{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# VBLL Regression" ] }, { "cell_type": "markdown", "metadata": { "id": "3BKVRl4Y3irE" }, "source": [ "\n", "In this notebook, we will walk through implementing a simple VBLL regression model. We will first set up a basic training loop on toy data, and show the model changes required to train a model with a VBLL last layer. Finally, we will show how VBLL models can be combined with other uncertainty quantification ideas." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "collapsed": true, "id": "Z7o5usagD8H3", "outputId": "f3cbd47d-bfff-4a93-ab55-8d7a56d05c75" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Collecting vbll\n", " Downloading vbll-0.1.3-py3-none-any.whl (7.2 kB)\n", "Requirement already satisfied: numpy>=1.21.0 in /usr/local/lib/python3.10/dist-packages (from vbll) (1.25.2)\n", "Requirement already satisfied: torch>=1.6.0 in /usr/local/lib/python3.10/dist-packages (from vbll) (2.2.1+cu121)\n", "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch>=1.6.0->vbll) (3.13.4)\n", "Requirement already satisfied: typing-extensions>=4.8.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.6.0->vbll) (4.11.0)\n", "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.6.0->vbll) (1.12)\n", "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.6.0->vbll) (3.3)\n", "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.6.0->vbll) (3.1.3)\n", "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from torch>=1.6.0->vbll) (2023.6.0)\n", "Collecting nvidia-cuda-nvrtc-cu12==12.1.105 (from torch>=1.6.0->vbll)\n", " Using cached nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (23.7 MB)\n", "Collecting nvidia-cuda-runtime-cu12==12.1.105 (from torch>=1.6.0->vbll)\n", " Using cached nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (823 kB)\n", "Collecting nvidia-cuda-cupti-cu12==12.1.105 (from torch>=1.6.0->vbll)\n", " Using cached nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (14.1 MB)\n", "Collecting nvidia-cudnn-cu12==8.9.2.26 (from torch>=1.6.0->vbll)\n", " Using cached nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl (731.7 MB)\n", "Collecting nvidia-cublas-cu12==12.1.3.1 (from torch>=1.6.0->vbll)\n", " Using cached nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl (410.6 MB)\n", "Collecting nvidia-cufft-cu12==11.0.2.54 (from torch>=1.6.0->vbll)\n", " Using cached nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl (121.6 MB)\n", "Collecting nvidia-curand-cu12==10.3.2.106 (from torch>=1.6.0->vbll)\n", " Using cached nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl (56.5 MB)\n", "Collecting nvidia-cusolver-cu12==11.4.5.107 (from torch>=1.6.0->vbll)\n", " Using cached nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl (124.2 MB)\n", "Collecting nvidia-cusparse-cu12==12.1.0.106 (from torch>=1.6.0->vbll)\n", " Using cached nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl (196.0 MB)\n", "Collecting nvidia-nccl-cu12==2.19.3 (from torch>=1.6.0->vbll)\n", " Using cached nvidia_nccl_cu12-2.19.3-py3-none-manylinux1_x86_64.whl (166.0 MB)\n", "Collecting nvidia-nvtx-cu12==12.1.105 (from torch>=1.6.0->vbll)\n", " Using cached nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (99 kB)\n", "Requirement already satisfied: triton==2.2.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.6.0->vbll) (2.2.0)\n", "Collecting nvidia-nvjitlink-cu12 (from nvidia-cusolver-cu12==11.4.5.107->torch>=1.6.0->vbll)\n", " Using cached nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl (21.1 MB)\n", "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=1.6.0->vbll) (2.1.5)\n", "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.6.0->vbll) (1.3.0)\n", "Installing collected packages: nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12, vbll\n", "Successfully installed nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.19.3 nvidia-nvjitlink-cu12-12.4.127 nvidia-nvtx-cu12-12.1.105 vbll-0.1.3\n" ] } ], "source": [ "# Install vbll\n", "!pip install vbll\n", "import vbll\n", "\n", "# Import necessary packages\n", "import torch\n", "import torch.nn as nn\n", "import numpy as np\n", "from dataclasses import dataclass\n", "from torch.utils.data import Dataset, DataLoader\n", "import matplotlib.pyplot as plt\n", "from copy import deepcopy" ] }, { "cell_type": "markdown", "metadata": { "id": "GWmK6jzk4ZYe" }, "source": [ "First, we will define and visualize a simple dataset." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 435 }, "id": "j9xMB4gVEuT6", "outputId": "fe32a41e-d29b-491f-9138-9da0cdb72ca7" }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "class SimpleFnDataset(Dataset):\n", " \"\"\"The simple function used in DUE/SNGP 1-d regression experiments.\n", " Based on the implementation presented in:\n", " https://github.com/y0ast/DUE/blob/main/toy_regression.ipynb\n", " \"\"\"\n", "\n", " def __init__(self, num_samples):\n", " self.num_samples = int(num_samples)\n", " self.X, self.Y = self.get_data()\n", "\n", " def get_data(self, noise=0.05, seed=2):\n", " np.random.seed(seed)\n", "\n", " W = np.random.randn(30, 1)\n", " b = np.random.rand(30, 1) * 2 * np.pi\n", "\n", " x = 5 * np.sign(np.random.randn(self.num_samples)) + np.random.randn(self.num_samples).clip(-2, 2)\n", " y = np.cos(W * x + b).sum(0)/5. + noise * np.random.randn(self.num_samples)\n", " return torch.tensor(x[..., None]).float()/10, torch.tensor(y[..., None]).float()\n", "\n", " def __len__(self):\n", " return self.num_samples\n", "\n", " def __getitem__(self, idx):\n", " return self.X[idx], self.Y[idx]\n", "\n", "def viz_data(dataset):\n", " plt.scatter(dataset.X, dataset.Y, color = 'k')\n", " plt.axis([-1.5, 1.5, -2, 2])\n", " plt.show()\n", "\n", "dataset = SimpleFnDataset(num_samples=128)\n", "\n", "viz_data(dataset)" ] }, { "cell_type": "markdown", "metadata": { "id": "pfXxCixq5SDo" }, "source": [ "We will start by defining a simple MLP with a standard last layer and loss function. We will also write a viz function to plot model predictions, and a standard training loop." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "id": "Ylf6Iq1rC_WA" }, "outputs": [], "source": [ "class MLP(nn.Module):\n", " \"\"\"\n", " A standard MLP regression model.\n", "\n", " cfg: a config containing model parameters.\n", " \"\"\"\n", " def __init__(self, cfg):\n", " super(MLP, self).__init__()\n", "\n", " # define model layers\n", " self.params = nn.ModuleDict({\n", " 'in_layer': nn.Linear(cfg.IN_FEATURES, cfg.HIDDEN_FEATURES),\n", " 'core': nn.ModuleList([nn.Linear(cfg.HIDDEN_FEATURES, cfg.HIDDEN_FEATURES) for i in range(cfg.NUM_LAYERS)]),\n", " 'out_layer': nn.Linear(cfg.HIDDEN_FEATURES, cfg.OUT_FEATURES)\n", " })\n", "\n", " # ELU activations are an arbitrary choice\n", " self.activations = nn.ModuleList([nn.ELU() for i in range(cfg.NUM_LAYERS)])\n", " self.cfg = cfg\n", "\n", " def forward(self, x):\n", " x = self.params['in_layer'](x)\n", "\n", " for layer, ac in zip(self.params['core'], self.activations):\n", " x = ac(layer(x))\n", "\n", " return self.params['out_layer'](x)\n", "\n", "def viz_model(model, dataloader, title=None):\n", " \"\"\"Visualize prediction of standard regression model.\"\"\"\n", " model.eval()\n", " X = torch.linspace(-1.5, 1.5, 1000)[..., None]\n", " Y_pred = model(X)\n", "\n", " plt.plot(X.detach().numpy(), Y_pred.detach().numpy())\n", " plt.scatter(dataloader.dataset.X, dataloader.dataset.Y, color='k')\n", " plt.axis([-1.5, 1.5, -2, 2])\n", " if not title == None:\n", " plt.title(title)\n", "\n", " plt.show()\n", "\n", "def train(dataloader, model, train_cfg, verbose = True):\n", " \"\"\"Train a standard regression model with MSE loss.\"\"\"\n", " loss_fn = nn.MSELoss()\n", "\n", " param_list = model.parameters()\n", " optimizer = train_cfg.OPT(param_list,\n", " lr=train_cfg.LR,\n", " weight_decay=train_cfg.WD)\n", "\n", " for epoch in range(train_cfg.NUM_EPOCHS + 1):\n", " model.train()\n", " running_loss = []\n", "\n", " for train_step, (x, y) in enumerate(dataloader):\n", " optimizer.zero_grad()\n", "\n", " out = model(x) # compute model output\n", " loss = loss_fn(out, y) # compute MSE loss\n", "\n", " loss.backward()\n", " optimizer.step()\n", " running_loss.append(loss.item())\n", "\n", " if epoch % train_cfg.VAL_FREQ == 0 and verbose:\n", " print('Epoch {} loss: {:.3f}'.format(epoch, np.mean(running_loss)))\n", " running_loss = []" ] }, { "cell_type": "markdown", "metadata": { "id": "B1C83ZzcHOvl" }, "source": [ "Having defined the model and the train loop, we can now specify hyperparameters and train the model." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 626 }, "id": "iL5ZW0NAGPB2", "outputId": "f536b295-8954-4c5d-90b0-8cb9be31e947" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 0 loss: 0.260\n", "Epoch 100 loss: 0.021\n", "Epoch 200 loss: 0.017\n", "Epoch 300 loss: 0.011\n", "Epoch 400 loss: 0.004\n", "Epoch 500 loss: 0.003\n", "Epoch 600 loss: 0.004\n", "Epoch 700 loss: 0.003\n", "Epoch 800 loss: 0.003\n", "Epoch 900 loss: 0.004\n", "Epoch 1000 loss: 0.002\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "class train_cfg:\n", " NUM_EPOCHS = 1000\n", " BATCH_SIZE = 32\n", " LR = 3e-3\n", " WD = 0.\n", " OPT = torch.optim.AdamW\n", " VAL_FREQ = 100\n", "\n", "class cfg:\n", " IN_FEATURES = 1\n", " HIDDEN_FEATURES = 64\n", " OUT_FEATURES = 1\n", " NUM_LAYERS = 4\n", "\n", "dataloader = DataLoader(dataset, batch_size=train_cfg.BATCH_SIZE, shuffle=True)\n", "model = MLP(cfg())\n", "train(dataloader, model, train_cfg())\n", "viz_model(model, dataloader)" ] }, { "cell_type": "markdown", "metadata": { "id": "88ywFhZCHjOQ" }, "source": [ "As can be seen above, the model has trained and makes good prediction. However, we don't know how well it predicts far from data, and we don't have any measure of the model's uncertainty. Next, we will modify the above loop to include a VBLL last layer.\n", "\n", "Notice that the only required change in the model definition is changing out_layer in the model params to a VBLLRegression layer. This layer also takes parameters:\n", "- REG_WEIGHT: the KL regularization strength. By default, this should be 1/(dataset size). This term primarily impacts the last layer _epistemic_ uncertainty.\n", "- PRIOR_SCALE: the scale of the last layer prior. This also behaves as a regularization term, and controls last layer regularization strength.\n", "- WISHART_SCALE: regularization strengthe for the noise covariance. This term impacts the estimated _aleatoric_ uncertainty." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "id": "uUmn3N68E6q6" }, "outputs": [], "source": [ "class VBLLMLP(nn.Module):\n", " \"\"\"\n", " An MLP model with a VBLL last layer.\n", "\n", " cfg: a config containing model parameters.\n", " \"\"\"\n", "\n", " def __init__(self, cfg):\n", " super(VBLLMLP, self).__init__()\n", "\n", " self.params = nn.ModuleDict({\n", " 'in_layer': nn.Linear(cfg.IN_FEATURES, cfg.HIDDEN_FEATURES),\n", " 'core': nn.ModuleList([nn.Linear(cfg.HIDDEN_FEATURES, cfg.HIDDEN_FEATURES) for i in range(cfg.NUM_LAYERS)]),\n", " 'out_layer': vbll.Regression(cfg.HIDDEN_FEATURES, cfg.OUT_FEATURES, cfg.REG_WEIGHT, prior_scale = cfg.PRIOR_SCALE, wishart_scale = cfg.WISHART_SCALE)\n", " })\n", "\n", " self.activations = nn.ModuleList([nn.ELU() for i in range(cfg.NUM_LAYERS)])\n", " self.cfg = cfg\n", "\n", " def forward(self, x):\n", " x = self.params['in_layer'](x)\n", "\n", " for layer, ac in zip(self.params['core'], self.activations):\n", " x = ac(layer(x))\n", "\n", " return self.params['out_layer'](x)\n", "\n", "def viz_vbll_model(model, dataloader, stdevs = 1., title = None):\n", " \"\"\"Visualize VBLL model predictions, including predictive uncertainty.\"\"\"\n", " model.eval()\n", " X = torch.linspace(-1.5, 1.5, 1000)[..., None]\n", " Xp = X.detach().numpy().squeeze()\n", "\n", " Y_pred = model(X).predictive\n", " Y_mean = Y_pred.mean.detach().numpy().squeeze()\n", " Y_stdev = torch.sqrt(Y_pred.covariance.squeeze()).detach().numpy()\n", "\n", " plt.plot(Xp, Y_mean)\n", " plt.fill_between(Xp, Y_mean - stdevs * Y_stdev, Y_mean + stdevs * Y_stdev, alpha=0.2, color='b')\n", " plt.fill_between(Xp, Y_mean - 2 * stdevs * Y_stdev, Y_mean + 2 * stdevs * Y_stdev, alpha=0.2, color='b')\n", " plt.scatter(dataloader.dataset.X, dataloader.dataset.Y, color='k')\n", " plt.axis([-1.5, 1.5, -2, 2])\n", " if not title == None:\n", " plt.title(title)\n", "\n", " plt.show()\n", "\n" ] }, { "cell_type": "markdown", "metadata": { "id": "-ISoGJt0JZ_m" }, "source": [ "Next, we will define our train loop. This is nearly identical to the standard training loop, with a couple critical differences. First, we set weight decay on the last layer to zero. This is theoretically principled and sometimes improves performance, but is not necessary.\n", "\n", "The VBLL model returns a dataclass containing functions used for training and evaluation. In particular, this dataclass contains both the predictive distribution (which can be to, for example, visualize the model), the training loss, and the validation loss. Since the train loss consists of a lower bound on the marginal likelihood, the train loss and the validation loss _are not the same_.\n", "\n", "Finally, we include gradient clipping in this train loop. It is strongly recommended that you use gradient clipping with VBLL models. Optimizing covariances can be less numerically stable than standard models, but gradient clipping effectively stabilizes training." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "id": "qw1GvCtsE8qv" }, "outputs": [], "source": [ "def train_vbll(dataloader, model, train_cfg, verbose = True):\n", " \"\"\"Train a VBLL model.\"\"\"\n", "\n", " # We explicitly list the model parameters and set last layer weight decay to 0\n", " # This isn't critical but can help performance.\n", " param_list = [\n", " {'params': model.params.in_layer.parameters(), 'weight_decay': train_cfg.WD},\n", " {'params': model.params.core.parameters(), 'weight_decay': train_cfg.WD},\n", " {'params': model.params.out_layer.parameters(), 'weight_decay': 0.}\n", " ]\n", "\n", " optimizer = train_cfg.OPT(param_list,\n", " lr=train_cfg.LR,\n", " weight_decay=train_cfg.WD)\n", "\n", " for epoch in range(train_cfg.NUM_EPOCHS + 1):\n", " model.train()\n", " running_loss = []\n", "\n", " for train_step, (x, y) in enumerate(dataloader):\n", " optimizer.zero_grad()\n", " out = model(x)\n", " loss = out.train_loss_fn(y) # note we use the output of the VBLL layer for the loss\n", "\n", " loss.backward()\n", " torch.nn.utils.clip_grad_norm_(model.parameters(), train_cfg.CLIP_VAL)\n", " optimizer.step()\n", " running_loss.append(loss.item())\n", "\n", " if epoch % train_cfg.VAL_FREQ == 0 and verbose:\n", " print('Epoch: {:4d}, loss: {:10.4f}'.format(epoch, np.mean(running_loss)))\n", " running_loss = []" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 626 }, "id": "_j1hEQjwE_I2", "outputId": "9e273f7c-ef1e-448f-eb38-a415502fdc0f" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch: 0, loss: 9.0380\n", "Epoch: 100, loss: 1.1825\n", "Epoch: 200, loss: 0.8222\n", "Epoch: 300, loss: 0.5296\n", "Epoch: 400, loss: 0.3261\n", "Epoch: 500, loss: 0.2124\n", "Epoch: 600, loss: 0.0471\n", "Epoch: 700, loss: -0.1281\n", "Epoch: 800, loss: -0.3459\n", "Epoch: 900, loss: -0.4347\n", "Epoch: 1000, loss: -0.5648\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "class train_cfg:\n", " NUM_EPOCHS = 1000\n", " BATCH_SIZE = 32\n", " LR = 1e-3\n", " WD = 1e-4\n", " OPT = torch.optim.AdamW\n", " CLIP_VAL = 1\n", " VAL_FREQ = 100\n", "\n", "class cfg:\n", " IN_FEATURES = 1\n", " HIDDEN_FEATURES = 64\n", " OUT_FEATURES = 1\n", " NUM_LAYERS = 4\n", " REG_WEIGHT = 1./dataset.__len__()\n", " PARAM = 'dense'\n", " PRIOR_SCALE = 1.\n", " WISHART_SCALE = .1\n", "\n", "vbll_model = VBLLMLP(cfg())\n", "train_vbll(dataloader, vbll_model, train_cfg())\n", "viz_vbll_model(vbll_model, dataloader)" ] }, { "cell_type": "markdown", "metadata": { "id": "D-9WRDUdKstm" }, "source": [ "Above, we visualize the trained VBLL models. You can see that we effectively represent uncertainty far from the data.\n", "\n", "What if the uncertainty doesn't match our expectations or goals? There are several ways to control uncertainty within VBLL models. The simplest and most effective method to control the scale of uncertainty that we have found is modifying the KL regularization weight, REG_WEIGHT. We can train a different VBLL model with a larger REG_WEIGHT:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 887 }, "id": "1F6WImFtRRll", "outputId": "71775e7c-b735-4d79-b80b-01036faca866" }, "outputs": [ { "data": { "image/png": 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", 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "new_cfg = deepcopy(cfg())\n", "new_cfg.REG_WEIGHT *= 10\n", "\n", "vbll_model = VBLLMLP(new_cfg)\n", "train_vbll(dataloader, vbll_model, train_cfg(), verbose = False)\n", "viz_vbll_model(vbll_model, dataloader, title='10x KL penalty')\n", "\n", "new_cfg = deepcopy(cfg())\n", "new_cfg.REG_WEIGHT *= 50\n", "\n", "vbll_model = VBLLMLP(new_cfg)\n", "train_vbll(dataloader, vbll_model, train_cfg(), verbose = False)\n", "viz_vbll_model(vbll_model, dataloader, title='50x KL penalty')" ] }, { "cell_type": "markdown", "metadata": { "id": "dOUWXc9HLI0T" }, "source": [ "We can pair VBLL last layers with other forms of uncertainty quantification. Effective methods include Bayesian feature learning via Bayes-by-backprop, dropout, or ensembles. One simple strategy it to control the features used in Bayesian regression. We build upon SNGP (Liu et al., JMLR 2022). In particular, we add three modifications:\n", "- A residual structure, in which layers are additive on a residual connection\n", "- Spectral normalization of layers\n", "- Random Fourier features as a last nonlinearity.\n", "\n", "In SNGP, the authors use an ad-hoc method for computing the last layer covariance. Here, we can combine the SNGP feature structure with VBLL last layer learning." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 626 }, "id": "7ikd-MWmtJf0", "outputId": "9a2439f6-2402-4f23-fea7-aa768eadffeb" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch: 0, loss: 4.5267\n", "Epoch: 100, loss: 1.2557\n", "Epoch: 200, loss: 0.5975\n", "Epoch: 300, loss: -0.0657\n", "Epoch: 400, loss: -0.0670\n", "Epoch: 500, loss: -0.3947\n", "Epoch: 600, loss: -0.3022\n", "Epoch: 700, loss: -0.4313\n", "Epoch: 800, loss: -0.5919\n", "Epoch: 900, loss: -0.5676\n", "Epoch: 1000, loss: -0.4588\n" ] }, { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from torch.nn.utils.parametrizations import spectral_norm\n", "class SNVResMLP(nn.Module):\n", " def __init__(self, cfg):\n", " super(SNVResMLP, self).__init__()\n", " self.cfg = cfg\n", " self.params = nn.ModuleDict({\n", " 'in_layer': nn.Linear(cfg.IN_FEATURES, cfg.HIDDEN_FEATURES),\n", " 'core': nn.ModuleList([spectral_norm(nn.Linear(cfg.HIDDEN_FEATURES, cfg.HIDDEN_FEATURES)) for i in range(cfg.NUM_LAYERS)]),\n", " 'out_layer': vbll.Regression(cfg.RFF_FEATURES, cfg.OUT_FEATURES, cfg.REG_WEIGHT, prior_scale = cfg.PRIOR_SCALE, wishart_scale = cfg.WISHART_SCALE)\n", " })\n", "\n", " self.activations = nn.ModuleList([nn.ELU() for i in range(cfg.NUM_LAYERS-1)])\n", " self.W = torch.normal(torch.zeros(cfg.RFF_FEATURES, cfg.HIDDEN_FEATURES), cfg.KERNEL_SCALE * torch.ones(cfg.RFF_FEATURES, cfg.HIDDEN_FEATURES))\n", " self.b = torch.rand(cfg.RFF_FEATURES)*2*torch.pi\n", "\n", " def forward(self, x):\n", " x = self.params['in_layer'](x)\n", " for layer, ac in zip(self.params['core'], self.activations):\n", " x = ac(layer(x)) + x\n", "\n", " x = torch.cos((self.W @ x[..., None]).squeeze(-1) + self.b)\n", " x = x * np.sqrt(2./self.cfg.RFF_FEATURES) * (self.cfg.KERNEL_SCALE)\n", "\n", " return self.params['out_layer'](x)\n", "\n", "class train_cfg:\n", " NUM_EPOCHS = 1000\n", " BATCH_SIZE = 32\n", " LR = 3e-3\n", " WD = 0.\n", " OPT = torch.optim.AdamW\n", " CLIP_VAL = 1\n", " VAL_FREQ = 100\n", "\n", "class cfg:\n", " IN_FEATURES = 1\n", " HIDDEN_FEATURES = 64\n", " RFF_FEATURES = 128\n", " OUT_FEATURES = 1\n", " DROPOUT_RATE = 0.0\n", " NUM_LAYERS = 4\n", " REG_WEIGHT = 1./dataset.__len__()\n", " PRIOR_SCALE = 1.\n", " WISHART_SCALE = .1\n", " KERNEL_SCALE = .5\n", "\n", "dataloader = DataLoader(dataset, batch_size=train_cfg.BATCH_SIZE, shuffle=True)\n", "snv_model = SNVResMLP(cfg())\n", "train_vbll(dataloader, snv_model, train_cfg())\n", "viz_vbll_model(snv_model, dataloader)" ] } ], "metadata": { "colab": { "provenance": [] }, "kernelspec": { "display_name": "Python 3", "name": "python3" }, "language_info": { "name": "python" } }, "nbformat": 4, "nbformat_minor": 0 }