Datasets:
File size: 22,032 Bytes
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"gnn-architecture-comparison": {
"sage-baseline": {
"experiment": "gnn-architecture-comparison",
"arm_name": "sage-baseline",
"description": "GraphSAGE baseline (original architecture)",
"instance_id": 34817102,
"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",
"metrics": {
"val_mae": 4.7816,
"val_mse": 68.0714,
"val_r2": 0.6354,
"best_val_loss": 68.0577,
"conv_type": "SAGE",
"hidden_dim": 64,
"num_layers": 3,
"dropout": 0.1,
"learning_rate": 0.001,
"epochs": 50
},
"exit_code": 0,
"error": "",
"duration_seconds": 712.9457042200083,
"timestamp": "2026-04-13T06:20:29.613824+00:00"
},
"gcn": {
"experiment": "gnn-architecture-comparison",
"arm_name": "gcn",
"description": "Graph Convolutional Network",
"instance_id": 34817109,
"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",
"metrics": {
"val_mae": 5.3207,
"val_mse": 81.6099,
"val_r2": 0.5628,
"best_val_loss": 81.5149,
"conv_type": "GCN",
"hidden_dim": 64,
"num_layers": 3,
"dropout": 0.1,
"learning_rate": 0.001,
"epochs": 50
},
"exit_code": 0,
"error": "",
"duration_seconds": 1049.5592152850004,
"timestamp": "2026-04-13T06:20:29.614482+00:00"
},
"gat": {
"experiment": "gnn-architecture-comparison",
"arm_name": "gat",
"description": "Graph Attention Network",
"instance_id": 34817119,
"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",
"metrics": {
"val_mae": 4.9519,
"val_mse": 73.1851,
"val_r2": 0.608,
"best_val_loss": 73.3893,
"conv_type": "GAT",
"hidden_dim": 64,
"num_layers": 3,
"dropout": 0.1,
"learning_rate": 0.001,
"epochs": 50
},
"exit_code": 0,
"error": "",
"duration_seconds": 478.46807387899025,
"timestamp": "2026-04-13T06:20:29.614500+00:00"
},
"gin": {
"experiment": "gnn-architecture-comparison",
"arm_name": "gin",
"description": "Graph Isomorphism Network",
"instance_id": 34817126,
"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",
"metrics": {
"val_mae": 4.5889,
"val_mse": 69.2775,
"val_r2": 0.6289,
"best_val_loss": 69.3397,
"conv_type": "GIN",
"hidden_dim": 64,
"num_layers": 3,
"dropout": 0.1,
"learning_rate": 0.001,
"epochs": 50
},
"exit_code": 0,
"error": "",
"duration_seconds": 397.1449088840018,
"timestamp": "2026-04-13T06:20:29.614511+00:00"
},
"graphconv": {
"experiment": "gnn-architecture-comparison",
"arm_name": "graphconv",
"description": "GraphConv (Morris et al.)",
"instance_id": 34817138,
"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",
"metrics": {
"val_mae": 4.8042,
"val_mse": 68.1418,
"val_r2": 0.635,
"best_val_loss": 68.0079,
"conv_type": "GraphConv",
"hidden_dim": 64,
"num_layers": 3,
"dropout": 0.1,
"learning_rate": 0.001,
"epochs": 50
},
"exit_code": 0,
"error": "",
"duration_seconds": 781.278599569996,
"timestamp": "2026-04-13T06:20:29.614519+00:00"
},
"sage-wide": {
"experiment": "gnn-architecture-comparison",
"arm_name": "sage-wide",
"description": "SAGE with 128 hidden dim",
"instance_id": 34817145,
"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",
"metrics": {
"val_mae": 4.8625,
"val_mse": 68.1472,
"val_r2": 0.635,
"best_val_loss": 68.0128,
"conv_type": "SAGE",
"hidden_dim": 128,
"num_layers": 3,
"dropout": 0.1,
"learning_rate": 0.001,
"epochs": 50
},
"exit_code": 0,
"error": "",
"duration_seconds": 857.3578274790052,
"timestamp": "2026-04-13T06:20:29.614526+00:00"
},
"gat-wide": {
"experiment": "gnn-architecture-comparison",
"arm_name": "gat-wide",
"description": "GAT with 128 hidden dim",
"instance_id": 34817151,
"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",
"metrics": {},
"exit_code": 124,
"error": "Training failed (exit 124): STDERR: Timed out after 1200s\nSTDOUT(tail): ",
"duration_seconds": 1200.0279779760021,
"timestamp": "2026-04-13T06:20:29.614536+00:00"
},
"sage-deep": {
"experiment": "gnn-architecture-comparison",
"arm_name": "sage-deep",
"description": "SAGE with 5 layers",
"instance_id": 34817159,
"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",
"metrics": {
"val_mae": 4.0184,
"val_mse": 54.3718,
"val_r2": 0.7087,
"best_val_loss": 54.4308,
"conv_type": "SAGE",
"hidden_dim": 64,
"num_layers": 5,
"dropout": 0.1,
"learning_rate": 0.001,
"epochs": 50
},
"exit_code": 0,
"error": "",
"duration_seconds": 549.5692676960025,
"timestamp": "2026-04-13T06:20:29.614542+00:00"
}
},
"gnn-generation-analysis": {
"improved-loss-gat": {
"experiment": "gnn-generation-analysis",
"arm_name": "improved-loss-gat",
"description": "Improved (cross-entropy) loss, GAT decoder",
"instance_id": 34818534,
"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",
"metrics": {
"syntactic_validity_pct": 0.0,
"val_loss": 7.7184,
"samples_evaluated": 100,
"valid_samples": 0,
"decoder_conv_type": "GAT",
"hidden_dim": 256,
"num_layers": 5,
"loss_fn": "improved",
"type_weight": 2.0,
"parent_weight": 1.0,
"learning_rate": 0.001,
"epochs": 30
},
"exit_code": 0,
"error": "",
"duration_seconds": 87.49750811600825,
"timestamp": "2026-04-13T06:43:41.644479+00:00"
},
"simple-loss-gat": {
"experiment": "gnn-generation-analysis",
"arm_name": "simple-loss-gat",
"description": "Simple (MSE) loss, GAT decoder",
"instance_id": 34818537,
"gpu_info": "",
"metrics": {},
"exit_code": -1,
"error": "SSH never became ready",
"duration_seconds": 0.0,
"timestamp": "2026-04-13T06:43:41.645165+00:00"
},
"comprehensive-loss-gat": {
"experiment": "gnn-generation-analysis",
"arm_name": "comprehensive-loss-gat",
"description": "Comprehensive (combined) loss, GAT decoder",
"instance_id": 34818538,
"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",
"metrics": {
"error": "training_failed",
"exit_code": 1
},
"exit_code": 1,
"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",
"duration_seconds": 16.827261095982976,
"timestamp": "2026-04-13T06:43:41.645183+00:00"
},
"improved-loss-sage": {
"experiment": "gnn-generation-analysis",
"arm_name": "improved-loss-sage",
"description": "Improved loss, SAGE decoder",
"instance_id": 34818541,
"gpu_info": "NVIDIA GeForce RTX 4090, 24564 MiB, 1, 16\n---\n total used free shared buff/cache available\nMem: 503Gi 117Gi 138Gi 15Gi 247Gi 367Gi\nModel name: AMD EPYC 7B13 64-Core Processor",
"metrics": {
"syntactic_validity_pct": 0.0,
"val_loss": 7.7897,
"samples_evaluated": 100,
"valid_samples": 0,
"decoder_conv_type": "SAGE",
"hidden_dim": 256,
"num_layers": 5,
"loss_fn": "improved",
"type_weight": 2.0,
"parent_weight": 1.0,
"learning_rate": 0.001,
"epochs": 30
},
"exit_code": 0,
"error": "",
"duration_seconds": 143.7897430199955,
"timestamp": "2026-04-13T06:43:41.645193+00:00"
},
"improved-loss-gin": {
"experiment": "gnn-generation-analysis",
"arm_name": "improved-loss-gin",
"description": "Improved loss, GIN decoder",
"instance_id": 34818545,
"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",
"metrics": {
"syntactic_validity_pct": 0.0,
"val_loss": 7.8025,
"samples_evaluated": 100,
"valid_samples": 0,
"decoder_conv_type": "GIN",
"hidden_dim": 256,
"num_layers": 5,
"loss_fn": "improved",
"type_weight": 2.0,
"parent_weight": 1.0,
"learning_rate": 0.001,
"epochs": 30
},
"exit_code": 0,
"error": "",
"duration_seconds": 82.56781898299232,
"timestamp": "2026-04-13T06:43:41.645201+00:00"
},
"improved-loss-gcn": {
"experiment": "gnn-generation-analysis",
"arm_name": "improved-loss-gcn",
"description": "Improved loss, GCN decoder",
"instance_id": 34818549,
"gpu_info": "NVIDIA GeForce RTX 4090, 24564 MiB, 1, 16\n---\n total used free shared buff/cache available\nMem: 1.0Ti 219Gi 271Gi 627Mi 516Gi 776Gi\nModel name: AMD EPYC 7C13 64-Core Processor",
"metrics": {
"syntactic_validity_pct": 0.0,
"val_loss": 7.7638,
"samples_evaluated": 100,
"valid_samples": 0,
"decoder_conv_type": "GCN",
"hidden_dim": 256,
"num_layers": 5,
"loss_fn": "improved",
"type_weight": 2.0,
"parent_weight": 1.0,
"learning_rate": 0.001,
"epochs": 30
},
"exit_code": 0,
"error": "",
"duration_seconds": 79.23930556201958,
"timestamp": "2026-04-13T06:43:41.645208+00:00"
},
"improved-loss-gat-wide": {
"experiment": "gnn-generation-analysis",
"arm_name": "improved-loss-gat-wide",
"description": "Improved loss, GAT decoder, hidden_dim=512",
"instance_id": 34818556,
"gpu_info": "NVIDIA GeForce RTX 4090, 24564 MiB, 1, 16\n---\n total used free shared buff/cache available\nMem: 2.0Ti 131Gi 444Gi 182Mi 1.4Ti 1.8Ti\nModel name: AMD EPYC 7702 64-Core Processor",
"metrics": {
"syntactic_validity_pct": 0.0,
"val_loss": 7.7262,
"samples_evaluated": 100,
"valid_samples": 0,
"decoder_conv_type": "GAT",
"hidden_dim": 512,
"num_layers": 5,
"loss_fn": "improved",
"type_weight": 2.0,
"parent_weight": 1.0,
"learning_rate": 0.001,
"epochs": 30
},
"exit_code": 0,
"error": "",
"duration_seconds": 259.52819745699526,
"timestamp": "2026-04-13T06:43:41.645217+00:00"
}
},
"gnn-decoder-topology": {
"chain-gat": {
"experiment": "gnn-decoder-topology",
"arm_name": "chain-gat",
"description": "Chain edges (legacy baseline), GAT decoder",
"instance_id": 34818971,
"gpu_info": "NVIDIA GeForce RTX 4090, 24564 MiB, 1, 16\n---\n total used free shared buff/cache available\nMem: 1.0Ti 157Gi 403Gi 41Gi 446Gi 802Gi\nModel name: AMD EPYC 7B13 64-Core Processor",
"metrics": {
"syntactic_validity_pct": 0.0,
"val_loss": 7.7151,
"samples_evaluated": 100,
"valid_samples": 0,
"decoder_edge_mode": "chain",
"decoder_conv_type": "GAT",
"hidden_dim": 256,
"num_layers": 5,
"loss_fn": "improved",
"type_weight": 2.0,
"parent_weight": 1.0,
"learning_rate": 0.001,
"epochs": 30
},
"exit_code": 0,
"error": "",
"duration_seconds": 93.43292950798059,
"timestamp": "2026-04-13T06:52:18.887589+00:00"
},
"teacher-forced-gat": {
"experiment": "gnn-decoder-topology",
"arm_name": "teacher-forced-gat",
"description": "Teacher-forced tree edges, GAT decoder",
"instance_id": 34818979,
"gpu_info": "NVIDIA GeForce RTX 4090, 24564 MiB, 1, 16\n---\n total used free shared buff/cache available\nMem: 503Gi 93Gi 210Gi 16Gi 199Gi 389Gi\nModel name: AMD EPYC 7B12 64-Core Processor",
"metrics": {
"syntactic_validity_pct": 0.0,
"val_loss": 7.7059,
"samples_evaluated": 100,
"valid_samples": 0,
"decoder_edge_mode": "teacher_forced",
"decoder_conv_type": "GAT",
"hidden_dim": 256,
"num_layers": 5,
"loss_fn": "improved",
"type_weight": 2.0,
"parent_weight": 1.0,
"learning_rate": 0.001,
"epochs": 30
},
"exit_code": 0,
"error": "",
"duration_seconds": 102.00913854799,
"timestamp": "2026-04-13T06:52:18.888261+00:00"
},
"iterative-gat": {
"experiment": "gnn-decoder-topology",
"arm_name": "iterative-gat",
"description": "Iterative predict\u2192refine, GAT decoder",
"instance_id": 34818982,
"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",
"metrics": {
"syntactic_validity_pct": 0.0,
"val_loss": 7.7649,
"samples_evaluated": 100,
"valid_samples": 0,
"decoder_edge_mode": "iterative",
"decoder_conv_type": "GAT",
"hidden_dim": 256,
"num_layers": 5,
"loss_fn": "improved",
"type_weight": 2.0,
"parent_weight": 1.0,
"learning_rate": 0.001,
"epochs": 30
},
"exit_code": 0,
"error": "",
"duration_seconds": 102.66292616000283,
"timestamp": "2026-04-13T06:52:18.888279+00:00"
},
"teacher-forced-sage": {
"experiment": "gnn-decoder-topology",
"arm_name": "teacher-forced-sage",
"description": "Teacher-forced tree edges, SAGE decoder",
"instance_id": 34818986,
"gpu_info": "NVIDIA GeForce RTX 4090, 24564 MiB, 1, 16\n---\n total used free shared buff/cache available\nMem: 566Gi 25Gi 143Gi 171Mi 398Gi 534Gi\nModel name: AMD EPYC 7763 64-Core Processor",
"metrics": {
"syntactic_validity_pct": 0.0,
"val_loss": 7.7987,
"samples_evaluated": 100,
"valid_samples": 0,
"decoder_edge_mode": "teacher_forced",
"decoder_conv_type": "SAGE",
"hidden_dim": 256,
"num_layers": 5,
"loss_fn": "improved",
"type_weight": 2.0,
"parent_weight": 1.0,
"learning_rate": 0.001,
"epochs": 30
},
"exit_code": 0,
"error": "",
"duration_seconds": 85.2959101049928,
"timestamp": "2026-04-13T06:52:18.888290+00:00"
},
"teacher-forced-gin": {
"experiment": "gnn-decoder-topology",
"arm_name": "teacher-forced-gin",
"description": "Teacher-forced tree edges, GIN decoder",
"instance_id": 34818988,
"gpu_info": "NVIDIA GeForce RTX 4090, 24564 MiB, 1, 16\n---\n total used free shared buff/cache available\nMem: 503Gi 4.6Gi 109Gi 9.0Mi 389Gi 494Gi\nModel name: AMD Ryzen Threadripper PRO 3955WX 16-Cores",
"metrics": {
"syntactic_validity_pct": 7.0,
"val_loss": 8.3833,
"samples_evaluated": 100,
"valid_samples": 7,
"decoder_edge_mode": "teacher_forced",
"decoder_conv_type": "GIN",
"hidden_dim": 256,
"num_layers": 5,
"loss_fn": "improved",
"type_weight": 2.0,
"parent_weight": 1.0,
"learning_rate": 0.001,
"epochs": 30
},
"exit_code": 0,
"error": "",
"duration_seconds": 57.38957904101699,
"timestamp": "2026-04-13T06:52:18.888298+00:00"
},
"teacher-forced-gat-comprehensive": {
"experiment": "gnn-decoder-topology",
"arm_name": "teacher-forced-gat-comprehensive",
"description": "Teacher-forced, GAT, comprehensive loss",
"instance_id": 34818993,
"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",
"metrics": {
"error": "training_failed",
"exit_code": 1
},
"exit_code": 1,
"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",
"duration_seconds": 21.593328246992314,
"timestamp": "2026-04-13T06:52:18.888305+00:00"
}
}
}
|