[Model] Upgrade Aria to transformers 4.48 (vllm-project#12203)

Signed-off-by: DarkLight1337 <[email protected]>
Signed-off-by: Matthew Hendrey <[email protected]>

examples/offline_inference/vision_language.py

@@ -26,11 +26,8 @@ def run_aria(question: str, modality: str):
 
     # NOTE: Need L40 (or equivalent) to avoid OOM
     llm = LLM(model=model_name,
-              tokenizer_mode="slow",
-              dtype="bfloat16",
               max_model_len=4096,
               max_num_seqs=2,
-              trust_remote_code=True,
               disable_mm_preprocessor_cache=args.disable_mm_preprocessor_cache)
 
     prompt = (f"<|im_start|>user\n<fim_prefix><|img|><fim_suffix>\n{question}"

tests/models/decoder_only/vision_language/test_models.py

@@ -10,7 +10,6 @@
 import pytest
 from transformers import AutoModelForVision2Seq
 from transformers import __version__ as TRANSFORMERS_VERSION
-from transformers.utils import is_flash_attn_2_available
 
 from vllm.platforms import current_platform
 from vllm.utils import identity
@@ -140,9 +139,7 @@
     #### Extended model tests
     "aria": VLMTestInfo(
         models=["rhymes-ai/Aria"],
-        tokenizer_mode="slow",
         test_type=(VLMTestType.IMAGE, VLMTestType.MULTI_IMAGE),
-        dtype="bfloat16",
         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: "<fim_prefix><|img|><fim_suffix>\n",
         max_model_len=4096,
@@ -158,8 +155,8 @@
         max_tokens=64,
         marks=[
             pytest.mark.skipif(
-                not is_flash_attn_2_available(),
-                reason="Model needs flash-attn for numeric convergence.",
+                TRANSFORMERS_VERSION < "4.48.0",
+                reason="HF model requires transformers>=4.48.0",
             ),
             large_gpu_mark(min_gb=64),
         ],

tests/models/multimodal/processing/test_common.py

@@ -11,6 +11,7 @@
 from vllm.multimodal.utils import cached_get_tokenizer
 
 from ....multimodal.utils import random_audio, random_image, random_video
+from ...registry import HF_EXAMPLE_MODELS
 
 
 def _test_processing_correctness(
@@ -20,12 +21,9 @@ def _test_processing_correctness(
     num_batches: int,
     simplify_rate: float,
 ):
-    if model_id == "TIGER-Lab/Mantis-8B-siglip-llama3":
-        hf_overrides = {"architectures": ["MantisForConditionalGeneration"]}
-    elif model_id == "deepseek-ai/deepseek-vl2-tiny":
-        hf_overrides = {"architectures": ["DeepseekVLV2ForCausalLM"]}
-    else:
-        hf_overrides = {}
+    model_info = HF_EXAMPLE_MODELS.find_hf_info(model_id)
+    model_info.check_available_online(on_fail="skip")
+    model_info.check_transformers_version(on_fail="skip")
 
     limit_mm_per_prompt = {
         modality: 3 if supports_multi else 1
@@ -41,7 +39,7 @@ def _test_processing_correctness(
         seed=0,
         dtype="float16",
         revision=None,
-        hf_overrides=hf_overrides,
+        hf_overrides=model_info.hf_overrides,
         limit_mm_per_prompt=limit_mm_per_prompt,
     )
 

tests/models/registry.py

@@ -1,5 +1,9 @@
 from dataclasses import dataclass, field
-from typing import AbstractSet, Mapping, Optional
+from typing import AbstractSet, Any, Literal, Mapping, Optional
+
+import pytest
+from packaging.version import Version
+from transformers import __version__ as TRANSFORMERS_VERSION
 
 
 @dataclass(frozen=True)
@@ -38,6 +42,50 @@ class _HfExamplesInfo:
     trust_remote_code: bool = False
     """The ``trust_remote_code`` level required to load the model."""
 
+    hf_overrides: dict[str, Any] = field(default_factory=dict)
+    """The ``hf_overrides`` required to load the model."""
+
+    def check_transformers_version(
+        self,
+        *,
+        on_fail: Literal["error", "skip"],
+    ) -> None:
+        """
+        If the installed transformers version does not meet the requirements,
+        perform the given action.
+        """
+        if self.min_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")
+
+            if on_fail == "error":
+                raise RuntimeError(msg)
+            else:
+                pytest.skip(msg)
+
+    def check_available_online(
+        self,
+        *,
+        on_fail: Literal["error", "skip"],
+    ) -> None:
+        """
+        If the model is not available online, perform the given action.
+        """
+        if not self.is_available_online:
+            msg = "Model is not available online"
+
+            if on_fail == "error":
+                raise RuntimeError(msg)
+            else:
+                pytest.skip(msg)
+
 
 # yapf: disable
 _TEXT_GENERATION_EXAMPLE_MODELS = {
@@ -48,8 +96,6 @@ class _HfExamplesInfo:
                                          trust_remote_code=True),
     "ArcticForCausalLM": _HfExamplesInfo("Snowflake/snowflake-arctic-instruct",
                                          trust_remote_code=True),
-    "AriaForConditionalGeneration": _HfExamplesInfo("rhymes-ai/Aria",
-                                                    trust_remote_code=True),
     "BaiChuanForCausalLM": _HfExamplesInfo("baichuan-inc/Baichuan-7B",
                                          trust_remote_code=True),
     "BaichuanForCausalLM": _HfExamplesInfo("baichuan-inc/Baichuan2-7B-chat",
@@ -176,14 +222,17 @@ class _HfExamplesInfo:
 
 _MULTIMODAL_EXAMPLE_MODELS = {
     # [Decoder-only]
+    "AriaForConditionalGeneration": _HfExamplesInfo("rhymes-ai/Aria",
+                                                    min_transformers_version="4.48"),
     "Blip2ForConditionalGeneration": _HfExamplesInfo("Salesforce/blip2-opt-2.7b"),  # noqa: E501
     "ChameleonForConditionalGeneration": _HfExamplesInfo("facebook/chameleon-7b"),  # noqa: E501
     "ChatGLMModel": _HfExamplesInfo("THUDM/glm-4v-9b",
                                     extras={"text_only": "THUDM/chatglm3-6b"},
                                     trust_remote_code=True),
     "ChatGLMForConditionalGeneration": _HfExamplesInfo("chatglm2-6b",
                                                        is_available_online=False),
-    "DeepseekVLV2ForCausalLM": _HfExamplesInfo("deepseek-ai/deepseek-vl2-tiny"),   # noqa: E501
+    "DeepseekVLV2ForCausalLM": _HfExamplesInfo("deepseek-ai/deepseek-vl2-tiny",  # noqa: E501
+                                               hf_overrides={"architectures": ["DeepseekVLV2ForCausalLM"]}),  # noqa: E501
     "FuyuForCausalLM": _HfExamplesInfo("adept/fuyu-8b"),
     "H2OVLChatModel": _HfExamplesInfo("h2oai/h2ovl-mississippi-800m"),
     "InternVLChatModel": _HfExamplesInfo("OpenGVLab/InternVL2-1B",
@@ -194,7 +243,8 @@ class _HfExamplesInfo:
     "LlavaNextForConditionalGeneration": _HfExamplesInfo("llava-hf/llava-v1.6-mistral-7b-hf"),  # noqa: E501
     "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
+    "MantisForConditionalGeneration": _HfExamplesInfo("TIGER-Lab/Mantis-8B-siglip-llama3",  # noqa: E501
+                                                      hf_overrides={"architectures": ["MantisForConditionalGeneration"]}),  # noqa: E501
     "MiniCPMV": _HfExamplesInfo("openbmb/MiniCPM-Llama3-V-2_5",
                                 trust_remote_code=True),
     "MolmoForCausalLM": _HfExamplesInfo("allenai/Molmo-7B-D-0924",
@@ -247,5 +297,12 @@ def get_supported_archs(self) -> AbstractSet[str]:
     def get_hf_info(self, model_arch: str) -> _HfExamplesInfo:
         return self.hf_models[model_arch]
 
+    def find_hf_info(self, model_id: str) -> _HfExamplesInfo:
+        for info in self.hf_models.values():
+            if info.default == model_id:
+                return info
+
+        raise ValueError(f"No example model defined for {model_id}")
+
 
 HF_EXAMPLE_MODELS = HfExampleModels(_EXAMPLE_MODELS)

tests/models/test_initialization.py

@@ -1,9 +1,7 @@
 from unittest.mock import patch
 
 import pytest
-from packaging.version import Version
 from transformers import PretrainedConfig
-from transformers import __version__ as TRANSFORMERS_VERSION
 
 from vllm import LLM
 
@@ -13,16 +11,8 @@
 @pytest.mark.parametrize("model_arch", HF_EXAMPLE_MODELS.get_supported_archs())
 def test_can_initialize(model_arch):
     model_info = HF_EXAMPLE_MODELS.get_hf_info(model_arch)
-    if not model_info.is_available_online:
-        pytest.skip("Model is not available online")
-    if model_info.min_transformers_version is not None:
-        current_version = TRANSFORMERS_VERSION
-        required_version = model_info.min_transformers_version
-        if Version(current_version) < Version(required_version):
-            pytest.skip(
-                f"You have `transformers=={current_version}` installed, but "
-                f"`transformers>={required_version}` is required to run this "
-                "model")
+    model_info.check_available_online(on_fail="skip")
+    model_info.check_transformers_version(on_fail="skip")
 
     # Avoid OOM
     def hf_overrides(hf_config: PretrainedConfig) -> PretrainedConfig:

tests/models/test_registry.py

@@ -21,6 +21,9 @@
 
 @pytest.mark.parametrize("model_arch", ModelRegistry.get_supported_archs())
 def test_registry_imports(model_arch):
+    model_info = HF_EXAMPLE_MODELS.get_hf_info(model_arch)
+    model_info.check_transformers_version(on_fail="skip")
+
     # Ensure all model classes can be imported successfully
     model_cls, _ = ModelRegistry.resolve_model_cls(model_arch)