diff --git a/docs/source/models/supported_models.md b/docs/source/models/supported_models.md index 0fa10e0734ad8..1705757d8308f 100644 --- a/docs/source/models/supported_models.md +++ b/docs/source/models/supported_models.md @@ -73,7 +73,7 @@ The Transformers fallback explicitly supports the following features: - (except GGUF) - -- (requires `transformers>=4.49.0`) +- #### Remote code diff --git a/requirements/common.txt b/requirements/common.txt index dfa20f5e3f08e..c7bbdb71b742c 100644 --- a/requirements/common.txt +++ b/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. diff --git a/requirements/test.in b/requirements/test.in index a7dd54151dee8..cf89794b93fc7 100644 --- a/requirements/test.in +++ b/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 diff --git a/requirements/test.txt b/requirements/test.txt index aed6a5653e2ad..26ed9dbe32cb5 100644 --- a/requirements/test.txt +++ b/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 diff --git a/tests/distributed/test_pipeline_parallel.py b/tests/distributed/test_pipeline_parallel.py index 751c4eb096ae0..6277a1009ffe4 100644 --- a/tests/distributed/test_pipeline_parallel.py +++ b/tests/distributed/test_pipeline_parallel.py @@ -245,7 +245,7 @@ TEST_MODELS = [ # [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", diff --git a/tests/models/decoder_only/vision_language/test_models.py b/tests/models/decoder_only/vision_language/test_models.py index ecb637c62e439..aa3ac7eea6d0d 100644 --- a/tests/models/decoder_only/vision_language/test_models.py +++ b/tests/models/decoder_only/vision_language/test_models.py @@ -8,9 +8,7 @@ from collections import defaultdict 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 @@ VLM_TEST_SETTINGS = { 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 @@ VLM_TEST_SETTINGS = { 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 @@ VLM_TEST_SETTINGS = { 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 @@ VLM_TEST_SETTINGS = { 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 @@ VLM_TEST_SETTINGS = { 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 @@ VLM_TEST_SETTINGS = { 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( diff --git a/tests/models/decoder_only/vision_language/vlm_utils/model_utils.py b/tests/models/decoder_only/vision_language/vlm_utils/model_utils.py index 2ddf28aca4f63..2e9190fc6893c 100644 --- a/tests/models/decoder_only/vision_language/vlm_utils/model_utils.py +++ b/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.""" diff --git a/tests/models/registry.py b/tests/models/registry.py index a733fedcdd6c0..7c8fac08befff 100644 --- a/tests/models/registry.py +++ b/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 @@ class _HfExamplesInfo: 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 @@ _MULTIMODAL_EXAMPLE_MODELS = { "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 @@ _MULTIMODAL_EXAMPLE_MODELS = { "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",