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效率与协作 · SKILL.md

tensor_api_buffer_contract

tensor_api_buffer_contract

【效率与协作】Validate direct state action observation and reward buffer contracts for Isaac Gym style pipelines.

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技能说明

GitHub

name: tensor_api_buffer_contract description: Validate direct state action observation and reward buffer contracts for Isaac Gym style pipelines.

Tensor API Buffer Contract

Use this skill when checking whether a reduced or real recovery preserves Isaac Gym's direct tensor-buffer idea. The skill validates named state, action, observation, reward, and reset buffers, their shapes, and whether a claimed direct path includes forbidden CPU staging.

Inputs

  • Buffer descriptors with name, role, shape, producer, consumer, and direct fields.
  • Expected environment count for the leading batch dimension.

Outputs

  • A report with ok, errors, direct_flow_ok, and roles_present.

Workflow

  1. Collect descriptors for physics state, policy action, observation, reward, and reset buffers.
  2. Verify each descriptor has a leading batch dimension matching the environment count.
  3. Reject missing producer/consumer ownership or direct=False when direct flow is claimed.
  4. Save the report as recovery evidence or use it as a cross-check from a harness.

Validation

Run python tests/test_buffer_contract.py or validate the skill tree with tests enabled.

Limitations

This deterministic checker verifies the contract. It cannot prove CUDA pointer aliasing without a real GPU tensor runtime.

Edge-Case Refinement

A negative check must fail when a descriptor uses the wrong leading environment dimension or marks a buffer as non-direct, because such staging would violate the paper Tensor API mechanism.

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