---

name: model-components description: "Use and adapt core policy, rollout, optimizer, distribution, and utility components in pytorch-a2c-ppo-acktr-gail." disable-model-invocation: true metadata: disco-role: operating license: MIT

Model Components

Use this sub-skill when a task needs programmatic inspection, safe modification, or debugging of the repository's core Python components rather than an end-to-end environment run.

Read This First

• API signatures, import paths, tensor shapes, and return values: references/api-reference.md.
• Architecture and modification guidance for policies, bases, rollouts, algorithms, KFAC, schedules, and log cleanup: references/implementation-notes.md.
• Common failures and fixes: references/troubleshooting.md.
• Safe CPU smoke script: scripts/smoke_model_components.py.

Best-Fit Tasks

Load this sub-skill for tasks such as:

• Instantiate Policy, CNNBase, MLPBase, action distributions, or RolloutStorage directly.
• Modify actor/critic base networks or recurrent policy behavior.
• Debug tensor shapes for Policy.act, Policy.evaluate_actions, rollout insertion, or PPO mini-batches.
• Reason about A2C_ACKTR, PPO, or KFACOptimizer update internals.
• Use update_linear_schedule or understand cleanup_log_dir side effects.

Route Elsewhere

• End-to-end CLI training, evaluation, checkpoint playback, Gym environment wrappers, and command construction belong in ../training-workflows/.
• GAIL expert-file schema, HDF5 conversion, discriminator updates, and imitation-learning workflow belong in ../gail-imitation/.
• Cross-cutting installation, Gym/PyTorch dependency, optional simulator, and backend issues belong in the root skill's troubleshooting reference.

Quick Smoke Check

From an environment where the package is installed, run:

python sub-skills/model-components/scripts/smoke_model_components.py

The script uses only CPU tensors and synthetic Gym spaces; it does not create environments, download data, or train an agent. A successful run prints PASS model-components smoke.