355,14 +355,14 @@ "\n", "- `x`: Input variable, where $x \\in [0, 2]$.\n", "- `y`: True target values from the function $f(x)$.\n", - "- `y_hat`: Predicted values produced by either the KAN or FBKAN model.\n", + "- `y_hat`: Predicted values produced by either the KAN or FBKAN model, $\\hat{y}$.\n", "\n", "**Data Loss for FBKAN:**\n", "\n", "The data loss for FBKAN, denoted as `loss_data_fbkan`, measures the mean squared error (MSE) between the FBKAN predictions, `y_hat`, and the true values, `y`:\n", "\n", "$$\n", - "\\ell_{\\text{data, FBKAN}} = \\text{scaling} \\cdot \\frac{1}{N_{\\text{data}}} \\sum_{i=1}^{N_{\\text{data}}} \\left( y_i - y_{\\text{hat, FBKAN}} \\right)^2\n", + "\\ell_{\\text{data, FBKAN}} = \\text{scaling} \\cdot \\frac{1}{N_{\\text{data}}} \\sum_{i=1}^{N_{\\text{data}}} \\left( y_i - \\hat{y}_i \\right)^2\n", "$$\n", "\n", "This loss guides the FBKAN model to approximate the target function values accurately.\n", @@ -372,7 +372,7 @@ "Similarly, the data loss for KAN, denoted as `loss_data_kan`, is the mean squared error between the KAN predictions, `y_hat`, and the true target values, `y`:\n", "\n", "$$\n", - "\\ell_{\\text{data, KAN}} = \\text{scaling} \\cdot \\frac{1}{N_{\\text{data}}} \\sum_{i=1}^{N_{\\text{data}}} \\left( y_i - y_{\\text{hat, KAN}} \\right)^2\n", + "\\ell_{\\text{data, KAN}} = \\text{scaling} \\cdot \\frac{1}{N_{\\text{data}}} \\sum_{i=1}^{N_{\\text{data}}} \\left( y_i - \\hat{y}_i \\right)^2\n", "$$\n", "\n", "This loss term helps the KAN model learn to approximate the target function.\n", @@ -419,7 +419,7 @@ "id": "9af5ad88-a719-4da0-b75c-b5fe2ac6b41b", "metadata": {}, "source": [ - "### Construct the Neuromancer Problem objects and train" + "### Construct the Neuromancer `Problem` objects and train" ] }, { diff --git a/examples/KANs/p2_fbkan_vs_kan_noise_data_2d.ipynb b/examples/KANs/p2_fbkan_vs_kan_noise_data_2d.ipynb index f81c4a9a..6fb83630 100644 --- a/examples/KANs/p2_fbkan_vs_kan_noise_data_2d.ipynb +++ b/examples/KANs/p2_fbkan_vs_kan_noise_data_2d.ipynb @@ -346,14 +346,14 @@ "\n", "- `x`, `y`: Input variables, where $x, y \\in [0, 1]^2$.\n", "- `z`: True target values from the function $f(x, y)$.\n", - "- `z_hat`: Predicted values produced by either the KAN or FBKAN model.\n", + "- `z_hat`: Predicted values produced by either the KAN or FBKAN model, $\\hat{z}$.\n", "\n", "**Data Loss for FBKAN:**\n", "\n", "The data loss for FBKAN, denoted as `loss_data_fbkan`, measures the mean squared error (MSE) between the FBKAN predictions, `z_hat`, and the true values, `z`:\n", "\n", "$$\n", - "\\ell_{\\text{data, FBKAN}} = \\text{scaling} \\cdot \\frac{1}{N_{\\text{data}}} \\sum_{i=1}^{N_{\\text{data}}} \\left( z_i - z_{\\text{hat, FBKAN}} \\right)^2\n", + "\\ell_{\\text{data, FBKAN}} = \\text{scaling} \\cdot \\frac{1}{N_{\\text{data}}} \\sum_{i=1}^{N_{\\text{data}}} \\left( z_i - \\hat{z}_i \\right)^2\n", "$$\n", "\n", "This loss guides the FBKAN model to approximate the target function values accurately.\n", @@ -363,7 +363,7 @@ "Similarly, the data loss for KAN, denoted as `loss_data_kan`, is the mean squared error between the KAN predictions, `z_hat`, and the true target values, `z`:\n", "\n", "$$\n", - "\\ell_{\\text{data, KAN}} = \\text{scaling} \\cdot \\frac{1}{N_{\\text{data}}} \\sum_{i=1}^{N_{\\text{data}}} \\left( z_i - z_{\\text{hat, KAN}} \\right)^2\n", + "\\ell_{\\text{data, KAN}} = \\text{scaling} \\cdot \\frac{1}{N_{\\text{data}}} \\sum_{i=1}^{N_{\\text{data}}} \\left( z_i - \\hat{z}_i \\right)^2\n", "$$\n", "\n", "This loss term helps the KAN model learn to approximate the target function.\n", @@ -411,7 +411,7 @@ "id": "9af5ad88-a719-4da0-b75c-b5fe2ac6b41b", "metadata": {}, "source": [ - "### Construct the Neuromancer Problem objects and train" + "### Construct the Neuromancer `Problem` objects and train" ] }, { diff --git a/examples/KANs/p3_mfkan_example_1d.ipynb b/examples/KANs/p3_mfkan_example_1d.ipynb index 6173dcb1..fea8c314 100644 --- a/examples/KANs/p3_mfkan_example_1d.ipynb +++ b/examples/KANs/p3_mfkan_example_1d.ipynb @@ -8,18 +8,53 @@ "source": [ "# Multi-Fidelity Kolmogorov-Arnold Networks (MFKANs) in Neuromancer\n", "\n", - "This tutorial demonstrates the use of Multi-Fidelity Kolmogorov-Arnold Networks (MFKANs) for learning functions from high and low-fidelity data sources.\n", + "This tutorial demonstrates the use of Multi-Fidelity Kolmogorov-Arnold Networks (MFKANs) for learning functions from both high and low-fidelity data sources. MFKANs enable efficient training with limited expensive high-fidelity data by leveraging correlations with more abundant low-fidelity data.\n", "\n", - "\n", + "This example is divided into three parts. First, we train a KAN with only low-fidelity data. We then proceed with training a KAN with only high-fidelity data. Finally, we demonstrate how to use an MFKAN to leverage both high-fidelity and low-fidelity data, yielding results that are more accurate.\n", "\n", "\n", + "### Kolmogorov-Arnold Networks (KANs)\n", + "KANs are neural networks inspired by the Kolmogorov-Arnold theorem, providing an alternative to traditional multilayer perceptrons (MLPs). KANs approximate multivariate functions by decomposing them into sums of nested univariate functions. Specifically, a KAN approximates a function $f(x)$ as:\n", + "\n", + "$$\n", + "f(x) \\approx \\sum_{i_{nl-1}=1}^{m_{nl-1}} \\phi_{nl-1, i_{nl-1}} \\left( \\cdots \\sum_{i_1=1}^{m_1} \\phi_{1, i_2, i_1} \\left( \\sum_{i_0=1}^{m_0} \\phi_{0, i_1, i_0}(x_{i_0}) \\right) \\cdots \\right)\n", + "$$\n", + "\n", + "where $\\phi_{j, i, k}$ are trainable, univariate activation functions represented by splines. This structure enables KANs to locally adjust function behavior with flexible resolution, making them effective for tasks with noisy data or where high interpretability is needed.\n", + "\n", + "### Multi-Fidelity KANs (MFKANs)\n", + "MFKANs extend KANs to efficiently learn from multiple data fidelities through a composite architecture consisting of three main components:\n", + "\n", + "1. **Low-fidelity KAN** ($\\mathcal{K}_L$): Standard KAN block, with polynomial degree $k>1$. Learns the low-fidelity data behavior.\n", + "2. **Linear KAN** ($\\mathcal{K}_l$): A linear KAN block (polynomial degree $k=1$) and two grid points. Captures linear correlations between fidelities.\n", + "3. **Nonlinear KAN** ($\\mathcal{K}_{nl}$): Standard KAN block, with polynomial degree $k>1$, but that also takes the outputs of the low-fidelity KAN as input. Models nonlinear corrections.\n", + "\n", + "The multi-fidelity prediction $\\mathcal{K}_M$ is given by a convex combination:\n", + "\n", + "$$\n", + "\\mathcal{K}_M(x) = \\alpha \\mathcal{K}_{nl}(x) + (1-\\alpha)\\mathcal{K}_l(x)\n", + "$$\n", + "\n", + "where $\\alpha$ is a trainable parameter, and $\\mathcal{K}_{nl}, \\mathcal{K}_l$ take as additional input the predictions of the low-fidelity KAN $\\mathcal{K}_L$. This structure allows MFKANs to:\n", + "- Leverage abundant low-fidelity data for basic feature learning\n", + "- Use limited high-fidelity data efficiently by separating linear and nonlinear correlations\n", + "- Maintain accuracy even with sparse high-fidelity sampling\n", + "\n", + "\"MFKAN\n", + "\n", + "### Key Applications\n", + "MFKANs are particularly useful for:\n", + "- Function fitting with multiple simulation fidelities\n", + "- Multi-resolution data fusion\n", + "- Efficient surrogate modeling for expensive computations\n", + "\n", "### References\n", "\n", "[1] [Liu, Ziming, et al. (2024). KAN: Kolmogorov-Arnold Networks.](https://arxiv.org/abs/2404.19756)\n", "\n", "[2] https://github.com/Blealtan/efficient-kan\n", "\n", - "[3] [Howard, Amanda A., et al. (2024) Multifidelity KANs.]\n" + "[3] [Howard, Amanda A., et al. (2024) Multifidelity Kolmogorov-Arnold networks.](https://arxiv.org/abs/2410.14764)\n" ] }, { @@ -35,7 +70,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -124,7 +159,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Generate data\n", + "### Generate and visualize data\n", "\n", "We will use the following jump function with a linear correlation. In this example we have sparse, high-fidelity data, which is not sufficient to capture the jump. \n", "$$\n", @@ -138,9 +173,9 @@ "y_H(x) = 2y_L(x) -2x + 2\n", "$$\n", "\n", - "for $ x \\in [0, 1].$ We take $ N_{LF}= 51 $ low-fidelity data points evenly distributed in $[0,1]$ and $ N_{HF} = 5 $ high-fidelity data points evenly spaced in $[0.1, 0.93]$. \n", + "for $ x \\in [0, 1].$ We take $ N_{L}= 51 $ low-fidelity data points evenly distributed in $[0,1]$ and $ N_{H} = 5 $ high-fidelity data points evenly spaced in $[0.1, 0.93]$. \n", "\n", - "We also generate $N_{full} = 200$ data points to test low, high and multi-fidelity models.\n" + "We also generate $N_\\text{full} = 200$ data points to test low, high and multi-fidelity models.\n" ] }, { @@ -161,16 +196,64 @@ "\n", "\n", "# Generate three datasets: low-fidelity \n", - "x_data_LF = torch.linspace(0, 1, 51).reshape(-1, 1)\n", - "y_data_LF = yL(x_data_LF)\n", + "x_data_L = torch.linspace(0, 1, 51).reshape(-1, 1)\n", + "y_data_L = yL(x_data_L)\n", "\n", - "x_data_HF = torch.linspace(.1, .93, 5).reshape(-1, 1)\n", - "y_data_HF = yH(x_data_HF)\n", + "x_data_H = torch.linspace(.1, .93, 5).reshape(-1, 1)\n", + "y_data_H = yH(x_data_H)\n", "\n", "x_data_full = torch.linspace(0, 1, 200).reshape(-1, 1)\n", "y_data_full = yH(x_data_full)\n" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A visualization of the data is shown below. \n", + "\n", + "The circular markers denote the sampled high-fidelity (green) and low-fidelity points, and the solid lines denote the exact functions defined above." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Visualize the data\n", + "plt.figure(figsize=(10, 4))\n", + "\n", + "# Plot data points\n", + "plt.scatter(x_data_L.numpy(), y_data_L.numpy(), c=\"#4e79a7\", label='LF data', alpha=0.8)\n", + "plt.scatter(x_data_H.numpy(), y_data_H.numpy(), c=\"#59a14f\", label='HF data', alpha=0.8)\n", + "\n", + "# Plot continuous functions\n", + "plt.plot(x_data_L.numpy(), yL(x_data_L).numpy(), \"#4e79a7\", label='LF', alpha=0.8)\n", + "plt.plot(x_data_L.numpy(), yH(x_data_L).numpy(), \"#59a14f\", label='HF', alpha=0.8)\n", + "\n", + "# Customize plot\n", + "plt.xlim(0, 1)\n", + "plt.xlabel('x', fontsize=14)\n", + "plt.ylabel('f(x)', fontsize=14)\n", + "plt.legend(fontsize=10)\n", + "plt.grid(True, alpha=0.3)\n", + "\n", + "plt.tight_layout()\n", + "plt.show()\n" + ] + }, { "cell_type": "code", "execution_count": 4, @@ -178,21 +261,21 @@ "outputs": [], "source": [ "# We will leverage Neuromancer's DictDataset to wrap the different datasets, giving them names\n", - "train_data_LF = DictDataset({'x': x_data_LF.to(device), 'y': y_data_LF.to(device)}, name='train_LF')\n", - "train_data_HF = DictDataset({'x': x_data_HF.to(device), 'y': y_data_HF.to(device)}, name='train_HF')\n", - "data_full = DictDataset({'x': x_data_full.to(device), 'y': y_data_full.to(device)}, name='data_full')\n", + "train_data_L = DictDataset({'x': x_data_L.to(device), 'y': y_data_L.to(device)}, name='train_L')\n", + "train_data_H = DictDataset({'x': x_data_H.to(device), 'y': y_data_H.to(device)}, name='train_H')\n", + "data_full = DictDataset({'x': x_data_full.to(device), 'y': y_data_full.to(device)}, name='data_full')\n", "\n", "# Here we leverage Torch's DataLoader class, that can use Neuromancer's DictDataset directly\n", - "batch_size_LF = train_data_LF.datadict['x'].shape[0]\n", - "batch_size_HF = train_data_HF.datadict['x'].shape[0]\n", + "batch_size_L = train_data_L.datadict['x'].shape[0]\n", + "batch_size_H = train_data_H.datadict['x'].shape[0]\n", "batch_size_full = data_full.datadict['x'].shape[0]\n", "\n", - "train_loader_LF = torch.utils.data.DataLoader(train_data_LF, batch_size=batch_size_LF,\n", - " collate_fn=train_data_LF.collate_fn,\n", + "train_loader_L = torch.utils.data.DataLoader(train_data_L, batch_size=batch_size_L,\n", + " collate_fn=train_data_L.collate_fn,\n", " shuffle=False)\n", "\n", - "train_loader_HF = torch.utils.data.DataLoader(train_data_HF, batch_size=batch_size_HF,\n", - " collate_fn=train_data_HF.collate_fn,\n", + "train_loader_H = torch.utils.data.DataLoader(train_data_H, batch_size=batch_size_H,\n", + " collate_fn=train_data_H.collate_fn,\n", " shuffle=False)\n", "\n", "\n", @@ -205,7 +288,23 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Part 1: Create a single-fidelity KAN and train on low-fidelity data" + "### Part 1: Create a single-fidelity KAN and train on low-fidelity data\n", + "\n", + "We begin by creating the low-fidelity KAN block, which will learn from the low-fidelity data. The `KANBlock` in Neuromancer provides a flexible implementation of Kolmogorov-Arnold Networks.\n", + "\n", + "- **`insize`**: *(int)* – Dimensionality of the input space. Set to 1 for our univariate function.\n", + "\n", + "- **`outsize`**: *(int)* – Dimensionality of the output space. Set to 1 as we're predicting a scalar value.\n", + "\n", + "- **`hsizes`**: *(list[int])* – Architecture of hidden layers. Here we use a single hidden layer with 5 nodes.\n", + "\n", + "- **`grid_sizes`**: *(list[int])* – Number of grid points for B-spline evaluation. Controls the resolution of our function approximation.\n", + "\n", + "- **`spline_order`**: *(int)* – Order of B-spline basis functions.\n", + "\n", + "- **`base_activation`**: *(callable)* – Base activation function.\n", + "\n", + "The low-fidelity KAN is wrapped in a Neuromancer `Node`. This node maps input 'x' to predicted output 'y_hat'.\n" ] }, { @@ -215,26 +314,52 @@ "outputs": [], "source": [ "# Define the low-fidelity KAN model\n", - "kan_LF = blocks.KANBlock(\n", - " insize=1, # Input size\n", - " outsize=1, # Output size\n", - " hsizes=[5], # KAN shape is [insize, hsizes, outsize]\n", - " grid_sizes=[5], # Grid size. Note: Neuromancer currently only support single-grid\n", - " spline_order=3, # 3rd order splines\n", - " grid_range=[0, 1], # Range for grid normalization \n", - " base_activation=torch.nn.Sigmoid, # Basis function\n", + "kan_L = blocks.KANBlock(\n", + " insize=1, # Input size\n", + " outsize=1, # Output size\n", + " hsizes=[5], # KAN shape is [insize, hsizes, outsize]\n", + " grid_sizes=[5], # Grid size. Note: Neuromancer currently only support single-grid\n", + " spline_order=3, # 3rd order splines\n", + " base_activation=torch.nn.Sigmoid, # Nonlinear base activation function\n", ").to(device)\n", "\n", "\n", "# Symbolic wrapper of the LF KAN\n", - "kan_wrapper_LF = Node(kan_LF, ['x'], ['y_hat'], name='wrapper_LF')\n" + "kan_wrapper_L = Node(kan_L, ['x'], ['y_hat'], name='wrapper_L')\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### Define symbolic variables and losses for low-fidelity KAN" + "#### Define symbolic variables and losses for low-fidelity model\n", + "\n", + "In the next cell, we construct a loss function for the low-fidelity model. The goal is to minimize the error between the predicted values, $\\hat{f}(x) = $ `y_hat`, and the true target values, $f(x) = $ `y`, across the dataset.\n", + "\n", + "**Symbolic Variables:**\n", + "\n", + "- `x`: Input variables, where $x \\in [0, 1]$.\n", + "- `y`: True target values from the function $f(x)$.\n", + "- `y_hat`: Predicted values produced by KAN model, $\\hat{y}$.\n", + "\n", + "\n", + "**Data Loss for KAN:**\n", + "\n", + "The data loss for the low-fidelity KAN, denoted as `loss_data_L`, is the mean squared error between the KAN predictions, `y_hat`, and the true target values, `y`:\n", + "\n", + "$$\n", + "\\ell_{\\text{L}} = \\text{scaling} \\cdot \\frac{1}{N_{\\text{L}}} \\sum_{i=1}^{N_{\\text{L}}} \\left( y_i - \\hat{y}_i \\right)^2\n", + "$$\n", + "\n", + "where $N_{\\text{L}}$ denotes the number of points in the low-fidelity dataset. This loss term guides the KAN model to learn the target function.\n", + "\n", + "**Loss Function:**\n", + "\n", + "The loss function is then constructed using Neuromancer's `PenaltyLoss`:\n", + "\n", + "- **`loss_L`**: Defined for the KAN model, using `loss_data_L`.\n", + "\n", + "In this case, we have left the problem unconstrainted. However, constraints can be added via the `constraints` argument." ] }, { @@ -243,29 +368,27 @@ "metadata": {}, "outputs": [], "source": [ - "# Define symbolic variables for LF model\n", - "x_LF = variable('x')\n", - "y_LF = variable('y')\n", - "y_hat_LF = variable('y_hat')\n", + "# Define symbolic variables for low-fidelity model\n", + "x_L = variable('x')\n", + "y_L = variable('y')\n", + "y_hat_L = variable('y_hat')\n", "\n", "# Define losses\n", - "loss_data_LF = (y_LF == y_hat_LF)^2\n", - "loss_data_LF.name = \"ref_loss_LF\"\n", + "loss_data_L = (y_L == y_hat_L)^2\n", + "loss_data_L.name = \"ref_loss_L\"\n", "\n", "# Create loss function\n", - "loss_LF = PenaltyLoss(objectives=[loss_data_LF], constraints=[])\n", - "\n", - "# Construct the optimization problem\n", - "problem_LF = Problem(nodes=[kan_wrapper_LF], loss=loss_LF, grad_inference=True)\n" + "loss_L = PenaltyLoss(objectives=[loss_data_L], constraints=[])\n", + "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### Train the model defined by the `problem_LF`\n", + "#### Construct Neuromancer `Problem` object and train low-fidelity model\n", "\n", - "Here we train a single-fidelity KAN with low-fidelity data alone." + "Here we train a single-fidelity KAN with low-fidelity data." ] }, { @@ -278,144 +401,61 @@ "output_type": "stream", "text": [ "Number of parameters: 100\n", - "epoch: 0\ttrain_LF_loss: 0.28923\teltime: 0.02929\n", - "epoch: 100\ttrain_LF_loss: 0.02990\teltime: 0.16434\n", - "epoch: 200\ttrain_LF_loss: 0.00099\teltime: 0.29818\n", - "epoch: 300\ttrain_LF_loss: 0.00057\teltime: 0.43077\n", - "epoch: 400\ttrain_LF_loss: 0.00040\teltime: 0.56490\n", - "epoch: 500\ttrain_LF_loss: 0.00030\teltime: 0.69451\n", - "epoch: 600\ttrain_LF_loss: 0.00023\teltime: 0.82519\n", - "epoch: 700\ttrain_LF_loss: 0.00017\teltime: 0.95411\n", - "epoch: 800\ttrain_LF_loss: 0.00012\teltime: 1.08317\n", - "epoch: 900\ttrain_LF_loss: 0.00008\teltime: 1.21211\n", - "epoch: 1000\ttrain_LF_loss: 0.00005\teltime: 1.34099\n", - "epoch: 1100\ttrain_LF_loss: 0.00003\teltime: 1.47295\n", - "epoch: 1200\ttrain_LF_loss: 0.00002\teltime: 1.60520\n", - "epoch: 1300\ttrain_LF_loss: 0.00001\teltime: 1.73394\n", - "epoch: 1400\ttrain_LF_loss: 0.00001\teltime: 1.86303\n", - "epoch: 1500\ttrain_LF_loss: 0.00001\teltime: 1.99600\n", - "epoch: 1600\ttrain_LF_loss: 0.00001\teltime: 2.12536\n", - "epoch: 1700\ttrain_LF_loss: 0.00000\teltime: 2.24995\n", - "epoch: 1800\ttrain_LF_loss: 0.00000\teltime: 2.37797\n", - "epoch: 1900\ttrain_LF_loss: 0.00000\teltime: 2.50702\n", - "epoch: 2000\ttrain_LF_loss: 0.00000\teltime: 2.63460\n", - "epoch: 2100\ttrain_LF_loss: 0.00000\teltime: 2.76854\n", - "epoch: 2200\ttrain_LF_loss: 0.00000\teltime: 2.89938\n", - "epoch: 2300\ttrain_LF_loss: 0.00000\teltime: 3.02265\n", - "epoch: 2400\ttrain_LF_loss: 0.00000\teltime: 3.15452\n", - "epoch: 2500\ttrain_LF_loss: 0.00000\teltime: 3.27297\n", - "epoch: 2600\ttrain_LF_loss: 0.00000\teltime: 3.40348\n", - "epoch: 2700\ttrain_LF_loss: 0.00000\teltime: 3.52100\n", - "epoch: 2800\ttrain_LF_loss: 0.00000\teltime: 3.64977\n", - "epoch: 2900\ttrain_LF_loss: 0.00000\teltime: 3.77446\n", - "epoch: 3000\ttrain_LF_loss: 0.00000\teltime: 3.89494\n", - "epoch: 3100\ttrain_LF_loss: 0.00000\teltime: 4.02866\n", - "epoch: 3200\ttrain_LF_loss: 0.00000\teltime: 4.15645\n", - "epoch: 3300\ttrain_LF_loss: 0.00000\teltime: 4.27763\n", - "epoch: 3400\ttrain_LF_loss: 0.00001\teltime: 4.40387\n", - "epoch: 3500\ttrain_LF_loss: 0.00000\teltime: 4.52443\n", - "epoch: 3600\ttrain_LF_loss: 0.00000\teltime: 4.65828\n", - "epoch: 3700\ttrain_LF_loss: 0.00000\teltime: 4.78050\n", - "epoch: 3800\ttrain_LF_loss: 0.00000\teltime: 4.90837\n", - "epoch: 3900\ttrain_LF_loss: 0.00000\teltime: 5.04141\n", - "epoch: 4000\ttrain_LF_loss: 0.00000\teltime: 5.15972\n", - "epoch: 4100\ttrain_LF_loss: 0.00000\teltime: 5.28684\n", - "epoch: 4200\ttrain_LF_loss: 0.00000\teltime: 5.41620\n", - "epoch: 4300\ttrain_LF_loss: 0.00000\teltime: 5.53584\n", - "epoch: 4400\ttrain_LF_loss: 0.00000\teltime: 5.66481\n", - "epoch: 4500\ttrain_LF_loss: 0.00001\teltime: 5.78742\n", - "epoch: 4600\ttrain_LF_loss: 0.00000\teltime: 5.90449\n", - "epoch: 4700\ttrain_LF_loss: 0.00000\teltime: 6.03360\n", - "epoch: 4800\ttrain_LF_loss: 0.00000\teltime: 6.15129\n", - "epoch: 4900\ttrain_LF_loss: 0.00000\teltime: 6.27380\n", - "epoch: 5000\ttrain_LF_loss: 0.00000\teltime: 6.40276\n", - "epoch: 5100\ttrain_LF_loss: 0.00000\teltime: 6.51812\n", - "epoch: 5200\ttrain_LF_loss: 0.00000\teltime: 6.64508\n", - "epoch: 5300\ttrain_LF_loss: 0.00000\teltime: 6.76892\n", - "epoch: 5400\ttrain_LF_loss: 0.00000\teltime: 6.89108\n", - "epoch: 5500\ttrain_LF_loss: 0.00000\teltime: 7.02495\n", - "epoch: 5600\ttrain_LF_loss: 0.00000\teltime: 7.14651\n", - "epoch: 5700\ttrain_LF_loss: 0.00000\teltime: 7.27781\n", - "epoch: 5800\ttrain_LF_loss: 0.00000\teltime: 7.41108\n", - "epoch: 5900\ttrain_LF_loss: 0.00000\teltime: 7.52457\n", - "epoch: 6000\ttrain_LF_loss: 0.00000\teltime: 7.64994\n", - "epoch: 6100\ttrain_LF_loss: 0.00004\teltime: 7.77374\n", - "epoch: 6200\ttrain_LF_loss: 0.00000\teltime: 7.88996\n", - "epoch: 6300\ttrain_LF_loss: 0.00000\teltime: 8.01677\n", - "epoch: 6400\ttrain_LF_loss: 0.00000\teltime: 8.13552\n", - "epoch: 6500\ttrain_LF_loss: 0.00000\teltime: 8.25520\n", - "epoch: 6600\ttrain_LF_loss: 0.00000\teltime: 8.38427\n", - "epoch: 6700\ttrain_LF_loss: 0.00000\teltime: 8.49959\n", - "epoch: 6800\ttrain_LF_loss: 0.00000\teltime: 8.62357\n", - "epoch: 6900\ttrain_LF_loss: 0.00000\teltime: 8.74854\n", - "epoch: 7000\ttrain_LF_loss: 0.00000\teltime: 8.86946\n", - "epoch: 7100\ttrain_LF_loss: 0.00000\teltime: 9.00702\n", - "epoch: 7200\ttrain_LF_loss: 0.00000\teltime: 9.12624\n", - "epoch: 7300\ttrain_LF_loss: 0.00000\teltime: 9.24753\n", - "epoch: 7400\ttrain_LF_loss: 0.00000\teltime: 9.36985\n", - "epoch: 7500\ttrain_LF_loss: 0.00000\teltime: 9.48475\n", - "epoch: 7600\ttrain_LF_loss: 0.00000\teltime: 9.61265\n", - "epoch: 7700\ttrain_LF_loss: 0.00000\teltime: 9.72883\n", - "epoch: 7800\ttrain_LF_loss: 0.00000\teltime: 9.85056\n", - "epoch: 7900\ttrain_LF_loss: 0.00000\teltime: 9.97873\n", - "epoch: 8000\ttrain_LF_loss: 0.00000\teltime: 10.09357\n", - "epoch: 8100\ttrain_LF_loss: 0.00000\teltime: 10.21628\n", - "epoch: 8200\ttrain_LF_loss: 0.00000\teltime: 10.34431\n", - "epoch: 8300\ttrain_LF_loss: 0.00000\teltime: 10.46160\n", - "epoch: 8400\ttrain_LF_loss: 0.00000\teltime: 10.58424\n", - "epoch: 8500\ttrain_LF_loss: 0.00000\teltime: 10.70324\n", - "epoch: 8600\ttrain_LF_loss: 0.00000\teltime: 10.81873\n", - "epoch: 8700\ttrain_LF_loss: 0.00000\teltime: 10.95177\n", - "epoch: 8800\ttrain_LF_loss: 0.00000\teltime: 11.06928\n", - "epoch: 8900\ttrain_LF_loss: 0.00000\teltime: 11.19095\n", - "epoch: 9000\ttrain_LF_loss: 0.00001\teltime: 11.31503\n", - "epoch: 9100\ttrain_LF_loss: 0.00000\teltime: 11.43006\n", - "epoch: 9200\ttrain_LF_loss: 0.00000\teltime: 11.55888\n", - "epoch: 9300\ttrain_LF_loss: 0.00000\teltime: 11.67542\n", - "epoch: 9400\ttrain_LF_loss: 0.00000\teltime: 11.79353\n", - "epoch: 9500\ttrain_LF_loss: 0.00000\teltime: 11.92035\n", - "epoch: 9600\ttrain_LF_loss: 0.00000\teltime: 12.03579\n", - "epoch: 9700\ttrain_LF_loss: 0.00000\teltime: 12.16444\n", - "epoch: 9800\ttrain_LF_loss: 0.00000\teltime: 12.28807\n", - "epoch: 9900\ttrain_LF_loss: 0.00000\teltime: 12.40648\n" + "epoch: 0\ttrain_L_loss: 0.28872\teltime: 0.03216\n", + "epoch: 1000\ttrain_L_loss: 0.00097\teltime: 1.33816\n", + "epoch: 2000\ttrain_L_loss: 0.00070\teltime: 2.64144\n", + "epoch: 3000\ttrain_L_loss: 0.00060\teltime: 3.92178\n", + "epoch: 4000\ttrain_L_loss: 0.00054\teltime: 5.23791\n", + "epoch: 5000\ttrain_L_loss: 0.00042\teltime: 6.52041\n", + "epoch: 6000\ttrain_L_loss: 0.00033\teltime: 7.82992\n", + "epoch: 7000\ttrain_L_loss: 0.00013\teltime: 9.15595\n", + "epoch: 8000\ttrain_L_loss: 0.00003\teltime: 10.45523\n", + "epoch: 9000\ttrain_L_loss: 0.00000\teltime: 11.71683\n" ] } ], "source": [ + "# Construct the optimization problem\n", + "problem_L = Problem(nodes=[kan_wrapper_L], loss=loss_L, grad_inference=True)\n", + "\n", "# Create trainer for LF model\n", "init_lr =0.005\n", - "epoch_verbose_lf = 100\n", - "num_epochs_lf=10000\n", - "logger_LF = LossLogger(args=None, savedir='test_LF', verbosity=epoch_verbose_lf, stdout=['train_LF_loss'])\n", - "\n", - "\n", - "trainer_LF = Trainer(\n", - " problem_LF.to(device),\n", - " train_data=train_loader_LF,\n", - " dev_data=train_loader_LF,\n", - " optimizer= torch.optim.Adam(problem_LF.parameters(), lr=init_lr),\n", - " epoch_verbose=epoch_verbose_lf,\n", - " logger=logger_LF,\n", - " epochs=num_epochs_lf,\n", - " train_metric='train_LF_loss',\n", - " eval_metric='train_LF_loss',\n", - " dev_metric='train_LF_loss',\n", - " warmup=num_epochs_lf,\n", + "epoch_verbose_L = 1000\n", + "num_epochs_L=10000\n", + "logger_L = LossLogger(args=None, savedir='test_L', verbosity=epoch_verbose_L, stdout=['train_L_loss'])\n", + "\n", + "\n", + "trainer_L = Trainer(\n", + " problem_L.to(device),\n", + " train_data=train_loader_L,\n", + " dev_data=train_loader_L,\n", + " optimizer= torch.optim.Adam(problem_L.parameters(), lr=init_lr),\n", + " epoch_verbose=epoch_verbose_L,\n", + " logger=logger_L,\n", + " epochs=num_epochs_L,\n", + " train_metric='train_L_loss',\n", + " eval_metric='train_L_loss',\n", + " dev_metric='train_L_loss',\n", + " warmup=num_epochs_L,\n", " device=device\n", ")\n", "\n", "\n", "# Train LF model\n", - "best_model_LF = trainer_LF.train()\n", - "problem_LF.load_state_dict(best_model_LF)\n", - "trained_model_LF = problem_LF.nodes[0]\n" + "best_model_L = trainer_L.train()\n", + "problem_L.load_state_dict(best_model_L)\n", + "trained_model_L = problem_L.nodes[0]\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Part 2: Create a single-fidelity KAN and train on high-fidelity data" + "### Part 2: Create a single-fidelity KAN and train on high-fidelity data\n", + "\n", + "Next, we construct a loss function for the high-fidelity model. \n", + "\n", + "The idea is the same as before: we will minimize the error between the predicted values, $\\hat{f}(x) = $ `y_hat`, and the true target values, $f(x) = $ `y`, across the high-fidelity dataset.\n" ] }, { @@ -425,25 +465,32 @@ "outputs": [], "source": [ "# Define the high-fidelity KAN model\n", - "kan_HF = blocks.KANBlock(\n", + "kan_H = blocks.KANBlock(\n", " insize=1, # Input size\n", " outsize=1, # Output size\n", " hsizes=[5], # KAN shape is [insize, hsizes, outsize]\n", " grid_sizes=[5], # Grid size. Note: Neuromancer currently only support single-grid\n", " spline_order=3, # 3rd order splines\n", - " grid_range=[0, 1], # Range for grid normalization \n", - " base_activation=torch.nn.Sigmoid, # Basis function\n", + " base_activation=torch.nn.Sigmoid, # Nonlinear base activation function\n", ").to(device)\n", "\n", "# Symbolic wrapper of the HF KAN\n", - "kan_wrapper_HF = Node(kan_HF, ['x'], ['y_hat'], name='wrapper_HF')\n" + "kan_wrapper_H = Node(kan_H, ['x'], ['y_hat'], name='wrapper_H')\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### Define symbolic variables and losses for high-fidelity KAN" + "#### Define symbolic variables and losses for high-fidelity KAN\n", + "\n", + "The data loss for the high-fidelity KAN, denoted as `loss_data_H`, is the mean squared error between the KAN predictions, `y_hat`, and the true target values, `y`:\n", + "\n", + "$$\n", + "\\ell_{\\text{H}} = \\text{scaling} \\cdot \\frac{1}{N_{\\text{H}}} \\sum_{i=1}^{N_{\\text{H}}} \\left( y_i - \\hat{y}_i \\right)^2\n", + "$$\n", + "\n", + "where $N_{\\text{H}}$ denotes the number of points in the high-fidelity dataset. Similarly to the low-fidelity case, we construct the loss function using Neuromancer's `PenaltyLoss`." ] }, { @@ -453,28 +500,26 @@ "outputs": [], "source": [ "# Define symbolic variables for HF model\n", - "x_HF = variable('x')\n", - "y_HF = variable('y')\n", - "y_hat_HF = variable('y_hat')\n", + "x_H = variable('x')\n", + "y_H = variable('y')\n", + "y_hat_H = variable('y_hat')\n", "\n", "# Define losses\n", - "loss_data_HF = (y_HF == y_hat_HF)^2\n", - "loss_data_HF.name = \"ref_loss_HF\"\n", + "loss_data_H = (y_H == y_hat_H)^2\n", + "loss_data_H.name = \"ref_loss_H\"\n", "\n", "# Create loss function\n", - "loss_HF = PenaltyLoss(objectives=[loss_data_HF], constraints=[])\n", - "\n", - "# Construct the HF optimization problem\n", - "problem_HF = Problem(nodes=[kan_wrapper_HF], loss=loss_HF, grad_inference=True)\n" + "loss_H = PenaltyLoss(objectives=[loss_data_H], constraints=[])\n", + "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### Train the model defined by the `problem_HF`\n", + "#### Construct Neuromancer `Problem` object and train high-fidelity model\n", "\n", - "Here we train a single-fidelity KAN with the high-fidelity data alone." + "Here we train a KAN with the high-fidelity data alone." ] }, { @@ -487,135 +532,48 @@ "output_type": "stream", "text": [ "Number of parameters: 100\n", - "epoch: 0\ttrain_HF_loss: 0.61907\teltime: 0.00270\n", - "epoch: 100\ttrain_HF_loss: 0.00110\teltime: 0.11428\n", - "epoch: 200\ttrain_HF_loss: 0.00000\teltime: 0.21474\n", - "epoch: 300\ttrain_HF_loss: 0.00000\teltime: 0.31609\n", - "epoch: 400\ttrain_HF_loss: 0.00000\teltime: 0.41249\n", - "epoch: 500\ttrain_HF_loss: 0.00000\teltime: 0.50663\n", - "epoch: 600\ttrain_HF_loss: 0.00000\teltime: 0.60414\n", - "epoch: 700\ttrain_HF_loss: 0.00000\teltime: 0.70197\n", - "epoch: 800\ttrain_HF_loss: 0.00000\teltime: 0.79531\n", - "epoch: 900\ttrain_HF_loss: 0.00000\teltime: 0.89208\n", - "epoch: 1000\ttrain_HF_loss: 0.00000\teltime: 0.98970\n", - "epoch: 1100\ttrain_HF_loss: 0.00000\teltime: 1.08312\n", - "epoch: 1200\ttrain_HF_loss: 0.00000\teltime: 1.18582\n", - "epoch: 1300\ttrain_HF_loss: 0.00000\teltime: 1.28156\n", - "epoch: 1400\ttrain_HF_loss: 0.00000\teltime: 1.37587\n", - "epoch: 1500\ttrain_HF_loss: 0.00000\teltime: 1.47076\n", - "epoch: 1600\ttrain_HF_loss: 0.00000\teltime: 1.56531\n", - "epoch: 1700\ttrain_HF_loss: 0.00000\teltime: 1.66175\n", - "epoch: 1800\ttrain_HF_loss: 0.00000\teltime: 1.75759\n", - "epoch: 1900\ttrain_HF_loss: 0.00000\teltime: 1.85336\n", - "epoch: 2000\ttrain_HF_loss: 0.00000\teltime: 1.94770\n", - "epoch: 2100\ttrain_HF_loss: 0.00000\teltime: 2.04235\n", - "epoch: 2200\ttrain_HF_loss: 0.00000\teltime: 2.13705\n", - "epoch: 2300\ttrain_HF_loss: 0.00000\teltime: 2.23081\n", - "epoch: 2400\ttrain_HF_loss: 0.00000\teltime: 2.32509\n", - "epoch: 2500\ttrain_HF_loss: 0.00000\teltime: 2.41951\n", - "epoch: 2600\ttrain_HF_loss: 0.00000\teltime: 2.51318\n", - "epoch: 2700\ttrain_HF_loss: 0.00000\teltime: 2.60754\n", - "epoch: 2800\ttrain_HF_loss: 0.00000\teltime: 2.70216\n", - "epoch: 2900\ttrain_HF_loss: 0.00000\teltime: 2.80034\n", - "epoch: 3000\ttrain_HF_loss: 0.00000\teltime: 2.89345\n", - "epoch: 3100\ttrain_HF_loss: 0.00000\teltime: 2.98654\n", - "epoch: 3200\ttrain_HF_loss: 0.00000\teltime: 3.08214\n", - "epoch: 3300\ttrain_HF_loss: 0.00000\teltime: 3.17693\n", - "epoch: 3400\ttrain_HF_loss: 0.00000\teltime: 3.27147\n", - "epoch: 3500\ttrain_HF_loss: 0.00000\teltime: 3.36933\n", - "epoch: 3600\ttrain_HF_loss: 0.00000\teltime: 3.46336\n", - "epoch: 3700\ttrain_HF_loss: 0.00000\teltime: 3.55791\n", - "epoch: 3800\ttrain_HF_loss: 0.00000\teltime: 3.65166\n", - "epoch: 3900\ttrain_HF_loss: 0.00000\teltime: 3.74749\n", - "epoch: 4000\ttrain_HF_loss: 0.00000\teltime: 3.84320\n", - "epoch: 4100\ttrain_HF_loss: 0.00000\teltime: 3.94093\n", - "epoch: 4200\ttrain_HF_loss: 0.00000\teltime: 4.03516\n", - "epoch: 4300\ttrain_HF_loss: 0.00000\teltime: 4.12984\n", - "epoch: 4400\ttrain_HF_loss: 0.00000\teltime: 4.22490\n", - "epoch: 4500\ttrain_HF_loss: 0.00000\teltime: 4.32297\n", - "epoch: 4600\ttrain_HF_loss: 0.00000\teltime: 4.42150\n", - "epoch: 4700\ttrain_HF_loss: 0.00000\teltime: 4.51528\n", - "epoch: 4800\ttrain_HF_loss: 0.00000\teltime: 4.60860\n", - "epoch: 4900\ttrain_HF_loss: 0.00000\teltime: 4.70197\n", - "epoch: 5000\ttrain_HF_loss: 0.00000\teltime: 4.79649\n", - "epoch: 5100\ttrain_HF_loss: 0.00000\teltime: 4.88983\n", - "epoch: 5200\ttrain_HF_loss: 0.00000\teltime: 4.98333\n", - "epoch: 5300\ttrain_HF_loss: 0.00000\teltime: 5.07733\n", - "epoch: 5400\ttrain_HF_loss: 0.00000\teltime: 5.17497\n", - "epoch: 5500\ttrain_HF_loss: 0.00000\teltime: 5.27349\n", - "epoch: 5600\ttrain_HF_loss: 0.00000\teltime: 5.39752\n", - "epoch: 5700\ttrain_HF_loss: 0.00000\teltime: 5.49568\n", - "epoch: 5800\ttrain_HF_loss: 0.00000\teltime: 5.59400\n", - "epoch: 5900\ttrain_HF_loss: 0.00000\teltime: 5.68871\n", - "epoch: 6000\ttrain_HF_loss: 0.00000\teltime: 5.78636\n", - "epoch: 6100\ttrain_HF_loss: 0.00000\teltime: 5.88455\n", - "epoch: 6200\ttrain_HF_loss: 0.00000\teltime: 5.98716\n", - "epoch: 6300\ttrain_HF_loss: 0.00000\teltime: 6.08131\n", - "epoch: 6400\ttrain_HF_loss: 0.00000\teltime: 6.17586\n", - "epoch: 6500\ttrain_HF_loss: 0.00000\teltime: 6.26988\n", - "epoch: 6600\ttrain_HF_loss: 0.00000\teltime: 6.36429\n", - "epoch: 6700\ttrain_HF_loss: 0.00000\teltime: 6.45828\n", - "epoch: 6800\ttrain_HF_loss: 0.00000\teltime: 6.55292\n", - "epoch: 6900\ttrain_HF_loss: 0.00000\teltime: 6.65106\n", - "epoch: 7000\ttrain_HF_loss: 0.00000\teltime: 6.74928\n", - "epoch: 7100\ttrain_HF_loss: 0.00000\teltime: 6.84368\n", - "epoch: 7200\ttrain_HF_loss: 0.00000\teltime: 6.94149\n", - "epoch: 7300\ttrain_HF_loss: 0.00000\teltime: 7.03986\n", - "epoch: 7400\ttrain_HF_loss: 0.00000\teltime: 7.13431\n", - "epoch: 7500\ttrain_HF_loss: 0.00000\teltime: 7.23205\n", - "epoch: 7600\ttrain_HF_loss: 0.00000\teltime: 7.33030\n", - "epoch: 7700\ttrain_HF_loss: 0.00000\teltime: 7.42895\n", - "epoch: 7800\ttrain_HF_loss: 0.00000\teltime: 7.52235\n", - "epoch: 7900\ttrain_HF_loss: 0.00000\teltime: 7.61578\n", - "epoch: 8000\ttrain_HF_loss: 0.00000\teltime: 7.71529\n", - "epoch: 8100\ttrain_HF_loss: 0.00000\teltime: 7.80847\n", - "epoch: 8200\ttrain_HF_loss: 0.00000\teltime: 7.90207\n", - "epoch: 8300\ttrain_HF_loss: 0.00000\teltime: 7.99743\n", - "epoch: 8400\ttrain_HF_loss: 0.00000\teltime: 8.09520\n", - "epoch: 8500\ttrain_HF_loss: 0.00000\teltime: 8.19344\n", - "epoch: 8600\ttrain_HF_loss: 0.00000\teltime: 8.28717\n", - "epoch: 8700\ttrain_HF_loss: 0.00000\teltime: 8.38186\n", - "epoch: 8800\ttrain_HF_loss: 0.00000\teltime: 8.47689\n", - "epoch: 8900\ttrain_HF_loss: 0.00000\teltime: 8.57462\n", - "epoch: 9000\ttrain_HF_loss: 0.00000\teltime: 8.66765\n", - "epoch: 9100\ttrain_HF_loss: 0.00000\teltime: 8.76147\n", - "epoch: 9200\ttrain_HF_loss: 0.00000\teltime: 8.85646\n", - "epoch: 9300\ttrain_HF_loss: 0.00000\teltime: 8.94994\n", - "epoch: 9400\ttrain_HF_loss: 0.00000\teltime: 9.04368\n", - "epoch: 9500\ttrain_HF_loss: 0.00000\teltime: 9.14018\n", - "epoch: 9600\ttrain_HF_loss: 0.00000\teltime: 9.23563\n", - "epoch: 9700\ttrain_HF_loss: 0.00000\teltime: 9.33089\n", - "epoch: 9800\ttrain_HF_loss: 0.00000\teltime: 9.43206\n", - "epoch: 9900\ttrain_HF_loss: 0.00000\teltime: 9.52504\n" + "epoch: 0\ttrain_H_loss: 0.62511\teltime: 0.00242\n", + "epoch: 1000\ttrain_H_loss: 0.00000\teltime: 1.00987\n", + "epoch: 2000\ttrain_H_loss: 0.00000\teltime: 1.98075\n", + "epoch: 3000\ttrain_H_loss: 0.00000\teltime: 2.96927\n", + "epoch: 4000\ttrain_H_loss: 0.00000\teltime: 3.93970\n", + "epoch: 5000\ttrain_H_loss: 0.00000\teltime: 4.90751\n", + "epoch: 6000\ttrain_H_loss: 0.00000\teltime: 5.88304\n", + "epoch: 7000\ttrain_H_loss: 0.00000\teltime: 6.87024\n", + "epoch: 8000\ttrain_H_loss: 0.00000\teltime: 7.88022\n", + "epoch: 9000\ttrain_H_loss: 0.00000\teltime: 8.85284\n" ] } ], "source": [ - "# Create trainer for HF model\n", + "# Construct the high-fidelity optimization problem\n", + "problem_H = Problem(nodes=[kan_wrapper_H], loss=loss_H, grad_inference=True)\n", + "\n", + "# Create trainer for high-fidelity model\n", "init_lr =0.005\n", - "epoch_verbose_hf = 100\n", - "num_epochs_hf=10000\n", - "logger_HF = LossLogger(args=None, savedir='test_HF', verbosity=epoch_verbose_hf, stdout=['train_HF_loss'])\n", - "\n", - "trainer_HF = Trainer(\n", - " problem_HF.to(device),\n", - " train_data=train_loader_HF,\n", - " dev_data=train_loader_HF,\n", - " optimizer= torch.optim.Adam(problem_HF.parameters(), lr=init_lr),\n", - " epoch_verbose=epoch_verbose_hf,\n", - " logger=logger_HF,\n", - " epochs=num_epochs_hf,\n", - " train_metric='train_HF_loss',\n", - " eval_metric='train_HF_loss',\n", - " dev_metric='train_HF_loss',\n", - " warmup=num_epochs_hf,\n", + "epoch_verbose_H = 1000\n", + "num_epochs_H=10000\n", + "logger_H = LossLogger(args=None, savedir='test_HF', verbosity=epoch_verbose_H, stdout=['train_H_loss'])\n", + "\n", + "trainer_H = Trainer(\n", + " problem_H.to(device),\n", + " train_data=train_loader_H,\n", + " dev_data=train_loader_H,\n", + " optimizer= torch.optim.Adam(problem_H.parameters(), lr=init_lr),\n", + " epoch_verbose=epoch_verbose_H,\n", + " logger=logger_H,\n", + " epochs=num_epochs_H,\n", + " train_metric='train_H_loss',\n", + " eval_metric='train_H_loss',\n", + " dev_metric='train_H_loss',\n", + " warmup=num_epochs_H,\n", " device=device\n", ")\n", "\n", "# Train HF model\n", - "best_model_HF = trainer_HF.train()\n", - "problem_HF.load_state_dict(best_model_HF)\n", - "trained_model_HF = problem_HF.nodes[0]\n", + "best_model_H = trainer_H.train()\n", + "problem_H.load_state_dict(best_model_H)\n", + "trained_model_H = problem_H.nodes[0]\n", "\n" ] }, @@ -623,9 +581,28 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Part 3: Create a multi-fidelity KAN\n", + "### Part 3: Create a multi-fidelity KAN and train\n", + "\n", + "The `MultiFidelityKAN` block in Neuromancer enables learning from both low and high-fidelity data sources. The architecture **uses a pre-trained, low-fidelity model, along with high-fidelity data to capture correlations between fidelities**.\n", + "\n", + "\n", + "- **`sfkan`**: *(KANBlock)* – Pre-trained low-fidelity KAN model that provides base predictions.\n", + "\n", + "- **`insize=1`**: *(int)* – Dimensionality of the input space. Set to 1 for our univariate function.\n", "\n", - "This network leverages the low-fidelity model and the high-fidelity data." + "- **`outsize=1`**: *(int)* – Dimensionality of the output space. Set to 1 as we're predicting a scalar value.\n", + "\n", + "- **`hsizes=[5]`**: *(list[int])* – Architecture of nonlinear KAN's hidden layers. The linear KAN is automatically configured as [insize, outsize].\n", + "\n", + "- **`grid_sizes=[4]`**: *(list[int])* – Number of grid points for B-spline evaluation in the nonlinear KAN.\n", + "\n", + "- **`spline_order=2`**: *(int)* – Order of B-spline basis functions.\n", + "\n", + "- **`alpha_init=0.1`**: *(float)* – Initial value for the learnable weight $\\alpha$ that controls the convex combination of linear and nonlinear networks.\n", + "\n", + "- **`base_activation`**: *(callable)* – Base activation function.\n", + "\n", + "The multi-fidelity KAN is wrapped in a Neuromancer `Node`. This node maps input 'x' to the high-fidelity prediction 'y_hat'.\n" ] }, { @@ -637,20 +614,19 @@ "# Define the multi-fidelity KAN model\n", "\n", "# Here we use Neuromancer's MultiFidelityKAN block. The syntax is very similar to KANBlock!\n", - "kan_MF = blocks.MultiFidelityKAN(\n", - " sfkan=kan_LF, # A trained, low-fidelity model\n", + "kan_M = blocks.MultiFidelityKAN(\n", + " sfkan=kan_L, # A trained, low-fidelity model\n", " insize=1, # Input size\n", " outsize=1, # Output size\n", " hsizes=[5], # Nonlinear KAN shape: [insize, hsizes, outsize]. Shape of linear KAN is always [insize, outsize].\n", " grid_sizes=[4], # Grid size. Note: Neuromancer currently only support single-grid\n", " spline_order=2, # 2nd order splines\n", - " grid_range=[0, 1], # Range for grid normalization \n", " alpha_init=0.1, # Initial value of learnable weight alpha, used in the convex combination of linear and nonlinear nets.\n", - " base_activation=torch.nn.Sigmoid, # Basis function\n", + " base_activation=torch.nn.Sigmoid, # Nonlinear base activation function\n", ").to(device)\n", "\n", "# Symbolic wrapper of the MF KAN\n", - "kan_wrapper_MF = Node(kan_MF, ['x'], ['y_hat'], name='kan_wrapper_MF')\n", + "kan_wrapper_M = Node(kan_M, ['x'], ['y_hat'], name='kan_wrapper_M')\n", "\n" ] }, @@ -658,7 +634,37 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "#### Define symbolic variables and losses for multi-fidelity KAN" + "#### Define symbolic variables and losses for multi-fidelity KAN\n", + "\n", + "The complete multi-fidelity KAN loss function consists of three components:\n", + "\n", + "1. **Data Loss** - Mean squared error between the MFKAN predictions, `y_hat`, and the true target values, `y` on the high-fidelity data:\n", + "$$\n", + "\\ell_{\\text{data}} = \\frac{1}{N_{\\text{H}}} \\sum_{i=1}^{N_{\\text{H}}} \\left( y_i - \\hat{y}_i \\right)^2\n", + "$$\n", + "\n", + "2. **Alpha Loss** - Penalizes the magnitude of $\\alpha$ to maximize linear correlations:\n", + "$$\n", + "\\ell_{\\text{alpha}} = \\alpha^n\n", + "$$\n", + "\n", + "3. **Regularization Loss** - Prevents overfitting by penalizing B-spline coefficients on each layer $L$ of each KAN:\n", + "$$\n", + "\\ell_{\\text{reg}} = w \\sum_{l=0}^{L-1} \\|\\Phi_{nl}\\|\n", + "$$ \n", + "$$\n", + "\\|\\Phi_{nl}\\| = \\frac{1}{n_{\\text{in}}n_{\\text{out}}} \\sum_{i=1}^{n_{\\text{in}}} \\sum_{j=1}^{n_{\\text{out}}} |\\phi_{i,j}^{nl}|^2\n", + "$$\n", + "\n", + "The complete loss function combines these terms:\n", + "$$\n", + "\\ell_{\\text{total}} = \\ell_{\\text{data}} + \\ell_{\\text{alpha}} + \\ell_{\\text{reg}}\n", + "$$\n", + "\n", + "***Note: In Neuromancer, the alpha and regularization losses are automatically handled internally, so that the user only need to set up the data loss!***\n", + "\n", + "\n", + "Finally, create a `PenaltyLoss` and use the `loss_data_MF` as our objective function. " ] }, { @@ -668,28 +674,25 @@ "outputs": [], "source": [ "# Define symbolic variables for MF model\n", - "x_MF = variable('x')\n", - "y_MF = variable('y')\n", - "y_hat_MF = variable('y_hat')\n", + "x_M = variable('x')\n", + "y_M = variable('y')\n", + "y_hat_M = variable('y_hat')\n", "\n", "# Define losses\n", - "loss_data_MF = (y_MF == y_hat_MF)^2\n", - "loss_data_MF.name = \"ref_loss_MF\"\n", + "loss_data_M = (y_M == y_hat_M)^2\n", + "loss_data_M.name = \"ref_loss_M\"\n", "\n", "# Create loss function\n", - "loss_MF = PenaltyLoss(objectives=[loss_data_MF], constraints=[])\n", - "\n", - "# Construct the MF optimization problem\n", - "problem_MF = Problem(nodes=[kan_wrapper_MF], loss=loss_MF, grad_inference=True)\n" + "loss_M = PenaltyLoss(objectives=[loss_data_M], constraints=[])\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "#### Train the model defined by the `problem_MF`\n", + "#### Construct Neuromancer `Problem` object and train multi-fidelity model\n", "\n", - "Here we train a multi-fidelity KAN using a low-fidelity, pre-trained model and high-fidelity, sparse data." + "In this section, we create and train the complete Multi-Fidelity KAN (MFKAN) architecture. We achieve multi-fidelity learning by using the low-fidelity, pre-trained model obtained in Part 1 with high-fidelity data.\n" ] }, { @@ -702,240 +705,63 @@ "output_type": "stream", "text": [ "Number of parameters: 131\n", - "epoch: 0\ttrain_HF_loss: 0.49794\teltime: 0.00381\n", - "epoch: 100\ttrain_HF_loss: 0.05398\teltime: 0.19552\n", - "epoch: 200\ttrain_HF_loss: 0.04039\teltime: 0.39655\n", - "epoch: 300\ttrain_HF_loss: 0.01642\teltime: 0.58579\n", - "epoch: 400\ttrain_HF_loss: 0.00703\teltime: 0.77287\n", - "epoch: 500\ttrain_HF_loss: 0.00391\teltime: 0.95766\n", - "epoch: 600\ttrain_HF_loss: 0.00253\teltime: 1.14821\n", - "epoch: 700\ttrain_HF_loss: 0.00177\teltime: 1.32636\n", - "epoch: 800\ttrain_HF_loss: 0.00129\teltime: 1.50102\n", - "epoch: 900\ttrain_HF_loss: 0.00099\teltime: 1.68525\n", - "epoch: 1000\ttrain_HF_loss: 0.00079\teltime: 1.87304\n", - "epoch: 1100\ttrain_HF_loss: 0.00064\teltime: 2.04949\n", - "epoch: 1200\ttrain_HF_loss: 0.00055\teltime: 2.21655\n", - "epoch: 1300\ttrain_HF_loss: 0.00044\teltime: 2.40254\n", - "epoch: 1400\ttrain_HF_loss: 0.00037\teltime: 2.59020\n", - "epoch: 1500\ttrain_HF_loss: 0.00030\teltime: 2.76811\n", - "epoch: 1600\ttrain_HF_loss: 0.00024\teltime: 2.96144\n", - "epoch: 1700\ttrain_HF_loss: 0.00020\teltime: 3.13274\n", - "epoch: 1800\ttrain_HF_loss: 0.00016\teltime: 3.31163\n", - "epoch: 1900\ttrain_HF_loss: 0.00013\teltime: 3.49370\n", - "epoch: 2000\ttrain_HF_loss: 0.00011\teltime: 3.66585\n", - "epoch: 2100\ttrain_HF_loss: 0.00009\teltime: 3.83847\n", - "epoch: 2200\ttrain_HF_loss: 0.00007\teltime: 4.01240\n", - "epoch: 2300\ttrain_HF_loss: 0.00005\teltime: 4.18102\n", - "epoch: 2400\ttrain_HF_loss: 0.00004\teltime: 4.34899\n", - "epoch: 2500\ttrain_HF_loss: 0.00003\teltime: 4.52197\n", - "epoch: 2600\ttrain_HF_loss: 0.00004\teltime: 4.69354\n", - "epoch: 2700\ttrain_HF_loss: 0.00001\teltime: 4.87159\n", - "epoch: 2800\ttrain_HF_loss: 0.00001\teltime: 5.03473\n", - "epoch: 2900\ttrain_HF_loss: 0.00006\teltime: 5.21688\n", - "epoch: 3000\ttrain_HF_loss: 0.00000\teltime: 5.38323\n", - "epoch: 3100\ttrain_HF_loss: 0.00001\teltime: 5.55701\n", - "epoch: 3200\ttrain_HF_loss: 0.00000\teltime: 5.73750\n", - "epoch: 3300\ttrain_HF_loss: 0.00000\teltime: 5.89653\n", - "epoch: 3400\ttrain_HF_loss: 0.00000\teltime: 6.07450\n", - "epoch: 3500\ttrain_HF_loss: 0.00000\teltime: 6.23402\n", - "epoch: 3600\ttrain_HF_loss: 0.00004\teltime: 6.40454\n", - "epoch: 3700\ttrain_HF_loss: 0.00000\teltime: 6.56518\n", - "epoch: 3800\ttrain_HF_loss: 0.00001\teltime: 6.73146\n", - "epoch: 3900\ttrain_HF_loss: 0.00000\teltime: 6.88974\n", - "epoch: 4000\ttrain_HF_loss: 0.00000\teltime: 7.04982\n", - "epoch: 4100\ttrain_HF_loss: 0.00000\teltime: 7.20961\n", - "epoch: 4200\ttrain_HF_loss: 0.00000\teltime: 7.36634\n", - "epoch: 4300\ttrain_HF_loss: 0.00000\teltime: 7.52261\n", - "epoch: 4400\ttrain_HF_loss: 0.00000\teltime: 7.68976\n", - "epoch: 4500\ttrain_HF_loss: 0.00000\teltime: 7.84454\n", - "epoch: 4600\ttrain_HF_loss: 0.00000\teltime: 8.00179\n", - "epoch: 4700\ttrain_HF_loss: 0.00000\teltime: 8.16284\n", - "epoch: 4800\ttrain_HF_loss: 0.00000\teltime: 8.32455\n", - "epoch: 4900\ttrain_HF_loss: 0.00000\teltime: 8.48521\n", - "epoch: 5000\ttrain_HF_loss: 0.00000\teltime: 8.64290\n", - "epoch: 5100\ttrain_HF_loss: 0.00002\teltime: 8.80497\n", - "epoch: 5200\ttrain_HF_loss: 0.00000\teltime: 8.96105\n", - "epoch: 5300\ttrain_HF_loss: 0.00006\teltime: 9.11873\n", - "epoch: 5400\ttrain_HF_loss: 0.00000\teltime: 9.27524\n", - "epoch: 5500\ttrain_HF_loss: 0.00002\teltime: 9.43070\n", - "epoch: 5600\ttrain_HF_loss: 0.00000\teltime: 9.58733\n", - "epoch: 5700\ttrain_HF_loss: 0.00000\teltime: 9.74352\n", - "epoch: 5800\ttrain_HF_loss: 0.00000\teltime: 9.90043\n", - "epoch: 5900\ttrain_HF_loss: 0.00000\teltime: 10.06250\n", - "epoch: 6000\ttrain_HF_loss: 0.00000\teltime: 10.21906\n", - "epoch: 6100\ttrain_HF_loss: 0.00000\teltime: 10.38037\n", - "epoch: 6200\ttrain_HF_loss: 0.00033\teltime: 10.54589\n", - "epoch: 6300\ttrain_HF_loss: 0.00000\teltime: 10.70106\n", - "epoch: 6400\ttrain_HF_loss: 0.00000\teltime: 10.85539\n", - "epoch: 6500\ttrain_HF_loss: 0.00000\teltime: 11.01700\n", - "epoch: 6600\ttrain_HF_loss: 0.00000\teltime: 11.17345\n", - "epoch: 6700\ttrain_HF_loss: 0.00000\teltime: 11.33450\n", - "epoch: 6800\ttrain_HF_loss: 0.00000\teltime: 11.49212\n", - "epoch: 6900\ttrain_HF_loss: 0.00000\teltime: 11.64926\n", - "epoch: 7000\ttrain_HF_loss: 0.00003\teltime: 11.80785\n", - "epoch: 7100\ttrain_HF_loss: 0.00000\teltime: 11.97048\n", - "epoch: 7200\ttrain_HF_loss: 0.00010\teltime: 12.13281\n", - "epoch: 7300\ttrain_HF_loss: 0.00000\teltime: 12.28854\n", - "epoch: 7400\ttrain_HF_loss: 0.00000\teltime: 12.44568\n", - "epoch: 7500\ttrain_HF_loss: 0.00000\teltime: 12.60751\n", - "epoch: 7600\ttrain_HF_loss: 0.00000\teltime: 12.76965\n", - "epoch: 7700\ttrain_HF_loss: 0.00005\teltime: 12.92561\n", - "epoch: 7800\ttrain_HF_loss: 0.00000\teltime: 13.08260\n", - "epoch: 7900\ttrain_HF_loss: 0.00000\teltime: 13.24395\n", - "epoch: 8000\ttrain_HF_loss: 0.00000\teltime: 13.40610\n", - "epoch: 8100\ttrain_HF_loss: 0.00000\teltime: 13.56460\n", - "epoch: 8200\ttrain_HF_loss: 0.00000\teltime: 13.74919\n", - "epoch: 8300\ttrain_HF_loss: 0.00000\teltime: 13.90511\n", - "epoch: 8400\ttrain_HF_loss: 0.00000\teltime: 14.07140\n", - "epoch: 8500\ttrain_HF_loss: 0.00009\teltime: 14.25007\n", - "epoch: 8600\ttrain_HF_loss: 0.00000\teltime: 14.40581\n", - "epoch: 8700\ttrain_HF_loss: 0.00000\teltime: 14.58163\n", - "epoch: 8800\ttrain_HF_loss: 0.00000\teltime: 14.73713\n", - "epoch: 8900\ttrain_HF_loss: 0.00000\teltime: 14.90421\n", - "epoch: 9000\ttrain_HF_loss: 0.00000\teltime: 15.08326\n", - "epoch: 9100\ttrain_HF_loss: 0.00000\teltime: 15.23869\n", - "epoch: 9200\ttrain_HF_loss: 0.00000\teltime: 15.40918\n", - "epoch: 9300\ttrain_HF_loss: 0.00000\teltime: 15.56601\n", - "epoch: 9400\ttrain_HF_loss: 0.00000\teltime: 15.73261\n", - "epoch: 9500\ttrain_HF_loss: 0.00001\teltime: 15.89992\n", - "epoch: 9600\ttrain_HF_loss: 0.00000\teltime: 16.05665\n", - "epoch: 9700\ttrain_HF_loss: 0.00000\teltime: 16.23551\n", - "epoch: 9800\ttrain_HF_loss: 0.00000\teltime: 16.39111\n", - "epoch: 9900\ttrain_HF_loss: 0.00000\teltime: 16.56118\n", - "epoch: 10000\ttrain_HF_loss: 0.00000\teltime: 16.72418\n", - "epoch: 10100\ttrain_HF_loss: 0.00000\teltime: 16.88834\n", - "epoch: 10200\ttrain_HF_loss: 0.00010\teltime: 17.07175\n", - "epoch: 10300\ttrain_HF_loss: 0.00000\teltime: 17.22786\n", - "epoch: 10400\ttrain_HF_loss: 0.00000\teltime: 17.38862\n", - "epoch: 10500\ttrain_HF_loss: 0.00002\teltime: 17.57103\n", - "epoch: 10600\ttrain_HF_loss: 0.00000\teltime: 17.72851\n", - "epoch: 10700\ttrain_HF_loss: 0.00000\teltime: 17.90562\n", - "epoch: 10800\ttrain_HF_loss: 0.00000\teltime: 18.06861\n", - "epoch: 10900\ttrain_HF_loss: 0.00000\teltime: 18.22485\n", - "epoch: 11000\ttrain_HF_loss: 0.00000\teltime: 18.41453\n", - "epoch: 11100\ttrain_HF_loss: 0.00000\teltime: 18.57161\n", - "epoch: 11200\ttrain_HF_loss: 0.00000\teltime: 18.73530\n", - "epoch: 11300\ttrain_HF_loss: 0.00000\teltime: 18.91516\n", - "epoch: 11400\ttrain_HF_loss: 0.00000\teltime: 19.07042\n", - "epoch: 11500\ttrain_HF_loss: 0.00000\teltime: 19.24921\n", - "epoch: 11600\ttrain_HF_loss: 0.00000\teltime: 19.41372\n", - "epoch: 11700\ttrain_HF_loss: 0.00000\teltime: 19.57605\n", - "epoch: 11800\ttrain_HF_loss: 0.00002\teltime: 19.75235\n", - "epoch: 11900\ttrain_HF_loss: 0.00000\teltime: 19.90924\n", - "epoch: 12000\ttrain_HF_loss: 0.00000\teltime: 20.08444\n", - "epoch: 12100\ttrain_HF_loss: 0.00000\teltime: 20.23792\n", - "epoch: 12200\ttrain_HF_loss: 0.00000\teltime: 20.41586\n", - "epoch: 12300\ttrain_HF_loss: 0.00000\teltime: 20.57516\n", - "epoch: 12400\ttrain_HF_loss: 0.00000\teltime: 20.72894\n", - "epoch: 12500\ttrain_HF_loss: 0.00013\teltime: 20.90862\n", - "epoch: 12600\ttrain_HF_loss: 0.00000\teltime: 21.06517\n", - "epoch: 12700\ttrain_HF_loss: 0.00000\teltime: 21.23664\n", - "epoch: 12800\ttrain_HF_loss: 0.00000\teltime: 21.39672\n", - "epoch: 12900\ttrain_HF_loss: 0.00000\teltime: 21.55203\n", - "epoch: 13000\ttrain_HF_loss: 0.00003\teltime: 21.73418\n", - "epoch: 13100\ttrain_HF_loss: 0.00000\teltime: 21.88853\n", - "epoch: 13200\ttrain_HF_loss: 0.00000\teltime: 22.05885\n", - "epoch: 13300\ttrain_HF_loss: 0.00003\teltime: 22.23299\n", - "epoch: 13400\ttrain_HF_loss: 0.00000\teltime: 22.39175\n", - "epoch: 13500\ttrain_HF_loss: 0.00000\teltime: 22.56750\n", - "epoch: 13600\ttrain_HF_loss: 0.00000\teltime: 22.72309\n", - "epoch: 13700\ttrain_HF_loss: 0.00000\teltime: 22.89708\n", - "epoch: 13800\ttrain_HF_loss: 0.00001\teltime: 23.07607\n", - "epoch: 13900\ttrain_HF_loss: 0.00000\teltime: 23.23045\n", - "epoch: 14000\ttrain_HF_loss: 0.00000\teltime: 23.39921\n", - "epoch: 14100\ttrain_HF_loss: 0.00012\teltime: 23.57696\n", - "epoch: 14200\ttrain_HF_loss: 0.00000\teltime: 23.73401\n", - "epoch: 14300\ttrain_HF_loss: 0.00000\teltime: 23.91380\n", - "epoch: 14400\ttrain_HF_loss: 0.00001\teltime: 24.09190\n", - "epoch: 14500\ttrain_HF_loss: 0.00000\teltime: 24.24850\n", - "epoch: 14600\ttrain_HF_loss: 0.00000\teltime: 24.43149\n", - "epoch: 14700\ttrain_HF_loss: 0.00000\teltime: 24.59704\n", - "epoch: 14800\ttrain_HF_loss: 0.00000\teltime: 24.76679\n", - "epoch: 14900\ttrain_HF_loss: 0.00000\teltime: 24.94718\n", - "epoch: 15000\ttrain_HF_loss: 0.00000\teltime: 25.11051\n", - "epoch: 15100\ttrain_HF_loss: 0.00000\teltime: 25.28891\n", - "epoch: 15200\ttrain_HF_loss: 0.00000\teltime: 25.45364\n", - "epoch: 15300\ttrain_HF_loss: 0.00000\teltime: 25.61920\n", - "epoch: 15400\ttrain_HF_loss: 0.00000\teltime: 25.80002\n", - "epoch: 15500\ttrain_HF_loss: 0.00000\teltime: 25.97354\n", - "epoch: 15600\ttrain_HF_loss: 0.00000\teltime: 26.12965\n", - "epoch: 15700\ttrain_HF_loss: 0.00000\teltime: 26.31680\n", - "epoch: 15800\ttrain_HF_loss: 0.00000\teltime: 26.48590\n", - "epoch: 15900\ttrain_HF_loss: 0.00000\teltime: 26.65200\n", - "epoch: 16000\ttrain_HF_loss: 0.00000\teltime: 26.83328\n", - "epoch: 16100\ttrain_HF_loss: 0.00000\teltime: 27.00038\n", - "epoch: 16200\ttrain_HF_loss: 0.00000\teltime: 27.16980\n", - "epoch: 16300\ttrain_HF_loss: 0.00000\teltime: 27.34440\n", - "epoch: 16400\ttrain_HF_loss: 0.00000\teltime: 27.50882\n", - "epoch: 16500\ttrain_HF_loss: 0.00000\teltime: 27.68831\n", - "epoch: 16600\ttrain_HF_loss: 0.00000\teltime: 27.85227\n", - "epoch: 16700\ttrain_HF_loss: 0.00000\teltime: 28.02868\n", - "epoch: 16800\ttrain_HF_loss: 0.00000\teltime: 28.18373\n", - "epoch: 16900\ttrain_HF_loss: 0.00000\teltime: 28.36474\n", - "epoch: 17000\ttrain_HF_loss: 0.00000\teltime: 28.52010\n", - "epoch: 17100\ttrain_HF_loss: 0.00000\teltime: 28.69638\n", - "epoch: 17200\ttrain_HF_loss: 0.00000\teltime: 28.85627\n", - "epoch: 17300\ttrain_HF_loss: 0.00000\teltime: 29.02591\n", - "epoch: 17400\ttrain_HF_loss: 0.00000\teltime: 29.18715\n", - "epoch: 17500\ttrain_HF_loss: 0.00000\teltime: 29.35103\n", - "epoch: 17600\ttrain_HF_loss: 0.00000\teltime: 29.51298\n", - "epoch: 17700\ttrain_HF_loss: 0.00000\teltime: 29.68411\n", - "epoch: 17800\ttrain_HF_loss: 0.00000\teltime: 29.85166\n", - "epoch: 17900\ttrain_HF_loss: 0.00000\teltime: 30.01409\n", - "epoch: 18000\ttrain_HF_loss: 0.00001\teltime: 30.18576\n", - "epoch: 18100\ttrain_HF_loss: 0.00000\teltime: 30.35149\n", - "epoch: 18200\ttrain_HF_loss: 0.00004\teltime: 30.52633\n", - "epoch: 18300\ttrain_HF_loss: 0.00000\teltime: 30.68439\n", - "epoch: 18400\ttrain_HF_loss: 0.00000\teltime: 30.86006\n", - "epoch: 18500\ttrain_HF_loss: 0.00000\teltime: 31.03315\n", - "epoch: 18600\ttrain_HF_loss: 0.00000\teltime: 31.23712\n", - "epoch: 18700\ttrain_HF_loss: 0.00000\teltime: 31.42047\n", - "epoch: 18800\ttrain_HF_loss: 0.00000\teltime: 31.57658\n", - "epoch: 18900\ttrain_HF_loss: 0.00000\teltime: 31.75771\n", - "epoch: 19000\ttrain_HF_loss: 0.00000\teltime: 31.92166\n", - "epoch: 19100\ttrain_HF_loss: 0.00012\teltime: 32.09438\n", - "epoch: 19200\ttrain_HF_loss: 0.00000\teltime: 32.25546\n", - "epoch: 19300\ttrain_HF_loss: 0.00000\teltime: 32.43944\n", - "epoch: 19400\ttrain_HF_loss: 0.00000\teltime: 32.59608\n", - "epoch: 19500\ttrain_HF_loss: 0.00014\teltime: 32.76947\n", - "epoch: 19600\ttrain_HF_loss: 0.00000\teltime: 32.93512\n", - "epoch: 19700\ttrain_HF_loss: 0.00000\teltime: 33.10188\n", - "epoch: 19800\ttrain_HF_loss: 0.00000\teltime: 33.25940\n", - "epoch: 19900\ttrain_HF_loss: 0.00000\teltime: 33.42611\n" + "epoch: 0\ttrain_H_loss: 0.50882\teltime: 0.00930\n", + "epoch: 2000\ttrain_H_loss: 0.01870\teltime: 3.63984\n", + "epoch: 4000\ttrain_H_loss: 0.00249\teltime: 7.14588\n", + "epoch: 6000\ttrain_H_loss: 0.00095\teltime: 10.51406\n", + "epoch: 8000\ttrain_H_loss: 0.00089\teltime: 13.85415\n", + "epoch: 10000\ttrain_H_loss: 0.00056\teltime: 17.26906\n", + "epoch: 12000\ttrain_H_loss: 0.00027\teltime: 20.61776\n", + "epoch: 14000\ttrain_H_loss: 0.00035\teltime: 23.99374\n", + "epoch: 16000\ttrain_H_loss: 0.00022\teltime: 27.38162\n", + "epoch: 18000\ttrain_H_loss: 0.00024\teltime: 30.81050\n" ] } ], "source": [ + "# Construct the MF optimization problem\n", + "problem_M = Problem(nodes=[kan_wrapper_M], loss=loss_M, grad_inference=True)\n", + "\n", "# Create trainer for MF model\n", - "num_epochs_mf = 20000\n", - "epoch_verbose_mf = 100\n", - "logger_MF = LossLogger(args=None, savedir='test_HF', verbosity=epoch_verbose_mf, stdout=['train_HF_loss'])\n", - "\n", - "\n", - "trainer_MF = Trainer(\n", - " problem_MF.to(device),\n", - " train_data=train_loader_HF,\n", - " dev_data=train_loader_HF,\n", - " optimizer=torch.optim.Adam(problem_MF.parameters(), lr=init_lr),\n", - " epoch_verbose=epoch_verbose_mf,\n", - " logger=logger_MF,\n", - " epochs=num_epochs_mf,\n", - " train_metric='train_HF_loss',\n", - " eval_metric='train_HF_loss',\n", - " dev_metric='train_HF_loss',\n", - " warmup=num_epochs_mf,\n", + "num_epochs_M = 20000\n", + "epoch_verbose_M = 2000\n", + "logger_M = LossLogger(args=None, savedir='test_H', verbosity=epoch_verbose_M, stdout=['train_H_loss'])\n", + "\n", + "\n", + "trainer_M = Trainer(\n", + " problem_M.to(device),\n", + " train_data=train_loader_H,\n", + " dev_data=train_loader_H,\n", + " optimizer=torch.optim.Adam(problem_M.parameters(), lr=init_lr),\n", + " epoch_verbose=epoch_verbose_M,\n", + " logger=logger_M,\n", + " epochs=num_epochs_M,\n", + " train_metric='train_H_loss',\n", + " eval_metric='train_H_loss',\n", + " dev_metric='train_H_loss',\n", + " warmup=num_epochs_M,\n", + " multi_fidelity=True,\n", " device=device\n", ")\n", "\n", "# Train MF model\n", - "best_model_MF = trainer_MF.train()\n", - "problem_MF.load_state_dict(best_model_MF)\n", - "trained_model_MF = problem_MF.nodes[0]\n" + "best_model_M = trainer_M.train()\n", + "problem_M.load_state_dict(best_model_M)\n", + "trained_model_M = problem_M.nodes[0]\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Print $\\alpha$ to verify\n", + "\n", + "The value of $\\alpha$, initially set as 0.1, changed during training. It should, however, remain small, as the model is penalized with $\\alpha^4$ to force the method to learn the maximum linear correlation. We can verify the value of $\\alpha$ by printing its value:" ] }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -943,13 +769,13 @@ "output_type": "stream", "text": [ "alpha_0 = Parameter containing:\n", - "tensor(0.3903, requires_grad=True)\n" + "tensor(0.0167, requires_grad=True)\n" ] } ], "source": [ "# Print value of final parameter alpha\n", - "for idx,alpha in enumerate(kan_MF.alpha):\n", + "for idx,alpha in enumerate(kan_M.alpha):\n", " print(f\"alpha_{idx} = {alpha}\")\n" ] }, @@ -957,17 +783,31 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Plot results" + "### Plot results\n", + "\n", + "In this section, we compare the predictions of the three models. To recap, we have:\n", + "\n", + "- A low-fidelity model $\\mathcal{K}_L$, trained on abundant, shifted low-fidelity data, $x_L$\n", + "- A high-fidelity model $\\mathcal{K}_H$, trained on sparse, high-fidelity data, $x_H$\n", + "- A multi-fidelity model, that is trained with high-fidelity data $x_H$ and predictions of the low-fidelity model on the high-fidelity data, i.e., $\\mathcal{K}_L(x_H)$\n", + "\n", + "Figures (a) and (b) show a comparison between low and high-fidelity data and the losses versus epochs, respectively.\n", + "\n", + "Figure (c) shows the predictions of the low-fidelity model versus the low-fidelity data, demonstrating that the low-fidelity KAN was able to learn the function.\n", + "\n", + "In Figure (d), we compare the high-fidelity and multi-fidelity model predictions. The red dotted line shows that even though the high-fidelity model was able to interpolate the sparse data (green dots), it severely missed the jump at $x = 0.5$. On the other hand, the multi-fidelity model was able to capture the jump and tracked the high-fidelity data with impressive accuracy. \n", + "\n", + "**Note: the multi-fidelity model only learned from the 5 high-fidelity points plus the predictions of the low-fidelity model on these high-fidelity points to achieve that level of accuracy!**" ] }, { "cell_type": "code", - "execution_count": 30, + "execution_count": null, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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" ] @@ -978,57 +818,61 @@ ], "source": [ "# Make predictions\n", - "preds_HF = trained_model_HF(data_full.datadict)['y_hat'].cpu().detach().numpy() # high-fidelity predictions of full data\n", - "preds_LF = trained_model_LF(train_data_LF.datadict)['y_hat'].cpu().detach().numpy() # low-fidelity predictions of low-fidelity data\n", - "preds_MF = trained_model_MF(data_full.datadict)['y_hat'].cpu().detach().numpy() # multi-fidelity predictions of full data\n", + "preds_H = trained_model_H(data_full.datadict)['y_hat'].cpu().detach().numpy() # high-fidelity predictions of full data\n", + "preds_L = trained_model_L(train_data_L.datadict)['y_hat'].cpu().detach().numpy() # low-fidelity predictions of low-fidelity data\n", + "preds_M = trained_model_M(data_full.datadict)['y_hat'].cpu().detach().numpy() # multi-fidelity predictions of full data\n", "\n", "# Create subplots\n", "fig, axs = plt.subplots(2, 2, figsize=(16, 8), constrained_layout=True)\n", "\n", "# Plot a): Sampled data and reference functions\n", - "axs[0, 0].scatter(x_data_LF.numpy(), y_data_LF.numpy(), c=\"#4e79a7\", label='LF data', alpha=0.8)\n", - "axs[0, 0].scatter(x_data_HF.numpy(), y_data_HF.numpy(), c=\"#59a14f\", label='HF data', alpha=0.8)\n", - "axs[0, 0].plot(x_data_LF.numpy(), yL(x_data_LF).numpy(), \"#4e79a7\", label='LF', alpha=0.8)\n", - "axs[0, 0].plot(x_data_LF.numpy(), yH(x_data_LF).numpy(), \"#59a14f\", label='HF', alpha=0.8)\n", + "axs[0, 0].scatter(x_data_L.numpy(), y_data_L.numpy(), c=\"#4e79a7\", label='LF data', alpha=0.8)\n", + "axs[0, 0].scatter(x_data_H.numpy(), y_data_H.numpy(), c=\"#59a14f\", label='HF data', alpha=0.8)\n", + "axs[0, 0].plot(x_data_L.numpy(), yL(x_data_L).numpy(), \"#4e79a7\", label='LF', alpha=0.8)\n", + "axs[0, 0].plot(x_data_L.numpy(), yH(x_data_L).numpy(), \"#59a14f\", label='HF', alpha=0.8)\n", "axs[0, 0].set_xlim(0,1)\n", "axs[0, 0].set_xlabel('x', fontsize=14)\n", "axs[0, 0].set_ylabel('f(x)', fontsize=14)\n", "axs[0, 0].legend(fontsize=10)\n", + "axs[0, 0].set_title('(a)', loc='left', fontweight='bold')\n", "\n", "# Plot b): Evolution of losses vs epochs\n", - "losses_LF = trainer_LF.logger.get_losses()\n", - "losses_HF = trainer_HF.logger.get_losses()\n", - "losses_MF = trainer_MF.logger.get_losses()\n", - "epoch_losses_LF = range(1, len(losses_LF['train'])*epoch_verbose_lf+1, epoch_verbose_lf)\n", - "epoch_losses_HF = range(1, len(losses_HF['train'])*epoch_verbose_hf+1, epoch_verbose_hf)\n", - "epoch_losses_MF = range(1, len(losses_MF['train'])*epoch_verbose_mf+1, epoch_verbose_mf)\n", - "\n", - "axs[0, 1].plot(epoch_losses_LF,losses_LF['train'], label='LF', color='#59a14f')\n", - "axs[0, 1].plot(epoch_losses_HF,losses_HF['train'], label='HF', linestyle='dotted', color='#4e79a7')\n", - "axs[0, 1].plot(epoch_losses_MF,losses_MF['train'], label='MF', color='#e15759') \n", + "losses_L = trainer_L.logger.get_losses()\n", + "losses_H = trainer_H.logger.get_losses()\n", + "losses_M = trainer_M.logger.get_losses()\n", + "epoch_losses_L = range(1, len(losses_L['train'])*epoch_verbose_L+1, epoch_verbose_L)\n", + "epoch_losses_H = range(1, len(losses_H['train'])*epoch_verbose_H+1, epoch_verbose_H)\n", + "epoch_losses_M = range(1, len(losses_M['train'])*epoch_verbose_M+1, epoch_verbose_M)\n", + "\n", + "axs[0, 1].plot(epoch_losses_L,losses_L['train'], label='LF', color='#59a14f')\n", + "axs[0, 1].plot(epoch_losses_H,losses_H['train'], label='HF', linestyle='dotted', color='#4e79a7')\n", + "axs[0, 1].plot(epoch_losses_M,losses_M['train'], label='MF', color='#e15759') \n", "axs[0, 1].set_xlabel('Epochs', fontsize=14)\n", "axs[0, 1].set_ylabel('Loss', fontsize=14)\n", "axs[0, 1].set_yscale('log')\n", "axs[0, 1].set_ylim(1e-16)\n", "axs[0, 1].legend(fontsize=10)\n", + "axs[0, 1].set_title('(b)', loc='left', fontweight='bold')\n", "\n", "# Plot c): LF predictions vs reference data\n", - "axs[1, 0].plot(x_data_LF.numpy(), yL(x_data_LF).numpy(), '#4e79a7', label='LF ref.', alpha=0.9)\n", - "axs[1, 0].plot(x_data_LF.numpy(), preds_LF, 'k--', label='LF pred.', linewidth=2)\n", + "axs[1, 0].plot(x_data_L.numpy(), yL(x_data_L).numpy(), '#4e79a7', label='LF ref.', alpha=0.9)\n", + "axs[1, 0].plot(x_data_L.numpy(), preds_L, 'k--', label='LF pred.', linewidth=2)\n", "axs[1, 0].set_xlim(0,1)\n", "axs[1, 0].set_xlabel('x', fontsize=14)\n", "axs[1, 0].set_ylabel('f(x)', fontsize=14)\n", "axs[1, 0].legend(fontsize=10)\n", + "axs[1, 0].set_title('(c)', loc='left', fontweight='bold')\n", "\n", "# Plot d): MF vs HF predictions and reference\n", - "axs[1,1].scatter(x_data_HF.numpy(), y_data_HF.numpy(), c=\"#59a14f\", label='HF data', alpha=0.7, s=50)\n", + "axs[1,1].scatter(x_data_H.numpy(), y_data_H.numpy(), c=\"#59a14f\", label='HF data', alpha=0.7, s=50)\n", "axs[1,1].plot(x_data_full.numpy(), y_data_full.numpy(), '#59a14f', label='HF ref.', alpha=0.8, linewidth=2) # HF ref.\n", - "axs[1,1].plot(x_data_full.numpy(), preds_MF, '--b', label='MF', alpha=0.8, linewidth=2) # Predictions of MF model on full data\n", - "axs[1,1].plot(x_data_full.numpy(), preds_HF, '#e15759', linestyle='dotted', label='HF only', alpha=0.8, linewidth=2) # Predictions of HF model on full data\n", + "axs[1,1].plot(x_data_full.numpy(), preds_M, '--b', label='MF', alpha=0.8, linewidth=2) # Predictions of MF model on full data\n", + "axs[1,1].plot(x_data_full.numpy(), preds_H, '#e15759', linestyle='dotted', label='HF only', alpha=0.8, linewidth=2) # Predictions of HF model on full data\n", "axs[1, 1].set_xlim(0,1)\n", "axs[1, 1].set_xlabel('x', fontsize=14)\n", "axs[1, 1].set_ylabel('f(x)', fontsize=14)\n", "axs[1, 1].legend(fontsize=10)\n", + "axs[1, 1].set_title('(d)', loc='left', fontweight='bold')\n", "\n", "plt.tight_layout()\n", "plt.show()\n", diff --git a/examples/figs/mfkan_diagram.png b/examples/figs/mfkan_diagram.png new file mode 100644 index 0000000000000000000000000000000000000000..d054993cab1ff54858e26b180c6f76a287bf4443 GIT binary patch literal 653157 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model.apply(_apply_fn) - class MLP(Block): """ Multi-Layer Perceptron consistent with blocks interface @@ -177,6 +176,10 @@ def block_eval(self, x): x = nlin(lin(x)) return x + + + + class KANLinear(torch.nn.Module): """ KANLinear module based on the efficient implementation of Kolmogorov-Arnold Network. @@ -389,13 +392,13 @@ def regularization_loss(self, regularize_activation=1.0, regularize_entropy=1.0) """ Approximate, memory-efficient implementation of the regularization loss. """ - l1_fake = (self.spline_weight.abs()**2).mean(-1) + l1_fake = self.spline_weight.abs().mean(-1) regularization_loss_activation = l1_fake.sum() p = l1_fake / regularization_loss_activation - #regularization_loss_entropy = -torch.sum(p * p.log()) + regularization_loss_entropy = -torch.sum(p * p.log()) return ( regularize_activation * regularization_loss_activation - #+ regularize_entropy * regularization_loss_entropy + + regularize_entropy * regularization_loss_entropy ) @@ -505,28 +508,23 @@ def __init__( self.verbose = verbose def block_eval(self, x): - if self.num_domains == 1: - for layer in self.kan_layers[0]: + def apply_layers(x, layers): + for layer in layers: x = layer(x) return x - else: - w = w_jl(x, self.num_domains) - - x_domain_outputs = torch.zeros(x.shape[0], self.num_domains, self.out_features, device=x.device) - - for i, domain_layers in enumerate(self.kan_layers): - x_domain = x - for layer in domain_layers: - x_domain = layer(x_domain) - x_domain_outputs[:, i, :] = x_domain - - x_final = torch.sum(w.unsqueeze(-1) * x_domain_outputs, dim=1) - - return x_final + # Compute outputs for all domains + domain_outputs = [apply_layers(x, domain_layers) for domain_layers in self.kan_layers] + domain_outputs = torch.stack(domain_outputs, dim=1) # Shape: [batchsize, num_domains, out_features] + if self.num_domains == 1: + x_final = domain_outputs.squeeze(1) + else: + w = window_functions(x, self.num_domains) # Shape: [batchsize, num_domains] + x_final = torch.sum(w.unsqueeze(-1) * domain_outputs, dim=1) + return x_final - def regularization_loss(self, regularize_activation=0.1, regularize_entropy=1.0): + def regularization_loss(self, regularize_activation=1.0, regularize_entropy=1.0): return sum( layer.regularization_loss(regularize_activation, regularize_entropy) for domain_layers in self.kan_layers @@ -638,7 +636,7 @@ def __init__( grid_updates=grid_updates, verbose=verbose ) - self.kan_layers.append(layers) + ) self.grid_sizes = grid_sizes self.grid_updates = grid_updates or [] @@ -1428,7 +1426,7 @@ def block_eval(self, src): "icnn": InputConvexNN, "pos_def": PosDef, "kan": KANBlock, + "multifidelity_kan": MultiFidelityKAN, "stacked_mlp": StackedMLP, "transformer": Transformer } - diff --git a/src/neuromancer/modules/functions.py b/src/neuromancer/modules/functions.py index 0124d032..1b61aebc 100644 --- a/src/neuromancer/modules/functions.py +++ b/src/neuromancer/modules/functions.py @@ -34,14 +34,13 @@ def bounds_clamp(x, xmin=None, xmax=None): return x -def w_jl(x, num_domains, delta=1.9): +def window_functions(x, num_domains, delta=1.9): """ Window functions for finite-basis domain decomposition. - :param: x: domain coordinates. - :param: num_domains: number of domains. Must be a magic square number. - :param: delta: overlapping ratio between window functions. - :return w: partition of unit window functions. - + :param x: input tensor representing the domain. + :param num_domains: number of domains. Must be a perfect square. + :param delta: overlapping ratio. Higher = more overlapping. + :return w/(s+eps): weighted window functions. """ eps = 1e-12 # Small epsilon to prevent division by zero @@ -78,6 +77,7 @@ def w_jl_i(x_i, n_domains, x_min, x_max): s = torch.sum(w, dim=1, keepdim=True) return w / (s + eps) + functions = { "bounds_scaling": bounds_scaling, "bounds_clamp": bounds_clamp, @@ -103,4 +103,4 @@ def w_jl_i(x_i, n_domains, x_min, x_max): print(torch.all(out_scale['x_new'] <= data['xmax'])) print(torch.all(out_scale['x_new'] >= data['xmin'])) print(torch.all(out_clamp['x_new'] <= data['xmax'])) - print(torch.all(out_clamp['x_new'] >= data['xmin'])) + print(torch.all(out_clamp['x_new'] >= data['xmin'])) \ No newline at end of file From 320dd825161c91441b83d5a058a477a7f13680f9 Mon Sep 17 00:00:00 2001 From: Bruno Jacob Date: Tue, 3 Dec 2024 17:43:47 -0800 Subject: [PATCH 6/6] adding hyperlink to paper in KANs README --- examples/KANs/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/KANs/README.md b/examples/KANs/README.md index 2928977f..c37e881f 100644 --- a/examples/KANs/README.md +++ b/examples/KANs/README.md @@ -20,4 +20,4 @@ Based on the Kolmogorov-Arnold representation theorem, KANs offer an alternative [3] [Howard, Amanda A., et al. (2024) Finite basis Kolmogorov-Arnold networks: domain decomposition for data-diven and physics-informed problems.](https://arxiv.org/abs/2406.19662) -[4] Howard, Amanda A., et al. (2024) Multi-fidelity Kolmogorov-Arnold networks. +[4] [Howard, Amanda A., et al. (2024) Multifidelity Kolmogorov-Arnold networks.](https://arxiv.org/abs/2410.14764)