Publish atlantis qwengr00t H8 evaluation artifacts

zero-latency/atlantis/vla/starvla-qwengr00t-h1/atlantis-qwengr00t-hist8-zero-s42-v1/README.md

@@ -1,8 +1,8 @@
-# Atlantis qwengr00t zero-latency H8 VLA
+# Atlantis qwengr00t zero-trained H8 VLA
 
 Current RGB and eight binary decision-history windows; action horizon one. Initialized from the pinned Qwen3-VL-4B backbone and random action head.
 
 - Training: 5000 steps, seed 42, global batch 128
 - W&B: https://wandb.ai/saberrr-zju/starvla_tasks/runs/60bc68a7
-- Evaluation: 100 episodes, seeds 1000000–1000099, GPU simulator, parallel 32, capacity 1, 60/15 Hz, 7200 raw-frame cap, zero latency
-- Mean raw return: 39662.0
+- Evaluation: 100 episodes, seeds 1000000–1000099, GPU simulator, parallel 32, capacity 1, 60/15 Hz, 7200 raw-frame cap, profile latency
+- Mean raw return: 8167.0

zero-latency/atlantis/vla/starvla-qwengr00t-h1/atlantis-qwengr00t-hist8-zero-s42-v1/eval_profile.json

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+  "experiment_name": "atlantis-qwengr00t-hist8-zero-s42-v1-step5000-history01-profile-par32",
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+  "timestamp_utc": "2026-09-24T12:37:10.944664+00:00"
+}

zero-latency/atlantis/vla/starvla-qwengr00t-h1/atlantis-qwengr00t-hist8-zero-s42-v1/evaluation_profile/action_audit.json

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+{
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+}

zero-latency/atlantis/vla/starvla-qwengr00t-h1/atlantis-qwengr00t-hist8-zero-s42-v1/evaluation_profile/eval_config.yaml

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+experiment:
+  name: atlantis-qwengr00t-hist8-zero-s42-v1-step5000-history01-profile-par32
+  seed: 1000000
+backend:
+  type: sample_factory
+  algo: APPO
+  device: cuda
+  train_dir: results/sample_factory
+  restart_behavior: resume
+  run_mode: eval
+  extra_args:
+  - --encoder_conv_architecture
+  - convnet_simple
+executor:
+  mode: simulated
+  simulated_worker_capacity: 1
+  simulated_inference_pool: true
+  inference_devices:
+  - cuda:0
+  - cuda:1
+  inference_batch_size: 16
+env:
+  name: gymnasium
+  task_name: atlantis
+  env_id: LatencyBench/Atlantis-v0
+  registration_imports:
+  - latency_bench.envs.gymnasium_atlantis
+  make_kwargs:
+    base_env_id: ALE/Atlantis-v5
+    render_mode: rgb_array
+    screen_size: 84
+    noop_max: 30
+    base_make_kwargs:
+      obs_type: rgb
+      frameskip: 1
+      repeat_action_probability: 0.0
+      full_action_space: false
+      mode: 0
+      difficulty: 0
+      max_num_frames_per_episode: 108000
+  env_fps: 60
+  obs_fps: 15
+  frame_stack: 1
+  simulator: gpu
+  terminal_on_life_loss: false
+  clip_reward: false
+  noop_action: noop
+  action_map:
+    noop: 0
+    fire: 1
+    rightfire: 2
+    leftfire: 3
+  action_order:
+  - noop
+  - fire
+  - rightfire
+  - leftfire
+  base_prompt: 'Defend Atlantis by firing at descending enemies. Choose exactly one
+    action from: noop, fire, rightfire, leftfire.'
+  obs_resize:
+  - 224
+  - 224
+  gpu_env_device: auto
+  noop_max: 30
+  action_history_decisions: 8
+latency:
+  method: temporal
+  profile_path: /home/ubuntu/codex/atari-hist8-20260924/outputs/tasks/atari_hist8_v1/teacher_configs/atlantis-qwengr00t/profile/profile.json
+  profile_worker_slot: 0
+  seed: 271828
+  add_latency_info: false
+scheduler:
+  hold_policy: hold
+  ordering_policy: issue_order_fifo
+policy:
+  type: starvla
+  actions:
+  - noop
+  - fire
+  - rightfire
+  - leftfire
+  checkpoint_path: /home/ubuntu/codex/atari-hist8-20260924/outputs/tasks/atari_hist8_v1/bundles/atlantis-qwengr00t-hist8-zero-s42-v1/checkpoints/model.pt
+  model_config_path: /home/ubuntu/codex/atari-hist8-20260924/outputs/tasks/atari_hist8_v1/bundles/atlantis-qwengr00t-hist8-zero-s42-v1/config.yaml
+  task_manifest_path: /home/ubuntu/codex/atari-hist8-20260924/outputs/tasks/atari_hist8_v1/bundles/atlantis-qwengr00t-hist8-zero-s42-v1/manifest.json
+  device: cuda:0
+  unnorm_key: new_embodiment
+  prompt_mode: latency_neutral
+  backbone_path: /home/ubuntu/.cache/huggingface/hub/models--Qwen--Qwen3-VL-4B-Instruct/snapshots/ebb281ec70b05090aa6165b016eac8ec08e71b17
+  worker_python_executable: /home/ubuntu/miniconda3/envs/starvla_rl_games_openvla/bin/python3.10
+  state_source: transport
+training:
+  train_for_env_steps: 1000000
+  num_workers: 4
+  num_envs_per_worker: 16
+  worker_num_splits: 1
+  num_policies: 1
+  batch_size: 1024
+  rollout: 64
+  recurrence: 32
+  num_epochs: 2
+  num_batches_per_epoch: 8
+  max_policy_lag: 300
+  learning_rate: 0.000303
+  lr_schedule: constant
+  nonlinearity: elu
+  gamma: 0.99
+  gae_lambda: 0.95
+  ppo_clip_ratio: 0.1
+  ppo_clip_value: 0.2
+  exploration_loss: entropy
+  exploration_loss_coeff: 0.003
+  value_loss_coeff: 0.5
+  max_grad_norm: 0.0
+  adam_eps: 1.0e-06
+  obs_scale: 1.0
+  adaptive_stddev: false
+  with_vtrace: false
+  async_rl: true
+  use_rnn: false
+  normalize_input: true
+  normalize_returns: true
+  stats_avg: 100
+  experiment_summaries_interval: 1
+  save_every_sec: 600
+  keep_checkpoints: 5
+evaluation:
+  eval_interval_steps: null
+  eval_episodes: 100
+  eval_parallel_envs: 32
+  eval_max_steps: 7200
+  eval_deterministic: true
+  eval_suites:
+    fixed: []
+    normal: []
+    uniform: []
+  latency_bench_env_backend: atlantis_gpu_batched
+  eval_raw_reward: true
+logging:
+  output_dir: /home/ubuntu/codex/atari-hist8-20260924/outputs/tasks/atari_hist8_v1/evals/atlantis-qwengr00t-hist8-zero-s42-v1/zero_to_profile
+  video:
+    enabled: false
+    num_bins: 1
+  save_step_records: true
+  save_action_records: true
+  save_latency_records: true
+  wandb_project: null
+  wandb_group: null
+  wandb_job_type: null
+  wandb_tags: ''

zero-latency/atlantis/vla/starvla-qwengr00t-h1/atlantis-qwengr00t-hist8-zero-s42-v1/evaluation_profile/provenance.json

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+{
+  "collection": {
+    "episodes": 200,
+    "filter_preset": "none",
+    "history": "decision_v1",
+    "history_decisions": 8,
+    "history_source": "teacher_transport",
+    "max_episode_raw_frames": 7200,
+    "rollout_overrides": {
+      "env_fps": 60,
+      "fixed_latency_ms": 0.0,
+      "latency_type": "fixed",
+      "obs_fps": 15,
+      "seed": 42
+    },
+    "student_image_frames": 1,
+    "teacher_checkpoint": "best_000026560_13598720_reward_675769.000.pth",
+    "teacher_path": "zero-latency/atlantis/small-policy/sample-factory-hist8-cpu15m-s0-v1",
+    "teacher_repo": "latency-sensitive-bench/benchmark-models",
+    "teacher_revision": "dfaeecb84cd6b5dfcc3adc0935d0ae86d0b504d2",
+    "teacher_sha256": "d41d728d8c2329d3623eb9e01bd9f3f2df4fc0d4f6f2c1f799c4badc24af78c5",
+    "train_labels": 324000,
+    "training_latency_condition": "zero"
+  },
+  "training_run_id": "atlantis-qwengr00t-hist8-zero-s42-v1",
+  "training_step": 5000,
+  "global_batch": 128,
+  "base_model": "Qwen/Qwen3-VL-4B-Instruct",
+  "wandb_run_id": "60bc68a7",
+  "checkpoint_sha256": "dc7081c898fd8324d5c9aa892b5221ad7388a83428cc3508c67b30fc71d0761a",
+  "eval_protocol_version": "hist8-history01-sf-render-v4",
+  "history_encoding": "binary_0_1",
+  "episodes": 100,
+  "env_condition": "profile",
+  "parallel_envs": 32,
+  "max_episode_raw_frames": 7200,
+  "inference_devices": [
+    "cuda:0",
+    "cuda:1"
+  ],
+  "episode_seeds": [
+    1000000,
+    1000099
+  ],
+  "profile_sha256": "13e970f85825c898ecb5730ff6adb6c71995a68406227733311a15b3f0c202e9"
+}

zero-latency/atlantis/vla/starvla-qwengr00t-h1/atlantis-qwengr00t-hist8-zero-s42-v1/profile_publication.json

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+{
+  "model": "qwengr00t",
+  "model_publication": {
+    "checkpoint_sha256": "dc7081c898fd8324d5c9aa892b5221ad7388a83428cc3508c67b30fc71d0761a",
+    "episodes": 100,
+    "mean_return": 39662.0,
+    "model": "qwengr00t",
+    "path": "zero-latency/atlantis/vla/starvla-qwengr00t-h1/atlantis-qwengr00t-hist8-zero-s42-v1",
+    "repo_id": "latency-sensitive-bench/benchmark-models",
+    "revision": "aaf650c36c93cb8ff87d3a5ff6ffd635d24c9004",
+    "run_id": "atlantis-qwengr00t-hist8-zero-s42-v1",
+    "task": "atlantis",
+    "training_status": "complete",
+    "zero_evaluation_status": "complete"
+  },
+  "profile": {
+    "GPU_CLASS": "1x-rtx3090",
+    "INSTANCE_ID": "instance_d907cdaf680040e0",
+    "PROFILE_PATH": "results/profiling/profiles/qwengr00t/1x-rtx3090/atlantis/instance_d907cdaf680040e0/profile.json",
+    "PROFILE_REF": "qwengr00t/1x-rtx3090/atlantis/instance_d907cdaf680040e0",
+    "RUN_ID": "20260924T112532341532Z"
+  },
+  "profile_path": "profiles/qwengr00t/1x-rtx3090/atlantis/instance_d907cdaf680040e0/profile.json",
+  "profile_repo": "latency-sensitive-bench/profiles",
+  "profile_revision": "a00f633aa3227e2be8648b4f1337d7ccd188d18f",
+  "profile_sha256": "13e970f85825c898ecb5730ff6adb6c71995a68406227733311a15b3f0c202e9",
+  "task": "atlantis"
+}

zero-latency/atlantis/vla/starvla-qwengr00t-h1/atlantis-qwengr00t-hist8-zero-s42-v1/publication_status.json

@@ -1,6 +1,8 @@
 {
   "episodes": 100,
-  "mean_return": 39662.0,
+  "mean_return": 8167.0,
+  "profile_evaluation_status": "complete",
+  "profile_mean_return": 8167.0,
   "training_status": "complete",
   "zero_evaluation_status": "complete"
 }