Upgrade transformers to v4.50.3

docs/source/models/supported_models.md

@@ -73,7 +73,7 @@ The Transformers fallback explicitly supports the following features:
 
 - <project:#quantization-index> (except GGUF)
 - <project:#lora-adapter>
-- <project:#distributed-serving> (requires `transformers>=4.49.0`)
+- <project:#distributed-serving>
 
 #### Remote code
 

requirements/common.txt

@@ -6,7 +6,7 @@ requests >= 2.26.0
 tqdm
 blake3
 py-cpuinfo
-transformers >= 4.48.2  # Required for Bamba model and Transformers backend.
+transformers >= 4.50.3
 tokenizers >= 0.19.1  # Required for Llama 3.
 protobuf # Required by LlamaTokenizer.
 fastapi[standard] >= 0.115.0 # Required by FastAPI's form models in the OpenAI API server's audio transcriptions endpoint.

requirements/test.in

@@ -30,7 +30,7 @@ matplotlib # required for qwen-vl test
 mistral_common[opencv] >= 1.5.4 # required for pixtral test
 datamodel_code_generator # required for minicpm3 test
 lm-eval[api]==0.4.4 # required for model evaluation test
-transformers==4.48.2
+transformers==4.50.3
 # quantization
 bitsandbytes>=0.45.3
 buildkite-test-collector==0.1.9

requirements/test.txt

@@ -643,7 +643,7 @@ tqdm==4.66.6
     #   transformers
 tqdm-multiprocess==0.0.11
     # via lm-eval
-transformers==4.48.2
+transformers==4.50.3
     # via
     #   -r requirements/test.in
     #   genai-perf

tests/distributed/test_pipeline_parallel.py

@@ -245,7 +245,7 @@ def iter_params(self, model_id: str):
     # [LANGUAGE GENERATION]
     "microsoft/Phi-3.5-MoE-instruct",
     "meta-llama/Llama-3.2-1B-Instruct",
-    # "ArthurZ/Ilama-3.2-1B", NOTE: Uncomment after #13905
+    "ArthurZ/Ilama-3.2-1B",
     "ibm/PowerLM-3b",
     # [LANGUAGE EMBEDDING]
     "intfloat/e5-mistral-7b-instruct",

tests/models/decoder_only/vision_language/test_models.py

@@ -8,9 +8,7 @@
 from pathlib import PosixPath
 
 import pytest
-from packaging.version import Version
 from transformers import AutoModelForImageTextToText, AutoModelForVision2Seq
-from transformers import __version__ as TRANSFORMERS_VERSION
 
 from vllm.platforms import current_platform
 from vllm.utils import identity
@@ -126,25 +124,6 @@
         dtype="bfloat16",
         marks=[pytest.mark.skip(reason="vLLM does not support PrefixLM attention mask")],  # noqa: E501
     ),
-    # TODO(ywang96): Move Qwen2-VL out of core models in favor of Qwen2.5-VL
-    # once we upgraded to transformers>=4.49.0.
-    "qwen2_vl": VLMTestInfo(
-        models=["Qwen/Qwen2-VL-2B-Instruct"],
-        test_type=(
-            VLMTestType.IMAGE,
-            VLMTestType.MULTI_IMAGE,
-            VLMTestType.VIDEO
-        ),
-        prompt_formatter=lambda img_prompt: f"<|im_start|>User\n{img_prompt}<|im_end|>\n<|im_start|>assistant\n", # noqa: E501
-        img_idx_to_prompt=lambda idx: "<|vision_start|><|image_pad|><|vision_end|>", # noqa: E501
-        video_idx_to_prompt=lambda idx: "<|vision_start|><|video_pad|><|vision_end|>", # noqa: E501
-        max_model_len=4096,
-        max_num_seqs=2,
-        auto_cls=AutoModelForVision2Seq,
-        vllm_output_post_proc=model_utils.qwen2_vllm_to_hf_output,
-        image_size_factors=[(), (0.25,), (0.25, 0.25, 0.25), (0.25, 0.2, 0.15)],
-        marks=[pytest.mark.core_model, pytest.mark.cpu_model],
-    ),
     "qwen2_5_vl": VLMTestInfo(
         models=["Qwen/Qwen2.5-VL-3B-Instruct"],
         test_type=(
@@ -218,12 +197,6 @@
         hf_output_post_proc=model_utils.deepseekvl2_trunc_hf_output,
         stop_str=["<｜end▁of▁sentence｜>", "<｜begin▁of▁sentence｜>"],  # noqa: E501
         image_size_factors=[(), (1.0, ), (1.0, 1.0, 1.0), (0.1, 0.5, 1.0)],
-        marks=[
-            pytest.mark.skipif(
-                Version(TRANSFORMERS_VERSION) >= Version("4.48"),
-                reason="HF model is not compatible with transformers>=4.48",
-            )
-        ],
     ),
     "fuyu": VLMTestInfo(
         models=["adept/fuyu-8b"],
@@ -336,6 +309,7 @@
         prompt_formatter=lambda vid_prompt: f"<|im_start|>user\n{vid_prompt}<|im_end|>\n<|im_start|>assistant\n",   # noqa: E501
         num_video_frames=16,
         max_model_len=16384,
+        hf_model_kwargs=model_utils.llava_onevision_hf_model_kwargs("llava-hf/llava-onevision-qwen2-0.5b-ov-hf"),   # noqa: E501
         auto_cls=AutoModelForVision2Seq,
         vllm_output_post_proc=model_utils.llava_onevision_vllm_to_hf_output,
         custom_test_opts=[CustomTestOptions(
@@ -365,12 +339,6 @@
         auto_cls=AutoModelForImageTextToText,
         vllm_output_post_proc=model_utils.mantis_vllm_to_hf_output,
         patch_hf_runner=model_utils.mantis_patch_hf_runner,
-        marks=[
-            pytest.mark.skipif(
-                Version(TRANSFORMERS_VERSION) >= Version("4.48"),
-                reason="HF model is not compatible with transformers>=4.48",
-            )
-        ],
     ),
     "minicpmv_25": VLMTestInfo(
         models=["openbmb/MiniCPM-Llama3-V-2_5"],
@@ -450,6 +418,23 @@
         vllm_output_post_proc=model_utils.qwen_vllm_to_hf_output,
         prompt_path_encoder=model_utils.qwen_prompt_path_encoder,
     ),
+    "qwen2_vl": VLMTestInfo(
+        models=["Qwen/Qwen2-VL-2B-Instruct"],
+        test_type=(
+            VLMTestType.IMAGE,
+            VLMTestType.MULTI_IMAGE,
+            VLMTestType.VIDEO
+        ),
+        prompt_formatter=lambda img_prompt: f"<|im_start|>User\n{img_prompt}<|im_end|>\n<|im_start|>assistant\n", # noqa: E501
+        img_idx_to_prompt=lambda idx: "<|vision_start|><|image_pad|><|vision_end|>", # noqa: E501
+        video_idx_to_prompt=lambda idx: "<|vision_start|><|video_pad|><|vision_end|>", # noqa: E501
+        max_model_len=4096,
+        max_num_seqs=2,
+        auto_cls=AutoModelForVision2Seq,
+        vllm_output_post_proc=model_utils.qwen2_vllm_to_hf_output,
+        image_size_factors=[(), (0.25,), (0.25, 0.25, 0.25), (0.25, 0.2, 0.15)],
+        marks=[pytest.mark.cpu_model],
+    ),
     "skywork_r1v": VLMTestInfo(
         models=["Skywork/Skywork-R1V-38B"],
         test_type=(VLMTestType.IMAGE, VLMTestType.MULTI_IMAGE),
@@ -515,6 +500,7 @@
         max_model_len=16384,
         max_num_seqs=2,
         auto_cls=AutoModelForVision2Seq,
+        hf_model_kwargs=model_utils.llava_onevision_hf_model_kwargs("llava-hf/llava-onevision-qwen2-0.5b-ov-hf"),   # noqa: E501
         vllm_output_post_proc=model_utils.llava_onevision_vllm_to_hf_output,
         custom_test_opts=[CustomTestOptions(
             inputs=custom_inputs.multi_image_multi_aspect_ratio_inputs(

tests/models/decoder_only/vision_language/vlm_utils/model_utils.py

@@ -104,6 +104,13 @@ def _llava_vllm_to_hf_output(vllm_output: RunnerOutput, model: str,
     return hf_output_ids, hf_output_str, out_logprobs
 
 
+def llava_onevision_hf_model_kwargs(model: str) -> dict:
+    """Workaround to fix the sliding window issue in llava_onevision."""
+    config = AutoConfig.from_pretrained(model)
+    config.text_config.sliding_window = None
+    return config.to_dict()
+
+
 def llava_onevision_vllm_to_hf_output(vllm_output: RunnerOutput,
                                       model: str) -> RunnerOutput:
     """Sanitize vllm output [llava-onevision] to compare with hf output."""

tests/models/registry.py

@@ -34,6 +34,16 @@ class _HfExamplesInfo:
     The minimum version of HF Transformers that is required to run this model.
     """
 
+    max_transformers_version: Optional[str] = None
+    """
+    The maximum version of HF Transformers that this model runs on.
+    """
+
+    transformers_version_reason: Optional[str] = None
+    """
+    The reason for the minimum/maximum version requirement.
+    """
+
     is_available_online: bool = True
     """
     Set this to ``False`` if the name of this architecture no longer exists on
@@ -57,21 +67,28 @@ def check_transformers_version(
         If the installed transformers version does not meet the requirements,
         perform the given action.
         """
-        if self.min_transformers_version is None:
+        if (self.min_transformers_version is None
+                and self.max_transformers_version is None):
             return
 
         current_version = TRANSFORMERS_VERSION
-        required_version = self.min_transformers_version
-        if Version(current_version) < Version(required_version):
-            msg = (
-                f"You have `transformers=={current_version}` installed, but "
-                f"`transformers>={required_version}` is required to run this "
-                "model")
+        min_version = self.min_transformers_version
+        max_version = self.max_transformers_version
+        msg = f"`transformers=={current_version}` installed, but `transformers"
+        if min_version and Version(current_version) < Version(min_version):
+            msg += f">={min_version}` is required to run this model."
+        elif max_version and Version(current_version) > Version(max_version):
+            msg += f"<={max_version}` is required to run this model."
+        else:
+            return
 
-            if on_fail == "error":
-                raise RuntimeError(msg)
-            else:
-                pytest.skip(msg)
+        if self.transformers_version_reason:
+            msg += f" Reason: {self.transformers_version_reason}"
+
+        if on_fail == "error":
+            raise RuntimeError(msg)
+        else:
+            pytest.skip(msg)
 
     def check_available_online(
         self,
@@ -245,6 +262,9 @@ def check_available_online(
     "Blip2ForConditionalGeneration": _HfExamplesInfo("Salesforce/blip2-opt-2.7b"),  # noqa: E501
     "ChameleonForConditionalGeneration": _HfExamplesInfo("facebook/chameleon-7b"),  # noqa: E501
     "DeepseekVLV2ForCausalLM": _HfExamplesInfo("deepseek-ai/deepseek-vl2-tiny",  # noqa: E501
+                                                extras={"fork": "Isotr0py/deepseek-vl2-tiny"},  # noqa: E501
+                                                max_transformers_version="4.48",  # noqa: E501
+                                                transformers_version_reason="HF model is not compatible.",  # noqa: E501
                                                hf_overrides={"architectures": ["DeepseekVLV2ForCausalLM"]}),  # noqa: E501
     "FuyuForCausalLM": _HfExamplesInfo("adept/fuyu-8b"),
     "Gemma3ForConditionalGeneration": _HfExamplesInfo("google/gemma-3-4b-it",
@@ -266,13 +286,19 @@ def check_available_online(
     "LlavaNextVideoForConditionalGeneration": _HfExamplesInfo("llava-hf/LLaVA-NeXT-Video-7B-hf"),  # noqa: E501
     "LlavaOnevisionForConditionalGeneration": _HfExamplesInfo("llava-hf/llava-onevision-qwen2-0.5b-ov-hf"),  # noqa: E501
     "MantisForConditionalGeneration": _HfExamplesInfo("TIGER-Lab/Mantis-8B-siglip-llama3",  # noqa: E501
+                                                      max_transformers_version="4.48",  # noqa: E501
+                                                      transformers_version_reason="HF model is not compatible.",  # noqa: E501
                                                       hf_overrides={"architectures": ["MantisForConditionalGeneration"]}),  # noqa: E501
     "MiniCPMO": _HfExamplesInfo("openbmb/MiniCPM-o-2_6",
+                                max_transformers_version="4.48",
+                                transformers_version_reason="Use of deprecated imports which have been removed.",  # noqa: E501
                                 trust_remote_code=True),
     "MiniCPMV": _HfExamplesInfo("openbmb/MiniCPM-Llama3-V-2_5",
                                 extras={"2.6": "openbmb/MiniCPM-V-2_6"},  # noqa: E501
                                 trust_remote_code=True),
     "MolmoForCausalLM": _HfExamplesInfo("allenai/Molmo-7B-D-0924",
+                                        max_transformers_version="4.48",
+                                        transformers_version_reason="Use of private method which no longer exists.",  # noqa: E501
                                         extras={"olmo": "allenai/Molmo-7B-O-0924"},  # noqa: E501
                                         trust_remote_code=True),
     "NVLM_D": _HfExamplesInfo("nvidia/NVLM-D-72B",