executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
results-opsInstall and operate DreamerV3 environments and backends, inspect result logdirs, and summarize score artifacts without reopening the source repository.
Independent GitHub snapshot · Automated classification · Original documentation governs
Use this sub-skill when a task is about making DreamerV3 runnable, checking optional environment/backend readiness, inspecting logdir outputs, viewing metrics, or summarizing benchmark score files.
Do not use this sub-skill for:
train-configure.embodied-dataflow.jax-models.metrics.jsonl, scores.jsonl, Scope summaries, TensorBoard/WandB/Expa outputs, or gzipped benchmark score artifacts.metrics.jsonl, scores.jsonl, or gzipped score-record JSON with only Python standard-library dependencies.python -m pip check
python - <<'PY'
import dreamerv3, embodied
from embodied.envs import dummy
import jax, jax.numpy as jnp
print('jax', jax.__version__, 'backend', jax.default_backend())
print('devices', jax.devices())
print('sum', float(jnp.array([1.0, 2.0]).sum()))
env = dummy.Dummy({'image': (8, 8, 3)}, {'action': (2,)})
print('dummy obs keys', sorted(env.obs_space.keys()))
PY
If this fails on an optional environment module but the selected task does not use that suite, treat it as optional rather than blocking the whole installation. Use the optional import checker to make the missing suite explicit.
python scripts/metrics_summary.py --input <logdir>/metrics.jsonl --list-keys
python scripts/metrics_summary.py --input <logdir>/scores.jsonl --key episode/score --last 10
python scripts/metrics_summary.py --input <logdir>/metrics.jsonl --key episode/length --last 10
If the key is absent, list keys first. DreamerV3 metric names commonly use slash-separated names such as episode/score, episode/length, fps/train, replay/inserts, and train/loss/....
python -m pip install -U scope
python -m scope.viewer --basedir <logdir-parent> --port 8000
Point Scope at a directory that contains one or more run logdirs. If Scope is unavailable, use the summary script above and the JSONL schema in references/results-and-plotting.md.
dreamer; import roots are dreamerv3 and embodied.jax[cuda12]==0.4.33; CPU-only use is possible by selecting the CPU JAX platform at runtime, while production defaults target CUDA.