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@sarckk sarckk commented Apr 17, 2025

Fixes #16414

The issue can be reproduced when setting max-model-len to a large value (e.g. 3600000) and sending requests without limiting the max number of requests (e.g. not restricting --max-num-seqs, sending requests without --max-concurrency) and/or not limiting max. number of tokens to be processed in a single iteration (--max-num-batched-tokens).

The error is IndexError: index out of range in self which happens in _prepare_inputs:

        torch.index_select(self.input_batch.token_ids_cpu_tensor.flatten(),
                           0,
                           torch.from_numpy(token_indices),
                           out=self.input_ids_cpu[:total_num_scheduled_tokens])

When it fails, the last several items of token_indices contains indices that are negative, due to int32 overflow. token_indices is given by:

        token_indices = (positions_np +
                         req_indices * self.input_batch.token_ids_cpu.shape[1])

Here, req_indices is a np.int32 array, e.g. np.array([0,1,2,...598]), and self.input_batch.token_ids_cpu.shape[1] is the max model len, e.g. 3,600,000. As an example, multiplying 598 * 3,600,000 gives us 2,152,800,000 which is greater np.int32 max value of 2,147,483,647 so it overflows and gives us a negative number for token index.

To avoid overflow, we can cast to int64 before the multiplication. the max token index can be given by max_req_index * max_model_len - 1.

To verify, I checked that below completes successfully on H200 (previously it would fail with index error after ~1000 requests). Without this fix, the max no. of concurrent requests we can serve with 3.6M context length would be 596.

VLLM_DISABLE_COMPILE_CACHE=1 vllm serve meta-llama/Llama-4-Scout-17B-16E-Instruct --disable-log-requests --gpu-memory-utilization=0.95 --max-model-len=3600000 -tp 8

python3 benchmarks/benchmark_serving.py --port=8000 --dataset-name=sharegpt --dataset-path=ShareGPT_V3_unfiltered_cleaned_split.json --tokenizer=meta-llama/Llama-4-Scout-17B-16E-Instruct --request-rate=64 --backend=vllm --num-prompts=19200 --model=meta-llama/Llama-4-Scout-17B-16E-Instruct --sharegpt-output-len=1024

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@mergify mergify bot added the v1 label Apr 17, 2025
@sarckk sarckk force-pushed the fix-long-context-overflow branch from 0a289b7 to 86c7260 Compare April 17, 2025 23:09
@sarckk sarckk marked this pull request as ready for review April 17, 2025 23:09
@sarckk sarckk marked this pull request as draft April 17, 2025 23:25
@sarckk sarckk mentioned this pull request Apr 17, 2025
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@sarckk sarckk force-pushed the fix-long-context-overflow branch from dda7860 to 7c1a09c Compare April 18, 2025 00:01
@sarckk sarckk marked this pull request as ready for review April 18, 2025 00:42
@mergify mergify bot added the tpu Related to Google TPUs label Apr 18, 2025
@sarckk sarckk force-pushed the fix-long-context-overflow branch from d02c4a1 to fbc8544 Compare April 18, 2025 00:55
@sarckk sarckk changed the title Fix int32 token index overflow when preparing input ids [BugFix] Fix int32 token index overflow when preparing input ids Apr 18, 2025
@sarckk sarckk changed the title [BugFix] Fix int32 token index overflow when preparing input ids [BugFix][V1] Fix int32 token index overflow when preparing input ids Apr 18, 2025
token_indices = (positions_np +
req_indices * self.input_batch.token_ids_cpu.shape[1])
req_indices.astype(self.token_indices_dtype) *
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shall we just create req_indices as token_indices_dtype instead of upcasting here?

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req_indices may be used in the following logic.

Another idea is always having int64 index for such use cases. But probably require a bigger change / refactor, thoughts, @WoosukKwon ? Shall we just land this fix, and think about a more thorough check in the following PR?

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I think we can create self.arange_np with dtype self.token_indices_dtype here. Increase in host memory is negligible even at 10M and we don't pay the cast at each scheduler step.
Computation is in i64 anyways as self.positions_cpu is already at i64, so that wouldn't be the only instance.

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makes sense, maybe we can just keep self.arange_np dtype in int64 similar to self.positions_cpu?

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Btw, @sarckk , could you lint the code?

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Thanks for fixing this!

token_indices = (positions_np +
req_indices * self.input_batch.token_ids_cpu.shape[1])
req_indices.astype(self.token_indices_dtype) *
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I think we can create self.arange_np with dtype self.token_indices_dtype here. Increase in host memory is negligible even at 10M and we don't pay the cast at each scheduler step.
Computation is in i64 anyways as self.positions_cpu is already at i64, so that wouldn't be the only instance.

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sarckk commented Apr 22, 2025

Btw, @sarckk , could you lint the code?

ran lint with pre-commit

@WoosukKwon WoosukKwon added the ready ONLY add when PR is ready to merge/full CI is needed label Apr 22, 2025
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LGTM! Thanks for the PR!

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Looks good. If it becomes a perf bottleneck, we can apply the optimization later.

@houseroad houseroad requested a review from NickLucche April 23, 2025 16:44
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Rerunning the CI and see how it goes.

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Looks clean, thanks!

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PS I think there's some commits missing a sign-off.

@WoosukKwon WoosukKwon merged commit 32d4b66 into vllm-project:main Apr 23, 2025
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gshtras added a commit to ROCm/vllm that referenced this pull request Apr 25, 2025
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Co-authored-by: varun sundar rabindranath <vsundarr@redhat.com>
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Co-authored-by: Mengqing Cao <cmq0113@163.com>
Co-authored-by: yexin(叶鑫) <yexin93@qq.com>
Co-authored-by: MagnetoWang <magnetowang@outlook.com>
Co-authored-by: 조상연[플레이스 AI] <sang-yeon.cho@navercorp.com>
Co-authored-by: rasmith <Randall.Smith@amd.com>
Co-authored-by: Luka Govedič <lgovedic@redhat.com>
Co-authored-by: Lu Fang <30275821+houseroad@users.noreply.github.com>
Co-authored-by: Alex Brooks <alex.brooks@ibm.com>
Co-authored-by: Cyrus Leung <tlleungac@connect.ust.hk>
Co-authored-by: Jasmond L <120363110+JasmondL@users.noreply.github.com>
adobrzyn pushed a commit to HabanaAI/vllm-fork that referenced this pull request Apr 30, 2025
…llm-project#16806)

Signed-off-by: Agata Dobrzyniewicz <adobrzyniewicz@habana.ai>
@sarckk sarckk deleted the fix-long-context-overflow branch May 9, 2025 19:36
RichardoMrMu pushed a commit to RichardoMrMu/vllm that referenced this pull request May 12, 2025
minpeter pushed a commit to minpeter/vllm that referenced this pull request Jun 24, 2025
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ready ONLY add when PR is ready to merge/full CI is needed tpu Related to Google TPUs v1
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[Bug]: Llama4 Scout fails on H200
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