Cooked#8
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- Added STARFORMER optimization branch in training.py, including TD loss computation and logging. - Introduced _compute_episode_rtg function for discounted return-to-go calculation. - Enhanced train function to support STARFORMER context management and episode tracking. - Updated select_action in utils.py to handle STARFORMER-specific action selection logic. - Created AGENTS.md for documentation on project structure and key files. - Added SKILL.md to outline coding patterns and conventions used in the project. - Introduced unit tests for Transition dataclass and StarformerQNet in tests/test_datamodel.py and tests/test_starformer_net.py. - Implemented tests for WindowPrioritizedReplayMemory in tests/test_window_replay.py to validate episode boundary and backfill logic.
- Added STARFORMER architecture integration with PPO in training.py. - Introduced windowed tensor building and action selection for STARFORMER. - Enhanced PPO optimization with AMP support and GAE computation. - Updated action selection logic in utils.py to accommodate STARFORMER. - Created new tests for STARFORMER network and PPO configurations. - Added documentation for agents and coding patterns in AGENTS.md and SKILL.md. - Established a test suite for datamodel and replay memory functionalities.
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cannot use PPO with random sampling it force to use uniform |
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