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abstract-reasoning
rule-conditioned-transformer
discrete-reasoning
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arc-it
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{
  "data": {
    "arc_agi1_path": "References/ARC-AGI",
    "arc_agi2_path": "References/ARC-AGI-2",
    "re_arc_path": "References/RE-ARC",
    "canvas_size": 64,
    "num_colors": 12,
    "max_grid_size": 30,
    "max_demos": 5,
    "re_arc_samples_per_task": 50,
    "repeat_factor": 1,
    "augmentation": {
      "geometric": true,
      "color_permutation": true,
      "num_color_perms": 10,
      "keep_background": true,
      "resolution_scaling": true,
      "translation": true
    }
  },
  "model": {
    "hidden_size": 384,
    "mlp_ratio": 2.5,
    "tokenizer": {
      "patch_size": 4
    },
    "rule_encoder": {
      "pair_layers": 2,
      "agg_layers": 2,
      "num_heads": 8,
      "num_rule_tokens": 64
    },
    "rule_applier": {
      "num_layers": 4,
      "num_heads": 8
    },
    "decoder": {
      "upsample_method": "transposed_conv",
      "hidden_channels": [
        192,
        96
      ]
    }
  },
  "training": {
    "batch_size": 64,
    "num_workers": 8,
    "gradient_clip": 1.0,
    "stage1": {
      "name": "pretrain",
      "data_sources": [
        "re_arc"
      ],
      "epochs": 50,
      "lr": 0.0003
    },
    "stage2": {
      "name": "finetune",
      "data_sources": [
        "agi1",
        "agi2"
      ],
      "epochs": 30,
      "lr": 0.0001
    },
    "stage3": {
      "name": "hard_focus",
      "data_sources": [
        "agi1",
        "agi2"
      ],
      "epochs": 10,
      "lr": 3e-05,
      "agi2_oversample": 2.0
    },
    "optimizer": {
      "name": "adamw",
      "weight_decay": 0.01,
      "betas": [
        0.9,
        0.999
      ]
    },
    "scheduler": {
      "name": "cosine",
      "warmup_ratio": 0.1
    },
    "log_every_n_steps": 100,
    "save_every_n_epochs": 10,
    "checkpoint_dir": "checkpoints"
  },
  "ttt": {
    "enabled": true,
    "steps": 100,
    "lr": 0.0001,
    "batch_size": 8,
    "num_candidates": 32
  },
  "evaluation": {
    "val_split_ratio": 0.1,
    "val_data_sources": [
      "agi1",
      "agi2"
    ],
    "metrics": [
      "pixel_accuracy",
      "grid_exact_match"
    ],
    "visualize_every_n_tasks": 50
  }
}