{"cells": [{"cell_type": "markdown", "metadata": {}, "source": "# Deep Active Learning for Fine-tuning Vision Transformers"}, {"cell_type": "markdown", "metadata": {}, "source": ["> **_Google Colab Note:_** If the notebook fails to run after installing the needed packages, try to restart the runtime (Ctrl + M) under Runtime -> Restart session.\n", "\n", "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/scikit-activeml/scikit-activeml.github.io/blob/gh-pages/development/generated/tutorials_colab//01_deep_pool_al_with_skorch.ipynb)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["**Notebook Dependencies**\n", "\n", "Uncomment the following cell to install all dependencies for this tutorial."]}, {"metadata": {}, "cell_type": "code", "outputs": [], "execution_count": null, "source": "# !pip install scikit-activeml[opt] torch torchvision tqdm pandas kornia transformers datasets"}, {"cell_type": "markdown", "metadata": {}, "source": ["
"]}, {"cell_type": "markdown", "metadata": {}, "source": ["In this brief tutorial, we show an example use-case of our package `skactiveml` with the Python package [skorch](https://skorch.readthedocs.io/en/stable/), which is a scikit-learn wrapper for Pytorch models. This way, we are able to implement and test deep learning models in combination with query strategies implemented in our framework."]}, {"cell_type": "code", "metadata": {"ExecuteTime": {"end_time": "2025-11-30T22:20:37.891177Z", "start_time": "2025-11-30T22:20:34.645195Z"}}, "source": ["# Comment in for speed up, if you have cuML installed.\n", "# %load_ext cuml.accel\n", "import matplotlib as mpl\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import os\n", "import torch\n", "import warnings\n", "\n", "from copy import deepcopy\n", "from datasets import load_dataset\n", "from kornia import augmentation as K\n", "from skactiveml.classifier import SkorchClassifier\n", "from skactiveml.pool import (\n", " RandomSampling,\n", " TypiClust,\n", " CoreSet,\n", " UncertaintySampling,\n", " Badge,\n", " DropQuery,\n", " SubSamplingWrapper,\n", ")\n", "from skactiveml.utils import call_func\n", "from skorch.callbacks import LRScheduler\n", "from torch import nn\n", "from torch.optim.lr_scheduler import CosineAnnealingLR\n", "from tqdm import tqdm\n", "\n", "\n", "MISSING_LABEL = -1\n", "RANDOM_STATE = 0\n", "CACHE_PATH = \".cache\"\n", "os.makedirs(CACHE_PATH, exist_ok=True)\n", "mpl.rcParams[\"figure.facecolor\"] = \"white\"\n", "np.random.seed(RANDOM_STATE)\n", "torch.manual_seed(RANDOM_STATE)\n", "torch.cuda.manual_seed(RANDOM_STATE)\n", "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n", "warnings.filterwarnings(\"ignore\")"], "outputs": [{"name": "stdout", "output_type": "stream", "text": ["cuML: Accelerator installed.\n"]}], "execution_count": 2}, {"cell_type": "markdown", "metadata": {}, "source": ["## Loading CIFAR10\n", "We rely on `HuggingFace` to download the `CIFAR10` dataset containing 32 x 32px images of generic object classes."]}, {"cell_type": "code", "metadata": {"ExecuteTime": {"end_time": "2025-11-30T22:20:46.813302Z", "start_time": "2025-11-30T22:20:37.936904Z"}}, "source": ["# Load CIFAR10 and convert to numpy.\n", "ds = load_dataset(\"cifar10\")\n", "X_train = np.array(ds[\"train\"][\"img\"], dtype=np.float32) / 255.0\n", "X_test = np.array(ds[\"test\"][\"img\"], dtype=np.float32) / 255.0\n", "X_train = np.transpose(X_train, (0, 3, 1, 2))\n", "X_test = np.transpose(X_test, (0, 3, 1, 2))\n", "y_train_true = np.array(ds[\"train\"][\"label\"], dtype=np.int64)\n", "y_test_true = np.array(ds[\"test\"][\"label\"], dtype=np.int64)\n", "classes = np.unique(y_train_true)\n", "missing_label = -1\n", "\n", "# Visualize 10 images.\n", "fig, axes = plt.subplots(1, 10, figsize=(15, 5))\n", "for j, ax in enumerate(axes):\n", " img = np.transpose(X_train[j], (1, 2, 0)) # (32, 32, 3)\n", " ax.imshow(img)\n", " ax.axis(\"off\")\n", "plt.tight_layout()\n", "plt.show()"], "outputs": [{"data": {"text/plain": ["
"], "image/png": 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"}, "metadata": {}, "output_type": "display_data", "jetTransient": {"display_id": null}}], "execution_count": 3}, {"cell_type": "markdown", "metadata": {}, "source": ["## Data Augmentation\n", "Data augmentation is used to artificially generate data from existing data points. In case of image data, this can be done by rotating or scaling the image. Other basic transformations are:\n", "* padding,\n", "* vertical and horizontal flipping,\n", "* translation,\n", "* cropping,\n", "* darkening, brightening, color modification,\n", "* grayscaling,\n", "* changing contrast,\n", "* adding noise,\n", "* random erasing.\n", "\n", "For more information on data augmentation take a look at the [Data Augmentation Tutorial](https://www.tensorflow.org/tutorials/images/data_augmentation) of [TensorFlow](https://www.tensorflow.org) or visit [Transforming And Augmenting Images](https://pytorch.org/vision/stable/transforms.html) on [PyTorch](https://pytorch.org). We define one transformation used during training and one used during evaluation."]}, {"cell_type": "code", "metadata": {"ExecuteTime": {"end_time": "2025-11-30T22:20:46.863951Z", "start_time": "2025-11-30T22:20:46.858951Z"}}, "source": ["# Transformers are designed to be used with a DINOv2 module.\n", "train_transform = K.AugmentationSequential(\n", " K.Resize((256, 256)),\n", " K.RandomResizedCrop((224, 224), scale=(0.75, 1.0)),\n", " K.RandomHorizontalFlip(p=0.5),\n", " K.ColorJitter(0.2, 0.2, 0.2, 0.1, p=0.8),\n", " K.Normalize(\n", " mean=torch.tensor([0.485, 0.456, 0.406]),\n", " std=torch.tensor([0.229, 0.224, 0.225]),\n", " ),\n", " data_keys=[\"input\"],\n", ")\n", "\n", "eval_transform = K.AugmentationSequential(\n", " K.Resize((256, 256)),\n", " K.CenterCrop((224, 224)),\n", " K.Normalize(\n", " mean=torch.tensor([0.485, 0.456, 0.406]),\n", " std=torch.tensor([0.229, 0.224, 0.225]),\n", " ),\n", " data_keys=[\"input\"],\n", ")"], "outputs": [], "execution_count": 4}, {"cell_type": "markdown", "metadata": {}, "source": ["## DINOv2: A Vision Foundation Model\n", "In the next step, we load DINOv2 ViT/S-14 as a popular vision foundation backbone as part of our classification module to be fine-tuned throughout the active learning cycles.\n", "\n", "> **Note:** There is an interdependency between the\n", "> - loss criterion (`nn.CrossEntropyLoss` in our example),\n", "> - the outputted quantities (logits in our example),\n", "> - and calling `predict_proba` to output actual probabilities (`predict_nonlinearity=nn.Softmax(dim=-1)` to normalize the logits)."]}, {"cell_type": "code", "metadata": {"ExecuteTime": {"end_time": "2025-11-30T22:20:47.635084Z", "start_time": "2025-11-30T22:20:46.902273Z"}}, "source": ["# Define simple classifier with a DINOv2 module as backbone.\n", "class DinoClassifier(nn.Module):\n", " def __init__(self, backbone, n_classes, train_tf=None, eval_tf=None):\n", " super().__init__()\n", " self.backbone = backbone\n", " self.head = nn.Linear(backbone.embed_dim, n_classes)\n", " self.train_tf = train_tf\n", " self.eval_tf = eval_tf\n", "\n", " def forward(self, x):\n", " if self.training and self.train_tf is not None:\n", " x = self.train_tf(x)\n", " if not self.training and self.eval_tf is not None:\n", " x = self.eval_tf(x)\n", " x_embed = self.backbone(x)\n", " logits = self.head(x_embed)\n", " return logits, x_embed\n", "\n", "\n", "# Method to define block-wise learning rates and weight decays.\n", "def dino_param_groups(backbone, base=0.01, decay=0.1, head_mult=1.0):\n", " L = len(getattr(backbone, \"blocks\", []))\n", " groups = [\n", " (\n", " \"backbone.patch_embed.*\",\n", " {\"lr\": base * decay ** (L + 1), \"weight_decay\": 0.0},\n", " ),\n", " (\n", " \"backbone.pos_embed\",\n", " {\"lr\": base * decay ** (L + 1), \"weight_decay\": 0.0},\n", " ),\n", " (\n", " \"backbone.cls_token\",\n", " {\"lr\": base * decay ** (L + 1), \"weight_decay\": 0.0},\n", " ),\n", " ]\n", " for i in range(L):\n", " wd = 0.0 if i >= L - 3 else 0.0 # lighter WD on last blocks\n", " groups.append(\n", " (\n", " f\"backbone.blocks.{i}.*\",\n", " {\"lr\": base * decay ** (L - i), \"weight_decay\": wd},\n", " )\n", " )\n", " groups += [\n", " (\"backbone.norm.*\", {\"lr\": base, \"weight_decay\": 0.0}),\n", " (\"head.weight\", {\"lr\": base * head_mult, \"weight_decay\": 0.0001}),\n", " (\"head.bias\", {\"lr\": base * head_mult, \"weight_decay\": 0.0}),\n", " (\"*.bias\", {\"weight_decay\": 0.0}),\n", " (\"*.norm.weight\", {\"weight_decay\": 0.0}),\n", " ]\n", " return groups\n", "\n", "\n", "# Load backbone from torch hub. Replace, if other foundations model are to be used.\n", "torch.hub.set_dir(CACHE_PATH)\n", "vit_backbone = torch.hub.load(\"facebookresearch/dinov2\", \"dinov2_vits14\")\n", "\n", "# Set optimizer parameters for the loaded backbone.\n", "param_groups = dino_param_groups(vit_backbone)\n", "\n", "clf_init = SkorchClassifier(\n", " module=DinoClassifier,\n", " criterion=nn.CrossEntropyLoss,\n", " forward_outputs={\n", " \"proba\": (0, nn.Softmax(dim=-1)), \"emb\": (1, None)\n", " },\n", " neural_net_param_dict={\n", " # Module-related parameters.\n", " \"module__backbone\": vit_backbone,\n", " \"module__n_classes\": len(classes),\n", " \"module__train_tf\": train_transform,\n", " \"module__eval_tf\": eval_transform,\n", " # Optimizer-related parameters.\n", " \"max_epochs\": 100,\n", " \"batch_size\": 128,\n", " \"optimizer\": torch.optim.RAdam,\n", " \"optimizer__param_groups\": param_groups,\n", " \"callbacks\": [\n", " (\"lr_scheduler\", LRScheduler(policy=CosineAnnealingLR, T_max=100))\n", " ],\n", " # General parameters.\n", " \"verbose\": 0,\n", " \"device\": device,\n", " \"train_split\": False,\n", " \"iterator_train__shuffle\": True,\n", " \"torch_load_kwargs\": {\"weights_only\": True},\n", " },\n", " classes=classes,\n", " missing_label=MISSING_LABEL,\n", ")"], "outputs": [{"name": "stderr", "output_type": "stream", "text": ["Using cache found in .cache/facebookresearch_dinov2_main\n"]}], "execution_count": 5}, {"cell_type": "markdown", "metadata": {}, "source": ["## Active Classification\n", "For our classifier, we evaluate six different query strategies regarding their sample selection. For this purpose, we start with zero labels and make 10 iterations of an active learning cycle with a batch size of 32.\n", "\n", "> **Note:** The execution time strongly depends on whether a GPU or CPU will be used."]}, {"cell_type": "code", "metadata": {"ExecuteTime": {"end_time": "2025-11-30T23:04:57.940890Z", "start_time": "2025-11-30T22:20:47.637453Z"}}, "source": ["# Define setup.\n", "n_cycles = 8\n", "batch_size = 25\n", "n_sub_set = 1000\n", "qs_dict = {\n", " \"RandomSampling\": RandomSampling(\n", " random_state=RANDOM_STATE, missing_label=MISSING_LABEL\n", " ),\n", " \"UncertaintySampling\": UncertaintySampling(\n", " random_state=RANDOM_STATE,\n", " missing_label=MISSING_LABEL,\n", " method=\"margin_sampling\",\n", " ),\n", " \"Badge\": Badge(\n", " clf_embedding_flag_name={\"extra_outputs\": \"emb\"},\n", " random_state=RANDOM_STATE,\n", " missing_label=MISSING_LABEL,\n", " ),\n", " \"DropQuery\": DropQuery(\n", " clf_embedding_flag_name={\"extra_outputs\": \"emb\"},\n", " random_state=RANDOM_STATE,\n", " missing_label=MISSING_LABEL,\n", " ),\n", " \"TypiClust\": TypiClust(\n", " random_state=RANDOM_STATE, missing_label=MISSING_LABEL\n", " ),\n", " \"CoreSet\": CoreSet(random_state=RANDOM_STATE, missing_label=MISSING_LABEL),\n", "}\n", "acc_dict = {key: np.zeros(n_cycles + 1) for key in qs_dict}\n", "\n", "# Perform active learning with each query strategy.\n", "for qs_name, qs in qs_dict.items():\n", " print(f\"Execute active learning using {qs_name}.\")\n", " # Set seed and copy classifier for consistent initialization.\n", " torch.manual_seed(RANDOM_STATE)\n", " torch.cuda.manual_seed(RANDOM_STATE)\n", " clf = deepcopy(clf_init)\n", "\n", " # Embedding function is not required by all query strategies.\n", " embed_samples_func = None\n", " if qs_name in [\"TypiClust\", \"CoreSet\"]:\n", "\n", " def embed_samples_func(X_to_embed):\n", " return clf.predict(X_to_embed, extra_outputs=\"emb\")[1]\n", "\n", " # Wrapper to subsample unlabeled samples.\n", " qs = SubSamplingWrapper(\n", " query_strategy=qs,\n", " max_candidates=n_sub_set,\n", " exclude_non_subsample=True,\n", " embed_samples_func=embed_samples_func,\n", " random_state=RANDOM_STATE,\n", " missing_label=MISSING_LABEL,\n", " )\n", "\n", " # Create array of missing labels as initial labels.\n", " y = np.full_like(y_train_true, fill_value=MISSING_LABEL, dtype=np.int64)\n", "\n", " # Execute active learning cycle.\n", " for c in tqdm(range(n_cycles)):\n", " # Fit and evaluate clf.\n", " acc = clf.fit(X_train, y).score(X_test, y_test_true)\n", " acc_dict[qs_name][c] = acc\n", "\n", " # Select and update training data.\n", " query_idx = call_func(\n", " qs.query,\n", " X=X_train,\n", " y=y,\n", " clf=clf,\n", " fit_clf=False,\n", " batch_size=batch_size,\n", " )\n", " y[query_idx] = y_train_true[query_idx]\n", "\n", " # Fit and evaluate clf.\n", " clf.fit(X_train, y)\n", " acc_dict[qs_name][n_cycles] = clf.score(X_test, y_test_true)"], "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Execute active learning using RandomSampling.\n"]}, {"name": "stderr", "output_type": "stream", "text": ["100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 8/8 [05:40<00:00, 42.57s/it]\n"]}, {"name": "stdout", "output_type": "stream", "text": ["Execute active learning using UncertaintySampling.\n"]}, {"name": "stderr", "output_type": "stream", "text": ["100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 8/8 [05:52<00:00, 44.09s/it]\n"]}, {"name": "stdout", "output_type": "stream", "text": ["Execute active learning using Badge.\n"]}, {"name": "stderr", "output_type": "stream", "text": ["100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 8/8 [05:53<00:00, 44.16s/it]\n"]}, {"name": "stdout", "output_type": "stream", "text": ["Execute active learning using DropQuery.\n"]}, {"name": "stderr", "output_type": "stream", "text": ["100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 8/8 [06:42<00:00, 50.28s/it]\n"]}, {"name": "stdout", "output_type": "stream", "text": ["Execute active learning using TypiClust.\n"]}, {"name": "stderr", "output_type": "stream", "text": ["100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 8/8 [05:55<00:00, 44.47s/it]\n"]}, {"name": "stdout", "output_type": "stream", "text": ["Execute active learning using CoreSet.\n"]}, {"name": "stderr", "output_type": "stream", "text": ["100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 8/8 [05:53<00:00, 44.23s/it]\n"]}], "execution_count": 6}, {"cell_type": "markdown", "metadata": {}, "source": ["## Visualize Results\n", "In the following, we plot the obtained learning curves including the area under learning curve (AULC) scores per query strategy."]}, {"cell_type": "code", "metadata": {"ExecuteTime": {"end_time": "2025-11-30T23:04:58.099937Z", "start_time": "2025-11-30T23:04:57.995171Z"}}, "source": ["cycles = np.arange(n_cycles + 1, dtype=int)\n", "plt.figure(figsize=(16, 9))\n", "for qs_name, acc in acc_dict.items():\n", " plt.plot(\n", " cycles * batch_size,\n", " acc,\n", " label=f\"{qs_name}: AULC={round(acc.mean(), 3)}\",\n", " )\n", "plt.xticks(cycles * batch_size, fontsize=\"x-large\")\n", "plt.yticks(np.arange(0.1, 1.0, 0.1), fontsize=\"x-large\")\n", "plt.grid()\n", "plt.xlabel(\"# labeled samples\", fontsize=\"x-large\")\n", "plt.ylabel(\"test accuracy\", fontsize=\"x-large\")\n", "plt.legend(loc=\"lower right\", fontsize=\"x-large\")\n", "plt.show()"], "outputs": [{"data": {"text/plain": ["
"], "image/png": 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"}, "metadata": {}, "output_type": "display_data", "jetTransient": {"display_id": null}}], "execution_count": 7}], "metadata": {"kernelspec": {"display_name": "skaml_skorch", "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": "3.11.11"}, "nbsphinx": {"orphan": true}}, "nbformat": 4, "nbformat_minor": 4}