[Bugfix] Fix hash topk dtype mismatch#43425
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Align hash routing metadata to the topk index dtype before invoking the sqrt-softplus topk custom op. DeepEP may request int64 topk indices while DeepSeek V4 hash MoE metadata remains int32, but the CUDA op dispatches hash metadata from the topk index dtype. Co-authored-by: Trae AI <trae-ai@users.noreply.github.com> Signed-off-by: wangyicong <wangyicong@bytedance.com>
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Code Review
This pull request updates the topk_hash_softplus_sqrt function in vllm/_custom_ops.py to ensure that input_tokens and hash_indices_table are cast to the same data type as topk_indices when they are provided. I have no feedback to provide as there were no review comments to evaluate.
| if input_tokens.dtype != topk_indices.dtype: | ||
| input_tokens = input_tokens.to(dtype=topk_indices.dtype) | ||
| if hash_indices_table.dtype != topk_indices.dtype: | ||
| hash_indices_table = hash_indices_table.to(dtype=topk_indices.dtype) |
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QQ: Will these changes launch the type conversion kernel?
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Yes. The current version is a quick and minimal correctness fix, and it may launch CUDA type conversion kernels when the dtypes do not match. If we want to avoid that entirely, the more complete solution would be to change the CUDA op / kernel contract so that topk_indices and the hash routing metadata (input_ids / tid2eid) do not have to use the same dtype. That should avoid the conversion kernels, but it is a larger kernel/dispatch change.
Without changing the CUDA kernel, a better way would be to move the dtype alignment upstream, so the static hash_indices_table is aligned once when the MoE backend determines the required topk_indices_dtype, instead of casting it before every custom op call.
Which way do you think is better? I can work on either direction next to fix this bug. @jeejeelee
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Sorry for missing this PR. It looks like #41183 has fixed this bug
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Purpose
This PR fixes a dtype mismatch in the DeepSeek V4 hash MoE sqrt-softplus top-k path.
We observed this issue on H20 servers using PD disaggregation and DeepEP during DeepSeek V4 Flash startup:
The issue happens because DeepEP's prepare/finalize path can request
topk_indiceswithtorch.int64, while DeepSeek V4 non-MegaMoE hash routing metadata (input_tokensandhash_indices_table) can remaintorch.int32.The CUDA op dispatch currently chooses the pointer type for hash metadata from
topk_indices.scalar_type(). As a result, whentopk_indicesis int64 but the hash metadata is int32, the op may try to read int32 tensors as int64 before kernel launch.This PR aligns only the hash metadata tensors (
input_tokensandhash_indices_table) totopk_indices.dtypebefore invoking_moe_C.topk_softplus_sqrt.token_expert_indicesis intentionally unchanged because the CUDA op reads it asint*.This may also fix the same dtype mismatch reported in #40862.
Test
Verified on Volcengine servers with:
deepep_high_throughputdeepep_low_latencyAfter applying this fix:
expected scalar type Long but found Interror is no longer reproduced.