LIBERO

Normalizer

LIBERO — metrics, requirements, and run commands.

Last updated: Jul 11, 2026

On this page

About Metrics Task YAML Primary Environment setup Runtime environment Evaluation data Checkpoints & assets Key environment variables Verify setup Run Evaluation Set Candidate Artifacts Import Official Results Score Generated Artifacts Direct In-Tree Runner Requirements Inputs Environment Outputs

About

LIBERO is a lifelong robot manipulation benchmark with language-conditioned tasks across spatial, object, goal, and long-horizon suites.

Metrics

LIBERO external benchmark task manifest for language-conditioned robot manipulation policy rollouts.

Task YAML

worldfoundry/data/benchmarks/tasks/external/libero.yaml

Primary

success_rate

Metric	Focus
`success_rate`	Share of episodes or tasks that complete successfully.
`task_success`	Share of episodes or tasks that complete successfully.
`episode_success`	Share of episodes or tasks that complete successfully.
`action_accuracy`	Correctness of predicted actions, states, or outcomes against the benchmark success criterion.

Environment setup

Runtime environment

Conda env: giga-world-policy-py311.
Separate setup: defaults to the unified WorldFoundry env (needs_new_env: false); a benchmark-only conda env is usually not required.
LIBERO Python 包可见；完整状态还需要 policy checkpoint、suite 选择和官方 rollout 结果。

Evaluation data

Candidate model outputs: set WORLDFOUNDRY_LIBERO_RESULTS_PATH to the generated-video or rollout artifact root.
${WORLDFOUNDRY_HFD_DATASET_ROOT}/yifengzhu-hf__LIBERO-datasets
${WORLDFOUNDRY_HFD_DATASET_ROOT}/lerobot__libero
${WORLDFOUNDRY_CACHE_DIR}/repos/Lifelong-Robot-Learning--LIBERO

Checkpoints & assets

Base-model / metric dependencies: libero_source_assets, libero_dataset_assets.
Default metric-checkpoint paths and override env vars are listed in the local assets guide.

Key environment variables

WORLDFOUNDRY_LIBERO_ROOT
WORLDFOUNDRY_LIBERO_RESULTS_PATH

Verify setup

PYTHONPATH=${WORLDFOUNDRY_CACHE_DIR}/repos/Lifelong-Robot-Learning--LIBERO:src ${WORLDFOUNDRY_CONDA_ENVS_ROOT}/worldfoundry-giga-world-policy-py311/bin/python -m worldfoundry.evaluation.tasks.execution.orchestration.runtime_preflight --profile libero --manifest worldfoundry/data/benchmarks/runtime_profiles/official/libero.yaml --output-dir tmp/worldfoundry_preflight/libero --json

Run Evaluation

After preparing the assets and candidate artifacts listed on this page, use the public run entry points below.

Set Candidate Artifacts

export WORLDFOUNDRY_GENERATED_ARTIFACT_DIR=/path/to/generated/artifacts

Import Official Results

worldfoundry-eval zoo benchmark-run \
  --benchmark-id libero \
  --mode normalizer \
  --official-results-path /path/to/official/results-or-report \
  --generated-artifact-dir "${WORLDFOUNDRY_GENERATED_ARTIFACT_DIR}" \
  --output-dir tmp/libero/normalizer \
  --json

Score Generated Artifacts

worldfoundry-eval zoo benchmark-run \
  --benchmark-id libero \
  --mode official-run \
  --generated-artifact-dir "${WORLDFOUNDRY_GENERATED_ARTIFACT_DIR}" \
  --output-dir tmp/libero/official-run \
  --json

Direct In-Tree Runner

worldfoundry-eval embodied run --config worldfoundry/data/benchmarks/eval_configs/embodied/libero/spatial.yaml

Requirements

Inputs

Upstream SAPIEN/Curobo simulator runtime
RoboTwin simulator assets
Policy checkpoint for selected upstream eval script
Official eval_result tree or structured result export

Environment

WORLDFOUNDRY_LIBERO_RESULTS_PATH

Outputs

scorecard.json
run_manifest.json
results.jsonl
metrics/summary.json

← Benchmark Hub

LIBERO

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