Skip to content

feat(tasks): add declarative task slices and rollout validation - #500

Merged
yuecideng merged 24 commits into
mainfrom
feat/expert-program-rollout-validation
Aug 24, 2026
Merged

feat(tasks): add declarative task slices and rollout validation#500
yuecideng merged 24 commits into
mainfrom
feat/expert-program-rollout-validation

Conversation

@yuecideng

@yuecidengyuecideng commented Aug 11, 2026

Copy link
Copy Markdown
Contributor

Description

Stack

Consolidation

Consolidates #499 into this layer. Scope: declarative task vertical slices and deterministic rollout validation.
Add deterministic Expert Program rollout measurement: fixed-seed execution, raw trial JSON, failure-preserving aggregation, Markdown reports, static migration-size checks, and supported-simulation gates.

Benchmark reporting distinguishes framework coverage, checked-in integrations, and physical acceptance instead of treating compilation success as task success.

Refs #471
Refs #474

Type of change

  • Enhancement (non-breaking change which improves existing functionality)

Screenshots

Not applicable.

Validation

  • Focused coverage: tests/benchmark/expert_program/test_demo_success.py and tests/scripts/tools/test_expert_program_rollout_report.py
  • Final affected-suite regression on the stack tip: 1215 passed, 2 skipped, 8 deselected
  • Changed Python files pass Black 26.3.1; the Sphinx build and rollout-report drift check pass at the stack tip

Checklist

  • Changed Python files pass Black 26.3.1.
  • Corresponding public/design documentation is included in this stack.
  • Tests cover the affected behavior.
  • No dependency update is required.

Make endpoint bindings, timed command frames, transports, routing, safe holds, and profile lowering controller-agnostic. Preserve joint trajectories as optional feedback artifacts and add staged, same-address invocation revision semantics for mobile and whole-body safety.
@yuecidengyuecideng added task A task written in openai gym format for imitation learning or reinforcement learning dataset docs Improvements or additions to documentation enhancement New feature or request labels Aug 11, 2026
@yuecideng
yuecideng marked this pull request as ready for review August 11, 2026 16:46
CopilotAI lite review requested due to automatic review settings August 11, 2026 16:46
@greptile-apps

greptile-appsBot commented Aug 11, 2026

Copy link
Copy Markdown

Greptile Summary

The PR consolidates two task integrations onto the declarative Expert Program runtime and adds deterministic rollout measurement and reporting.

  • Removes the legacy repeated-pick/place and drawer task implementations and configurations.
  • Adds fixed-seed demo execution, raw trial artifacts, failure-preserving aggregation, and Markdown reporting.
  • Adds migration-size and capability snapshots plus focused package, task, and simulation tests.

Confidence Score: 5/5

The PR appears safe to merge because no blocking failure remains in the eligible follow-up review scope.

No blocking failure remains.

Important Files Changed

FilenameOverview
scripts/benchmark/expert_program/demo_success.pyAdds fixed-seed, no-retry demo execution with failure-preserving raw artifacts and deterministic aggregation.
scripts/tools/expert_program_rollout_report.pyGenerates and checks the static capability and migration-size report from explicit source snapshots.
embodichain_tasks/embodichain_tasks/expert_program/repeated_pick_place.pySimplifies the canonical repeated-pick environment by removing its task-local contact observer while explicitly withholding physical acceptance.
embodichain_tasks/configs/gym/expert_program/repeated_pick_place.jsonAdds dataset recording metadata and removes the contact sensor from the structurally supported but physically unqualified task.
tests/benchmark/expert_program/test_demo_success.pyProvides broad pure-Python coverage for deterministic execution, failures, aggregation, serialization, and cleanup behavior.
tests/test_expert_program_package_data.pyVerifies Expert Program resources are included and decodable from staged package output.

Flowchart

%%{init: {'theme': 'neutral'}}%%
flowchart LR
A[Fixed benchmark seeds] --> B[Seeded non-saving reset]
B --> C[Execute declarative demo once]
C --> D[Normalize per-environment results]
D --> E[Non-saving discard reset]
E --> F[Raw JSON trials]
F --> G[Aggregate metrics]
G --> H[Markdown report]
Loading

Reviews (5): Last reviewed commit: "Merge remote-tracking branch 'origin/mai..." | Re-trigger Greptile

CopilotAI left a comment

Copy link
Copy Markdown
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Copilot was unable to review this pull request because the user who requested the review has reached their quota limit.

@yuecideng
yuecideng changed the base branch from feat/declarative-task-vertical-slices to feat/mllm-expert-program-frontendAugust 11, 2026 17:47
@yuecidengyuecideng changed the title feat(benchmark): add expert program rollout validationfeat(tasks): add declarative task slices and rollout validationAug 11, 2026
@skywhite1024
skywhite1024force-pushed the feat/expert-program-rollout-validation branch 2 times, most recently from 872b8a1 to 9b59c70CompareAugust 21, 2026 11:31
Base automatically changed from feat/mllm-expert-program-frontend to mainAugust 24, 2026 08:52
@yuecideng
yuecideng merged commit 760bcd9 into mainAug 24, 2026
5 checks passed
@yuecideng
yuecideng deleted the feat/expert-program-rollout-validation branch August 24, 2026 15:18
Sign up for freeto join this conversation on GitHub. Already have an account? Sign in to comment

Labels

datasetdocsImprovements or additions to documentationenhancementNew feature or requesttaskA task written in openai gym format for imitation learning or reinforcement learning

Projects

None yet

Development

Successfully merging this pull request may close these issues.

2 participants

@yuecideng