docs: Enhance agent and API docs #162
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Note Other AI code review bot(s) detectedCodeRabbit has detected other AI code review bot(s) in this pull request and will avoid duplicating their findings in the review comments. This may lead to a less comprehensive review. 📝 WalkthroughWalkthroughReorganizes API docs to reference data-oriented pages instead of schema, introduces a new Workload component and dedicated Workload documentation, makes Changes
Sequence Diagram(s)(omitted — changes are documentation and schema reorganizations without new multi-component runtime control flow) Estimated code review effort🎯 3 (Moderate) | ⏱️ ~25 minutes Possibly related PRs
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Summary of ChangesHello @Ubospica, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request significantly enhances the API and agent documentation for FlashInfer-Bench. The primary focus is on improving the clarity and structure of the data schema documentation, notably by introducing a distinct Highlights
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Code Review
This pull request significantly enhances the documentation for the FlashInfer-Bench project, focusing on the API and the FlashInfer Trace schema. Key improvements include a clearer structure for API references, a dedicated and detailed document for the 'Workload' component, and refined descriptions across various schema-related files. The changes improve readability, consistency, and navigation through the documentation, making it easier for users to understand the core components and their relationships. A minor formatting adjustment was also made in the apply_api.py file.
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Actionable comments posted: 1
🤖 Fix all issues with AI agents
In `@docs/flashinfer_trace/workload.md`:
- Around line 33-36: Add blank lines immediately before the table that follows
the "Additional fields for type `scalar`:" heading and immediately after the
table so it is separated from surrounding paragraphs (this satisfies
markdownlint MD058); locate the table block (the pipe-delimited rows including
the header row "| **Field** | **Type** | **Required** | **Description** |") and
insert one blank line above and one blank line below it.
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Actionable comments posted: 1
Caution
Some comments are outside the diff and can’t be posted inline due to platform limitations.
⚠️ Outside diff range comments (1)
docs/flashinfer_trace/trace.md (1)
29-37: Fix the contradiction between required fields and nullable table.Lines 34-35 mark
correctnessandperformanceas Required (Yes), but the nullable table at lines 64-72 explicitly states these fields can beNonedepending on thestatus. This is a direct contradiction that will confuse readers.The "Required" column should reflect that these fields are conditionally required. Consider:
- Changing "Yes" to "Conditional" or "See nullable table below"
- Adding a note referencing the nullable table
- Or restructuring to make the dependency on
statusclear upfront📝 Suggested clarification
Update the table to indicate conditional requirements:
| **Field** | **Type** | **Required** | **Description** | | --- | --- | --- | --- | | `status` | string | Yes | The final status of the evaluation run. Has to be one of the following: `"PASSED"`, `"INCORRECT_SHAPE"`, `"INCORRECT_NUMERICAL"`, `"INCORRECT_DTYPE"`, `"RUNTIME_ERROR"`, `"COMPILE_ERROR"`. | | `log` | string | Yes | The embedded record of the stdout and stderr of the evaluation run. | -| `correctness` | object | Yes | The summarized correctness results across all entries in the dataset. | -| `performance` | object | Yes | The summarized performance metrics across all entries in the dataset. | +| `correctness` | object | Conditional* | The summarized correctness results across all entries in the dataset. | +| `performance` | object | Conditional* | The summarized performance metrics across all entries in the dataset. | | `environment` | object | Yes | A snapshot of the hardware and software execution environment. | | `timestamp` | string | Yes | The ISO 8601 timestamp of when this summary was generated. | + +\* See the nullable table below for status-dependent requirements.
🤖 Fix all issues with AI agents
In `@docs/flashinfer_trace/workload.md`:
- Around line 9-11: Clarify whether the JSONL files contain standalone Workload
objects or full Trace objects: update the description so it explicitly states
the storage unit (either "each line is a Workload object containing only the
workload fields" or "each line is a Trace object with definition and workload
populated and solution/evaluation null"), and make the examples match that
wording; reference the Trace and Workload types and the fields definition,
workload, solution, and evaluation when editing the text and/or examples so the
doc and sample JSONL lines are consistent.
♻️ Duplicate comments (1)
docs/flashinfer_trace/workload.md (1)
33-36: Add blank line before thescalartable to satisfy MD058.The table immediately following "Additional fields for type
scalar:" lacks a preceding blank line, which violates markdownlint MD058. Thesafetensorstable (lines 40-43) correctly has a blank line before it.🧹 Proposed fix
Additional fields for type `scalar`: + | **Field** | **Type** | **Required** | **Description** | | --- | --- | --- | --- | | `value` | int, float, bool | **Yes** | The concrete value of the input. |
🧹 Nitpick comments (4)
docs/flashinfer_trace/workload.md (1)
29-36: Consider documenting thatrandomtype has no additional required fields.The documentation covers additional fields for
scalarandsafetensorstypes but doesn't explicitly mention thatrandomhas no additional fields. Adding a brief note would improve clarity for readers.📝 Suggested addition
| `type` | string | **Yes** | Data source type. Could be `random`, `scalar`, or `safetensors`. | +The type `random` requires no additional fields; tensors will be generated with random values matching the shape and dtype specified in the Definition. + Additional fields for type `scalar`:docs/flashinfer_trace/trace.md (3)
7-9: Clarify the purpose of a Trace without solution/evaluation.The statement that a Trace "describes a workload entry in the dataset" when
solutionandevaluationare omitted is unclear. What is the intended use case for a Trace object that only contains a workload reference? If the goal is simply to store workload configurations, wouldn't it be more straightforward to use the Workload object directly?Consider adding a brief explanation of when and why users would create a Trace without evaluation results, or provide an example demonstrating this use case.
64-72: Consider clarifyingenvironmentandtimestamprequirements for error statuses.The nullable table addresses
correctnessandperformancebut doesn't mentionenvironmentandtimestamp, which are marked as always required in the evaluation schema. Should environment information and timestamps be available for all error types, includingCOMPILE_ERROR?If these fields should always be present regardless of status, consider adding a note confirming this. If they can be absent for certain error cases, update the nullable table accordingly.
74-121: Consider adding examples for optional and error cases.The current example demonstrates a successful run with all fields populated, which is helpful. However, the documentation would benefit from additional examples showing:
- A Trace with optional
solutionandevaluationfields omitted (as described in lines 7-9)- An error case (e.g.,
INCORRECT_NUMERICALorCOMPILE_ERROR) demonstrating the nullablecorrectness/performancefieldsThese examples would clarify the optional/nullable behavior described in the schema.
| **Storage Format:** In the FlashInfer-Bench dataset, a standalone Workload is stored using the [Trace](trace.md) data structure with only the `definition` and `workload` fields populated, while `solution` and `evaluation` are set to `null`. | ||
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| In FlashInfer Trace dataset, all workloads of the same definition are stored in a single JSONL file where each line is a `Workload` object. |
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Clarify the storage format description vs. examples.
Line 11 states "each line is a Workload object," but the examples (lines 47-75 and 79-99) show full Trace objects containing definition, workload, solution, and evaluation fields. Consider clarifying whether JSONL files contain standalone Workload objects or Trace objects with embedded workloads.
🤖 Prompt for AI Agents
In `@docs/flashinfer_trace/workload.md` around lines 9 - 11, Clarify whether the
JSONL files contain standalone Workload objects or full Trace objects: update
the description so it explicitly states the storage unit (either "each line is a
Workload object containing only the workload fields" or "each line is a Trace
object with definition and workload populated and solution/evaluation null"),
and make the examples match that wording; reference the Trace and Workload types
and the fields definition, workload, solution, and evaluation when editing the
text and/or examples so the doc and sample JSONL lines are consistent.
2 participants
This PR enhances API docs by adding the workload docs and refining other docs.
Signed-off-by: Ubospica ubospica@gmail.com
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