Publish hist8 zero deadly_corridor qwenpi_v3 step5000

zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/README.md

@@ -0,0 +1,36 @@
+# deadly_corridor / qwenpi_v3 — hist8 zero training
+
+Run `deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2`; final optimizer step **5000**, seed **42**. [W&B](https://wandb.ai/saberrr-zju/starvla_tasks/runs/2f9d64db).
+
+Checkpoint SHA256: `ba72ed7f1ba94daa0eba7d36fdb36eb7ce76db4a448bdbb29499e3f72ed0912f`.
+
+## Model and inputs
+
+Full StarVLA state dict in `checkpoints/model.pt` (original evaluated bytes). Initialize the matching Qwen model with `config.yaml` and `dataset_statistics.json`. Base: `Qwen/Qwen3-VL-4B-Instruct@ebb281ec70b05090aa6165b016eac8ec08e71b17`; model-specific action head trained from random initialization.
+
+One current RGB image, eight prior causal decision histories (120 raw 0/1 values), action horizon 1. `h1` in this repository path is the action horizon; `hist8` is input history. Pass history as `transport`, preserve all-zero reset, and use identity state normalization. Prompt and action order are in `task_contract.json` and `manifest.json`.
+
+Training: 2 GPUs, bf16/ZeRO-2, batch 64 per rank, accumulation 1, global batch 128; 16 dataloader workers per rank and prefetch 4. Backbone LR 3e-6, action head 1e-4; other groups retain the recorded configuration. Warmup 100, cosine min_lr_rate 1/30, 5000 steps. Full historical training configuration and code snapshot are included.
+
+## Formal evaluation
+
+| Environment | Episodes | Return mean ± std | Mean raw frames |
+|---|---:|---:|---:|
+| zero | 100 | 2104.0864 ± 572.5117 | 175.16 |
+| profile | 100 | 140.9386 ± 170.2019 | 75.27 |
+
+Seeds 1,000,000–1,000,099; parallel 32; capacity 1; FPS/decision Hz 35/8.75; max 3600 raw frames. Zero-trained models have both zero and profile evaluations; profile-trained models have the matching profile evaluation. `profiles/profile.json` is the exact model-specific latency profile, with SHA in provenance.
+
+Each `evaluations/<condition>/` contains the evaluated config, 100 episode records, action audit including raw-score summaries, verification, provenance and evaluator code snapshot. Evaluation configs retain original machine paths as execution evidence; replace checkpoint, model-config, backbone, profile and output paths when replaying locally. Deadly Corridor requires 160×120 RGB with HUD, no crosshair, weapon enabled, decals/particles disabled before resizing.
+
+These are one-training-seed results. Architectures use different latency profiles. Zero/profile training also uses different teachers and collected data, so their score difference is not an isolated learning-rate ablation.
+
+## Download
+
+```python
+from huggingface_hub import snapshot_download
+prefix = "zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2"
+repo = snapshot_download("latency-sensitive-bench/benchmark-models", allow_patterns=[prefix + "/**"])
+```
+
+Use a pinned repository commit for reproduction. Preserve the original checkpoint SHA above. Optimizer/RNG resume state remains in the source training archive; this publication contains the inference checkpoint.

zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/bundle.complete.json

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+{
+  "checkpoint_sha256": "ba72ed7f1ba94daa0eba7d36fdb36eb7ce76db4a448bdbb29499e3f72ed0912f",
+  "training_step": 5000
+}

zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/checkpoint.sha256

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zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/checkpoints/model.pt

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+size 10922868893

zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/collection_quality_report.json

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+{
+  "episodes": 8250,
+  "train_episodes": 7425,
+  "val_episodes": 825,
+  "train_labels": 328296,
+  "val_labels": 36395,
+  "raw_frames_quantiles": [
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+    180.0,
+    184.0,
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+    2276.1326248168943,
+    2281.683174133301,
+    2285.899638366699,
+    2287.405059814453
+  ],
+  "termination_reasons": {
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+    "50": 3,
+    "51": 2,
+    "52": 14,
+    "53": 2
+  },
+  "previous_decision_admitted_fraction": 1.0
+}

zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/config.full.yaml

@@ -0,0 +1,302 @@
+framework:
+  name: QwenPI_v3
+  qwenvl:
+    base_vlm: /home/ubuntu/.cache/huggingface/hub/models--Qwen--Qwen3-VL-4B-Instruct/snapshots/ebb281ec70b05090aa6165b016eac8ec08e71b17
+    attn_implementation: flash_attention_2
+    vl_hidden_dim: 2560
+    num_vl_layers: 36
+    enable_gradient_checkpointing: true
+  action_model:
+    action_model_type: LayerwiseFM
+    action_dim: 7
+    state_dim: 120
+    state_encoding: continuous_projector
+    task_objective: null
+    action_horizon: 1
+    repeated_diffusion_steps: 2
+    num_inference_timesteps: 4
+    add_pos_embed: true
+    max_seq_len: 1024
+    num_target_vision_tokens: 32
+    noise_beta_alpha: 1.5
+    noise_beta_beta: 1.0
+    noise_s: 0.999
+    num_timestep_buckets: 1000
+    diffusion_model_cfg:
+      action_dit_hidden_dim: 1024
+      dropout: 0.2
+      final_dropout: true
+      interleave_self_attention: true
+      norm_type: ada_norm
+      positional_embeddings: null
+      attention_head_dim: 64
+      output_dim: 1024
+      num_layers: 36
+      input_embedding_dim: 1024
+      cross_attention_dim: 1024
+      num_attention_heads: 16
+    loss_type: l1
+    future_action_window_size: 0
+    past_action_window_size: 0
+    action_env_dim: 7
+  kv_memory:
+    enabled: false
+    window: 4
+    rollout_len: 8
+    packed_train: false
+    rebased_sink: true
+datasets:
+  vla_data:
+    dataset_py: lerobot_datasets
+    include_state: true
+    data_root_dir: /home/ubuntu/codex/hist8-vla-v2-20260923/outputs/tasks/decision_history_vla_hist8_v2/data_zero/deadly_corridor
+    data_mix: lerobot
+    eval_data_mix: lerobot__val
+    custom_mixtures_path: /home/ubuntu/codex/hist8-vla-v2-20260923/outputs/tasks/decision_history_vla_hist8_v2/data_zero/deadly_corridor/_generated_mixtures/lerobot.json
+    action_type: discrete
+    sequential_step_sampling: false
+    eval_sequential_step_sampling: null
+    num_workers: 16
+    eval_num_workers: 16
+    prefetch_factor: 4
+    persistent_workers: true
+    pin_memory: true
+    shuffle: true
+    action_balance:
+      enabled: false
+      strategy: balanced_epoch
+      action_key: action_id
+      target_flap_fraction: 0.3
+      noop_id: 0
+      flap_id: 1
+    latency_curriculum:
+      enabled: false
+      strategy: exclusive
+      latencies: null
+      phase_steps: null
+      phase_distributions: null
+      new_latency_passes: 1.0
+      replay_passes: 0.25
+      target_total_passes: 2.0
+      final_equalization: true
+      step_budget_mode: auto
+      eval_at_phase_end: false
+      save_at_phase_end: false
+      computed_plan: null
+    per_device_batch_size: 64
+    load_all_data_for_training: true
+    num_obs_frames: 1
+    image_mode: single
+    prompt_mode: raw
+    stitch_grid:
+    - 2
+    - 2
+    obs_image_size: null
+    video_backend: torchvision_av
+dataset:
+  source_hf: ''
+  config_name: null
+  source_subdir: null
+  converted_name: deadly_corridor_train
+  single_source_hf: ''
+  mixed_source_hf: ''
+  single_converted_name: deadly_corridor_train
+  mixed_converted_name: deadly_corridor_mixed_latency_train
+  single_latency_filter: null
+  mixed_latency_filter: null
+  force_download: false
+  setup_force: false
+  skip_verification: false
+  target_latency_unit: observation_steps
+  verify_rows: 200
+  max_episodes: null
+  episodes_per_latency: null
+  latency_filter: null
+  debug_subset:
+    enabled: false
+    max_episodes: 5
+    suffix: debug
+base_model:
+  repo_id: Qwen/Qwen3-VL-4B-Instruct
+initialization:
+  checkpoint_local_dir: null
+  checkpoint_hf_repo_id: null
+  checkpoint_filename: null
+trainer:
+  max_train_steps: 5000
+  num_warmup_steps: 100
+  save_interval: 500
+  eval_interval: 500
+  eval_num_batches: 50
+  per_latency_eval_num_batches: null
+  eval_action_classification: false
+  eval_action_classification_interval: null
+  cc_f1_tolerance: 1
+  learning_rate:
+    base: 3.0e-05
+    qwen_vl_interface: 3.0e-06
+    action_model: 0.0001
+  lr_scheduler_type: cosine_with_min_lr
+  scheduler_specific_kwargs:
+    min_lr_rate: 0.03333333333333333
+  freeze_modules: ''
+  freeze_vit: false
+  freeze_tied_embedding: false
+  freeze_llm_layers: []
+  loss_scale:
+    vla: 1.0
+    vlm: 0.0
+  max_grad_norm: 1.0
+  weight_decay: 0.0
+  logging_frequency: 1
+  profile_timing:
+    enabled: false
+    log_interval: 10
+  gradient_clipping: 1.0
+  gradient_accumulation_steps: 1
+  distributed_backend: deepspeed
+  is_resume: false
+  pretrained_checkpoint: null
+  resume_step: 0
+  reload_modules: null
+  optimizer:
+    name: AdamW
+    betas:
+    - 0.9
+    - 0.95
+    eps: 1.0e-08
+    weight_decay: 1.0e-08
+    fused: true
+  save_format: pt
+  hist8_diagnostics:
+    steps:
+    - 0
+    - 500
+    - 1000
+    - 2500
+    - 5000
+    sample_count: 2048
+    noise_seeds:
+    - 1729
+    - 1730
+    - 1731
+    - 1732
+    sample_seed: 42
+    batch_size: 8
+    bootstrap_repeats: 4000
+workspace_dir: WORKSPACE_DIR
+run_root_dir: /home/ubuntu/codex/hist8-vla-v2-20260923/outputs/tasks/decision_history_vla_hist8_v2/train
+seed: 42
+wandb_entity: saberrr-zju
+wandb_project: starvla_tasks
+auth:
+  env_file: null
+  hf_token_env: HF_TOKEN
+  wandb_api_key_env: WANDB_API_KEY
+paths:
+  run_root_dir: results/Checkpoints
+  dataset_local_dir: playground/Datasets/rl_games
+  dataset_cache_dir: null
+  base_model_dir: /home/ubuntu/.cache/huggingface/hub/models--Qwen--Qwen3-VL-4B-Instruct/snapshots/ebb281ec70b05090aa6165b016eac8ec08e71b17
+  accelerate_config: starVLA/config/deepseeds/deepspeed_zero2.yaml
+launch:
+  use_accelerate: true
+  gpus: null
+  num_processes: 1
+  dry_run: false
+conda:
+  enabled: true
+  env_name: null
+rl_games:
+  model_alias: pi-0.5
+  env_eval:
+    image_size: 224
+    frameskip: 4
+    image_transform: raw_rgb
+    prompt_mode: raw
+    ghost_trail:
+      history_frames: 5
+      gamma: 1.3
+      min_alpha: 35
+      scroll_px_per_step: 4.0
+      ground_fraction: 0.22
+    seed: 42
+    fixed_episode_seeds: true
+    latency_seed_stride: 0
+    task_seed_stride: 0
+    task_description: You are playing Deadly Corridor in VizDoom. Choose actions from
+      MOVE_FORWARD, MOVE_BACKWARD, MOVE_LEFT, MOVE_RIGHT, TURN_LEFT, TURN_RIGHT, ATTACK.
+    eval_parallel_envs: 5
+    action_chunk_execution:
+      enabled: false
+      chunk_size: null
+    deadly:
+      action_layout: multibinary_7
+      multibinary_threshold: null
+    enabled: false
+    eval_backend: latency_bench
+    distributed_mode: none
+    vectorized:
+      enabled: false
+      batch_size: 1
+    latency:
+      prompt_map_path: null
+      mode: single
+      values:
+      - 0
+    mid_train:
+      enabled: false
+      interval_steps: 100
+      latencies:
+      - 0
+      num_episodes: 5
+      max_steps_per_episode: 3600
+    post_train:
+      enabled: false
+      latencies:
+      - 0
+      - 1
+      - 2
+      - 3
+      - 4
+      num_episodes: 5
+      max_steps_per_episode: 3600
+  task: deadly_corridor
+  deadly_corridor_loss_type: null
+  initialization_mode: scratch
+  action_carrier: native
+model: pi05
+env: deadly_corridor
+init: scratch
+mode: single
+checkpoint:
+  load: none
+  hf_repo_id: null
+  save_best_model: false
+  save_final_model: true
+  save_pt_file: true
+  save_training_state: true
+  save_safetensors_file: false
+  local:
+    keep_last_n: 2
+  sync:
+    enabled: false
+    repo_id: null
+    keep_last_n: 0
+    sync_every_n_checkpoints: 1
+    resume_policy: local_latest
+run_id: deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2
+output_dir: /home/ubuntu/codex/hist8-vla-v2-20260923/outputs/tasks/decision_history_vla_hist8_v2/train/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2
+config_yaml: /home/ubuntu/codex/hist8-vla-v2-20260923/outputs/tasks/decision_history_vla_hist8_v2/train/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/train.yaml
+is_debug: false
+version_id: '0.21'
+wandb_name: deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2
+wandb_group: decision-history-vla-h8-v2
+wandb_tags:
+- deadly_corridor
+- qwenpi_v3
+- hist8-v2
+- history01
+- scratch
+- zero-latency
+training_latency_condition: zero-latency

zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/config.yaml

@@ -0,0 +1,57 @@
+framework:
+  name: QwenPI_v3
+  qwenvl:
+    base_vlm: Qwen/Qwen3-VL-4B-Instruct
+    attn_implementation: flash_attention_2
+    vl_hidden_dim: 2560
+    num_vl_layers: 36
+    enable_gradient_checkpointing: true
+  action_model:
+    action_model_type: LayerwiseFM
+    action_dim: 7
+    state_dim: 120
+    state_encoding: continuous_projector
+    task_objective: null
+    action_horizon: 1
+    repeated_diffusion_steps: 2
+    num_inference_timesteps: 4
+    add_pos_embed: true
+    max_seq_len: 1024
+    num_target_vision_tokens: 32
+    noise_beta_alpha: 1.5
+    noise_beta_beta: 1.0
+    noise_s: 0.999
+    num_timestep_buckets: 1000
+    diffusion_model_cfg:
+      action_dit_hidden_dim: 1024
+      dropout: 0.2
+      final_dropout: true
+      interleave_self_attention: true
+      norm_type: ada_norm
+      positional_embeddings: null
+      attention_head_dim: 64
+      output_dim: 1024
+      num_layers: 36
+      input_embedding_dim: 1024
+      cross_attention_dim: 1024
+      num_attention_heads: 16
+    loss_type: l1
+    future_action_window_size: 0
+    past_action_window_size: 0
+    action_env_dim: 7
+  kv_memory:
+    enabled: false
+    window: 4
+    rollout_len: 8
+    packed_train: false
+    rebased_sink: true
+version_id: '0.21'
+datasets:
+  vla_data:
+    include_state: true
+    obs_image_size: null
+    image_mode: single
+    num_obs_frames: 1
+    robot_type: rl_games_deadly_corridor
+trainer:
+  pretrained_checkpoint: null

zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/dataset_statistics.json

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zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/eval_l0.json

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zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/eval_profile.json

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zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/evaluations/profile/eval_config.yaml

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+experiment:
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+  seed: 1000000
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zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/evaluations/profile/provenance.json

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+}

zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/evaluations/profile/resolved_config.yaml

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+experiment:
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+  seed: 1000000
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zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/evaluations/profile/verification.json

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zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/evaluations/zero/action_audit.json

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zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/evaluations/zero/eval_config.yaml

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+experiment:
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+  seed: 1000000
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+  actions:
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+  - MOVE_LEFT
+  - MOVE_RIGHT
+  - TURN_LEFT
+  - TURN_RIGHT
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+  checkpoint_path: /home/ubuntu/codex/hist8-vla-v2-20260923/outputs/tasks/decision_history_vla_hist8_v2/bundles/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/checkpoints/model.pt
+  model_config_path: /home/ubuntu/codex/hist8-vla-v2-20260923/outputs/tasks/decision_history_vla_hist8_v2/bundles/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/config.yaml
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+  wandb_tags: ''

zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/evaluations/zero/provenance.json

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+{
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+}

zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/evaluations/zero/resolved_config.yaml

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+experiment:
+  name: deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2-step5000-history01-zero-par32
+  seed: 1000000
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+  - MOVE_BACKWARD
+  - MOVE_LEFT
+  - MOVE_RIGHT
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+  - TURN_RIGHT
+  - ATTACK
+  checkpoint_path: /home/ubuntu/codex/hist8-vla-v2-20260923/outputs/tasks/decision_history_vla_hist8_v2/bundles/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/checkpoints/model.pt
+  model_config_path: /home/ubuntu/codex/hist8-vla-v2-20260923/outputs/tasks/decision_history_vla_hist8_v2/bundles/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/config.yaml
+  device: cuda:0
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+  action_layout: multibinary_7
+  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
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zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/provenance.json

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+  "base_prompt": "You are playing Deadly Corridor in VizDoom. Your goal is to survive the corridor, fight enemies, and reach the green armor vest at the far end. The available actions are: MOVE_FORWARD, MOVE_BACKWARD, MOVE_LEFT, MOVE_RIGHT, TURN_LEFT, TURN_RIGHT, and ATTACK. Choose the best next action from the current visual observation.",
+  "checkpoint_config": {
+    "actor_critic_share_weights": true,
+    "actor_worker_gpus": [],
+    "adam_beta1": 0.9,
+    "adam_beta2": 0.999,
+    "adam_eps": 1e-06,
+    "adaptive_stddev": true,
+    "add_latency_info": false,
+    "algo": "APPO",
+    "async_rl": true,
+    "batch_size": 1024,
+    "batched_sampling": false,
+    "benchmark": false,
+    "cli_args": {
+      "add_latency_info": false,
+      "algo": "APPO",
+      "async_rl": true,
+      "batch_size": 1024,
+      "device": "gpu",
+      "disable_reward_scaling": true,
+      "env": "doom_deadly_corridor",
+      "env_fps": 35.0,
+      "env_frameskip": 1,
+      "episode_metrics_path": "results/checkpoints/jitter_destructiveness/real_profile/teachers_latency0/deadly_corridor_teacher_fixed_l0_obs8p75_seed0/episode_metrics.jsonl",
+      "eval_deterministic": true,
+      "eval_env_frameskip": 1,
+      "eval_episodes": 100,
+      "eval_max_steps": 7200,
+      "eval_parallel_envs": 1,
+      "eval_raw_reward": true,
+      "experiment": "deadly_corridor_teacher_fixed_l0_obs8p75_seed0",
+      "experiment_summaries_interval": 1,
+      "exploration_loss": "symmetric_kl",
+      "exploration_loss_coeff": 0.001,
+      "fixed_latency_ms": 0.0,
+      "frame_stack": 4,
+      "gae_lambda": 0.95,
+      "gamma": 0.99,
+      "hold_policy": "hold",
+      "keep_checkpoints": 5,
+      "latency_type": "fixed",
+      "learning_rate": 0.0001,
+      "max_grad_norm": 4.0,
+      "mode": "train",
+      "normalize_input": true,
+      "normalize_returns": true,
+      "num_batches_per_epoch": 2,
+      "num_envs_per_worker": 4,
+      "num_epochs": 2,
+      "num_policies": 1,
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+      "ordering_policy": "latest_ready",
+      "ppo_clip_ratio": 0.1,
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+      "recurrence": 128,
+      "res_h": 72,
+      "res_w": 128,
+      "restart_behavior": "resume",
+      "rnn_size": 512,
+      "rnn_type": "gru",
+      "rollout": 128,
+      "save_every_sec": 600,
+      "seed": 0,
+      "simulator": "cpu",
+      "stats_avg": 100,
+      "train_dir": "results/checkpoints/jitter_destructiveness/real_profile/teachers_latency0",
+      "train_for_env_steps": 25000000,
+      "use_rnn": true,
+      "value_loss_coeff": 0.5,
+      "wandb_group": "deadly-corridor-obs8p75-fixed_l0",
+      "wandb_job_type": "sample_factory",
+      "wandb_project": "latency-sensitive-bench",
+      "wandb_tags": [
+        "real_profile_latency0_teacher",
+        "deadly-corridor",
+        "teacher",
+        "fixed",
+        "fixed_l0",
+        "obs8p75",
+        "seed0"
+      ],
+      "wide_aspect_ratio": false,
+      "with_wandb": true,
+      "worker_num_splits": 2
+    },
+    "command_line": "--mode train --algo APPO --env doom_deadly_corridor --experiment deadly_corridor_teacher_fixed_l0_obs8p75_seed0 --train_dir results/checkpoints/jitter_destructiveness/real_profile/teachers_latency0 --restart_behavior resume --device gpu --seed 0 --episode_metrics_path results/checkpoints/jitter_destructiveness/real_profile/teachers_latency0/deadly_corridor_teacher_fixed_l0_obs8p75_seed0/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 fixed --fixed-latency-ms 0.0 --add-latency-info False --eval-episodes 100 --eval-parallel-envs 1 --eval-max-steps 7200 --eval-deterministic True --eval-raw-reward --with_wandb True --wandb_project latency-sensitive-bench --wandb_group deadly-corridor-obs8p75-fixed_l0 --wandb_job_type sample_factory --wandb_tags real_profile_latency0_teacher deadly-corridor teacher fixed fixed_l0 obs8p75 seed0 --env-fps 35 --obs-fps 8.75 --res_w 128 --res_h 72 --wide_aspect_ratio False --frame_stack 4 --simulator cpu --disable-reward-scaling True --hold-policy hold --ordering-policy latest_ready",
+    "continuous_tanh_scale": 0.0,
+    "decoder_mlp_layers": [],
+    "decorrelate_envs_on_one_worker": true,
+    "decorrelate_experience_max_seconds": 0,
+    "default_niceness": 0,
+    "device": "gpu",
+    "disable_reward_scaling": true,
+    "encoder_conv_architecture": "convnet_simple",
+    "encoder_conv_mlp_layers": [
+      512
+    ],
+    "encoder_mlp_layers": [
+      512,
+      512
+    ],
+    "env": "doom_deadly_corridor",
+    "env_fps": 35,
+    "env_frameskip": 1,
+    "env_framestack": 1,
+    "env_gpu_actions": false,
+    "env_gpu_observations": true,
+    "episode_metrics_path": "results/checkpoints/jitter_destructiveness/real_profile/teachers_latency0/deadly_corridor_teacher_fixed_l0_obs8p75_seed0/episode_metrics.jsonl",
+    "eval_deterministic": true,
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+    "eval_episodes": 100,
+    "eval_latency_raw_frame_values": "0,1,2,3,4,5,10,15,40",
+    "eval_max_steps": 7200,
+    "eval_parallel_envs": 1,
+    "eval_raw_reward": true,
+    "experiment": "deadly_corridor_teacher_fixed_l0_obs8p75_seed0",
+    "experiment_summaries_interval": 1,
+    "exploration_loss": "symmetric_kl",
+    "exploration_loss_coeff": 0.001,
+    "fixed_latency_ms": 0.0,
+    "flush_summaries_interval": 30,
+    "force_envs_single_thread": false,
+    "fps": 35,
+    "frame_stack": 4,
+    "gae_lambda": 0.95,
+    "gamma": 0.99,
+    "git_hash": "unknown",
+    "git_repo_name": "not a git repository",
+    "heartbeat_interval": 20,
+    "heartbeat_reporting_interval": 600,
+    "help": false,
+    "hold_policy": "hold",
+    "initial_stddev": 1.0,
+    "keep_checkpoints": 5,
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+    "latency_seed": null,
+    "latency_type": "fixed",
+    "learning_rate": 0.0001,
+    "load_checkpoint_kind": "latest",
+    "log_to_file": true,
+    "lr_adaptive_max": 0.01,
+    "lr_adaptive_min": 1e-06,
+    "lr_schedule": "constant",
+    "lr_schedule_kl_threshold": 0.008,
+    "max_episode_steps": 0,
+    "max_grad_norm": 4.0,
+    "max_latency_ms": null,
+    "max_pending_actions": null,
+    "max_policy_lag": 1000,
+    "mean_latency_ms": null,
+    "min_latency_ms": null,
+    "mode": "train",
+    "nonlinearity": "elu",
+    "normalize_input": true,
+    "normalize_input_keys": null,
+    "normalize_returns": true,
+    "num_agents": -1,
+    "num_batches_per_epoch": 2,
+    "num_batches_to_accumulate": 2,
+    "num_bots": -1,
+    "num_envs_per_worker": 4,
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+    "num_humans": 0,
+    "num_policies": 1,
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+    "obs_fps": 8.75,
+    "obs_scale": 255.0,
+    "obs_subtract_mean": 0.0,
+    "optimizer": "adam",
+    "ordering_policy": "latest_ready",
+    "output_dir": "outputs/jitter_destructiveness/real_profile/teacher_latency0/deadly_corridor/train/teacher/fixed_l0/obs8p75/seed_0",
+    "pbt_mix_policies_in_one_env": true,
+    "pbt_mutation_rate": 0.15,
+    "pbt_optimize_gamma": false,
+    "pbt_period_env_steps": 5000000,
+    "pbt_perturb_max": 1.5,
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+    "pbt_replace_fraction": 0.3,
+    "pbt_replace_reward_gap": 0.1,
+    "pbt_replace_reward_gap_absolute": 1e-06,
+    "pbt_start_mutation": 20000000,
+    "pbt_target_objective": "true_objective",
+    "pixel_format": "CHW",
+    "policy_init_gain": 1.0,
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+    "record_to": null,
+    "recurrence": 128,
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+    "reward_clip": 1000.0,
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+    "save_best_every_sec": 5,
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+    "save_every_sec": 600,
+    "save_milestones_sec": -1,
+    "seed": 42,
+    "serial_mode": false,
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+    "start_bot_difficulty": null,
+    "stats_avg": 100,
+    "std_latency_ms": null,
+    "summaries_use_frameskip": true,
+    "timelimit": null,
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+    "train_for_env_steps": 25000000,
+    "train_for_seconds": 10000000000,
+    "use_env_info_cache": false,
+    "use_record_episode_statistics": false,
+    "use_rnn": true,
+    "value_bootstrap": false,
+    "value_loss_coeff": 0.5,
+    "vizdoom_init_lock_max_wait_sec": 60.0,
+    "vizdoom_init_lock_timeout_sec": 5.0,
+    "vizdoom_init_max_parallel": 10,
+    "vizdoom_init_retry_jitter_sec": 0.25,
+    "vtrace_c": 1.0,
+    "vtrace_rho": 1.0,
+    "wandb_group": "deadly-corridor-obs8p75-fixed_l0",
+    "wandb_job_type": "sample_factory",
+    "wandb_project": "latency-sensitive-bench",
+    "wandb_tags": [
+      "real_profile_latency0_teacher",
+      "deadly-corridor",
+      "teacher",
+      "fixed",
+      "fixed_l0",
+      "obs8p75",
+      "seed0"
+    ],
+    "wandb_unique_id": "deadly-corridor-obs8p75-fixed_l0-s0",
+    "wandb_user": null,
+    "wide_aspect_ratio": false,
+    "with_pbt": false,
+    "with_vtrace": false,
+    "with_wandb": true,
+    "worker_num_splits": 2
+  },
+  "checkpoint_experiment_dir": "/home/ubuntu/codex/hist8-vla-v2-20260923/outputs/tasks/decision_history_vla_hist8_v2/data_zero/deadly_corridor/teacher_runtime",
+  "checkpoint_path": "/home/ubuntu/codex/hist8-vla-v2-20260923/outputs/tasks/decision_history_vla_hist8_v2/data_zero/deadly_corridor/teacher_runtime/best_000040896_20938752_reward_2260.797.pth",
+  "checkpoint_train_step": 40896,
+  "config_source": "/home/ubuntu/codex/hist8-vla-v2-20260923/outputs/tasks/decision_history_vla_hist8_v2/data_zero/deadly_corridor/teacher_runtime/config.json",
+  "context_image_count": 0,
+  "context_window": 1,
+  "env_fps": 35.0,
+  "env_name": "deadly_corridor",
+  "episode_return_field": "episode_raw_return",
+  "filter_preset": "none",
+  "filter_report": {
+    "accepted_episodes": 8250,
+    "accepted_train_episodes": 7425,
+    "accepted_val_episodes": 825,
+    "attempted_episodes": 8250,
+    "preset": "none",
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+    "train_rows_after_row_filter": 328296,
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+    "val_rows_after_row_filter": 36395,
+    "val_rows_before_row_filter": 36395
+  },
+  "frame_stack": 4,
+  "image_resolution": [
+    120,
+    160,
+    3
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+  "image_transform": {
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+    "ground_fraction": 0.22,
+    "history_frames": 5,
+    "image_transform": "raw_rgb",
+    "min_alpha": 35,
+    "scroll_px_per_step": 4.0
+  },
+  "image_transform_prompt_contexts": {
+    "demon_attack_ghost_trail": " You can see the recent motion of the ship, missiles, and demons in the image. Use it to make your decision.",
+    "flappy_ghost_trail": " You can see the past motion of the bird in the image. Use it to make your decision."
+  },
+  "latency_override": null,
+  "latency_source": "checkpoint",
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+  "max_steps_per_episode": 3600,
+  "max_steps_unit": "raw_frame",
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+  "obs_fps": 8.75,
+  "obs_stride_raw_frames": 4,
+  "prompt_source": "sample_factory_checkpoint:base_prompt",
+  "replay_num_envs": 8,
+  "reward_field": "raw_reward",
+  "reward_semantics": "raw_reward",
+  "rows_unit": "decision_step",
+  "schema_version": 2,
+  "split_seed": 0,
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+  "total_rows": 364691,
+  "train_episodes": 7425,
+  "train_rows": 328296,
+  "val_episodes": 825,
+  "val_fraction": 0.1,
+  "val_rows": 36395
+}

zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/run_metadata.json

@@ -0,0 +1,18 @@
+{
+  "training_run_id": "deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2",
+  "wandb_run_id": "2f9d64db",
+  "recipe_version": "hist8-v2",
+  "history_encoding": "binary_0_1",
+  "training_condition": "zero",
+  "initialization_seed": 42,
+  "vlm_lr": 3e-06,
+  "max_train_steps": 5000,
+  "stop_after_steps": null,
+  "num_workers_per_rank": 16,
+  "eval_num_workers_per_rank": 16,
+  "prefetch_factor": 4,
+  "base_model_revision": "ebb281ec70b05090aa6165b016eac8ec08e71b17",
+  "dataset_dir": "/home/ubuntu/codex/hist8-vla-v2-20260923/outputs/tasks/decision_history_vla_hist8_v2/data_zero/deadly_corridor/lerobot",
+  "dataset_manifest_sha256": "5d208b6ad0e526018e6c602d1066c5ae4f63cf300d67f514a29db3a14a3d8f7f",
+  "code_snapshot_sha256": "5ee627a7c7397387c3722678c74ec2740dc260d5f9d8fb14b0199f722b9c7962"
+}

zero-latency/deadly-corridor/vla/starvla-qwenpi_v3-h1/deadly_corridor-qwenpi_v3-hist8-zero-scratch-s42-v2/task_contract.json

@@ -0,0 +1,62 @@
+{
+  "task": "deadly_corridor",
+  "model": "qwenpi_v3",
+  "action_horizon": 1,
+  "image_frames": 1,
+  "state_source": "transport",
+  "state_dim": 120,
+  "history_decisions": 8,
+  "history_encoding": "binary_0_1",
+  "history_normalization": "identity",
+  "history_reset": "all_zero",
+  "history_order": "oldest_to_newest",
+  "history_entry_fields": [
+    "admission_bit",
+    "admitted_command_non_noop_bits",
+    "last_applied_action_non_noop_bits"
+  ],
+  "history_action_bit_order": [
+    "TURN_LEFT",
+    "TURN_RIGHT",
+    "MOVE_FORWARD",
+    "MOVE_BACKWARD",
+    "MOVE_LEFT",
+    "MOVE_RIGHT",
+    "ATTACK"
+  ],
+  "action_dim": 7,
+  "action_layout": "multibinary_7",
+  "action_labels": [
+    "MOVE_FORWARD",
+    "MOVE_BACKWARD",
+    "MOVE_LEFT",
+    "MOVE_RIGHT",
+    "TURN_LEFT",
+    "TURN_RIGHT",
+    "ATTACK"
+  ],
+  "task_prompts": [
+    "You are playing Deadly Corridor in VizDoom. Your goal is to survive the corridor, fight enemies, and reach the green armor vest at the far end. The available actions are: MOVE_FORWARD, MOVE_BACKWARD, MOVE_LEFT, MOVE_RIGHT, TURN_LEFT, TURN_RIGHT, and ATTACK. Choose the best next action from the current visual observation."
+  ],
+  "env_fps": 35,
+  "obs_fps": 8.75,
+  "evaluation": {
+    "episodes": 100,
+    "seeds": [
+      1000000,
+      1000099
+    ],
+    "parallel_envs": 32,
+    "capacity": 1,
+    "max_raw_frames": 3600,
+    "protocol_version": "hist8-history01-sf-render-v4"
+  },
+  "rendering": {
+    "screen_resolution": "RES_160X120",
+    "render_hud": true,
+    "render_crosshair": false,
+    "render_weapon": true,
+    "render_decals": false,
+    "render_particles": false
+  }
+}