FGM-script.ipynb

{"cells":[{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":17741,"status":"ok","timestamp":1713794306696,"user":{"displayName":"Matina Mahdizadeh Sani","userId":"11802686618008573471"},"user_tz":240},"id":"_lt6QVPzzNSO","outputId":"f2625d22-53ce-43ce-c231-89e4e3cd2ef3"},"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive\n"]}],"source":["from google.colab import drive\n","drive.mount('/content/drive')"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"FL8xJdGT0SrN"},"outputs":[],"source":["import sys\n","sys.path.append('/content/drive/MyDrive/stat940project')"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"8oTVbMZ20yeb"},"outputs":[],"source":["%load_ext autoreload\n","%autoreload 2"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"J__g1f5O00ai"},"outputs":[],"source":["%reload_ext autoreload"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"yPWJVTi_zXoC"},"outputs":[],"source":["import torch\n","import torch.nn as nn\n","import torch.nn.functional as F\n","from torchvision import transforms\n","from torch.utils.data import DataLoader, Dataset\n","import os\n","import numpy as np\n","import random\n","import math\n","import torch.optim as optim\n","from tqdm.auto import tqdm, trange"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"t3Wl4NvE03XU"},"outputs":[],"source":["from dataset import load_data, save_data, load_targets, AdversarialDataset, load_adv_data\n","from utils.augmentations import *\n","from utils.utils import run, set_seed, pcshow\n","from models import Pointnet, DGCNN\n","from attacks import FGM, IFGM"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"VshOd57t1alr"},"outputs":[],"source":["set_seed(1)"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"Dmam3Wu2lybS"},"outputs":[],"source":["parent_dir = '/content/drive/MyDrive/stat940project'\n","data_path = os.path.join(parent_dir, 'data/ModelNet40')"]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":4674,"status":"ok","timestamp":1713794376892,"user":{"displayName":"Matina Mahdizadeh Sani","userId":"11802686618008573471"},"user_tz":240},"id":"hmh4IdAtnq_J","colab":{"base_uri":"https://localhost:8080/"},"outputId":"38d627ef-e7b7-43b2-f1d4-1bb7b468cf3b"},"outputs":[{"output_type":"stream","name":"stdout","text":["running on GPU\n"]}],"source":["if torch.cuda.is_available():\n","    device = torch.device('cuda:0')\n","    print('running on GPU')\n","\n","else:\n","    device = torch.device('cpu')\n","    print('running on CPU')\n","\n","test_X, test_y = load_data(data_path, mode='test')\n","test_targets = load_targets(data_path)\n","\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"o6daeqjrnxBk"},"outputs":[],"source":["default_transforms = transforms.Compose(\n","    [\n","        ToTensor()\n","    ]\n",")"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"FHVayGE9oKHP"},"outputs":[],"source":["testset = AdversarialDataset(test_X, test_y, test_targets, transforms=default_transforms)\n","testloader = DataLoader(testset, batch_size=64, shuffle=False)"]},{"cell_type":"code","source":["def run(targeted, file_name, output_path, model_name, signed = False):\n","      if model_name == \"pointnet\":\n","          model = Pointnet(device=device).to(device)\n","      else:\n","          model = DGCNN().to(device)\n","      checkpoint_path = os.path.join(parent_dir, f'checkpoints/{model_name}/best.pt')\n","      model.load_state_dict(torch.load(checkpoint_path, map_location=device)[\"model_state_dict\"])\n","      model.eval()\n","\n","      all_adv_pc = []\n","      all_gt_labels = []\n","      all_target_labels = []\n","      all_success = 0\n","\n","      attacker = FGM(model, epsilon=0.2)\n","\n","      for pc, labels, targets in tqdm(testloader):\n","          with torch.no_grad():\n","              pc = pc.to(device)\n","              labels = labels.to(device)\n","              targets = targets.to(device)\n","\n","          if targeted:\n","              adv_pc, success_num = attacker.attack(pc, targets, device, targeted=targeted)\n","          else:\n","              adv_pc, success_num = attacker.attack(pc, labels, device, targeted=targeted)\n","\n","          all_adv_pc += [adv_pc]\n","          all_gt_labels += [labels.detach().cpu().numpy()]\n","          all_target_labels += [targets.detach().cpu().numpy()]\n","          all_success += success_num\n","          print()\n","\n","      print(f\"Success Rate: {all_success / len(test_X)}\")\n","\n","\n","      all_adv_pc = np.concatenate(all_adv_pc, axis=0)\n","      all_gt_labels = np.concatenate(all_gt_labels, axis=0)\n","      all_target_labels = np.concatenate(all_target_labels, axis=0)\n","\n","\n","\n","      save_data(all_adv_pc, file_name, output_path)\n","      save_data(all_gt_labels, 'test_labels', output_path)\n","      save_data(all_adv_pc, 'target_labels', output_path)\n","      return all_adv_pc"],"metadata":{"id":"t6bM89766mnM"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["adv_data_path = os.path.join(parent_dir, f'data/FGM/DGCNN')\n","all_adv_pc, _ , _= load_adv_data(adv_data_path, targeted=False)"],"metadata":{"id":"zQ_jOQtjGU6u"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["path = os.path.join(parent_dir, 'data/FGM/Pointnet')\n","if not os.path.exists(path):\n","    os.makedirs(path)\n","all_adv_pc = run(False, 'adv_test_untarget', path, 'pointnet', signed = False)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000,"referenced_widgets":["27d5c44a4cbb42e2b66fd026a8b8b239","408837bf2d554167bb811ca5356c37d1","5f061282254f400ead0badafa36a67ad","b58c9993d02e4cd0b2a170e4b07aa6d0","670010c83f7b49cba670cf679f195929","e27ec9a6d0654b38a307b7bb9e754241","009bf0b610e14467a0d31670322a27e1","e8dbcdedfd054e218039c82dfeb3ce56","4170c6e3b8b94906a0d98fe1ee05a419","4b18ccccaf4e4249b150c78fce4662de","2e9fbc66fdfe45de8cf68fe4891f29c1"]},"id":"fteKUcV6wVCs","executionInfo":{"status":"ok","timestamp":1713404556632,"user_tz":240,"elapsed":21046,"user":{"displayName":"Matina Mahdizadeh Sani","userId":"11802686618008573471"}},"outputId":"5e47706e-a19d-4698-a77a-7f66ab74f1ec"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["  0%|          | 0/39 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"27d5c44a4cbb42e2b66fd026a8b8b239"}},"metadata":{}},{"output_type":"stream","name":"stdout","text":["41/64 successful attacks\n","\n","35/64 successful attacks\n","\n","38/64 successful attacks\n","\n","38/64 successful attacks\n","\n","38/64 successful attacks\n","\n","40/64 successful attacks\n","\n","38/64 successful attacks\n","\n","41/64 successful attacks\n","\n","42/64 successful attacks\n","\n","38/64 successful attacks\n","\n","43/64 successful attacks\n","\n","37/64 successful attacks\n","\n","38/64 successful attacks\n","\n","34/64 successful attacks\n","\n","31/64 successful attacks\n","\n","34/64 successful attacks\n","\n","34/64 successful attacks\n","\n","34/64 successful attacks\n","\n","40/64 successful attacks\n","\n","35/64 successful attacks\n","\n","41/64 successful attacks\n","\n","40/64 successful attacks\n","\n","35/64 successful attacks\n","\n","32/64 successful 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Sani","userId":"11802686618008573471"}},"colab":{"base_uri":"https://localhost:8080/","height":1000},"outputId":"e4615668-2230-4742-e624-5d8bcf70941a"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/html":["<html>\n","<head><meta charset=\"utf-8\" /></head>\n","<body>\n","    <div>            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n","        <script charset=\"utf-8\" src=\"https://cdn.plot.ly/plotly-2.24.1.min.js\"></script>                <div id=\"a30324e2-2cfc-41dd-9302-28e7b6f57749\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">             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attacks\n","\n","1/64 successful attacks\n","\n","1/64 successful attacks\n","\n","1/64 successful attacks\n","\n","2/64 successful attacks\n","\n","2/64 successful attacks\n","\n","3/64 successful attacks\n","\n","1/64 successful attacks\n","\n","2/64 successful attacks\n","\n","3/64 successful attacks\n","\n","1/64 successful attacks\n","\n","1/64 successful attacks\n","\n","3/64 successful attacks\n","\n","1/64 successful attacks\n","\n","2/64 successful attacks\n","\n","5/64 successful attacks\n","\n","1/64 successful attacks\n","\n","2/64 successful attacks\n","\n","1/64 successful attacks\n","\n","1/64 successful attacks\n","\n","3/64 successful attacks\n","\n","1/36 successful attacks\n","\n","Success Rate: 0.0320097244732577\n"]}]},{"cell_type":"code","source":["x1, y1, z1 = all_adv_pc[2].T\n","x2, y2, z2 = test_X[2].T\n","pcshow(x1, y1, z1, color='red')\n","pcshow(x2, y2, z2, 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attacks\n","\n","17/64 successful attacks\n","\n","9/64 successful attacks\n","\n","10/64 successful attacks\n","\n","9/64 successful attacks\n","\n","11/64 successful attacks\n","\n","11/64 successful attacks\n","\n","8/64 successful attacks\n","\n","9/64 successful attacks\n","\n","19/64 successful attacks\n","\n","11/64 successful attacks\n","\n","21/64 successful attacks\n","\n","14/64 successful attacks\n","\n","19/64 successful attacks\n","\n","13/64 successful attacks\n","\n","11/64 successful attacks\n","\n","20/64 successful attacks\n","\n","7/64 successful attacks\n","\n","17/64 successful attacks\n","\n","13/64 successful attacks\n","\n","5/36 successful attacks\n","\n","Success Rate: 0.22042139384116693\n"]}]},{"cell_type":"code","source":["x1, y1, z1 = all_adv_pc[6].T\n","x2, y2, z2 = test_X[6].T\n","pcshow(x1, y1, z1, color='red')\n","pcshow(x2, y2, z2, 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attacks\n","\n","1/64 successful attacks\n","\n","0/64 successful attacks\n","\n","2/64 successful attacks\n","\n","0/64 successful attacks\n","\n","0/64 successful attacks\n","\n","0/64 successful attacks\n","\n","1/64 successful attacks\n","\n","0/64 successful attacks\n","\n","1/64 successful attacks\n","\n","1/64 successful attacks\n","\n","0/64 successful attacks\n","\n","1/64 successful attacks\n","\n","0/64 successful attacks\n","\n","0/64 successful attacks\n","\n","2/64 successful attacks\n","\n","0/64 successful attacks\n","\n","1/64 successful attacks\n","\n","0/64 successful attacks\n","\n","1/64 successful attacks\n","\n","2/64 successful attacks\n","\n","0/36 successful attacks\n","\n","Success Rate: 0.008914100486223663\n"]}]},{"cell_type":"code","source":["x1, y1, z1 = all_adv_pc[4].T\n","x2, y2, z2 = test_X[4].T\n","pcshow(x1, y1, z1, color='red')\n","pcshow(x2, y2, z2, 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