| project_name | group_name | hostname | status | time | time_per_image_ms | acc_nat | acc_pgdlinf | acc_pgdl2 | agg | error_msg |
|---|
jean-ponce | Master-IASD | coktailjet | Success | 4372.12 | 218.61 | 100.0 | 97.97 | 99.32 | 197.29 | None | BestOf2023-1 | profs | upnquick | Success | 175.25 | 8.76 | 75.0 | 70.3 | 70.92 | 141.22 | None | noeyedeer | Master-IASD | coktailjet | Success | 2592.8 | 129.64 | 75.0 | 51.52 | 68.86 | 120.38 | None | rattataque | Master-IASD | coktailjet | Success | 2371.97 | 118.6 | 75.0 | 48.43 | 70.67 | 119.09 | None | exocet | Master-IASD | upnquick | Success | 1241.83 | 62.09 | 66.25 | 51.23 | 66.16 | 117.38 | None | BestOf2024-1 | profs | upnquick | Success | 2582.94 | 129.15 | 76.25 | 51.31 | 63.63 | 114.94 | None | BestOfMiles | profs | upnquick | Success | 5195.0 | 259.75 | 78.75 | 51.98 | 62.8 | 114.78 | None | the-taithon-canon | Master-IASD | upnquick | Success | 3510.24 | 175.51 | 62.5 | 49.11 | 65.62 | 114.73 | None | BestOf2024-2 | profs | coktailjet | Success | 1160.66 | 58.03 | 75.0 | 52.36 | 59.5 | 111.86 | None | best_defense_is_attack | Master-IASD | coktailjet | Success | 2791.12 | 139.56 | 81.25 | 50.97 | 59.25 | 110.22 | None | counter_attack | Master-IASD | upnquick | Success | 1334.56 | 66.73 | 61.25 | 46.11 | 63.13 | 109.25 | None | attackonpixels | Master-IASD | upnquick | Success | 1602.85 | 80.14 | 75.0 | 44.15 | 52.87 | 97.02 | None | neural-nightmare | Master-IASD | upnquick | Success | 1263.38 | 63.17 | 81.25 | 41.87 | 53.07 | 94.94 | None | BestOf2023-2 | profs | coktailjet | Success | 116.66 | 5.83 | 56.25 | 40.89 | 53.47 | 94.36 | None | invisible_attack | Master-IASD | upnquick | Success | 6555.28 | 327.76 | 68.75 | 31.29 | 51.97 | 83.25 | None | gradient-hackers | Master-IASD | coktailjet | Success | 135.43 | 6.77 | 50.0 | 29.16 | 34.9 | 64.06 | None | attaquedestitans | Master-IASD | upnquick | Success | 123.19 | 6.16 | 81.25 | 18.66 | 38.4 | 57.06 | None | attack_mesonet | Master-IASD | coktailjet | Success | 71.27 | 3.56 | 43.75 | 22.45 | 33.3 | 55.75 | None | attack-of-babrumen | Master-IASD | upnquick | Success | 163.46 | 8.17 | 43.75 | 13.45 | 31.39 | 44.84 | None | attackonnetworks | Master-IASD | coktailjet | Success | 77.09 | 3.85 | 43.75 | 8.69 | 28.03 | 36.72 | None | attackus | Master-IASD | coktailjet | Success | 73.7 | 3.68 | 68.75 | 6.0 | 25.15 | 31.15 | None | nyc | Master-IASD | upnquick | Success | 165.34 | 8.27 | 62.5 | 6.01 | 25.12 | 31.13 | None | base_model | profs | coktailjet | Success | 115.13 | 5.76 | 37.5 | 6.0 | 25.11 | 31.11 | None | compo-4-3-3 | Master-IASD | coktailjet | Success | 2793.26 | 139.66 | 62.5 | 7.26 | 7.32 | 14.58 | None | blast_attack | Master-IASD | coktailjet | Success | 1180.3 | 59.02 | 6.25 | 5.33 | 7.95 | 13.28 | None | attaqueoudefense | Master-IASD | coktailjet | Error | 0 | 0 | 0 | 0 | 0 | 0 | RuntimeError: Error(s) in loading state_dict for Net:
Missing key(s) in state_dict: "conv1.bias", "conv2.weight", "conv2.bias", "fc1.weight", "fc1.bias", "fc2.weight", "fc2.bias", "fc3.weight", "fc3.bias".
Unexpected key(s) in state_dict: "layer1.0.bn1.weight", "layer1.0.bn1.bias", "layer1.0.bn1.running_mean", "layer1.0.bn1.running_var", "layer1.0.bn1.num_batches_tracked", "layer1.0.conv1.weight", "layer1.0.bn2.weight", "layer1.0.bn2.bias", "layer1.0.bn2.running_mean", "layer1.0.bn2.running_var", "layer1.0.bn2.num_batches_tracked", "layer1.0.conv2.weight", "layer1.0.shortcut.weight", "layer1.1.bn1.weight", "layer1.1.bn1.bias", "layer1.1.bn1.running_mean", "layer1.1.bn1.running_var", "layer1.1.bn1.num_batches_tracked", "layer1.1.conv1.weight", "layer1.1.bn2.weight", "layer1.1.bn2.bias", "layer1.1.bn2.running_mean", "layer1.1.bn2.running_var", "layer1.1.bn2.num_batches_tracked", "layer1.1.conv2.weight", "layer2.0.bn1.weight", "layer2.0.bn1.bias", "layer2.0.bn1.running_mean", "layer2.0.bn1.running_var", "layer2.0.bn1.num_batches_tracked", "layer2.0.conv1.weight", "layer2.0.bn2.weight", "layer2.0.bn2.bias", "layer2.0.bn2.running_mean", "layer2.0.bn2.running_var", "layer2.0.bn2.num_batches_tracked", "layer2.0.conv2.weight", "layer2.0.shortcut.weight", "layer2.1.bn1.weight", "layer2.1.bn1.bias", "layer2.1.bn1.running_mean", "layer2.1.bn1.running_var", "layer2.1.bn1.num_batches_tracked", "layer2.1.conv1.weight", "layer2.1.bn2.weight", "layer2.1.bn2.bias", "layer2.1.bn2.running_mean", "layer2.1.bn2.running_var", "layer2.1.bn2.num_batches_tracked", "layer2.1.conv2.weight", "layer3.0.bn1.weight", "layer3.0.bn1.bias", "layer3.0.bn1.running_mean", "layer3.0.bn1.running_var", "layer3.0.bn1.num_batches_tracked", "layer3.0.conv1.weight", "layer3.0.bn2.weight", "layer3.0.bn2.bias", "layer3.0.bn2.running_mean", "layer3.0.bn2.running_var", "layer3.0.bn2.num_batches_tracked", "layer3.0.conv2.weight", "layer3.0.shortcut.weight", "layer3.1.bn1.weight", "layer3.1.bn1.bias", "layer3.1.bn1.running_mean", "layer3.1.bn1.running_var", "layer3.1.bn1.num_batches_tracked", "layer3.1.conv1.weight", "layer3.1.bn2.weight", "layer3.1.bn2.bias", "layer3.1.bn2.running_mean", "layer3.1.bn2.running_var", "layer3.1.bn2.num_batches_tracked", "layer3.1.conv2.weight", "bn1.weight", "bn1.bias", "bn1.running_mean", "bn1.running_var", "bn1.num_batches_tracked", "fc.weight", "fc.bias".
size mismatch for conv1.weight: copying a param with shape torch.Size([16, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([6, 3, 5, 5]). | ciclose-10 | Master-IASD | coktailjet | Error | 0 | 0 | 0 | 0 | 0 | 0 | FileNotFoundError: [Errno 2] No such file or directory: '/home/lamsade/testplatform/test-platform-a3/repos/Master-IASD/ciclose-10/models/default_model.pth' | harissa | Master-IASD | coktailjet | Error | 0 | 0 | 0 | 0 | 0 | 0 | FileNotFoundError: The config file does not exist. Model could not be loaded properly. | madraf | Master-IASD | upnquick | Error | 0 | 0 | 0 | 0 | 0 | 0 | TypeError: Net.load() missing 1 required positional argument: 'device' | team_joie | Master-IASD | upnquick | Error | 0 | 0 | 0 | 0 | 0 | 0 | RuntimeError: Error(s) in loading state_dict for Net:
Missing key(s) in state_dict: "conv1.weight", "conv1.bias", "conv2.weight", "conv2.bias", "conv3.weight", "conv3.bias", "conv4.weight", "conv4.bias", "fc1.weight", "fc1.bias", "fc2.weight", "fc2.bias", "fc3.weight", "fc3.bias".
Unexpected key(s) in state_dict: "model.conv1.weight", "model.bn1.weight", "model.bn1.bias", "model.bn1.running_mean", "model.bn1.running_var", "model.bn1.num_batches_tracked", "model.layer1.0.conv1.weight", "model.layer1.0.bn1.weight", "model.layer1.0.bn1.bias", "model.layer1.0.bn1.running_mean", "model.layer1.0.bn1.running_var", "model.layer1.0.bn1.num_batches_tracked", "model.layer1.0.conv2.weight", "model.layer1.0.bn2.weight", "model.layer1.0.bn2.bias", "model.layer1.0.bn2.running_mean", "model.layer1.0.bn2.running_var", "model.layer1.0.bn2.num_batches_tracked", "model.layer1.1.conv1.weight", "model.layer1.1.bn1.weight", "model.layer1.1.bn1.bias", "model.layer1.1.bn1.running_mean", "model.layer1.1.bn1.running_var", "model.layer1.1.bn1.num_batches_tracked", "model.layer1.1.conv2.weight", "model.layer1.1.bn2.weight", "model.layer1.1.bn2.bias", "model.layer1.1.bn2.running_mean", "model.layer1.1.bn2.running_var", "model.layer1.1.bn2.num_batches_tracked", "model.layer2.0.conv1.weight", "model.layer2.0.bn1.weight", "model.layer2.0.bn1.bias", "model.layer2.0.bn1.running_mean", "model.layer2.0.bn1.running_var", "model.layer2.0.bn1.num_batches_tracked", "model.layer2.0.conv2.weight", "model.layer2.0.bn2.weight", "model.layer2.0.bn2.bias", "model.layer2.0.bn2.running_mean", "model.layer2.0.bn2.running_var", "model.layer2.0.bn2.num_batches_tracked", "model.layer2.0.downsample.0.weight", "model.layer2.0.downsample.1.weight", "model.layer2.0.downsample.1.bias", "model.layer2.0.downsample.1.running_mean", "model.layer2.0.downsample.1.running_var", "model.layer2.0.downsample.1.num_batches_tracked", "model.layer2.1.conv1.weight", "model.layer2.1.bn1.weight", "model.layer2.1.bn1.bias", "model.layer2.1.bn1.running_mean", "model.layer2.1.bn1.running_var", "model.layer2.1.bn1.num_batches_tracked", "model.layer2.1.conv2.weight", "model.layer2.1.bn2.weight", "model.layer2.1.bn2.bias", "model.layer2.1.bn2.running_mean", "model.layer2.1.bn2.running_var", "model.layer2.1.bn2.num_batches_tracked", "model.layer3.0.conv1.weight", "model.layer3.0.bn1.weight", "model.layer3.0.bn1.bias", "model.layer3.0.bn1.running_mean", "model.layer3.0.bn1.running_var", "model.layer3.0.bn1.num_batches_tracked", "model.layer3.0.conv2.weight", "model.layer3.0.bn2.weight", "model.layer3.0.bn2.bias", "model.layer3.0.bn2.running_mean", "model.layer3.0.bn2.running_var", "model.layer3.0.bn2.num_batches_tracked", "model.layer3.0.downsample.0.weight", "model.layer3.0.downsample.1.weight", "model.layer3.0.downsample.1.bias", "model.layer3.0.downsample.1.running_mean", "model.layer3.0.downsample.1.running_var", "model.layer3.0.downsample.1.num_batches_tracked", "model.layer3.1.conv1.weight", "model.layer3.1.bn1.weight", "model.layer3.1.bn1.bias", "model.layer3.1.bn1.running_mean", "model.layer3.1.bn1.running_var", "model.layer3.1.bn1.num_batches_tracked", "model.layer3.1.conv2.weight", "model.layer3.1.bn2.weight", "model.layer3.1.bn2.bias", "model.layer3.1.bn2.running_mean", "model.layer3.1.bn2.running_var", "model.layer3.1.bn2.num_batches_tracked", "model.layer4.0.conv1.weight", "model.layer4.0.bn1.weight", "model.layer4.0.bn1.bias", "model.layer4.0.bn1.running_mean", "model.layer4.0.bn1.running_var", "model.layer4.0.bn1.num_batches_tracked", "model.layer4.0.conv2.weight", "model.layer4.0.bn2.weight", "model.layer4.0.bn2.bias", "model.layer4.0.bn2.running_mean", "model.layer4.0.bn2.running_var", "model.layer4.0.bn2.num_batches_tracked", "model.layer4.0.downsample.0.weight", "model.layer4.0.downsample.1.weight", "model.layer4.0.downsample.1.bias", "model.layer4.0.downsample.1.running_mean", "model.layer4.0.downsample.1.running_var", "model.layer4.0.downsample.1.num_batches_tracked", "model.layer4.1.conv1.weight", "model.layer4.1.bn1.weight", "model.layer4.1.bn1.bias", "model.layer4.1.bn1.running_mean", "model.layer4.1.bn1.running_var", "model.layer4.1.bn1.num_batches_tracked", "model.layer4.1.conv2.weight", "model.layer4.1.bn2.weight", "model.layer4.1.bn2.bias", "model.layer4.1.bn2.running_mean", "model.layer4.1.bn2.running_var", "model.layer4.1.bn2.num_batches_tracked", "model.fc.weight", "model.fc.bias". | the-advengers | Master-IASD | upnquick | Error | 0 | 0 | 0 | 0 | 0 | 0 | AttributeError: module 'model' has no attribute 'Net' | troublemakers | Master-IASD | coktailjet | Error | 0 | 0 | 0 | 0 | 0 | 0 | FileNotFoundError: [Errno 2] No such file or directory: '/home/lamsade/testplatform/test-platform-a3/repos/Master-IASD/troublemakers/models/ensemble_adp_model_0.pth' | jogabonito | Master-IASD | upnquick | Error | 0 | 0 | 0 | 0 | 0 | 0 | Exception: Timeout |
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