[CI] Bump Transformers version to 5.19.0 (#60381)

Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>

requirements/common.txt

@@ -7,7 +7,7 @@ requests >= 2.33.0
 tqdm
 blake3
 py-cpuinfo
-transformers >= 5.16.1, < 5.19.0
+transformers >= 5.16.1, < 5.20.0
 huggingface_hub >= 1.31.0  # Required for the `huggingface_hub.utils.httpx` re-export
 tokenizers >= 0.23.2  # Required for fast incremental detokenization.
 safetensors >= 0.6.2  # MXFP4/MXFP6 dtype support (F8_E8M0, F4) added in 0.6.0: https://github.com/huggingface/safetensors/pull/611

requirements/test/cpu.txt

@@ -1228,7 +1228,7 @@ traitlets==5.16.1
     # via
     #   jupyter-client
     #   jupyter-core
-transformers==5.18.0
+transformers==5.19.0
     # via
     #   -r requirements/test/../common.txt
     #   -r requirements/test/cuda.in

requirements/test/cuda.in

@@ -40,7 +40,7 @@ datamodel_code_generator>=0.64.0 # required for minicpm3 test
 nltk>=3.10.3 # pin transitive rouge-score/lm-eval dep for known GHSAs
 lm-eval[api]>=0.4.12 # required for model evaluation test
 mteb[bm25s]>=2, <3 # required for mteb test
-transformers==5.18.0
+transformers==5.19.0
 schemathesis>=4.0.0 # Required for openai schema test.
 # quantization
 buildkite-test-collector==0.1.9

requirements/test/cuda.txt

@@ -1335,7 +1335,7 @@ traitlets==5.16.1
     # via
     #   jupyter-client
     #   jupyter-core
-transformers==5.18.0
+transformers==5.19.0
     # via
     #   -c requirements/common.txt
     #   -r requirements/test/../common.txt

requirements/test/nightly-torch.txt

@@ -29,7 +29,7 @@ opencv-python-headless >= 4.13.0 # required for video test
 datamodel_code_generator>=0.64.0 # required for minicpm3 test
 lm-eval[api]>=0.4.12 # required for model evaluation test
 mteb[bm25s]>=2, <3 # required for mteb test
-transformers==5.18.0
+transformers==5.19.0
 schemathesis>=4.0.0 # Required for openai schema test.
 # quantization
 buildkite-test-collector==0.1.9

requirements/test/rocm.in

@@ -36,7 +36,7 @@ datamodel_code_generator>=0.64.0 # required for minicpm3 test
 nltk>=3.10.3 # pin transitive rouge-score/lm-eval dep for known GHSAs
 lm-eval[api]>=0.4.12 # required for model evaluation test
 mteb[bm25s]>=2, <3 # required for mteb test
-transformers==5.18.0
+transformers==5.19.0
 schemathesis>=4.0.0 # Required for openai schema test
 # quantization
 bitsandbytes==0.50.0

requirements/test/rocm.txt

@@ -1282,7 +1282,7 @@ traitlets==5.16.1
     # via
     #   jupyter-client
     #   jupyter-core
-transformers==5.18.0
+transformers==5.19.0
     # via
     #   -c requirements/common.txt
     #   -r requirements/test/../common.txt

requirements/test/xpu.in

@@ -20,7 +20,7 @@ nltk>=3.10.3 # pin transitive rouge-score/lm-eval dep for known GHSAs
 modelscope<1.38
 runai-model-streamer[s3,gcs,azure]>=0.15.7
 tensorizer==2.10.1
-transformers==5.18.0
+transformers==5.19.0
 
 # --- Audio Processing ---
 av

requirements/test/xpu.txt

@@ -1134,7 +1134,7 @@ traitlets==5.16.1
     # via
     #   jupyter-client
     #   jupyter-core
-transformers==5.18.0
+transformers==5.19.0
     # via
     #   -c requirements/common.txt
     #   -r requirements/test/../common.txt

tests/models/multimodal/pooling/test_embedding_gemma2.py

@@ -9,20 +9,11 @@ import textwrap
 import pytest
 import torch
 
-from tests.models.registry import HF_EXAMPLE_MODELS
-
 MODEL = os.environ.get("EG2_MODEL_PATH")
 needs_model = pytest.mark.skipif(not MODEL, reason="EG2_MODEL_PATH not set")
 TEXT_COS, MM_COS = 0.999, 0.999
 
 
-@pytest.fixture
-def needs_hf_embedding_gemma2():
-    """Skip when the installed transformers has no `embedding_gemma2` module."""
-    model_info = HF_EXAMPLE_MODELS.get_hf_info("EmbeddingGemma2Model")
-    model_info.check_transformers_version(on_fail="skip")
-
-
 def _cos(a, b):
     return torch.nn.functional.cosine_similarity(
         torch.tensor(a, dtype=torch.float32),
@@ -248,7 +239,7 @@ def test_tower_skip(vllm_runner, monkeypatch):
         )
 
 
-def test_encoder_contract(needs_hf_embedding_gemma2):
+def test_encoder_contract():
     from vllm.model_executor.models.embedding_gemma2 import EmbeddingGemma2Model
     from vllm.model_executor.models.gemma4_mm import (
         Gemma4ForConditionalGeneration as G,
@@ -432,7 +423,7 @@ def test_video_loader_duplicate_expansion_e2e(vllm_runner, st_model):
     assert len(out[0]) == 768
 
 
-def test_video_loader_indices(needs_hf_embedding_gemma2):
+def test_video_loader_indices():
     from transformers.models.embedding_gemma2.video_processing_embedding_gemma2 import (
         EmbeddingGemma2VideoProcessor,
     )
@@ -517,7 +508,7 @@ def test_video_loader_indices(needs_hf_embedding_gemma2):
     assert v_4h == h_4h, f"1fps/4h mismatch: {v_4h[-2:]} vs {h_4h[-2:]}"
 
 
-def test_video_loader_duplicate_expansion(needs_hf_embedding_gemma2):
+def test_video_loader_duplicate_expansion():
     from transformers.models.embedding_gemma2.video_processing_embedding_gemma2 import (
         EmbeddingGemma2VideoProcessor,
     )

tests/models/registry.py

@@ -583,7 +583,6 @@ _EMBEDDING_EXAMPLE_MODELS = {
     ),
     "EmbeddingGemma2Model": _HfExamplesInfo(
         "google/embeddinggemma-2",
-        min_transformers_version="5.19.0",
         is_available_online=False,
     ),
     "Gemma2Model": _HfExamplesInfo("BAAI/bge-multilingual-gemma2"),

vllm/transformers_utils/processor.py

@@ -181,7 +181,11 @@ def get_video_processor_cls_name_from_config(
     # given type when torchvision is unavailable; callers then use opencv.
     model_config = get_hf_file_to_dict("config.json", processor_name, revision=revision)
     if model_config and "model_type" in model_config:
-        return VIDEO_PROCESSOR_MAPPING_NAMES.get(model_config["model_type"])
+        video_processor = VIDEO_PROCESSOR_MAPPING_NAMES.get(model_config["model_type"])
+        # Transformers >= 5.19 maps to {"torchvision": name}
+        if isinstance(video_processor, dict):
+            video_processor = video_processor.get("torchvision")
+        return video_processor
     return None