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Publish five temporal H8 profiled small checkpoints

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  1. latency-aware/deadly-corridor/small-policy/sample-factory-qwenoft-rtx3090-temporal-hist8-capacity1-native35-s42-v1/README.md +10 -0
  2. latency-aware/deadly-corridor/small-policy/sample-factory-qwenoft-rtx3090-temporal-hist8-capacity1-native35-s42-v1/best_000044776_22925312_reward_2084.409.pth +3 -0
  3. latency-aware/deadly-corridor/small-policy/sample-factory-qwenoft-rtx3090-temporal-hist8-capacity1-native35-s42-v1/config.json +271 -0
  4. latency-aware/deadly-corridor/small-policy/sample-factory-qwenoft-rtx3090-temporal-hist8-capacity1-native35-s42-v1/provenance.json +16 -0
  5. latency-aware/demon-attack/small-policy/sample-factory-qwenoft-rtx3090-temporal-hist8-capacity1-s42-v1/README.md +10 -0
  6. latency-aware/demon-attack/small-policy/sample-factory-qwenoft-rtx3090-temporal-hist8-capacity1-s42-v1/best_000048224_24690688_reward_9340.850.pth +3 -0
  7. latency-aware/demon-attack/small-policy/sample-factory-qwenoft-rtx3090-temporal-hist8-capacity1-s42-v1/config.json +278 -0
  8. latency-aware/demon-attack/small-policy/sample-factory-qwenoft-rtx3090-temporal-hist8-capacity1-s42-v1/provenance.json +16 -0
  9. latency-aware/flappy/small-policy/sample-factory-gr00t-rtx3090-temporal-hist8-capacity1-s42-v1/README.md +10 -0
  10. latency-aware/flappy/small-policy/sample-factory-gr00t-rtx3090-temporal-hist8-capacity1-s42-v1/best_000048832_25001984_reward_3570.134.pth +3 -0
  11. latency-aware/flappy/small-policy/sample-factory-gr00t-rtx3090-temporal-hist8-capacity1-s42-v1/config.json +296 -0
  12. latency-aware/flappy/small-policy/sample-factory-gr00t-rtx3090-temporal-hist8-capacity1-s42-v1/provenance.json +16 -0
  13. latency-aware/flappy/small-policy/sample-factory-pi05-rtx3090-temporal-hist8-capacity1-s42-v1/README.md +10 -0
  14. latency-aware/flappy/small-policy/sample-factory-pi05-rtx3090-temporal-hist8-capacity1-s42-v1/best_000045712_23429120_reward_1021.035.pth +3 -0
  15. latency-aware/flappy/small-policy/sample-factory-pi05-rtx3090-temporal-hist8-capacity1-s42-v1/config.json +296 -0
  16. latency-aware/flappy/small-policy/sample-factory-pi05-rtx3090-temporal-hist8-capacity1-s42-v1/provenance.json +16 -0
  17. latency-aware/flappy/small-policy/sample-factory-qwenoft-rtx3090-temporal-hist8-capacity1-s42-v1/README.md +10 -0
  18. latency-aware/flappy/small-policy/sample-factory-qwenoft-rtx3090-temporal-hist8-capacity1-s42-v1/best_000047872_24543232_reward_1331.159.pth +3 -0
  19. latency-aware/flappy/small-policy/sample-factory-qwenoft-rtx3090-temporal-hist8-capacity1-s42-v1/config.json +296 -0
  20. latency-aware/flappy/small-policy/sample-factory-qwenoft-rtx3090-temporal-hist8-capacity1-s42-v1/provenance.json +16 -0
latency-aware/deadly-corridor/small-policy/sample-factory-qwenoft-rtx3090-temporal-hist8-capacity1-native35-s42-v1/README.md ADDED
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+ # deadly corridor — qwenoft temporal H8 profiled small policy
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+
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+ Sample Factory APPO small policy trained with an RTX 3090 temporal latency profile, one simulated inference worker, and an eight-decision causal history. This folder contains the training-selected best checkpoint and its exact Sample Factory config.
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+
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+ - W&B run ID: `deadly-corridor-fs4-qwenoft_rtx3090_temporal_hist8_capacity1_native35-s42`
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+ - Checkpoint: `best_000044776_22925312_reward_2084.409.pth`
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+ - Training seed: 42; target: 25 million environment steps.
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+ - Profile SHA256: `bbfb93cef9f63750a9a159ec10a93a9fc6c25e4cb0cac3b39532663b4dc11eba`
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+
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+ The reward in the checkpoint filename is a training selection metric, not a formal evaluation result. See `provenance.json` for exact source paths and hashes.
latency-aware/deadly-corridor/small-policy/sample-factory-qwenoft-rtx3090-temporal-hist8-capacity1-native35-s42-v1/best_000044776_22925312_reward_2084.409.pth ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:62eee5b587bde20cc912fde9c068d92498a6433b62dec28f8e994004fb8e7e18
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+ size 36517737
latency-aware/deadly-corridor/small-policy/sample-factory-qwenoft-rtx3090-temporal-hist8-capacity1-native35-s42-v1/config.json ADDED
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+ {
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+ "help": false,
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+ "algo": "APPO",
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+ "env": "doom_deadly_corridor",
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+ "experiment": "deadly_corridor_frame_stack_qwenoft_rtx3090_temporal_hist8_capacity1_native35_fs4_seed42",
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+ "train_dir": "results/checkpoints/deadly_corridor/decision_history_native35_temporal_25m_seed42",
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+ "restart_behavior": "resume",
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+ "device": "gpu",
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+ "seed": 42,
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+ "initial_model_path": null,
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+ "num_policies": 1,
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+ "async_rl": true,
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+ "serial_mode": false,
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+ "batched_sampling": false,
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+ "num_batches_to_accumulate": 2,
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+ "worker_num_splits": 2,
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+ "policy_workers_per_policy": 1,
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+ "max_policy_lag": 1000,
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+ "num_workers": 32,
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+ "num_envs_per_worker": 4,
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+ "batch_size": 1024,
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+ "num_batches_per_epoch": 2,
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+ "num_epochs": 2,
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+ "rollout": 128,
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+ "fasttd3_replay_capacity": 6553600,
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+ "fasttd3_replay_batch_size": 32768,
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+ "fasttd3_action_chunk_horizon": 1,
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+ "fasttd3_transitions_per_update": 64,
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+ "fasttd3_train_for_optimizer_steps": 10000000000,
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+ "fasttd3_v_min": -250.0,
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+ "fasttd3_v_max": 250.0,
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+ "fasttd3_actor_action_l2": 0.0,
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+ "fasttd3_compile": true,
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+ "recurrence": 128,
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+ "shuffle_minibatches": false,
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+ "gamma": 0.99,
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+ "reward_scale": 1.0,
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+ "reward_clip": 1000.0,
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+ "value_bootstrap": false,
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+ "normalize_returns": true,
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+ "exploration_loss_coeff": 0.001,
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+ "value_loss_coeff": 0.5,
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+ "kl_loss_coeff": 0.0,
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+ "exploration_loss": "symmetric_kl",
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+ "gae_lambda": 0.95,
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+ "ppo_clip_ratio": 0.1,
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+ "ppo_clip_value": 0.2,
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+ "with_vtrace": false,
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+ "vtrace_rho": 1.0,
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+ "vtrace_c": 1.0,
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+ "optimizer": "adam",
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+ "adam_eps": 1e-06,
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+ "adam_beta1": 0.9,
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+ "adam_beta2": 0.999,
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+ "max_grad_norm": 4.0,
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+ "learning_rate": 0.0001,
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+ "lr_schedule": "constant",
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+ "lr_schedule_kl_threshold": 0.008,
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+ "lr_adaptive_min": 1e-06,
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+ "lr_adaptive_max": 0.01,
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+ "obs_subtract_mean": 0.0,
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+ "obs_scale": 255.0,
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+ "normalize_input": true,
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+ "normalize_input_keys": null,
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+ "decorrelate_experience_max_seconds": 0,
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+ "decorrelate_envs_on_one_worker": true,
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+ "actor_worker_gpus": [],
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+ "set_workers_cpu_affinity": true,
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+ "force_envs_single_thread": false,
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+ "default_niceness": 0,
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+ "log_to_file": true,
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+ "experiment_summaries_interval": 1,
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+ "flush_summaries_interval": 30,
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+ "stats_avg": 100,
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+ "summaries_use_frameskip": true,
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+ "heartbeat_interval": 20,
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+ "heartbeat_reporting_interval": 600,
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+ "train_for_env_steps": 25000000,
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+ "train_for_seconds": 10000000000,
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+ "save_every_sec": 600,
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+ "keep_checkpoints": 5,
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+ "load_checkpoint_kind": "latest",
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+ "save_milestones_sec": -1,
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+ "save_best_every_sec": 5,
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+ "save_best_metric": "reward",
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+ "save_best_after": 100000,
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+ "benchmark": false,
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+ "encoder_mlp_layers": [
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+ 512,
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+ 512
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+ ],
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+ "encoder_conv_architecture": "convnet_simple",
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+ "encoder_conv_mlp_layers": [
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+ 512
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+ ],
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+ "use_rnn": true,
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+ "rnn_size": 512,
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+ "rnn_type": "gru",
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+ "rnn_num_layers": 1,
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+ "decoder_mlp_layers": [],
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+ "nonlinearity": "elu",
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+ "policy_initialization": "orthogonal",
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+ "policy_init_gain": 1.0,
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+ "actor_critic_share_weights": true,
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+ "adaptive_stddev": true,
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+ "continuous_tanh_scale": 0.0,
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+ "initial_stddev": 1.0,
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+ "use_env_info_cache": false,
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+ "env_gpu_actions": false,
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+ "env_gpu_observations": true,
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+ "env_frameskip": 1,
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+ "env_framestack": 1,
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+ "pixel_format": "CHW",
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+ "use_record_episode_statistics": false,
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+ "episode_counter": false,
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+ "with_wandb": true,
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+ "wandb_user": null,
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+ "wandb_project": "starvla_tasks",
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+ "wandb_group": "deadly-corridor-fs4-qwenoft_rtx3090_temporal_hist8_capacity1_native35",
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+ "wandb_job_type": "deadly_corridor_decision_history_native35_temporal",
121
+ "wandb_tags": [
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+ "deadly_corridor_decision_history_native35_temporal_25m_seed42",
123
+ "deadly-corridor",
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+ "frame_stack",
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+ "temporal",
126
+ "qwenoft_rtx3090_temporal_hist8_capacity1_native35",
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+ "fs4",
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+ "seed42"
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+ ],
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+ "wandb_dir": "/mnt/ssd/latency-sensitive-bench/wandb",
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+ "with_pbt": false,
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+ "pbt_mix_policies_in_one_env": true,
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+ "pbt_period_env_steps": 5000000,
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+ "pbt_start_mutation": 20000000,
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+ "pbt_replace_fraction": 0.3,
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+ "pbt_mutation_rate": 0.15,
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+ "pbt_replace_reward_gap": 0.1,
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+ "pbt_replace_reward_gap_absolute": 1e-06,
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+ "pbt_optimize_gamma": false,
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+ "pbt_target_objective": "true_objective",
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+ "pbt_perturb_min": 1.1,
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+ "pbt_perturb_max": 1.5,
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+ "num_agents": -1,
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+ "num_humans": 0,
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+ "num_bots": -1,
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+ "start_bot_difficulty": null,
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+ "res_w": 128,
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+ "wide_aspect_ratio": false,
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+ "record_to": null,
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+ "mode": "train",
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+ "env_fps": 35.0,
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+ "obs_fps": 8.75,
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+ "latency_type": "profile_sample",
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+ "fixed_latency_ms": null,
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+ "mean_latency_ms": null,
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+ "std_latency_ms": null,
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+ "min_latency_ms": null,
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+ "max_latency_ms": null,
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+ "latency_seed": 42,
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+ "latency_profile_path": "results/profiling/profiles/openvla/1x-rtx3090/deadly_corridor/instance_a5037b165aa0cedc/profile.json",
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+ "latency_profile_worker_slot": 0,
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+ "simulated_worker_capacity": 1,
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+ "add_latency_info": false,
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+ "max_pending_actions": null,
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+ "hold_policy": "hold",
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+ "ordering_policy": "latest_ready",
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+ "eval_episodes": 100,
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+ "eval_parallel_envs": 1,
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+ "eval_latency_raw_frame_values": "0,1,2,3,4,5,10,15,40",
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+ "eval_max_steps": 3600,
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+ "eval_raw_reward": true,
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+ "eval_deterministic": true,
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+ "disable_reward_scaling": true,
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+ "frame_stack": 4,
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+ "action_history_decisions": 8,
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+ "max_episode_steps": 0,
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+ "simulator": "cpu",
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+ "episode_metrics_path": "results/checkpoints/deadly_corridor/decision_history_native35_temporal_25m_seed42/deadly_corridor_frame_stack_qwenoft_rtx3090_temporal_hist8_capacity1_native35_fs4_seed42/episode_metrics.jsonl",
181
+ "vizdoom_init_max_parallel": 10,
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+ "vizdoom_init_lock_timeout_sec": 5.0,
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+ "vizdoom_init_lock_max_wait_sec": 60.0,
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+ "vizdoom_init_retry_jitter_sec": 0.25,
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+ "eval_env_frameskip": 1,
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+ "fps": 35,
187
+ "command_line": "--mode train --algo APPO --env doom_deadly_corridor --experiment deadly_corridor_frame_stack_qwenoft_rtx3090_temporal_hist8_capacity1_native35_fs4_seed42 --train_dir results/checkpoints/deadly_corridor/decision_history_native35_temporal_25m_seed42 --restart_behavior resume --device gpu --seed 42 --episode_metrics_path results/checkpoints/deadly_corridor/decision_history_native35_temporal_25m_seed42/deadly_corridor_frame_stack_qwenoft_rtx3090_temporal_hist8_capacity1_native35_fs4_seed42/episode_metrics.jsonl --train_for_env_steps 25000000 --num_workers 32 --num_envs_per_worker 4 --num_policies 1 --batch_size 1024 --rollout 128 --recurrence 128 --num_epochs 2 --num_batches_per_epoch 2 --worker_num_splits 2 --learning_rate 0.0001 --gamma 0.99 --gae_lambda 0.95 --ppo_clip_ratio 0.1 --ppo_clip_value 0.2 --exploration_loss symmetric_kl --exploration_loss_coeff 0.001 --value_loss_coeff 0.5 --max_grad_norm 4.0 --rnn_type gru --rnn_size 512 --save_every_sec 600 --keep_checkpoints 5 --stats_avg 100 --experiment_summaries_interval 1 --async_rl True --use_rnn True --normalize_returns True --normalize_input True --latency-type profile_sample --latency-seed 42 --latency-profile-path results/profiling/profiles/openvla/1x-rtx3090/deadly_corridor/instance_a5037b165aa0cedc/profile.json --latency-profile-worker-slot 0 --simulated-worker-capacity 1 --add-latency-info False --eval-episodes 100 --eval-parallel-envs 1 --eval-max-steps 3600 --eval-deterministic True --eval-raw-reward --with_wandb True --wandb_project starvla_tasks --wandb_group deadly-corridor-fs4-qwenoft_rtx3090_temporal_hist8_capacity1_native35 --wandb_job_type deadly_corridor_decision_history_native35_temporal --wandb_tags deadly_corridor_decision_history_native35_temporal_25m_seed42 deadly-corridor frame_stack temporal qwenoft_rtx3090_temporal_hist8_capacity1_native35 fs4 seed42 --env-fps 35 --obs-fps 8.75 --res_w 128 --res_h 72 --wide_aspect_ratio False --frame_stack 4 --action-history-decisions 8 --simulator cpu --disable-reward-scaling True --hold-policy hold --ordering-policy latest_ready",
188
+ "cli_args": {
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+ "algo": "APPO",
190
+ "env": "doom_deadly_corridor",
191
+ "experiment": "deadly_corridor_frame_stack_qwenoft_rtx3090_temporal_hist8_capacity1_native35_fs4_seed42",
192
+ "train_dir": "results/checkpoints/deadly_corridor/decision_history_native35_temporal_25m_seed42",
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+ "restart_behavior": "resume",
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+ "device": "gpu",
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+ "seed": 42,
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+ "num_policies": 1,
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+ "async_rl": true,
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+ "worker_num_splits": 2,
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+ "num_workers": 32,
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+ "num_envs_per_worker": 4,
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+ "batch_size": 1024,
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+ "num_batches_per_epoch": 2,
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+ "num_epochs": 2,
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+ "rollout": 128,
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+ "recurrence": 128,
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+ "gamma": 0.99,
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+ "normalize_returns": true,
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+ "exploration_loss_coeff": 0.001,
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+ "value_loss_coeff": 0.5,
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+ "exploration_loss": "symmetric_kl",
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+ "gae_lambda": 0.95,
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+ "ppo_clip_ratio": 0.1,
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+ "ppo_clip_value": 0.2,
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+ "max_grad_norm": 4.0,
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+ "learning_rate": 0.0001,
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+ "normalize_input": true,
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+ "experiment_summaries_interval": 1,
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+ "stats_avg": 100,
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+ "train_for_env_steps": 25000000,
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+ "save_every_sec": 600,
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+ "keep_checkpoints": 5,
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+ "use_rnn": true,
223
+ "rnn_size": 512,
224
+ "rnn_type": "gru",
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+ "with_wandb": true,
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+ "wandb_project": "starvla_tasks",
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+ "wandb_group": "deadly-corridor-fs4-qwenoft_rtx3090_temporal_hist8_capacity1_native35",
228
+ "wandb_job_type": "deadly_corridor_decision_history_native35_temporal",
229
+ "wandb_tags": [
230
+ "deadly_corridor_decision_history_native35_temporal_25m_seed42",
231
+ "deadly-corridor",
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+ "frame_stack",
233
+ "temporal",
234
+ "qwenoft_rtx3090_temporal_hist8_capacity1_native35",
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+ "fs4",
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+ "seed42"
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+ ],
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+ "res_w": 128,
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+ "res_h": 72,
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+ "wide_aspect_ratio": false,
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+ "mode": "train",
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+ "env_fps": 35.0,
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+ "obs_fps": 8.75,
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+ "latency_type": "profile_sample",
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+ "latency_seed": 42,
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+ "latency_profile_path": "results/profiling/profiles/openvla/1x-rtx3090/deadly_corridor/instance_a5037b165aa0cedc/profile.json",
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+ "latency_profile_worker_slot": 0,
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+ "simulated_worker_capacity": 1,
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+ "add_latency_info": false,
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+ "hold_policy": "hold",
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+ "ordering_policy": "latest_ready",
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+ "eval_episodes": 100,
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+ "eval_parallel_envs": 1,
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+ "eval_max_steps": 3600,
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+ "eval_raw_reward": true,
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+ "eval_deterministic": true,
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+ "disable_reward_scaling": true,
258
+ "frame_stack": 4,
259
+ "action_history_decisions": 8,
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+ "simulator": "cpu",
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+ "episode_metrics_path": "results/checkpoints/deadly_corridor/decision_history_native35_temporal_25m_seed42/deadly_corridor_frame_stack_qwenoft_rtx3090_temporal_hist8_capacity1_native35_fs4_seed42/episode_metrics.jsonl",
262
+ "env_frameskip": 1,
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+ "eval_env_frameskip": 1,
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+ "output_dir": "outputs/tasks/deadly_corridor/decision_history_native35_temporal_25m_seed42/train/frame_stack/qwenoft_rtx3090_temporal_hist8_capacity1_native35/fs4/seed_42",
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+ "wandb_unique_id": "deadly-corridor-fs4-qwenoft_rtx3090_temporal_hist8_capacity1_native35-s42"
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+ },
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+ "git_hash": "unknown",
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+ "git_repo_name": "not a git repository",
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+ "output_dir": "outputs/tasks/deadly_corridor/decision_history_native35_temporal_25m_seed42/train/frame_stack/qwenoft_rtx3090_temporal_hist8_capacity1_native35/fs4/seed_42",
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+ "wandb_unique_id": "deadly-corridor-fs4-qwenoft_rtx3090_temporal_hist8_capacity1_native35-s42"
271
+ }
latency-aware/deadly-corridor/small-policy/sample-factory-qwenoft-rtx3090-temporal-hist8-capacity1-native35-s42-v1/provenance.json ADDED
@@ -0,0 +1,16 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "task": "deadly_corridor",
3
+ "method": "Sample Factory APPO; decision_v1 history of eight completed decisions",
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+ "training_seed": 42,
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+ "training_target_env_steps": 25000000,
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+ "wandb_run_id": "deadly-corridor-fs4-qwenoft_rtx3090_temporal_hist8_capacity1_native35-s42",
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+ "wandb_source_run": "saberrr-zju/starvla_tasks/deadly-corridor-fs4-qwenoft_rtx3090_temporal_hist8_capacity1_native35-s42",
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+ "source_checkpoint": "/mnt/ssd/latency-sensitive-bench/results/checkpoints/deadly_corridor/decision_history_native35_temporal_25m_seed42/deadly_corridor_frame_stack_qwenoft_rtx3090_temporal_hist8_capacity1_native35_fs4_seed42/checkpoint_p0/best_000044776_22925312_reward_2084.409.pth",
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+ "checkpoint_sha256": "62eee5b587bde20cc912fde9c068d92498a6433b62dec28f8e994004fb8e7e18",
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+ "checkpoint_selection": "training best",
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+ # demon attack — qwenoft temporal H8 profiled small policy
2
+
3
+ Sample Factory APPO small policy trained with an RTX 3090 temporal latency profile, one simulated inference worker, and an eight-decision causal history. This folder contains the training-selected best checkpoint and its exact Sample Factory config.
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+
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+ - W&B run ID: `demon-attack-fs4-qwenoft_rtx3090_temporal_hist8_capacity1-s42`
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+ - Checkpoint: `best_000048224_24690688_reward_9340.850.pth`
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+ - Training seed: 42; target: 25 million environment steps.
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+ - Profile SHA256: `9b1ecf42b4cbd1f28970668922610509f1e7e3302ff34aaa854b1795986eeccb`
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+
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+ The reward in the checkpoint filename is a training selection metric, not a formal evaluation result. See `provenance.json` for exact source paths and hashes.
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+ "wandb_job_type": "demon_attack_decision_history_temporal",
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+ "wandb_tags": [
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+ "demon-attack",
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+ "frame_stack",
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+ "temporal",
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+ "qwenoft_rtx3090_temporal_hist8_capacity1",
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+ "fs4",
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+ "seed42"
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+ "wandb_dir": "/mnt/ssd/latency-sensitive-bench/wandb",
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+ "with_pbt": false,
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+ "command_line": "--mode train --algo APPO --env latency_demon_attack --experiment demon_attack_frame_stack_qwenoft_rtx3090_temporal_hist8_capacity1_fs4_seed42 --train_dir results/checkpoints/demon_attack/decision_history_temporal_25m_seed42 --restart_behavior resume --device gpu --actor_worker_gpus 0 --env_gpu_observations True --env_gpu_actions True --gpu-env-batch-size 512 --seed 42 --episode_metrics_path results/checkpoints/demon_attack/decision_history_temporal_25m_seed42/demon_attack_frame_stack_qwenoft_rtx3090_temporal_hist8_capacity1_fs4_seed42/episode_metrics.jsonl --train_for_env_steps 25000000 --num_workers 1 --num_envs_per_worker 1 --num_policies 1 --batch_size 1024 --rollout 64 --recurrence 32 --num_epochs 2 --num_batches_per_epoch 8 --worker_num_splits 1 --max_policy_lag 300 --learning_rate 0.000303 --lr_schedule linear_decay --gamma 0.99 --gae_lambda 0.95 --ppo_clip_ratio 0.1 --ppo_clip_value 0.2 --value_loss_coeff 0.5 --max_grad_norm 0.0 --save_every_sec 600 --keep_checkpoints 5 --stats_avg 100 --experiment_summaries_interval 1 --batched_sampling True --async_rl True --batched_sampling True --use_rnn False --normalize_returns True --normalize_input True --latency-type profile_sample --latency-seed 42 --latency-profile-path results/profiling/profiles/openvla/1x-rtx3090/demon_attack/instance_a5037b165aa0cedc/profile.json --latency-profile-worker-slot 0 --simulated-worker-capacity 1 --add-latency-info False --eval-episodes 100 --eval-parallel-envs 1 --eval-max-steps 14400 --eval-deterministic True --eval-raw-reward --with_wandb True --wandb_project starvla_tasks --wandb_group demon-attack-fs4-qwenoft_rtx3090_temporal_hist8_capacity1 --wandb_job_type demon_attack_decision_history_temporal --wandb_tags demon_attack_decision_history_temporal_25m_seed42 demon-attack frame_stack temporal qwenoft_rtx3090_temporal_hist8_capacity1 fs4 seed42 --env_id ALE/DemonAttack-v5 --env-fps 60 --obs-fps 15.0 --screen_size 84 --noop_max 30 --reset-mode fire --frame_stack 4 --action-history-decisions 8 --terminal_on_life_loss True --clip_reward True --repeat_action_probability 0.0 --full_action_space False --max_episode_steps 25000 --simulator gpu --gpu-env-device auto --hold-policy hold --ordering-policy latest_ready",
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+ "algo": "APPO",
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latency-aware/flappy/small-policy/sample-factory-gr00t-rtx3090-temporal-hist8-capacity1-s42-v1/README.md ADDED
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1
+ # flappy — gr00t temporal H8 profiled small policy
2
+
3
+ Sample Factory APPO small policy trained with an RTX 3090 temporal latency profile, one simulated inference worker, and an eight-decision causal history. This folder contains the training-selected best checkpoint and its exact Sample Factory config.
4
+
5
+ - W&B run ID: `flappy-obs10-gr00t_rtx3090_temporal_hist8_capacity1-s42`
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+ - Checkpoint: `best_000048832_25001984_reward_3570.134.pth`
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+ - Training seed: 42; target: 25 million environment steps.
8
+ - Profile SHA256: `0654f7097e292cc837a483ef8e5f7ed9c3410fd684582b31b7d8358719452b60`
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+
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+ The reward in the checkpoint filename is a training selection metric, not a formal evaluation result. See `provenance.json` for exact source paths and hashes.
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+ "task": "flappy",
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+ "method": "Sample Factory APPO; decision_v1 history of eight completed decisions",
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latency-aware/flappy/small-policy/sample-factory-pi05-rtx3090-temporal-hist8-capacity1-s42-v1/README.md ADDED
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+ # flappy — pi05 temporal H8 profiled small policy
2
+
3
+ Sample Factory APPO small policy trained with an RTX 3090 temporal latency profile, one simulated inference worker, and an eight-decision causal history. This folder contains the training-selected best checkpoint and its exact Sample Factory config.
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+
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+ - W&B run ID: `flappy-obs10-pi05_rtx3090_temporal_hist8_capacity1-s42`
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+ - Checkpoint: `best_000045712_23429120_reward_1021.035.pth`
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+ - Training seed: 42; target: 25 million environment steps.
8
+ - Profile SHA256: `be2cd7a2a7fdf40c5c967d0c3cc16b912969d0ac0b4acc785aac3d0e4133df30`
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+
10
+ The reward in the checkpoint filename is a training selection metric, not a formal evaluation result. See `provenance.json` for exact source paths and hashes.
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latency-aware/flappy/small-policy/sample-factory-qwenoft-rtx3090-temporal-hist8-capacity1-s42-v1/README.md ADDED
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+ # flappy — qwenoft temporal H8 profiled small policy
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+
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+ Sample Factory APPO small policy trained with an RTX 3090 temporal latency profile, one simulated inference worker, and an eight-decision causal history. This folder contains the training-selected best checkpoint and its exact Sample Factory config.
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+
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+ - W&B run ID: `flappy-obs10-qwenoft_rtx3090_temporal_hist8_capacity1-s42`
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+ - Training seed: 42; target: 25 million environment steps.
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+ - Profile SHA256: `c266cba7ebac05c7e37bc83f1f16fe4b27dab97942ff43290e6c41514f6e39fc`
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+
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+ The reward in the checkpoint filename is a training selection metric, not a formal evaluation result. See `provenance.json` for exact source paths and hashes.
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latency-aware/flappy/small-policy/sample-factory-qwenoft-rtx3090-temporal-hist8-capacity1-s42-v1/provenance.json ADDED
@@ -0,0 +1,16 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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