IX2-0529
① SA Source
- Source: 開啟完整 SA 文章
- Section:
Core Changes Since InferenceXv1 - Line hint:
766
Context Before
We have made a few core architectural changes to the InferenceX repository to make it easier to understand and reproduce benchmarks. Additionally, we have fully subscribed to AI usage to maximize productivity and increase developer velocity.
Core Changes Since InferenceXv1
Evidence
Previously, we were jestermaxing and performed a full sweep over each configuration nightly
Context After
We now trigger sweeps based on additions to a changelog ↗at the root of the repo. When a developer makes a performance-impacting change to a given config, they add an entry to the changelog listing the affected config along with a brief description of the change. All configs are defined in a master configuration YAML file ↗, which serves as the stateful representation of every data point to be swept, including core settings like ISL/OSL, EP, TP, DP, MTP, and so on. When a PR containing a changelog addition is merged, a workflow parses the referenced config keys, pulls the corresponding sweep definitions from the master config, and fans them out as individual GitHub Actions jobs. The jobs collect all data points for the full sweep and upload the results as artifacts.
Below is a high-level diagram of how InferenceX launches jobs.
② Atomic Claim
關於 InferenceX：過去會每晚對所有 configuration 執行一次完整 sweep。
- Epistemic Mode:
ASSERTED - Mapping Status:
PARTIAL
③ Semantic Frame
{
"attribute": "UNSPECIFIED_ATTRIBUTE",
"context_nodes": [],
"entity": {
"id": "04_knowledge_base/InferenceX",
"label": "InferenceX"
},
"frame_type": "ATTRIBUTE",
"qualifiers": {
"condition_text": null,
"numeric_mentions": [],
"temporal_mentions": []
},
"value": {
"numeric_mentions": [],
"value_text": "關於 InferenceX：過去會每晚對所有 configuration 執行一次完整 sweep。"
}
}④ Canonical Entity Mapping
| Role | Surface Label | Canonical Target |
|---|---|---|
| entity | InferenceX | InferenceX |
⑤ Human Review
請在 Properties 逐項確認：
- 原文 → Atomic Claim 是否忠實
- Atomic Claim → Semantic Frame 是否忠實
- Canonical Entity mapping 是否正確
- Epistemic mode 是否保留原文語氣
- 最後選擇
review_action
Review state
Markdown 內文不是正式 approval。只有 Apply bridge 寫入的 Decision Ledger event 才是正式決策。