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results/experiments.json
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| 1 |
+
{
|
| 2 |
+
"gnn-architecture-comparison": {
|
| 3 |
+
"sage-baseline": {
|
| 4 |
+
"experiment": "gnn-architecture-comparison",
|
| 5 |
+
"arm_name": "sage-baseline",
|
| 6 |
+
"description": "GraphSAGE baseline (original architecture)",
|
| 7 |
+
"instance_id": 34817102,
|
| 8 |
+
"gpu_info": "NVIDIA GeForce RTX 4090, 23028 MiB, 1, 16\n---\n total used free shared buff/cache available\nMem: 251Gi 57Gi 136Gi 51Mi 58Gi 191Gi\nModel name: AMD EPYC 7763 64-Core Processor",
|
| 9 |
+
"metrics": {
|
| 10 |
+
"val_mae": 4.7816,
|
| 11 |
+
"val_mse": 68.0714,
|
| 12 |
+
"val_r2": 0.6354,
|
| 13 |
+
"best_val_loss": 68.0577,
|
| 14 |
+
"conv_type": "SAGE",
|
| 15 |
+
"hidden_dim": 64,
|
| 16 |
+
"num_layers": 3,
|
| 17 |
+
"dropout": 0.1,
|
| 18 |
+
"learning_rate": 0.001,
|
| 19 |
+
"epochs": 50
|
| 20 |
+
},
|
| 21 |
+
"exit_code": 0,
|
| 22 |
+
"error": "",
|
| 23 |
+
"duration_seconds": 712.9457042200083,
|
| 24 |
+
"timestamp": "2026-04-13T06:20:29.613824+00:00"
|
| 25 |
+
},
|
| 26 |
+
"gcn": {
|
| 27 |
+
"experiment": "gnn-architecture-comparison",
|
| 28 |
+
"arm_name": "gcn",
|
| 29 |
+
"description": "Graph Convolutional Network",
|
| 30 |
+
"instance_id": 34817109,
|
| 31 |
+
"gpu_info": "NVIDIA GeForce RTX 4090, 24564 MiB, 1, 16\n---\n total used free shared buff/cache available\nMem: 1.0Ti 156Gi 405Gi 41Gi 445Gi 803Gi\nModel name: AMD EPYC 7B13 64-Core Processor",
|
| 32 |
+
"metrics": {
|
| 33 |
+
"val_mae": 5.3207,
|
| 34 |
+
"val_mse": 81.6099,
|
| 35 |
+
"val_r2": 0.5628,
|
| 36 |
+
"best_val_loss": 81.5149,
|
| 37 |
+
"conv_type": "GCN",
|
| 38 |
+
"hidden_dim": 64,
|
| 39 |
+
"num_layers": 3,
|
| 40 |
+
"dropout": 0.1,
|
| 41 |
+
"learning_rate": 0.001,
|
| 42 |
+
"epochs": 50
|
| 43 |
+
},
|
| 44 |
+
"exit_code": 0,
|
| 45 |
+
"error": "",
|
| 46 |
+
"duration_seconds": 1049.5592152850004,
|
| 47 |
+
"timestamp": "2026-04-13T06:20:29.614482+00:00"
|
| 48 |
+
},
|
| 49 |
+
"gat": {
|
| 50 |
+
"experiment": "gnn-architecture-comparison",
|
| 51 |
+
"arm_name": "gat",
|
| 52 |
+
"description": "Graph Attention Network",
|
| 53 |
+
"instance_id": 34817119,
|
| 54 |
+
"gpu_info": "NVIDIA GeForce RTX 4090, 24564 MiB, 1, 16\n---\n total used free shared buff/cache available\nMem: 251Gi 38Gi 82Gi 36Mi 130Gi 210Gi\nModel name: AMD Ryzen Threadripper PRO 3975WX 32-Cores",
|
| 55 |
+
"metrics": {
|
| 56 |
+
"val_mae": 4.9519,
|
| 57 |
+
"val_mse": 73.1851,
|
| 58 |
+
"val_r2": 0.608,
|
| 59 |
+
"best_val_loss": 73.3893,
|
| 60 |
+
"conv_type": "GAT",
|
| 61 |
+
"hidden_dim": 64,
|
| 62 |
+
"num_layers": 3,
|
| 63 |
+
"dropout": 0.1,
|
| 64 |
+
"learning_rate": 0.001,
|
| 65 |
+
"epochs": 50
|
| 66 |
+
},
|
| 67 |
+
"exit_code": 0,
|
| 68 |
+
"error": "",
|
| 69 |
+
"duration_seconds": 478.46807387899025,
|
| 70 |
+
"timestamp": "2026-04-13T06:20:29.614500+00:00"
|
| 71 |
+
},
|
| 72 |
+
"gin": {
|
| 73 |
+
"experiment": "gnn-architecture-comparison",
|
| 74 |
+
"arm_name": "gin",
|
| 75 |
+
"description": "Graph Isomorphism Network",
|
| 76 |
+
"instance_id": 34817126,
|
| 77 |
+
"gpu_info": "NVIDIA GeForce RTX 4090, 24564 MiB, 1, 16\n---\n total used free shared buff/cache available\nMem: 503Gi 5.0Gi 30Gi 17Mi 468Gi 494Gi\nModel name: AMD Ryzen Threadripper PRO 3955WX 16-Cores",
|
| 78 |
+
"metrics": {
|
| 79 |
+
"val_mae": 4.5889,
|
| 80 |
+
"val_mse": 69.2775,
|
| 81 |
+
"val_r2": 0.6289,
|
| 82 |
+
"best_val_loss": 69.3397,
|
| 83 |
+
"conv_type": "GIN",
|
| 84 |
+
"hidden_dim": 64,
|
| 85 |
+
"num_layers": 3,
|
| 86 |
+
"dropout": 0.1,
|
| 87 |
+
"learning_rate": 0.001,
|
| 88 |
+
"epochs": 50
|
| 89 |
+
},
|
| 90 |
+
"exit_code": 0,
|
| 91 |
+
"error": "",
|
| 92 |
+
"duration_seconds": 397.1449088840018,
|
| 93 |
+
"timestamp": "2026-04-13T06:20:29.614511+00:00"
|
| 94 |
+
},
|
| 95 |
+
"graphconv": {
|
| 96 |
+
"experiment": "gnn-architecture-comparison",
|
| 97 |
+
"arm_name": "graphconv",
|
| 98 |
+
"description": "GraphConv (Morris et al.)",
|
| 99 |
+
"instance_id": 34817138,
|
| 100 |
+
"gpu_info": "NVIDIA GeForce RTX 4090, 24564 MiB, 1, 16\n---\n total used free shared buff/cache available\nMem: 1.0Ti 137Gi 264Gi 149Mi 606Gi 860Gi\nModel name: AMD EPYC 7V13 64-Core Processor",
|
| 101 |
+
"metrics": {
|
| 102 |
+
"val_mae": 4.8042,
|
| 103 |
+
"val_mse": 68.1418,
|
| 104 |
+
"val_r2": 0.635,
|
| 105 |
+
"best_val_loss": 68.0079,
|
| 106 |
+
"conv_type": "GraphConv",
|
| 107 |
+
"hidden_dim": 64,
|
| 108 |
+
"num_layers": 3,
|
| 109 |
+
"dropout": 0.1,
|
| 110 |
+
"learning_rate": 0.001,
|
| 111 |
+
"epochs": 50
|
| 112 |
+
},
|
| 113 |
+
"exit_code": 0,
|
| 114 |
+
"error": "",
|
| 115 |
+
"duration_seconds": 781.278599569996,
|
| 116 |
+
"timestamp": "2026-04-13T06:20:29.614519+00:00"
|
| 117 |
+
},
|
| 118 |
+
"sage-wide": {
|
| 119 |
+
"experiment": "gnn-architecture-comparison",
|
| 120 |
+
"arm_name": "sage-wide",
|
| 121 |
+
"description": "SAGE with 128 hidden dim",
|
| 122 |
+
"instance_id": 34817145,
|
| 123 |
+
"gpu_info": "NVIDIA GeForce RTX 4090, 24564 MiB, 1, 16\n---\n total used free shared buff/cache available\nMem: 566Gi 25Gi 142Gi 171Mi 398Gi 534Gi\nModel name: AMD EPYC 7763 64-Core Processor",
|
| 124 |
+
"metrics": {
|
| 125 |
+
"val_mae": 4.8625,
|
| 126 |
+
"val_mse": 68.1472,
|
| 127 |
+
"val_r2": 0.635,
|
| 128 |
+
"best_val_loss": 68.0128,
|
| 129 |
+
"conv_type": "SAGE",
|
| 130 |
+
"hidden_dim": 128,
|
| 131 |
+
"num_layers": 3,
|
| 132 |
+
"dropout": 0.1,
|
| 133 |
+
"learning_rate": 0.001,
|
| 134 |
+
"epochs": 50
|
| 135 |
+
},
|
| 136 |
+
"exit_code": 0,
|
| 137 |
+
"error": "",
|
| 138 |
+
"duration_seconds": 857.3578274790052,
|
| 139 |
+
"timestamp": "2026-04-13T06:20:29.614526+00:00"
|
| 140 |
+
},
|
| 141 |
+
"gat-wide": {
|
| 142 |
+
"experiment": "gnn-architecture-comparison",
|
| 143 |
+
"arm_name": "gat-wide",
|
| 144 |
+
"description": "GAT with 128 hidden dim",
|
| 145 |
+
"instance_id": 34817151,
|
| 146 |
+
"gpu_info": "NVIDIA GeForce RTX 4090, 24564 MiB, 1, 16\n---\n total used free shared buff/cache available\nMem: 2.0Ti 105Gi 470Gi 174Mi 1.4Ti 1.8Ti\nModel name: AMD EPYC 7702 64-Core Processor",
|
| 147 |
+
"metrics": {},
|
| 148 |
+
"exit_code": 124,
|
| 149 |
+
"error": "Training failed (exit 124): STDERR: Timed out after 1200s\nSTDOUT(tail): ",
|
| 150 |
+
"duration_seconds": 1200.0279779760021,
|
| 151 |
+
"timestamp": "2026-04-13T06:20:29.614536+00:00"
|
| 152 |
+
},
|
| 153 |
+
"sage-deep": {
|
| 154 |
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"experiment": "gnn-architecture-comparison",
|
| 155 |
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"arm_name": "sage-deep",
|
| 156 |
+
"description": "SAGE with 5 layers",
|
| 157 |
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"instance_id": 34817159,
|
| 158 |
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"gpu_info": "NVIDIA GeForce RTX 4090, 24564 MiB, 1, 16\n---\n total used free shared buff/cache available\nMem: 503Gi 340Gi 3.1Gi 0.0Ki 160Gi 159Gi\nModel name: AMD Ryzen Threadripper PRO 3995WX 64-Cores",
|
| 159 |
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"metrics": {
|
| 160 |
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"val_mae": 4.0184,
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| 161 |
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|
| 162 |
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|
| 163 |
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"best_val_loss": 54.4308,
|
| 164 |
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"conv_type": "SAGE",
|
| 165 |
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"hidden_dim": 64,
|
| 166 |
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"num_layers": 5,
|
| 167 |
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"dropout": 0.1,
|
| 168 |
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| 169 |
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"epochs": 50
|
| 170 |
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},
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| 171 |
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| 172 |
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"error": "",
|
| 173 |
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"duration_seconds": 549.5692676960025,
|
| 174 |
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"timestamp": "2026-04-13T06:20:29.614542+00:00"
|
| 175 |
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}
|
| 176 |
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},
|
| 177 |
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"gnn-generation-analysis": {
|
| 178 |
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"improved-loss-gat": {
|
| 179 |
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"experiment": "gnn-generation-analysis",
|
| 180 |
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"arm_name": "improved-loss-gat",
|
| 181 |
+
"description": "Improved (cross-entropy) loss, GAT decoder",
|
| 182 |
+
"instance_id": 34818534,
|
| 183 |
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"gpu_info": "NVIDIA GeForce RTX 4090, 23028 MiB, 1, 16\n---\n total used free shared buff/cache available\nMem: 251Gi 59Gi 133Gi 51Mi 58Gi 189Gi\nModel name: AMD EPYC 7763 64-Core Processor",
|
| 184 |
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"metrics": {
|
| 185 |
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| 186 |
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| 187 |
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| 188 |
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| 189 |
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|
| 190 |
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|
| 191 |
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|
| 192 |
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| 193 |
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|
| 194 |
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| 195 |
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| 196 |
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|
| 197 |
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},
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| 198 |
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| 199 |
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"error": "",
|
| 200 |
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"duration_seconds": 87.49750811600825,
|
| 201 |
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"timestamp": "2026-04-13T06:43:41.644479+00:00"
|
| 202 |
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},
|
| 203 |
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"simple-loss-gat": {
|
| 204 |
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"experiment": "gnn-generation-analysis",
|
| 205 |
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"arm_name": "simple-loss-gat",
|
| 206 |
+
"description": "Simple (MSE) loss, GAT decoder",
|
| 207 |
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"instance_id": 34818537,
|
| 208 |
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"gpu_info": "",
|
| 209 |
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|
| 210 |
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"exit_code": -1,
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| 211 |
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"error": "SSH never became ready",
|
| 212 |
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|
| 213 |
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"timestamp": "2026-04-13T06:43:41.645165+00:00"
|
| 214 |
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},
|
| 215 |
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"comprehensive-loss-gat": {
|
| 216 |
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"experiment": "gnn-generation-analysis",
|
| 217 |
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"arm_name": "comprehensive-loss-gat",
|
| 218 |
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"description": "Comprehensive (combined) loss, GAT decoder",
|
| 219 |
+
"instance_id": 34818538,
|
| 220 |
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"gpu_info": "NVIDIA GeForce RTX 4090, 24564 MiB, 1, 16\n---\n total used free shared buff/cache available\nMem: 503Gi 5.0Gi 30Gi 17Mi 468Gi 494Gi\nModel name: AMD Ryzen Threadripper PRO 3955WX 16-Cores",
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"metrics": {
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| 222 |
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"error": "training_failed",
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| 223 |
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"exit_code": 1
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},
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"exit_code": 1,
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| 226 |
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"error": "setup:\n Optimizer: Adam (lr=0.001)\n Scheduler: ReduceLROnPlateau (patience=5)\n Loss function: Improved Reconstruction Loss\n AMP Enabled: True\n\n\ud83c\udfcb\ufe0f Starting training...\n==================================================\nTraceback (most recent call last):\n File \"/workspace/experiment/train_autoencoder.py\", line 393, in <module>\n main()\n File \"/workspace/experiment/train_autoencoder.py\", line 332, in main\n train_loss = train_epoch(model, train_loader, optimizer, device, args.type_weight, args.parent_weight, scaler, loss_fn=loss_fn)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/workspace/experiment/train_autoencoder.py\", line 65, in train_epoch\n loss = loss_fn(\n ^^^^^^^^\nTypeError: ast_reconstruction_loss_comprehensive() got an unexpected keyword argument 'type_weight'\nERROR: train_autoencoder.py exited with code 1\nMETRICS:{\"error\": \"training_failed\", \"exit_code\": 1}\n",
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| 227 |
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"duration_seconds": 16.827261095982976,
|
| 228 |
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"timestamp": "2026-04-13T06:43:41.645183+00:00"
|
| 229 |
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},
|
| 230 |
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"improved-loss-sage": {
|
| 231 |
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"experiment": "gnn-generation-analysis",
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| 232 |
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"arm_name": "improved-loss-sage",
|
| 233 |
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"description": "Improved loss, SAGE decoder",
|
| 234 |
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"instance_id": 34818541,
|
| 235 |
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| 236 |
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"metrics": {
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| 237 |
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| 238 |
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| 240 |
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| 242 |
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| 243 |
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| 244 |
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| 245 |
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| 246 |
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| 248 |
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| 249 |
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},
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| 252 |
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|
| 254 |
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},
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| 255 |
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|
| 256 |
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"experiment": "gnn-generation-analysis",
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| 257 |
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| 258 |
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| 259 |
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| 262 |
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| 267 |
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| 268 |
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| 269 |
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| 270 |
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| 278 |
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"timestamp": "2026-04-13T06:43:41.645201+00:00"
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| 279 |
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},
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| 280 |
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"improved-loss-gcn": {
|
| 281 |
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"experiment": "gnn-generation-analysis",
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| 282 |
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"arm_name": "improved-loss-gcn",
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| 283 |
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"description": "Improved loss, GCN decoder",
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| 284 |
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| 286 |
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| 291 |
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| 294 |
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},
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| 304 |
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},
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| 309 |
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| 311 |
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| 317 |
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| 319 |
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| 323 |
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},
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| 327 |
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| 329 |
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}
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| 330 |
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},
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| 331 |
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"gnn-decoder-topology": {
|
| 332 |
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"chain-gat": {
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| 333 |
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"experiment": "gnn-decoder-topology",
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| 334 |
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"arm_name": "chain-gat",
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| 335 |
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"description": "Chain edges (legacy baseline), GAT decoder",
|
| 336 |
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"instance_id": 34818971,
|
| 337 |
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| 338 |
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| 339 |
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| 340 |
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| 341 |
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| 342 |
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| 343 |
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| 344 |
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| 345 |
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| 346 |
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| 347 |
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| 348 |
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| 352 |
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},
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| 355 |
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| 356 |
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| 357 |
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},
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| 358 |
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| 359 |
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"experiment": "gnn-decoder-topology",
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| 360 |
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"arm_name": "teacher-forced-gat",
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| 361 |
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"description": "Teacher-forced tree edges, GAT decoder",
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| 362 |
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"instance_id": 34818979,
|
| 363 |
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| 364 |
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"metrics": {
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| 365 |
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| 366 |
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| 368 |
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| 369 |
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| 370 |
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| 371 |
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| 372 |
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| 373 |
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| 374 |
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| 378 |
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},
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| 381 |
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| 382 |
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"timestamp": "2026-04-13T06:52:18.888261+00:00"
|
| 383 |
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},
|
| 384 |
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"iterative-gat": {
|
| 385 |
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"experiment": "gnn-decoder-topology",
|
| 386 |
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"arm_name": "iterative-gat",
|
| 387 |
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"description": "Iterative predict\u2192refine, GAT decoder",
|
| 388 |
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"instance_id": 34818982,
|
| 389 |
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"gpu_info": "NVIDIA GeForce RTX 4090, 24564 MiB, 1, 16\n---\n total used free shared buff/cache available\nMem: 503Gi 3.6Gi 379Gi 27Mi 120Gi 495Gi\nModel name: AMD EPYC 7282 16-Core Processor",
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| 390 |
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| 392 |
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| 396 |
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| 397 |
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| 398 |
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},
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"timestamp": "2026-04-13T06:52:18.888279+00:00"
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| 409 |
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},
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| 410 |
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"teacher-forced-sage": {
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| 411 |
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"experiment": "gnn-decoder-topology",
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| 412 |
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| 413 |
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"description": "Teacher-forced tree edges, SAGE decoder",
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| 414 |
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| 415 |
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},
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"timestamp": "2026-04-13T06:52:18.888290+00:00"
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| 435 |
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},
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| 436 |
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| 437 |
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"experiment": "gnn-decoder-topology",
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| 438 |
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"arm_name": "teacher-forced-gin",
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| 439 |
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"description": "Teacher-forced tree edges, GIN decoder",
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| 440 |
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| 441 |
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| 442 |
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},
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"timestamp": "2026-04-13T06:52:18.888298+00:00"
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| 461 |
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},
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| 462 |
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"teacher-forced-gat-comprehensive": {
|
| 463 |
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"experiment": "gnn-decoder-topology",
|
| 464 |
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"arm_name": "teacher-forced-gat-comprehensive",
|
| 465 |
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"description": "Teacher-forced, GAT, comprehensive loss",
|
| 466 |
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"instance_id": 34818993,
|
| 467 |
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"gpu_info": "NVIDIA GeForce RTX 4090, 24564 MiB, 1, 16\n---\n total used free shared buff/cache available\nMem: 503Gi 25Gi 5.7Gi 252Mi 472Gi 474Gi\nModel name: AMD EPYC 7K62 48-Core Processor",
|
| 468 |
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"metrics": {
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| 469 |
+
"error": "training_failed",
|
| 470 |
+
"exit_code": 1
|
| 471 |
+
},
|
| 472 |
+
"exit_code": 1,
|
| 473 |
+
"error": "setup:\n Optimizer: Adam (lr=0.001)\n Scheduler: ReduceLROnPlateau (patience=5)\n Loss function: Improved Reconstruction Loss\n AMP Enabled: True\n\n\ud83c\udfcb\ufe0f Starting training...\n==================================================\nTraceback (most recent call last):\n File \"/workspace/experiment/train_autoencoder.py\", line 393, in <module>\n main()\n File \"/workspace/experiment/train_autoencoder.py\", line 332, in main\n train_loss = train_epoch(model, train_loader, optimizer, device, args.type_weight, args.parent_weight, scaler, loss_fn=loss_fn)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/workspace/experiment/train_autoencoder.py\", line 65, in train_epoch\n loss = loss_fn(\n ^^^^^^^^\nTypeError: ast_reconstruction_loss_comprehensive() got an unexpected keyword argument 'type_weight'\nERROR: train_autoencoder.py exited with code 1\nMETRICS:{\"error\": \"training_failed\", \"exit_code\": 1}\n",
|
| 474 |
+
"duration_seconds": 21.593328246992314,
|
| 475 |
+
"timestamp": "2026-04-13T06:52:18.888305+00:00"
|
| 476 |
+
}
|
| 477 |
+
}
|
| 478 |
+
}
|