Upgrade transformers==5.3.0 by JustinTong0323 · Pull Request #17784 · sgl-project/sglang

JustinTong0323 · 2026-01-26T23:03:12Z

Motivation

Address #17779 — Upgrade transformers to 5.3.0.

Changes

Bump transformers>=5.2.0, huggingface_hub>=1.0.0; remove hf_transfer
get_rope_config() utility for backward-compatible config.rope_parameters access
Qwen2: remove padding_idx (transformers#41541)
Gemma3: adapt for v5 API changes
LLaVA: handle CLIPImageProcessorFast returning torch.Tensor instead of ndarray
Qwen2.5-VL encoder: use pooler_output instead of last_hidden_state
Tokenizer: explicitly use_fast=True in auto mode; fix special_tokens_pattern; sync text_config
Config: register custom configs with AutoConfig; GGUF version parsing workaround
Tests: fix _apply_rotary_emb import path; fix Qwen2.5-VL .visual → .model.visual
InternVL test: patch meta-tensor .item() and missing all_tied_weights_keys for v5 compat

TODO

…ple files - Updated `huggingface_hub` dependency to version `>=1.0.0` in `pyproject_cpu.toml`, `pyproject_npu.toml`, `pyproject_other.toml`, `pyproject_xpu.toml`, and `pyproject.toml`. - Upgraded `transformers` dependency to version `5.0.0` in the same files. - Removed `hf_transfer` from the dependencies in the aforementioned files. - Refactored the handling of `rope_theta` and `rope_scaling` parameters to use `config.rope_parameters` in various model files for consistency and improved maintainability. Signed-off-by: Xinyuan Tong <xinyuantong.cs@gmail.com>

gemini-code-assist · 2026-01-26T23:04:13Z

Summary of Changes

Hello @JustinTong0323, 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!

This pull request primarily focuses on upgrading core dependencies, most notably the transformers library to version 5.0.0 and huggingface_hub to >=1.0.0. These updates necessitate significant refactoring across various model implementations to align with changes in how Rotary Positional Embedding (RoPE) parameters (rope_theta and rope_scaling) are accessed, moving towards a more unified config.rope_parameters approach. Additionally, the hf_transfer dependency has been removed, and test runners have been adapted to new API changes in the transformers library for multimodal models. The overall impact is enhanced compatibility with the latest Hugging Face ecosystem and improved code consistency.

Highlights

Dependency Upgrades: The transformers library has been updated to version 5.0.0, and huggingface_hub to >=1.0.0 across all pyproject.toml configurations.
hf_transfer Removal: The hf_transfer dependency and its related activation logic have been removed from project configurations and utility files, streamlining dependencies.
RoPE Parameter Refactoring: The handling of rope_theta and rope_scaling parameters has been refactored across numerous model implementations to consistently use config.rope_parameters.get() for improved maintainability and compatibility with the updated transformers library.
Test Runner Adaptations: Model loading and feature extraction logic in sglang/test/runners.py have been updated to reflect changes in the transformers library, specifically replacing AutoModelForVision2Seq with AutoModelForImageTextToText and adjusting feature extraction calls to use return_dict=True and pooler_output.
Tokenizer Usage Update: A minor adjustment was made in test/registered/core/test_score_api.py to use tokenizer() directly instead of tokenizer.encode_plus().

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gemini-code-assist

Code Review

This pull request primarily focuses on updating the transformers library to version 5.0.0 and adapting the codebase to changes introduced in this new version. Key modifications include updating huggingface_hub and transformers dependencies, removing the hf_transfer dependency and its associated code, and refactoring the access pattern for rope_theta and rope_scaling parameters across various model files to use config.rope_parameters.get(...). Additionally, transformers API calls in test files have been updated to reflect changes in class names and output access methods. These changes are well-justified and necessary for compatibility with the upgraded transformers library, improving overall code maintainability and consistency.

…les for cleaner dependency management. Signed-off-by: Xinyuan Tong <xinyuantong.cs@gmail.com>

JustinTong0323 · 2026-01-26T23:22:42Z

/tag-and-rerun-ci run again again

…files for v5 compatibility. Signed-off-by: Xinyuan Tong <xinyuantong.cs@gmail.com>

tugot17 · 2026-01-29T13:03:01Z

The tokenizer_manager.py also will have to be changed right?

# Wrap each token ID in its own list for batch_decode to decode them separately
 # batch_decode([1, 2, 3]) concatenates tokens, batch_decode([[1], [2], [3]]) decodes separately
token_texts = self.tokenizer.batch_decode([[idx] for idx in token_logprobs_idx])

at least I had to change this to make it run with sglang after manually upgrading

Fix tokenizer behavior in auto mode to ensure compatibility with Transformers v5 by explicitly setting use_fast=True when not provided.

…lang into update-transformers-v5

alisonshao · 2026-03-17T00:39:46Z

stage-b-test-small-1-gpu (5) test_embedding_models.py passed on main

CI Status Update (Run 23168742145 @ 17888cc)

After merging latest main (including #20715 sglang-kernel CI fix):

✅ All stage-b tests pass (except known pre-existing issue)

stage-b-test-small-1-gpu: 7/8 passed — shard 5 fails on Qwen3-Embedding numerical precision on Blackwell (pre-existing, same on main)

stage-b-test-large-1-gpu: 14/14 passed (shard 10 passed on rerun — port conflict flake)

stage-b-test-large-2-gpu: 4/4 passed

stage-b-test-4-gpu-b200: passed

DSV3 accuracy test (MLA + torch compile + FA3 + MTP) all pass

❌ Blocked by pre-existing issues

stage-c all skipped — blocked by wait-for-stage-b gate failing due to shard 5

multimodal-gen-test — FLUX.2-dev 401 auth (gated model access)

The only blocking failure (stage-b-test-small-1-gpu (5) Qwen3-Embedding) is a known pre-existing Blackwell issue that also fails on main. Could a maintainer bypass this gate to run stage-c tests?

JustinTong0323 · 2026-03-17T14:06:17Z

stage-b-test-small-1-gpu (5) test_embedding_models.py passed on main

fixed in be57936

…asses The _fix_v5_add_bos_eos_token function was blindly restoring add_eos_token from tokenizer_config.json for all models, but Qwen2Tokenizer did not support this flag in v4. This caused gte-Qwen2-1.5B-instruct to add an unexpected EOS token, breaking embedding similarity tests. Changes: - Only restore BOS/EOS flags for tokenizer classes that supported them in v4 (LlamaTokenizer, GemmaTokenizer, etc.) - Use v4 defaults (add_bos_token=True) when config value is null/missing to prevent update_post_processor() from dropping BOS - Apply the same tokenizer fix to sentence-transformers in the HF test runner so HF reference and SRT produce matching tokens

…duce dead code - Extract compute_mla_mscale_scaling() to replace 4 copy-pasted rope scaling blocks in model_config.py and deepseek_v2.py - Extract _resolve_local_or_cached_file() to deduplicate local-path-then -hf_hub_download pattern across 3 tokenizer/processor fix functions - Extract ensure_numpy() in mm_utils.py to deduplicate torch.Tensor to numpy conversion in mm_utils.py and llava.py - Restructure get_hf_text_config() as proper elif chain with documented priority (thinker > llm > language > text), fixing assert that fired on text_config even when llm_config would override it - Add thinker_config to early dict-to-PretrainedConfig conversion loop - Remove dead dict-conversion branch in _patch_text_config (already handled by early loop in get_hf_text_config) - Use from_dict instead of from_pretrained in get_config KeyError handler to avoid redundant disk read - Add warning log for AutoImageProcessor failures in _build_processor_manually instead of silent swallow

- Fix operator precedence in is_deepseek_nsa: extract index_topk to separate variable for clarity - Fix llama_eagle3 wrong nested key: rope_parameters["rope_type"] instead of rope_parameters["rope_scaling"]["rope_type"] - Fix midashenglm same nested key bug: directly delete mrope_section from rope_parameters instead of writing to nonexistent nested key - Fix gemma3n_causal _tied_weights_keys: use v5 dict format {target: source} instead of v4 list format - Add debug logging to broad except clauses in hf_transformers_utils - Narrow _ensure_llama_flash_attention2_compat exception to ImportError - Improve batch_decode comment in tokenizer_manager

Signed-off-by: Xinyuan Tong <xinyuantong.cs@gmail.com>

nvpohanh · 2026-03-18T02:28:59Z

@JustinTong0323 Please let me know if you need help with fixing the issues after transformers version upgrade. Thanks!

JustinTong0323 · 2026-03-18T03:20:50Z

@JustinTong0323 Please let me know if you need help with fixing the issues after transformers version upgrade. Thanks!

Thanks! I think most of the work is done and we only need to pass the CI now.

This reverts commit d1e95af.

…ccuracy threshold PR sgl-project#17784 (transformers 5.3.0 upgrade) changed grok.py to access config.rope_parameters["rope_theta"] directly, but GitConfig (grok-2) does not have this attribute, crashing the server on startup with AttributeError: 'GitConfig' object has no attribute 'rope_parameters'. Restore safe access via getattr with fallback, matching the pattern used elsewhere in the codebase. Also lower the MI325 Grok-2 GSM8K accuracy threshold from 0.915 to 0.90 to match the MI35x test, since nightly sgl-project#636 showed 0.910 which is within normal run-to-run variance.

guapisolo · 2026-03-20T19:40:19Z

Great job.

Signed-off-by: Xinyuan Tong <xinyuantong.cs@gmail.com> Co-authored-by: Kangyan-Zhou <zky314343421@gmail.com> Co-authored-by: Alison Shao <alisonshao@mac.lan> Co-authored-by: Mick <mickjagger19@icloud.com>

yudian0504 · 2026-03-26T08:38:14Z

K2.5 failed with new transformers==5.3.0:

Traceback (most recent call last):
  File "/opt/conda/lib/python3.10/runpy.py", line 196, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "/opt/conda/lib/python3.10/runpy.py", line 86, in _run_code
    exec(code, run_globals)
  File "/opt/conda/lib/python3.10/site-packages/sglang/launch_server.py", line 68, in <module>
    run_server(server_args)
  File "/opt/conda/lib/python3.10/site-packages/sglang/launch_server.py", line 52, in run_server
    launch_server(server_args)
  File "/opt/conda/lib/python3.10/site-packages/sglang/srt/entrypoints/http_server.py", line 2235, in launch_server
    Engine._launch_subprocesses(
  File "/opt/conda/lib/python3.10/site-packages/sglang/srt/entrypoints/engine.py", line 681, in _launch_subprocesses
    tokenizer_manager, template_manager = init_tokenizer_manager_func(
  File "/opt/conda/lib/python3.10/site-packages/sglang/srt/entrypoints/engine.py", line 131, in init_tokenizer_manager
    tokenizer_manager = TokenizerManagerClass(server_args, port_args)
  File "/opt/conda/lib/python3.10/site-packages/sglang/srt/managers/tokenizer_manager.py", line 269, in __init__
    self.init_tokenizer_and_processor()
  File "/opt/conda/lib/python3.10/site-packages/sglang/srt/managers/tokenizer_manager.py", line 335, in init_tokenizer_and_processor
    _processor = _get_processor_wrapper(server_args)
  File "/opt/conda/lib/python3.10/site-packages/sglang/srt/managers/tokenizer_manager.py", line 3015, in _get_processor_wrapper
    processor = get_processor(
  File "/opt/conda/lib/python3.10/site-packages/sglang/srt/utils/hf_transformers_utils.py", line 1180, in get_processor
    processor = AutoProcessor.from_pretrained(
  File "/opt/conda/lib/python3.10/site-packages/transformers/models/auto/processing_auto.py", line 407, in from_pretrained
    return processor_class.from_pretrained(
  File "/opt/conda/lib/python3.10/site-packages/transformers/processing_utils.py", line 1403, in from_pretrained
    args = cls._get_arguments_from_pretrained(pretrained_model_name_or_path, processor_dict, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/transformers/processing_utils.py", line 1517, in _get_arguments_from_pretrained
    tokenizer = cls._load_tokenizer_from_pretrained(
  File "/opt/conda/lib/python3.10/site-packages/transformers/processing_utils.py", line 1464, in _load_tokenizer_from_pretrained
    tokenizer = auto_processor_class.from_pretrained(
  File "/opt/conda/lib/python3.10/site-packages/transformers/models/auto/tokenization_auto.py", line 732, in from_pretrained
    tokenizer_class = get_class_from_dynamic_module(class_ref, pretrained_model_name_or_path, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/transformers/dynamic_module_utils.py", line 583, in get_class_from_dynamic_module
    return get_class_in_module(class_name, final_module, force_reload=force_download)
  File "/opt/conda/lib/python3.10/site-packages/transformers/dynamic_module_utils.py", line 309, in get_class_in_module
    module_spec.loader.exec_module(module)
  File "<frozen importlib._bootstrap_external>", line 883, in exec_module
  File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed
  File "/root/.cache/huggingface/modules/transformers_modules/tokenization_kimi.py", line 11, in <module>
    from transformers.models.gpt2.tokenization_gpt2 import bytes_to_unicode
ImportError: cannot import name 'bytes_to_unicode' from 'transformers.models.gpt2.tokenization_gpt2' (/opt/conda/lib/python3.10/site-packages/transformers/models/gpt2/tokenization_gpt2.py)

yudian0504 · 2026-03-26T09:01:16Z

K2.5 failed with new transformers==5.3.0:

Traceback (most recent call last):
  File "/opt/conda/lib/python3.10/runpy.py", line 196, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "/opt/conda/lib/python3.10/runpy.py", line 86, in _run_code
    exec(code, run_globals)
  File "/opt/conda/lib/python3.10/site-packages/sglang/launch_server.py", line 68, in <module>
    run_server(server_args)
  File "/opt/conda/lib/python3.10/site-packages/sglang/launch_server.py", line 52, in run_server
    launch_server(server_args)
  File "/opt/conda/lib/python3.10/site-packages/sglang/srt/entrypoints/http_server.py", line 2235, in launch_server
    Engine._launch_subprocesses(
  File "/opt/conda/lib/python3.10/site-packages/sglang/srt/entrypoints/engine.py", line 681, in _launch_subprocesses
    tokenizer_manager, template_manager = init_tokenizer_manager_func(
  File "/opt/conda/lib/python3.10/site-packages/sglang/srt/entrypoints/engine.py", line 131, in init_tokenizer_manager
    tokenizer_manager = TokenizerManagerClass(server_args, port_args)
  File "/opt/conda/lib/python3.10/site-packages/sglang/srt/managers/tokenizer_manager.py", line 269, in __init__
    self.init_tokenizer_and_processor()
  File "/opt/conda/lib/python3.10/site-packages/sglang/srt/managers/tokenizer_manager.py", line 335, in init_tokenizer_and_processor
    _processor = _get_processor_wrapper(server_args)
  File "/opt/conda/lib/python3.10/site-packages/sglang/srt/managers/tokenizer_manager.py", line 3015, in _get_processor_wrapper
    processor = get_processor(
  File "/opt/conda/lib/python3.10/site-packages/sglang/srt/utils/hf_transformers_utils.py", line 1180, in get_processor
    processor = AutoProcessor.from_pretrained(
  File "/opt/conda/lib/python3.10/site-packages/transformers/models/auto/processing_auto.py", line 407, in from_pretrained
    return processor_class.from_pretrained(
  File "/opt/conda/lib/python3.10/site-packages/transformers/processing_utils.py", line 1403, in from_pretrained
    args = cls._get_arguments_from_pretrained(pretrained_model_name_or_path, processor_dict, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/transformers/processing_utils.py", line 1517, in _get_arguments_from_pretrained
    tokenizer = cls._load_tokenizer_from_pretrained(
  File "/opt/conda/lib/python3.10/site-packages/transformers/processing_utils.py", line 1464, in _load_tokenizer_from_pretrained
    tokenizer = auto_processor_class.from_pretrained(
  File "/opt/conda/lib/python3.10/site-packages/transformers/models/auto/tokenization_auto.py", line 732, in from_pretrained
    tokenizer_class = get_class_from_dynamic_module(class_ref, pretrained_model_name_or_path, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/transformers/dynamic_module_utils.py", line 583, in get_class_from_dynamic_module
    return get_class_in_module(class_name, final_module, force_reload=force_download)
  File "/opt/conda/lib/python3.10/site-packages/transformers/dynamic_module_utils.py", line 309, in get_class_in_module
    module_spec.loader.exec_module(module)
  File "<frozen importlib._bootstrap_external>", line 883, in exec_module
  File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed
  File "/root/.cache/huggingface/modules/transformers_modules/tokenization_kimi.py", line 11, in <module>
    from transformers.models.gpt2.tokenization_gpt2 import bytes_to_unicode
ImportError: cannot import name 'bytes_to_unicode' from 'transformers.models.gpt2.tokenization_gpt2' (/opt/conda/lib/python3.10/site-packages/transformers/models/gpt2/tokenization_gpt2.py)

update: solved by updating https://huggingface.co/moonshotai/Kimi-K2.5/blob/main/tokenization_kimi.py

Signed-off-by: Xinyuan Tong <xinyuantong.cs@gmail.com> Co-authored-by: Kangyan-Zhou <zky314343421@gmail.com> Co-authored-by: Alison Shao <alisonshao@mac.lan> Co-authored-by: Mick <mickjagger19@icloud.com>

JustinTong0323 requested review from Fridge003, ch-wan, fzyzcjy, ispobock, merrymercy, mickqian, yhyang201 and zhyncs as code owners January 26, 2026 23:03

github-actions bot added quant LLM Quantization dependencies Pull requests that update a dependency file deepseek npu diffusion SGLang Diffusion labels Jan 26, 2026

gemini-code-assist bot reviewed Jan 26, 2026

View reviewed changes

Remove huggingface_hub>=1.0.0 dependency from multiple pyproject fi…

24b2db0

…les for cleaner dependency management. Signed-off-by: Xinyuan Tong <xinyuantong.cs@gmail.com>

github-actions bot added the run-ci label Jan 26, 2026

Fridge003 added the high priority label Jan 27, 2026

JustinTong0323 and others added 3 commits January 27, 2026 12:16

Update peft dependency to version >=0.18.0 in multiple pyproject …

a5584c3

…files for v5 compatibility. Signed-off-by: Xinyuan Tong <xinyuantong.cs@gmail.com>

Merge branch 'main' into update-transformers-v5

c2328d9

Merge branch 'main' into update-transformers-v5

f298583

vincentzed mentioned this pull request Jan 29, 2026

[Liquid AI] Support LFM VL #17954

Open

5 tasks

Merge branch 'main' into update-transformers-v5

4d5cc69

JustinTong0323 requested review from Ying1123, hnyls2002 and xiezhq-hermann as code owners February 2, 2026 05:30

fix batch decode

330fbcd

Fix tokenizer behavior in auto mode to ensure compatibility with Transformers v5 by explicitly setting use_fast=True when not provided.

JustinTong0323 and others added 5 commits March 16, 2026 13:31

Merge remote-tracking branch 'upstream/main' into update-transformers-v5

c32ad73

Merge branch 'main' into update-transformers-v5

634ba2e

Merge remote-tracking branch 'upstream/main' into update-transformers-v5

f73d0b8

Merge branch 'update-transformers-v5' of github.com:JustinTong0323/sg…

41a4fb1

…lang into update-transformers-v5

Merge branch 'main' into update-transformers-v5

17888cc

nvpohanh mentioned this pull request Mar 17, 2026

[Tracking] GLM-5 (G)B200 Functional Support and Optimizations #19380

Open

JustinTong0323 added 4 commits March 17, 2026 15:13

lint

a2ccf3b

Signed-off-by: Xinyuan Tong <xinyuantong.cs@gmail.com>

Fridge003 approved these changes Mar 18, 2026

View reviewed changes

Fridge003 merged commit d1e95af into sgl-project:main Mar 18, 2026
374 of 413 checks passed

Talantan1102 pushed a commit to randgun/sglang that referenced this pull request Mar 19, 2026

Revert "Upgrade transformers==5.3.0 (sgl-project#17784)"

500c56d

This reverts commit d1e95af.

yuan-luo mentioned this pull request Mar 20, 2026

[Fix] SGLANG_USE_CUDA_IPC_TRANSPORT=1 and SGLANG_ENABLE_MM_SPLITTING=1 do not work at the same time. #19915

Merged

5 tasks

michaelzhang-ai mentioned this pull request Mar 20, 2026

[AMD] Fix Grok-2 nightly: safe rope_parameters access + relax MI325 accuracy threshold #20985

Closed

3 tasks

chx96642264 mentioned this pull request Mar 20, 2026

[Bug][Func][SDV]Service startup failed using Qwen3 and Llama models. Ascend/sglang#121

Closed

5 tasks

alphabetc1 mentioned this pull request Mar 22, 2026

fix: use get_rope_config() to support models without rope_parameters #21135

Merged

5 tasks

michaelzhang-ai mentioned this pull request Mar 24, 2026

[AMD] 4-GPU tests: lowered accuracy thresholds on ROCm with triton backend #21340

Open

dougyster mentioned this pull request Apr 2, 2026

fix: mistral embedding regression fix #21913

Merged

5 tasks

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alisonshao commented Mar 17, 2026

CI Status Update (Run 23168742145 @ 17888cc)

✅ All stage-b tests pass (except known pre-existing issue)

❌ Blocked by pre-existing issues

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JustinTong0323 commented Jan 26, 2026 •

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