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@zerollzeng zerollzeng commented Jul 22, 2025

Summary by CodeRabbit

  • New Features

    • Added tracking of decoding iterations during text generation, now visible in output metrics.
    • Introduced a new "request accuracy rate" metric in benchmarking, including mean, median, standard deviation, and percentiles, which are now reported and saved with benchmark results.
  • Enhancements

    • Benchmarking reports now display request accuracy metrics alongside existing performance data.

Description

Test Coverage

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coderabbitai bot commented Jul 22, 2025

"""

Walkthrough

A new integer field, decode_iteration, was added to the output of backend request functions to track decoding steps. Benchmarking code was updated to compute and report a new "request accuracy rate" metric, with related statistics integrated throughout the benchmarking workflow, including reporting, saving, and command-line interface options.

Changes

File(s) Change Summary
tensorrt_llm/serve/scripts/backend_request_func.py Added decode_iteration field to RequestFuncOutput and logic to track decoding iterations in request functions.
tensorrt_llm/serve/scripts/benchmark_serving.py Added calculation, reporting, and saving of "request accuracy rate" metric and related statistics; updated CLI and data structures.

Estimated code review effort

2 (~20 minutes)

Poem

A rabbit counts each hop and leap,
Now decoding steps we also keep!
With accuracy rates we now compare,
Each request’s journey, tracked with care.
Metrics grow, the benchmarks sing,
🐇 Data hops on every spring!
"""


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  • tensorrt_llm/serve/scripts/backend_request_func.py (11 hunks)
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Actionable comments posted: 3

📜 Review details

Configuration used: CodeRabbit UI
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📥 Commits

Reviewing files that changed from the base of the PR and between ee45e0c and 90ac3a1.

📒 Files selected for processing (2)
  • tensorrt_llm/serve/scripts/backend_request_func.py (11 hunks)
  • tensorrt_llm/serve/scripts/benchmark_serving.py (9 hunks)
🪛 Ruff (0.12.2)
tensorrt_llm/serve/scripts/benchmark_serving.py

480-480: Line too long (132 > 120)

(E501)

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🪛 Ruff (0.12.2)
tensorrt_llm/serve/scripts/benchmark_serving.py

480-480: Line too long (132 > 120)

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🔇 Additional comments (8)
tensorrt_llm/serve/scripts/backend_request_func.py (3)

47-47: LGTM: Clean addition of decode_iteration field.

The new field is well-documented, properly typed, and has a sensible default value.


180-180: LGTM: Well-implemented decode_iteration tracking.

This implementation correctly:

  • Increments only when actual text content is received (line 218)
  • Uses output_tokens for non-streaming estimation, which is more accurate than word count
  • Provides consistent fallback behavior

This approach is better than the TRT-LLM implementation.

Also applies to: 217-220, 234-234, 245-246


323-323: LGTM: Consistent implementation with OpenAI completions.

The decode_iteration tracking follows the same solid pattern as the completions function:

  • Conditional increment for actual content
  • Proper use of output_tokens for non-streaming estimation
  • Consistent behavior across OpenAI-compatible endpoints

Also applies to: 354-357, 366-366, 376-377

tensorrt_llm/serve/scripts/benchmark_serving.py (5)

80-84: LGTM: Well-structured addition of request_ar metrics to dataclass.

The new fields follow existing naming conventions and are properly typed. The integration is clean and consistent with other metrics.


248-252: LGTM: Consistent metrics calculation for request_ar.

The metrics calculation follows the established pattern and properly handles edge cases with the or 0 fallback.


456-459: LGTM: Consistent reporting of request_ar metrics.

The console output and result dictionary updates follow established patterns and maintain consistency with other metrics.

Also applies to: 472-473


571-572: LGTM: Consistent updates to save functionality.

The save functions properly include request_ar summary metrics while correctly excluding raw arrays when detailed saving is disabled. The implementation maintains consistency across both save functions.

Also applies to: 576-576, 800-801


1001-1005: LGTM: Appropriate CLI updates for request_ar metric.

The CLI argument updates properly include request_ar in the default percentile metrics and update the help text accordingly. The changes maintain consistency with the existing argument structure.

@zerollzeng zerollzeng changed the title Add AR calculation to benchmark_serving Add Acceptance Rate calculation to benchmark_serving Jul 22, 2025
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PR_Github #12497 [ run ] triggered by Bot

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PR_Github #12497 [ run ] completed with state FAILURE
/LLM/main/L0_MergeRequest_PR pipeline #9286 completed with status: 'FAILURE'

@zerollzeng zerollzeng force-pushed the request-ar branch 2 times, most recently from d7b0098 to e3eaf1a Compare July 22, 2025 06:14
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PR_Github #12529 [ run ] completed with state FAILURE
/LLM/main/L0_MergeRequest_PR pipeline #9314 completed with status: 'FAILURE'

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PR_Github #12535 [ run ] triggered by Bot

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PR_Github #12535 [ run ] completed with state SUCCESS
/LLM/main/L0_MergeRequest_PR pipeline #9318 completed with status: 'FAILURE'

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PR_Github #12632 [ run ] completed with state SUCCESS
/LLM/main/L0_MergeRequest_PR pipeline #9389 completed with status: 'FAILURE'

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