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add a folder tracking our best models#430

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eugenevinitsky wants to merge 1 commit into
emerge/temp_trainingfrom
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Open

add a folder tracking our best models#430
eugenevinitsky wants to merge 1 commit into
emerge/temp_trainingfrom
ev/model_folder

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Copilot AI review requested due to automatic review settings May 19, 2026 23:34
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Pull request overview

Adds a new models/4_19_26_rocket/ folder intended to track a “best model” configuration and a short description for reproducibility.

Changes:

  • Added a model training/eval configuration YAML under models/4_19_26_rocket/rocket-baseline-scaling/.
  • Added a brief text description documenting provenance/compatibility.

Reviewed changes

Copilot reviewed 2 out of 29 changed files in this pull request and generated 1 comment.

File Description
models/4_19_26_rocket/rocket-baseline-scaling/config.yaml Adds a full training/eval config snapshot for the “rocket baseline scaling” model.
models/4_19_26_rocket/description.txt Adds a one-line note about who trained the model and repo compatibility.
Comments suppressed due to low confidence (2)

models/4_19_26_rocket/rocket-baseline-scaling/config.yaml:96

  • These wosac_* entries include ; ... annotations and extra quoting, which YAML will treat as part of the value. As written, fields like wosac_control_mode / wosac_init_mode will not equal the expected enums (control_wosac, create_all_valid), and fields like wosac_aggregate_results / wosac_goal_radius won’t parse as bool/float. Replace the ; ... notes with # ... YAML comments and remove the embedded quotes so the values parse to the intended types.
  wosac_aggregate_results: True ; Only return aggregate results across all scenes
  wosac_control_mode: '"control_wosac"  ; Control the tracks to predict'
  wosac_goal_radius: 2.0 ; Can shrink goal radius for WOSAC evaluation
  wosac_init_mode: '"create_all_valid"  ; Initialize from the tracks to predict'
  wosac_init_steps: 10 ; When to start the simulation

models/4_19_26_rocket/rocket-baseline-scaling/config.yaml:98

  • wosac_num_agents and wosac_num_rollouts also include ; ... annotations; with YAML this makes them parse as strings rather than integers. If these are consumed programmatically (e.g., for sizing envs/rollouts), this will cause type errors or incorrect behavior. Use # for comments and keep the scalar values numeric.
  wosac_num_agents: 256  ; Total number of WOSAC agents to evaluate
  wosac_num_rollouts: 32  ; Number of policy rollouts per scene

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Comment on lines +83 to +98
human_replay_control_mode: '"control_sdc_only" ; Control only the self-driving car'
human_replay_eval: false
human_replay_num_agents: 64 ; This equals the number of scenarios, since we control
one agent in each
map_dir: pufferlib/resources/drive/binaries/eval
multi_scenario_eval: false
multi_scenario_num_scenarios: 250
multi_scenario_simulation_mode: replay
num_agents: 512
wosac_aggregate_results: True ; Only return aggregate results across all scenes
wosac_control_mode: '"control_wosac" ; Control the tracks to predict'
wosac_goal_radius: 2.0 ; Can shrink goal radius for WOSAC evaluation
wosac_init_mode: '"create_all_valid" ; Initialize from the tracks to predict'
wosac_init_steps: 10 ; When to start the simulation
wosac_num_agents: 256 ; Total number of WOSAC agents to evaluate
wosac_num_rollouts: 32 ; Number of policy rollouts per scene
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3 participants