| { |
| "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" |
| } |
| } |
| } |
|
|
