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Correctly abort the failed grammar requests & Improve the handling of abort #6803
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Hello @merrymercy, 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!
Summary of Changes
Hello! Gemini or gemini-code-assist here, providing a summary of this pull request. This PR primarily focuses on improving the handling of failed grammar requests and standardizing the process for aborting requests within the system. It introduces a dedicated object (INVALID_GRAMMAR_OBJ
) to represent invalid grammar states, ensuring these failures are explicitly tracked and cached. Requests encountering invalid grammars or other validation errors are now consistently marked for abortion using a new helper method (set_finish_with_abort
). Furthermore, the PR adds the capability to abort requests that are currently waiting in the grammar processing queue and includes metrics to track aborted requests. Minor adjustments are also made to CUDA graph capture batch sizes, memory pool size, logging, and test utilities.
Highlights
- Standardized Request Abortion: Introduced a new method
set_finish_with_abort
on theReq
class to provide a consistent way to mark requests for abortion with a specific error message and status code. This replaces scattered logic for handling various validation failures. - Improved Invalid Grammar Handling: Created a dedicated
INVALID_GRAMMAR_OBJ
to represent grammar compilation failures. Grammar backends now return this object instead ofNone
on failure. The scheduler checks for this object (including in the cache) and aborts the corresponding request. - Grammar Queue Abort Support: Implemented the ability to abort requests that are currently waiting in the grammar processing queue, ensuring that
AbortReq
signals are handled promptly for these requests. - Metrics for Aborted Requests: Added a new Prometheus counter (
sglang:num_aborted_requests
) to track the total number of requests that are aborted.
Changelog
Click here to see the changelog
- python/sglang/srt/constrained/base_grammar_backend.py
- Added a default
copy
implementation returningself
(L63). - Introduced
INVALID_GRAMMAR_OBJ
(L102). - Changed
CacheEntry.value
type hint fromOptional[BaseGrammarObject]
toBaseGrammarObject
(L107).
- Added a default
- python/sglang/srt/constrained/llguidance_backend.py
- Imported
INVALID_GRAMMAR_OBJ
(L31). - Changed error handling in
_from_serialized
,dispatch_json
,dispatch_ebnf
, anddispatch_structural_tag
to returnINVALID_GRAMMAR_OBJ
instead ofNone
on failure (L131, L143, L156, L174). - Changed logging level from
warning
toerror
for grammar compilation failures (L130, L142, L155, L173).
- Imported
- python/sglang/srt/constrained/outlines_backend.py
- Imported
INVALID_GRAMMAR_OBJ
(L27). - Changed error handling in
_compile_regex
anddispatch_json
to returnINVALID_GRAMMAR_OBJ
instead ofNone
on failure (L156, L175). - Changed logging level from
warning
toerror
for JSON schema failures (L174).
- Imported
- python/sglang/srt/constrained/xgrammar_backend.py
- Imported
INVALID_GRAMMAR_OBJ
(L31). - Wrapped tokenizer info initialization in
if True
(L156). - Changed error handling in
dispatch_json
,dispatch_ebnf
,dispatch_regex
, anddispatch_structural_tag
to returnINVALID_GRAMMAR_OBJ
instead ofNone
on failure (L186, L194, L202, L221). - Changed logging level from
warning
toerror
for grammar compilation failures (L185, L193, L201, L220). - Removed conditional check for
self.grammar_compiler
inreset
(L225).
- Imported
- python/sglang/srt/entrypoints/http_server.py
- Added
[http_server]
prefix to error logs instream_results
andgenerate
(L259, L277).
- Added
- python/sglang/srt/managers/schedule_batch.py
- Imported
HTTPStatus
(L40) andget_tensor_model_parallel_rank
(L55). - Removed import of
get_compiler_backend
(L65). - Added
set_finish_with_abort
method to theReq
class for standardized abortion (L776-L784).
- Imported
- python/sglang/srt/managers/scheduler.py
- Imported
INVALID_GRAMMAR_OBJ
(L39). - Updated
handle_generate_request
to useset_finish_with_abort
for disaggregation errors (L960), multimodal prompt length errors (L991), input length errors (L1007), and logprob_start_len errors (L1021). - Added check in
handle_generate_request
to abort requests hitting a cachedINVALID_GRAMMAR_OBJ
(L1059-L1061). - Updated
handle_embedding_request
to useset_finish_with_abort
for multimodal prompt length errors (L1109). - Updated
move_ready_grammar_requests
to handle requests already finished (aborted) (L1783-L1785). - Updated
move_ready_grammar_requests
to handleINVALID_GRAMMAR_OBJ
from grammar backend results and abort requests (L1788-L1791, L1822-L1825). - Renamed
num_abort_reqs
tonum_timeout_reqs
inmove_ready_grammar_requests
(L1780, L1810, L1814). - Updated timeout handling in
move_ready_grammar_requests
to useset_finish_with_abort
and cacheINVALID_GRAMMAR_OBJ
(L1834-L1835). - Removed TODO comment about aborting grammar queue requests (L2027).
- Added logic to
abort_request
to cancel and abort requests found in thegrammar_queue
(L2056-L2061).
- Imported
- python/sglang/srt/managers/tokenizer_manager.py
- Initialized
mm_processor
toNone
if multimodal is not enabled (L224). - Updated
_tokenize_one_request
to only process multimodal data ifmm_processor
is available (L465). - Ensured
image_inputs
isNone
if multimodal processing is skipped (L475). - Modified
_send_one_request
to return the createdReqState
(L635). - Modified
_wait_one_response
to acceptReqState
as an argument instead of looking it up (L640). - Updated calls to
_wait_one_response
in_handle_batch_request
to pass theReqState
(L714, L722, L748, L757). - Added metrics observation for aborted requests in
abort_request
(L793-L794).
- Initialized
- python/sglang/srt/managers/utils.py
- Removed manual setting of
finished_reason
and logging invalidate_input_length
(L38-L41), as this is now handled byset_finish_with_abort
in the scheduler.
- Removed manual setting of
- python/sglang/srt/metrics/collector.py
- Added
num_aborted_requests_total
counter (L405-L408). - Added
observe_one_aborted_request
method to increment the aborted requests counter (L543-L544).
- Added
- python/sglang/srt/model_executor/cuda_graph_runner.py
- Removed unused import
two_batch_overlap
(L27). - Adjusted default CUDA graph capture batch sizes, especially for speculative decoding and larger GPUs (L135, L144-L145, L150).
- Removed logic adding
size - 1
to capture sizes (L155-L157). - Removed filtering of batch sizes based on
enable_two_batch_overlap
(L159-L160). - Added assertion check for
capture_bs
(L165).
- Removed unused import
- python/sglang/srt/model_executor/model_runner.py
- Changed
ReqToTokenPool
size frommax_num_reqs + 1
tomax_num_reqs
(L921).
- Changed
- python/sglang/srt/utils.py
- Added
is_blackwell
helper function (L2058-L2061).
- Added
- python/sglang/test/send_one.py
- Added check for non-200 HTTP status code and print response before returning (L130-L132).
- python/sglang/test/test_utils.py
- Changed
STDERR_FILENAME
andSTDOUT_FILENAME
to use/tmp/
directory (L884-L885). - Reduced sleep time in
read_output
from 1 second to 0.01 seconds (L891). - Added try-except block for
FileNotFoundError
inread_output
(L897-L901).
- Changed
- scripts/killall_sglang.sh
- Added conditional logic to skip nvidia-smi calls and GPU process killing if the first argument is 'rocm' (L3-L8, L10-L33).
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Grammar fails, a syntax error,
No longerNone
, but a clear terror.
Requests now abort,
A cleaner report,
No more hidden, silent bearer.
Footnotes
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Review the Privacy Notices, Generative AI Prohibited Use Policy, Terms of Service, and learn how to configure Gemini Code Assist in GitHub here. Gemini can make mistakes, so double check it and use code with caution. ↩
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Code Review
This pull request significantly improves the handling of failed and aborted grammar requests. Key improvements include:
- Correct Abort Handling: Requests in the grammar queue are now correctly aborted, and a new
set_finish_with_abort
method in theReq
class centralizes the logic for aborting requests, which simplifies the codebase. - Clearer Error Signaling: Invalid grammar requests now consistently return an
INVALID_GRAMMAR_OBJ
and log errors instead of warnings, making issues more visible and easier to debug. - Code Simplification: Redundant code for handling aborted requests has been refactored using the new
set_finish_with_abort
method.
The changes are well-aligned with the PR's objectives and enhance the robustness and clarity of the error handling mechanisms. There are a few minor areas for improvement noted below.
Summary of Findings
- Improved Error Handling for Grammar Requests: The PR successfully standardizes error handling for invalid grammar requests by introducing
INVALID_GRAMMAR_OBJ
and consistently usinglogger.error
. - Centralized Request Abort Logic: The new
Req.set_finish_with_abort()
method effectively centralizes and simplifies the logic for aborting requests, improving code maintainability. - Correct Abort of Grammar Queue Requests: The
abort_request
method in the scheduler now correctly handles aborting requests that are pending in the grammar queue. - Redundant Code Removal: A redundant
if True:
block was identified inxgrammar_backend.py
. - Logging Consistency: A minor inconsistency in logging levels (
logger.warning
vslogger.error
) was noted inoutlines_backend.py
for similar error conditions.
Merge Readiness
This pull request introduces valuable improvements to error handling and request abortion logic, significantly enhancing the robustness and maintainability of the grammar processing components. The changes are well-structured and address the stated objectives effectively.
There are a few minor points (a redundant if True:
, a logging consistency question, and a query about enable_two_batch_overlap
's CUDA graph implications) that would be good to address or clarify. Once these are considered, the PR should be in excellent shape for merging.
I am unable to approve pull requests, so please ensure other reviewers take a look and approve before merging.
except interegular.patterns.InvalidSyntax as e: | ||
logger.warning(f"skip invalid regex schema: {regex=}, {e=}") | ||
return None | ||
return INVALID_GRAMMAR_OBJ |
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In _compile_regex
, a logger.warning
is used for invalid regex schemas, while other similar error handling spots in this PR (e.g., dispatch_json
in this file, and other backend files) have been updated to use logger.error
and return INVALID_GRAMMAR_OBJ
.
Is there a specific reason to keep logger.warning
here? For consistency with the goal of returning errors immediately for invalid grammar requests, perhaps logger.error
would be more appropriate, even if this is an internal helper method.
if True: | ||
tokenizer_info = TokenizerInfo.from_huggingface( | ||
tokenizer, vocab_size=vocab_size | ||
) | ||
override_stop_tokens = None |
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def reset(self): | ||
if self.grammar_compiler: | ||
self.grammar_compiler.clear_cache() | ||
self.grammar_compiler.clear_cache() |
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The if self.grammar_compiler:
check was removed from the reset
method. This implies self.grammar_compiler
is guaranteed to be initialized. While this seems to be the case from the constructor, could you confirm if there are any scenarios where self.grammar_compiler
might not be set before reset
is called? If it's always set, this change is fine.
logger.error(f"{error_msg}, {self.rid=}") | ||
self.multimodal_inputs = None | ||
self.grammar = None | ||
self.origin_input_ids = [0] # set it to one token to skip the long prefill |
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The line self.origin_input_ids = [0]
with the comment "set it to one token to skip the long prefill" is a bit of an implicit contract. While the comment explains the intent, it might be worth considering if there's a more explicit way to signal to the prefill logic that the request is aborted and should be skipped or handled minimally, rather than relying on a specific input ID pattern. However, if this is a well-established pattern in the codebase, it's acceptable.
if max(capture_bs) > model_runner.req_to_token_pool.size: | ||
# In some case (e.g., with a small GPU or --max-running-requests), the #max-running-requests | ||
# In some cases (e.g., with a small GPU or --max-running-requests), the #max-running-requests | ||
# is very small. We add more values here to make sure we capture the maximum bs. | ||
capture_bs += [model_runner.req_to_token_pool.size - 1] + [ | ||
model_runner.req_to_token_pool.size | ||
] | ||
|
||
if server_args.enable_two_batch_overlap: | ||
capture_bs = [bs for bs in capture_bs if bs >= 2] | ||
capture_bs += [model_runner.req_to_token_pool.size] |
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The logic for enable_two_batch_overlap
(previously filtering capture_bs
for bs >= 2
) has been removed. Does this mean enable_two_batch_overlap
is no longer supported, or is its handling for CUDA graph capture managed elsewhere? If the feature is still intended to work, it might be good to clarify how this change affects it.
Merge branch 'sgl_20250610_sync_tag047 of [email protected]:Theta/SGLang.git into main https://code.alipay.com/Theta/SGLang/pull_requests/52 Reviewed-by: 剑川 <[email protected]> * [Bugfix] Fix slice operation when chunk size mismatch (sgl-project#6697) * [Bugfix] Fix ChatCompletion endpoint of mini_lb when stream is set (sgl-project#6703) * [CI] Fix setup of disaggregation with different tp (sgl-project#6706) * [PD] Remove Unnecessary Exception Handling for FastQueue.get() (sgl-project#6712) * Fuse routed_scaling_factor in DeepSeek (sgl-project#6710) * Overlap two kernels in DeepSeek with communication (sgl-project#6711) * Minor refactor two-batch overlap (sgl-project#6682) * Speed up when having padding tokens two-batch overlap (sgl-project#6668) * [Feature] Support Flashinfer fp8 blockwise GEMM kernel on Blackwell (sgl-project#6479) * Fix LoRA bench (sgl-project#6719) * temp * Fix PP for Qwen3 MoE (sgl-project#6709) * [feat] triton kernel for get_last_loc (sgl-project#6676) * [fix] more mem for draft_extend cuda_graph (sgl-project#6726) * [PD] bug fix: Update status if nixl receiver send a a dummy req. (sgl-project#6720) * Tune memory arguments on B200 (sgl-project#6718) * Add DeepSeek-R1-0528 function call chat template (sgl-project#6725) * refactor(tool call): Fix BaseFormatDetector tool_index issue and refactor `parse_streaming_increment` (sgl-project#6715) * Add draft extend CUDA graph for Triton backend (sgl-project#6705) * refactor apply_w8a8_block_fp8_linear in fp (sgl-project#6545) * [PD] Support completion endpoint (sgl-project#6729) * PD Rust LB (PO2) (sgl-project#6437) * Super tiny enable sole usage of expert distribution metrics and update doc (sgl-project#6680) * Support picking variants of EPLB algorithms (sgl-project#6728) * Support tuning DeepEP configs (sgl-project#6742) * [test] add ut and bm for get_last_loc (sgl-project#6746) * Fix mem_fraction_static for AMD CI (sgl-project#6748) * [fix][RL] Fix DeepSeekV3ForCausalLM.post_load_weights for multiple update weight (sgl-project#6265) * Improve EPLB logical to physical dispatch map (sgl-project#6727) * Update DeepSeek-R1-0528 function call chat template (sgl-project#6765) * [PD] Optimize time out logic and add env var doc for mooncake (sgl-project#6761) * Fix aiohttp 'Chunk too big' in bench_serving (sgl-project#6737) * Support sliding window in triton backend (sgl-project#6509) * Fix shared experts fusion error (sgl-project#6289) * Fix one bug in the grouped-gemm triton kernel (sgl-project#6772) * update llama4 chat template and pythonic parser (sgl-project#6679) * feat(tool call): Enhance Llama32Detector for improved JSON parsing in non-stream (sgl-project#6784) * Support token-level quantization for EP MoE (sgl-project#6782) * Temporarily lower mmlu threshold for triton sliding window backend (sgl-project#6785) * ci: relax test_function_call_required (sgl-project#6786) * Add intel_amx backend for Radix Attention for CPU (sgl-project#6408) * Fix incorrect LoRA weight loading for fused gate_up_proj (sgl-project#6734) * fix(PD-disaggregation): Can not get local ip (sgl-project#6792) * [FIX] mmmu bench serving result display error (sgl-project#6525) (sgl-project#6791) * Bump torch to 2.7.0 (sgl-project#6788) * chore: bump sgl-kernel v0.1.5 (sgl-project#6794) * Improve profiler and integrate profiler in bench_one_batch_server (sgl-project#6787) * chore: upgrade sgl-kernel v0.1.5 (sgl-project#6795) * [Minor] Always append newline after image token when parsing chat message (sgl-project#6797) * Update CI tests for Llama4 models (sgl-project#6421) * [Feat] Enable PDL automatically on Hopper architecture (sgl-project#5981) * chore: update blackwell docker (sgl-project#6800) * misc: cache is_hopper_arch (sgl-project#6799) * Remove contiguous before Flashinfer groupwise fp8 gemm (sgl-project#6804) * Correctly abort the failed grammar requests & Improve the handling of abort (sgl-project#6803) * [EP] Add cuda kernel for moe_ep_pre_reorder (sgl-project#6699) * Add draft extend CUDA graph for flashinfer backend (sgl-project#6805) * Refactor CustomOp to avoid confusing bugs (sgl-project#5382) * Tiny log prefill time (sgl-project#6780) * Tiny fix EPLB assertion about rebalancing period and recorder window size (sgl-project#6813) * Add simple utility to dump tensors for debugging (sgl-project#6815) * Fix profiles do not have consistent names (sgl-project#6811) * Speed up rebalancing when using non-static dispatch algorithms (sgl-project#6812) * [1/2] Add Kernel support for Cutlass based Fused FP4 MoE (sgl-project#6093) * [Router] Fix k8s Service Discovery (sgl-project#6766) * Add CPU optimized kernels for topk and rope fusions (sgl-project#6456) * fix new_page_count_next_decode (sgl-project#6671) * Fix wrong weight reference in dynamic EPLB (sgl-project#6818) * Minor add metrics to expert location updater (sgl-project#6816) * [Refactor] Rename `n_share_experts_fusion` as `num_fused_shared_experts` (sgl-project#6735) * [FEAT] Add transformers backend support (sgl-project#5929) * [fix] recover auto-dispatch for rmsnorm and rope (sgl-project#6745) * fix ep_moe_reorder kernel bugs (sgl-project#6858) * [Refactor] Multimodal data processing for VLM (sgl-project#6659) * Decoder-only Scoring API (sgl-project#6460) * feat: add dp-rank to KV events (sgl-project#6852) * Set `num_fused_shared_experts` as `num_shared_experts` when shared_experts fusion is not disabled (sgl-project#6736) * Fix one missing arg in DeepEP (sgl-project#6878) * Support LoRA in TestOpenAIVisionServer and fix fused kv_proj loading bug. (sgl-project#6861) * support 1 shot allreduce in 1-node and 2-node using mscclpp (sgl-project#6277) * Fix Qwen3MoE missing token padding optimization (sgl-project#6820) * Tiny update error hints (sgl-project#6846) * Support layerwise rebalancing experts (sgl-project#6851) * Tiny allow profiler API to auto create directory (sgl-project#6865) * Support Blackwell DeepEP docker images (sgl-project#6868) * [EP] Add cuda kernel for moe_ep_post_reorder (sgl-project#6837) * [theta]merge 0605 * oai: fix openAI client error with single request via batch api (sgl-project#6170) * [PD] Fix potential perf spike caused by tracker gc and optimize doc (sgl-project#6764) * Use deepgemm instead of triton for fused_qkv_a_proj_with_mqa (sgl-project#6890) * [CUTLASS-FP4-MOE] Introduce CutlassMoEParams class for easy initialization of Cutlass Grouped Gems Metadata (sgl-project#6887) * bugfix(OAI): Fix image_data processing for jinja chat templates (sgl-project#6877) * [CPU] enable CI for PRs, add Dockerfile and auto build task (sgl-project#6458) * AITER backend extension and workload optimizations (sgl-project#6838) * [theta]merge * [theta]merge * [Feature] Support Flashinfer fmha on Blackwell (sgl-project#6930) * Fix a bug in abort & Improve docstrings for abort (sgl-project#6931) * Tiny support customize DeepEP max dispatch tokens per rank (sgl-project#6934) * Sync the changes on cuda graph runners (sgl-project#6932) * [PD] Optimize transfer queue forward logic for dummy rank (sgl-project#6922) * [Refactor] image data process in bench_serving (sgl-project#6879) * [fix] logical_to_all_physical_map index 256 is out of bounds in EP parallel. (sgl-project#6767) * Add triton fused moe kernel config for E=257 on B200 (sgl-project#6939) * [sgl-kernel] update deepgemm (sgl-project#6942) * chore: bump sgl-kernel v0.1.6 (sgl-project#6943) * Minor compile fused topk (sgl-project#6944) * [Bugfix] pipeline parallelism and Eagle Qwen2 (sgl-project#6910) * Tiny re-introduce profile id logging (sgl-project#6912) * Add triton version as a fused_moe_triton config search key to avoid performace decrease in different Triton version (sgl-project#5955) * reduce torch.zeros overhead in moe align block size kernel (sgl-project#6369) * chore: upgrade sgl-kernel v0.1.6 (sgl-project#6945) * add fbgemm moe grouped gemm kernel benchmark (sgl-project#6924) * [Docker] Add docker file for SGL Router (sgl-project#6915) * Disabling mixed chunked prefill when eagle is enabled (sgl-project#6874) * Add canary for EPLB rebalancing (sgl-project#6895) * Refactor global_server_args_dict (sgl-project#6866) * Fuse routed scaling factor in topk_reduce kernel (sgl-project#6220) * Update server timeout time in AMD CI. (sgl-project#6953) * [misc] add is_cpu() (sgl-project#6950) * Add H20 fused MoE kernel tuning configs for DeepSeek-R1/V3 (sgl-project#6885) * Add a CUDA kernel for fusing mapping and weighted sum for MoE. (sgl-project#6916) * chore: bump sgl-kernel v0.1.6.post1 (sgl-project#6955) * chore: upgrade sgl-kernel v0.1.6.post1 (sgl-project#6957) * [DeepseekR1-FP4] Add Support for nvidia/DeepSeekR1-FP4 model (sgl-project#6853) * Revert "Fuse routed scaling factor in topk_reduce kernel (sgl-project#6220)" (sgl-project#6968) * [AMD] Add more tests to per-commit-amd (sgl-project#6926) * chore: bump sgl-kernel v0.1.7 (sgl-project#6963) * Slightly improve the sampler to skip unnecessary steps (sgl-project#6956) * rebase h20 fused_moe config (sgl-project#6966) * Fix CI and triton moe Configs (sgl-project#6974) * Remove unnecessary kernels of num_token_non_padded (sgl-project#6965) * Extend cuda graph capture bs for B200 (sgl-project#6937) * Fuse routed scaling factor in deepseek (sgl-project#6970) * Sync cuda graph runners (sgl-project#6976) * Fix draft extend ut stability with flush cache (sgl-project#6979) * Fix triton sliding window test case (sgl-project#6981) * Fix expert distribution dumping causes OOM (sgl-project#6967) * Minor remove one kernel for DeepSeek (sgl-project#6977) * [perf][sgl-kernel] extend cutlass_mla_decode to support num_head < 128 (sgl-project#6929) * Enable more unit tests for AMD CI. (sgl-project#6983) * Use torch.compile to fuse flash attention decode metadata preparation (sgl-project#6973) * Eliminate stream sync to speed up LoRA batch init (sgl-project#6960) * support qwen3 emebedding (sgl-project#6990) * Fix torch profiler bugs for bench_offline_throughput.py (sgl-project#6557) * chore: upgrade flashinfer v0.2.6.post1 jit (sgl-project#6958) * cleanup tmp dir (sgl-project#7007) * chore: update pr test xeon (sgl-project#7008) * Fix cutlass MLA gets almost zero accuracy (sgl-project#6998) * Update amd nightly models CI. (sgl-project#6992) * feat: add direct routing strategy to DP worker (sgl-project#6884) * Fallback to lower triton version for unfound fused moe configs (sgl-project#7013) * Fix torchvision version for Blackwell (sgl-project#7015) * Simplify prepare_extend_after_decode (sgl-project#6987) * Migrate to assertEqual (sgl-project#6741) * Fix torch version in blackwell dockerfile (sgl-project#7017) * chore: update pr test xeon (sgl-project#7018) * Update default settings for blackwell (sgl-project#7023) * Support both approximate and exact expert distribution collection (sgl-project#6964) * Add decode req pool (sgl-project#6980) * [theta]merge 0610 * [theta]merge 0610 * [CI] Add CI workflow for sgl-router docker build (sgl-project#7027) * Fix fused_moe triton configs (sgl-project#7029) * CPU: map changes from developing branch in sgl-kernel (sgl-project#6833) * chore: bump v0.4.7 (sgl-project#7038) * Update README.md (sgl-project#7040)
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