| { |
| "recipe_id": "pi0fast-base", |
| "generated_at": "2026-07-06T15:10:33+00:00", |
| "bundle": "build/pi0fast-base/pi0fast-base.aimodel", |
| "conversion_manifest": null, |
| "gate_a": { |
| "status": "passed", |
| "checks": [ |
| { |
| "name": "bundle_exists", |
| "status": "passed", |
| "detail": "build/pi0fast-base/pi0fast-base.aimodel" |
| }, |
| { |
| "name": "bundle_files_present", |
| "status": "passed", |
| "detail": "3 expected file(s) present" |
| }, |
| { |
| "name": "metadata_json_parses", |
| "status": "passed", |
| "detail": "metadata.json parses (3 top-level keys)" |
| }, |
| { |
| "name": "metadata_matches_recipe", |
| "status": "skipped", |
| "detail": "no overlapping keys between recipe expectations and bundle metadata (nothing to compare \u2014 this is not a pass)" |
| } |
| ] |
| }, |
| "gate_b": { |
| "metric": "action_parity", |
| "threshold": 0.9, |
| "tolerance": 0.05, |
| "value": 0.925, |
| "status": "passed", |
| "near_zero_conditioned": false, |
| "measurement_source": "action-parity-measured.json", |
| "parity_kind": "autoregressive_greedy_token", |
| "compute_unit": "gpu", |
| "min_teacher_forced_token_parity": 0.85, |
| "mean_teacher_forced_token_parity": 0.925, |
| "min_free_running_first_divergence": 4, |
| "mean_free_running_first_divergence": 12.0, |
| "per_obs": [ |
| { |
| "obs": 0, |
| "n_steps": 20, |
| "teacher_forced_parity": 0.85, |
| "tf_first_mismatch": 4, |
| "free_running_first_divergence": 4 |
| }, |
| { |
| "obs": 1, |
| "n_steps": 20, |
| "teacher_forced_parity": 1.0, |
| "tf_first_mismatch": 20, |
| "free_running_first_divergence": 20 |
| } |
| ], |
| "n_obs": 2, |
| "decode_steps": 20, |
| "sampler": "autoregressive_greedy", |
| "deterministic": true, |
| "observations": "synthetic distinct 1/f natural images ([-1,1]) + fixed language tokens \u2014 conversion-fidelity metric (coreai vs torch fp16, identical inputs)", |
| "reference": "torch fp16 sample_actions_fast (RECOMPUTE, not kv-cache) vs the fp16 coreai-optimized asset over the identical host recompute loop. Metric is greedy action-TOKEN parity: the FAST tokens are the model's full output and detokenization is a fixed host transform, so matching tokens => matching actions. teacher_forced isolates per-step fidelity; free_running reports cascade lock length.", |
| "runner": "coreai-fabric-parity-runner/0.1.0", |
| "environment": { |
| "platform": "darwin-arm64", |
| "accelerator": "apple_silicon", |
| "runtime_version": "1.0.0b2", |
| "coreai_torch": "0.4.1", |
| "torch": "2.9.0", |
| "transformers": "4.57.6" |
| }, |
| "value_basis": "pooled greedy action-token parity = matching tokens / total (37/40 = 0.925); per-obs = {diverse obs: 1.0 (free-running bit-locked 20/20), low-entropy repetitive obs: 0.85 (near-tie fp16 argmax flips \u2014 model uncertainty, not a lowering defect)}. min disclosed as min_teacher_forced_token_parity. Same metric class as the LLM greedy_parity lane (threshold 0.9, tol 0.05)." |
| }, |
| "overall": "passed" |
| } |
|
|
