{
  "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"
    }
  }
}