fix: Fix trtllm-gen prefill IMA when batch_size==1 by bkryu · Pull Request #1912 · flashinfer-ai/flashinfer

bkryu · 2025-10-10T18:06:33Z

📌 Description

Current PR fixes the test and benchmark codes IMAs when running trtllm-gen paged & ragged prefill with batch size 1 -- the issue was described in #1898

Root cause of the issue: flashinfer.prefill.trtllm_ragged_attention_deepseek and flashinfer.prefill.trtllm_batch_context_with_kv_cache both require max_q_len to match the length of the query when batch size is 1.

Updated PR:
Issue has been addressed from the kernel-side so that the "max_q_len to match the length of the query when batch size is 1" is no longer required.

Current PR updates trtllm-gen FMHA cubins to latest and brings minor updates to kernel metadata.

Unit test results after PR:

$ pytest tests/attention/test_trtllm_gen_attention.py 
...
platform linux -- Python 3.12.11, pytest-8.4.2, pluggy-1.6.0
rootdir: /flashinfer
configfile: pytest.ini
collected 2320 items   
...
2055 passed, 264 skipped, 1 xfailed in 224.43s (0:03:44)

Description of previous solution:
Updating max_q_len to cum_seq_lens_q[-1].item() within the trtllm_ragged_attention_deepseek or trtllm_batch_context_with_kv_cache functions are not a viable option because the CPU-side synchronization breaks the deterministic and fully device-side execution required during CUDA graph capture. The workaround was thus to update the test & benchmark codes that call the trtllm prefill functions, and clearly state in the docstring that when batch_size == 1, max_q_len must match the query size.

🔍 Related Issues

#1898

🚀 Pull Request Checklist

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🧪 Tests

Tests have been added or updated as needed.
All tests are passing (unittest, etc.).

Reviewer Notes

Summary by CodeRabbit

Bug Fixes
- Enabled an additional native attention backend for batch_size=1 where other constraints allow, expanding supported scenarios.
New Features
- Added a kernel parameter to enable future block-sparse attention support (no change to current behavior).
Documentation
- Updated benchmarks docs to note support for an additional attention optimization/backend.
Tests
- Expanded test coverage with configurable sequence lengths and a dedicated batch-size-1 test; removed a previous expected-failure for that path.

yzh119 · 2025-10-14T03:02:53Z

@@ -932,6 +928,12 @@ def testBatchPrefillWithPagedKVCacheWrapper(args):
        v_fp8 = (v_data / v_scale).to(kv_dtype)
        kv_cache = torch.cat([k_fp8, v_fp8], dim=1)

+    if batch_size == 1:
+        # trtllm kernel requires max_q_len to be the same as the seqlen of the query when batch_size=1


Why qo_indptr[-1] could be different to s_qo, is it because we want to be compatible with cudagraphs and s_qo will always be the maximum length?

Short answer is yes.

Longer answer: In a batch_size > 1 situation, the CUDA graph containing prefill.trtllm_batch_context_with_kv_cache() can be reused with multiple sequence lengths but not when batch_size==1. For example,

If batch_size is 3 and we have two batches with query lengths [100, 200, 300] and [16, 500, 1024], we can set s_qo=1024, when we construct the CUDA graph and use the same CUDA graph for the two batches.

However for batch_size=1, where we have batches of query lengths [100] and [1024], a CUDA graph must be constructed each time -- first with s_qo=100 and second with s_qo=1024.

Not sure whether the above is a real concern at the framework level. Nevertheless, s_qo goes in as the max_q_len input argument where it is the max sequence length for query. We may at least want to consider whether the wording in the documentation is clear 😄

yzh119 · 2025-10-16T18:40:32Z

Hi @bkryu does upgrading to latest trtllm-gen fixing the issue?

bkryu · 2025-10-16T20:17:51Z

Hi @bkryu does upgrading to latest trtllm-gen fixing the issue?

Hi @yzh119, I'm currently checking. Upgrading to the latest trtllm-gen does fix the batch size 1 unit test, but I am seeing some errors in otherplaces. Will verify what is happening before marking the PR as ready

bkryu · 2025-10-16T20:40:01Z

/bot run

flashinfer-bot · 2025-10-16T20:40:46Z

GitLab MR !83 has been created, and the CI pipeline #36750562 is currently running. I'll report back once the pipeline job completes.

flashinfer-bot · 2025-10-17T01:01:23Z

[FAILED] Pipeline #36750562: 1/17 passed

coderabbitai · 2025-10-17T16:51:55Z

Walkthrough

Re-enables trtllm-gen-native for batch_size==1 in benchmark routines, updates three TRTLLM_GEN_FMHA artifact hash constants, adds mUseBlockSparseAttention to KernelParams, extends attention tests with sequence-length parameters and a bs1 test, and updates benchmark documentation to mention deepseek support.

Changes

Cohort / File(s)	Summary
Backend constraint change `benchmarks/routines/attention.py`	Removed the automatic skip that excluded `trtllm-gen-native` when `batch_size == 1` in `testBatchPrefillWithPagedKVCacheWrapper` and `testBatchPrefillWithRaggedKVCacheWrapper`; other constraints remain.
Documentation `benchmarks/README.md`	Added a bullet noting `BatchPrefillWithRaggedKVCacheWrapper` also supports `trtllm_ragged_attention_deepseek` (in addition to existing options).
Artifact hash updates `flashinfer/artifacts.py`	Updated three string constants for `TRTLLM_GEN_FMHA`: `ArtifactPath.TRTLLM_GEN_FMHA`, `MetaInfoHash.TRTLLM_GEN_FMHA`, and `CheckSumHash.TRTLLM_GEN_FMHA` (values changed).
Kernel parameters `include/flashinfer/trtllm/fmha/kernelParams.h`	Added public data member `bool mUseBlockSparseAttention` to `KernelParams` and set it to `false` in `setKernelParams`; included a TODO for future block-sparse integration.
Tests `tests/attention/test_trtllm_gen_attention.py`	Parameterized `test_trtllm_batch_prefill` with `max_q_len` and `max_kv_len`, added `test_trtllm_batch_prefill_bs1` (delegates to the parametrized test), and removed an explicit `pytest.xfail` for a bs1 deepseek case.

Sequence Diagram(s)

sequenceDiagram
  participant Test as Test Runner
  participant Bench as Benchmark Routine
  participant Selector as Backend Selector
  participant Backend as trtllm-gen-native
  participant Kernel as KernelParams

  Note over Test,Bench: Parametrized batch-prefill tests (including bs==1)

  Test->>Bench: invoke testBatchPrefill(max_q_len, max_kv_len, ...)
  Bench->>Selector: request eligible backends (batch_size considered)
  Note right of Selector: bs==1 no longer auto-skipped
  Selector-->>Backend: select trtllm-gen-native when constraints met
  Backend->>Kernel: build KernelParams (mUseBlockSparseAttention = false)
  Kernel-->>Backend: return params
  Backend-->>Bench: execute prefill using returned params
  Bench-->>Test: return results

Estimated code review effort

🎯 3 (Moderate) | ⏱️ ~20 minutes

Possibly related issues

[Bug] trtllm-gen attention kernel issues for batch size 1 #1898 — Related: both touch trtllm-gen attention execution for batch_size==1; this change re-enables bs==1 test paths that the issue discusses.

Suggested reviewers

yzh119

Poem

🐇 I hopped through hashes, nudged a test to try,
Reopened a path where a lone batch may fly,
A flag set false, a TODO kept near,
Sequences extend — the benches cheer,
Hop on, small kernel, the trail is clear!

Pre-merge checks and finishing touches

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 40.00% which is insufficient. The required threshold is 80.00%.	You can run `@coderabbitai generate docstrings` to improve docstring coverage.

✅ Passed checks (2 passed)

Check name	Status	Explanation
Title Check	✅ Passed	The title "fix: Fix trtllm-gen prefill IMA when batch_size==1" directly and clearly describes the main objective of the pull request. The changes focus on resolving an issue where trtllm-gen prefill functions failed when batch_size==1, with fixes applied at both the kernel level (updated FMHA cubins and kernel metadata) and the test/benchmark code level (updated parameterization to remove the batch_size==1 constraint). The title is concise, specific, and accurately reflects the primary purpose without vague terminology.
Description Check	✅ Passed	The pull request description comprehensively follows the provided template structure. The 📌 Description section clearly explains what the PR does, including the root cause, kernel-side resolution, and specific updates to FMHA cubins and kernel metadata, along with test results. The 🔍 Related Issues section properly links to issue #1898. The 🚀 Pull Request Checklist is fully completed with both Pre-commit Checks and Tests sections marked as done [x], and the optional Reviewer Notes section is present. All major required sections are present with substantive information rather than placeholder text.

✨ Finishing touches

📝 Generate docstrings

🧪 Generate unit tests (beta)

Create PR with unit tests
Post copyable unit tests in a comment

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bkryu · 2025-10-17T16:57:17Z

/bot run

flashinfer-bot · 2025-10-17T16:57:34Z

GitLab MR !83 has been updated with latest changes, and the CI pipeline #36805526 is currently running. I'll report back once the pipeline job completes.

coderabbitai

Actionable comments posted: 0

🧹 Nitpick comments (2)

benchmarks/README.md (1)
19-19: LGTM! Documentation correctly updated.

The documentation now accurately reflects that BatchPrefillWithRaggedKVCacheWrapper supports trtllm_ragged_attention_deepseek for ragged attention operations.

Optional: Fix list indentation for consistency.

The static analysis tool flags that this line uses 8 spaces for indentation instead of the expected 4 for nested list items.
-        - Also supports computationally similar `cudnn_batch_prefill_with_kv_cache` and  `trtllm_ragged_attention_deepseek`.
+    - Also supports computationally similar `cudnn_batch_prefill_with_kv_cache` and  `trtllm_ragged_attention_deepseek`.
tests/attention/test_trtllm_gen_attention.py (1)
348-361: LGTM! Function signature correctly updated.

The new max_q_len and max_kv_len parameters are properly integrated into the function signature and correctly passed to generate_seq_lens_prefill.

Optional: Prefix unused variable with underscore.

Line 360 unpacks in_kv_lens from generate_seq_lens_prefill, but the variable is never used in the function body. Consider prefixing it with an underscore to indicate it's intentionally unused:
-    q_lens, in_kv_lens, seq_lens = generate_seq_lens_prefill(
+    q_lens, _in_kv_lens, seq_lens = generate_seq_lens_prefill(
         batch_size, max_q_len, max_kv_len
     )

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📒 Files selected for processing (5)

benchmarks/README.md (1 hunks)
benchmarks/routines/attention.py (0 hunks)
flashinfer/artifacts.py (3 hunks)
include/flashinfer/trtllm/fmha/kernelParams.h (2 hunks)
tests/attention/test_trtllm_gen_attention.py (3 hunks)

💤 Files with no reviewable changes (1)

benchmarks/routines/attention.py

🚧 Files skipped from review as they are similar to previous changes (2)

include/flashinfer/trtllm/fmha/kernelParams.h
flashinfer/artifacts.py

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🧬 Code graph analysis (1)

tests/attention/test_trtllm_gen_attention.py (1)

flashinfer/utils.py (1)

get_compute_capability (251-254)

🪛 markdownlint-cli2 (0.18.1)

benchmarks/README.md

19-19: Unordered list indentation
Expected: 4; Actual: 8

(MD007, ul-indent)

🪛 Ruff (0.14.0)

tests/attention/test_trtllm_gen_attention.py

360-360: Unpacked variable in_kv_lens is never used

Prefix it with an underscore or any other dummy variable pattern

(RUF059)

⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (1)

GitHub Check: Deploy Docs

🔇 Additional comments (2)

tests/attention/test_trtllm_gen_attention.py (2)

334-335: LGTM! Parameterization enhances test flexibility.

Adding max_q_len and max_kv_len as test parameters allows testing different sequence length combinations, which is essential for validating the batch_size==1 fix across various configurations.

530-578: LGTM! Dedicated batch_size=1 test addresses PR objective.

The new test_trtllm_batch_prefill_bs1 function specifically tests the batch_size==1 scenario with large sequence lengths (8192), which directly addresses the issue described in #1898. The test properly delegates to the main test function with appropriate parameters and minimal configuration to focus on the batch_size==1 edge case.

flashinfer-bot · 2025-10-18T08:49:52Z

[FAILED] Pipeline #36805526: 1/17 passed

yzh119

LGTM

yzh119 · 2025-10-20T07:11:32Z

Failed UT are not relevant and are scheduled to be fixed in #1950 and #1953

bkryu · 2025-10-20T18:42:39Z

@nvmbreughe , can I get a review on the PR? Zihao and Perkz already approved, but due to code owner review requirements, it seems like I need a review from you

nvmbreughe

LGTM!

…special treatments

coderabbitai

Actionable comments posted: 0

🧹 Nitpick comments (1)

tests/attention/test_trtllm_gen_attention.py (1)
360-362: Optional: Consider using underscore for unused unpacked variable.

The in_kv_lens variable is unpacked but never used. Consider using _ to signal this is intentional:
-    q_lens, in_kv_lens, seq_lens = generate_seq_lens_prefill(
-        batch_size, max_q_len, max_kv_len
-    )
+    q_lens, _, seq_lens = generate_seq_lens_prefill(
+        batch_size, max_q_len, max_kv_len
+    )

📜 Review details

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📒 Files selected for processing (5)

benchmarks/README.md (1 hunks)
benchmarks/routines/attention.py (0 hunks)
flashinfer/artifacts.py (3 hunks)
include/flashinfer/trtllm/fmha/kernelParams.h (2 hunks)
tests/attention/test_trtllm_gen_attention.py (3 hunks)

💤 Files with no reviewable changes (1)

benchmarks/routines/attention.py

🚧 Files skipped from review as they are similar to previous changes (2)

flashinfer/artifacts.py
include/flashinfer/trtllm/fmha/kernelParams.h

🧰 Additional context used

🧬 Code graph analysis (1)

tests/attention/test_trtllm_gen_attention.py (1)

flashinfer/utils.py (1)

get_compute_capability (251-254)

🪛 markdownlint-cli2 (0.18.1)

benchmarks/README.md

19-19: Unordered list indentation
Expected: 4; Actual: 8

(MD007, ul-indent)

🪛 Ruff (0.14.1)

tests/attention/test_trtllm_gen_attention.py

360-360: Unpacked variable in_kv_lens is never used

Prefix it with an underscore or any other dummy variable pattern

(RUF059)

🔇 Additional comments (3)

benchmarks/README.md (1)

19-19: LGTM! Documentation correctly reflects deepseek support.

The addition of trtllm_ragged_attention_deepseek to the supported operations for BatchPrefillWithRaggedKVCacheWrapper is accurate and aligns with the PR's objective to fix and enable trtllm-gen prefill with deepseek attention.

tests/attention/test_trtllm_gen_attention.py (2)

334-335: Good parameterization for flexible sequence length testing.

Adding max_q_len and max_kv_len parameters allows testing different sequence length scenarios while preserving existing test behavior with sensible defaults. This enables the new batch_size=1 test to use longer sequences.

Also applies to: 348-349, 361-361

530-578: Well-targeted regression test for batch_size=1 with large sequences.

This test specifically validates the kernel fix for batch_size==1 by using large sequence lengths (8192+8192=16384 total), which was the failing scenario described in issue #1898. The narrow parameter space is appropriate for a focused regression test.

## 📌 Description In #1898, it was raised that trtllm-gen's attention kernels fail for batch size 1. The prefill kernel was fixed in #1912 and prefill tests have been enabled. Further updates to trtllm-gen kernels have also fixed the decode batch size 1 issue. Current PR re-enables testing.  ## 🔍 Related Issues  ## 🚀 Pull Request Checklist Thank you for contributing to FlashInfer! Before we review your pull request, please make sure the following items are complete. ### ✅ Pre-commit Checks - [x] I have installed `pre-commit` by running `pip install pre-commit` (or used your preferred method). - [x] I have installed the hooks with `pre-commit install`. - [x] I have run the hooks manually with `pre-commit run --all-files` and fixed any reported issues. > If you are unsure about how to set up `pre-commit`, see [the pre-commit documentation](https://pre-commit.com/). ## 🧪 Tests - [ ] Tests have been added or updated as needed. - [ ] All tests are passing (`unittest`, etc.). ## Reviewer Notes   ## Summary by CodeRabbit * **Tests** * Expanded batch_decode test scenarios to cover additional small-batch and page-size combinations. * Increased coverage for max_in_kv_len by testing multiple length options instead of a single value. * Restored previously marked-as-expected-failure case to run normally, improving overall test pass coverage.  --------- Co-authored-by: Zihao Ye <expye@outlook.com>

## 📌 Description In flashinfer-ai#1898, it was raised that trtllm-gen's attention kernels fail for batch size 1. The prefill kernel was fixed in flashinfer-ai#1912 and prefill tests have been enabled. Further updates to trtllm-gen kernels have also fixed the decode batch size 1 issue. Current PR re-enables testing.  ## 🔍 Related Issues  ## 🚀 Pull Request Checklist Thank you for contributing to FlashInfer! Before we review your pull request, please make sure the following items are complete. ### ✅ Pre-commit Checks - [x] I have installed `pre-commit` by running `pip install pre-commit` (or used your preferred method). - [x] I have installed the hooks with `pre-commit install`. - [x] I have run the hooks manually with `pre-commit run --all-files` and fixed any reported issues. > If you are unsure about how to set up `pre-commit`, see [the pre-commit documentation](https://pre-commit.com/). ## 🧪 Tests - [ ] Tests have been added or updated as needed. - [ ] All tests are passing (`unittest`, etc.). ## Reviewer Notes   ## Summary by CodeRabbit * **Tests** * Expanded batch_decode test scenarios to cover additional small-batch and page-size combinations. * Increased coverage for max_in_kv_len by testing multiple length options instead of a single value. * Restored previously marked-as-expected-failure case to run normally, improving overall test pass coverage.  --------- Co-authored-by: Zihao Ye <expye@outlook.com>

bkryu self-assigned this Oct 10, 2025

yzh119 reviewed Oct 14, 2025

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bkryu force-pushed the trtllm-attention-debug branch from 4dade1b to 197a7a0 Compare October 16, 2025 17:23

bkryu marked this pull request as ready for review October 17, 2025 16:59

bkryu changed the title ~~fix: Fix test and benchmark for trtllm-gen prefill batch size 1~~ fix: Fix trtllm-gen prefill IMA when batch_size==1 Oct 17, 2025

bkryu force-pushed the trtllm-attention-debug branch from 57e47ea to 003ef55 Compare October 17, 2025 21:36

coderabbitai Bot reviewed Oct 17, 2025

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PerkzZheng approved these changes Oct 20, 2025

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yzh119 approved these changes Oct 20, 2025

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yzh119 requested review from Anerudhan, aleozlx, cyx-6, joker-eph, kahyunnam, nvmbreughe, wenscarl and yongwww as code owners October 20, 2025 07:10

yzh119 enabled auto-merge (squash) October 20, 2025 07:11

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bkryu added 5 commits October 20, 2025 22:43

Add missing params

8e04cbd

Update cubin artifacts to latest trtllm-gen fmha. Undo batch_size==1 …

71fca41

…special treatments

Undo change in prefill

56ed50a

Update checksums

9cb2b38

Add new mUseBlockSparseAttention; parameter to KernelParams

1b7f9e8

bkryu force-pushed the trtllm-attention-debug branch from fa62171 to 1b7f9e8 Compare October 20, 2025 22:43

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yzh119 merged commit c3f2596 into flashinfer-ai:main Oct 21, 2025
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bkryu mentioned this pull request Oct 21, 2025

[Bug] trtllm-gen attention kernel issues for batch size 1 #1898

Closed

yzh119 mentioned this pull request Oct 22, 2025

[Bug]: TRTLLM attention + full cudagraph produces incorrect output at long context length (>128k) on Blackwell #1968

Open

bkryu deleted the trtllm-attention-debug branch October 23, 2025 20:49

coderabbitai Bot mentioned this pull request Nov 8, 2025

Fix: several bugs/issues with trtllm-gen attention kernels. #2062

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5 tasks

bkryu mentioned this pull request Nov 18, 2025

test: Enable testing for trtllm-gen decode bs1 #2103

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coderabbitai Bot mentioned this pull request Nov 24, 2025

fix: some bugs of headDim 256 trtllm-gen fmha kernels. #2137

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This was referenced Dec 10, 2025

feat: support variable sequence length in decode kernel of trtllm-gen attention #2125

Merged

docs: Fix inaccurate API docstrings for attention prefill #2196

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This was referenced Mar 17, 2026

[fix] bugfix 1419: Add batch size shape validation in decode and prefill run() APIs #2801

Merged

[Fmha] support nvfp4 output keepsMmaAb generation kernels #2795

Closed

[Perf] Add FMHAv2 to flashinfer_benchmark.py and eliminate unnecessary H2D #2841

Merged

This was referenced Apr 2, 2026

[Do not merget yet] test: add trtllm-gen prefill tests for reproducing sm103 hang #2953

Closed

[Fmha] Add head_dim=512 support for trtllm attention kernels #2959

Merged

This was referenced Apr 10, 2026

trtllm non causal support #3020

Merged

Loosened trtllm_ragged_attention_deepseek shape assertion #3064

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This was referenced May 1, 2026

Enable TRT-LLM Gen sparse MLA block-sparse path #3199

Open

Add dynamic tokens-per-page TRTLLM-GEN GQA kernels #3259

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Sequence Diagram(s)

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