Skip models that cannot currently init on Transformers v5 (#28471)
Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
(cherry picked from commit 51c599f0ec)
This commit is contained in:
committed by
Kevin H. Luu
parent
a035b5cffb
commit
caf412e593
@@ -868,12 +868,12 @@ steps:
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optional: true
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optional: true
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commands:
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commands:
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- pip install --upgrade git+https://github.com/huggingface/transformers
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- pip install --upgrade git+https://github.com/huggingface/transformers
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- pytest -v -s tests/models/test_initialization.py
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- pytest -v -s tests/models/test_initialization.py -k 'not (Gemma3 or ModernBert or Qwen2_5_VL or Qwen2_5vl or Qwen2VL or TransformersMultiModalEmbeddingModel or TransformersMultiModalForSequenceClassification or Ultravox or Phi4Multimodal or LlavaNextVideo or MiniCPMO or Lfm2Moe or PaliGemma or RobertaForSequenceClassification or Ovis2_5 or Fuyu or DeepseekOCR or KimiVL)'
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- pytest -v -s tests/models/test_transformers.py
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- pytest -v -s tests/models/test_transformers.py
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- pytest -v -s tests/models/multimodal/processing/
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# - pytest -v -s tests/models/multimodal/processing/
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- pytest -v -s tests/models/multimodal/test_mapping.py
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- pytest -v -s tests/models/multimodal/test_mapping.py -k 'not (Gemma3 or Qwen2VL or Qwen2_5_VL)'
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- python3 examples/offline_inference/basic/chat.py
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- python3 examples/offline_inference/basic/chat.py
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- python3 examples/offline_inference/vision_language.py --model-type qwen2_5_vl
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# - python3 examples/offline_inference/vision_language.py --model-type qwen2_5_vl
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# Whisper needs spawn method to avoid deadlock
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# Whisper needs spawn method to avoid deadlock
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- VLLM_WORKER_MULTIPROC_METHOD=spawn python3 examples/offline_inference/audio_language.py --model-type whisper
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- VLLM_WORKER_MULTIPROC_METHOD=spawn python3 examples/offline_inference/audio_language.py --model-type whisper
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@@ -82,7 +82,8 @@ enable_hf_transfer()
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class DisabledTqdm(tqdm):
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class DisabledTqdm(tqdm):
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def __init__(self, *args, **kwargs):
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def __init__(self, *args, **kwargs):
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super().__init__(*args, **kwargs, disable=True)
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kwargs["disable"] = True
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super().__init__(*args, **kwargs)
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def get_lock(model_name_or_path: str | Path, cache_dir: str | None = None):
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def get_lock(model_name_or_path: str | Path, cache_dir: str | None = None):
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@@ -13,7 +13,6 @@ from transformers import (
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BatchFeature,
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BatchFeature,
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WhisperConfig,
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WhisperConfig,
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WhisperFeatureExtractor,
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WhisperFeatureExtractor,
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WhisperProcessor,
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)
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)
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from transformers.models.whisper.modeling_whisper import sinusoids
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from transformers.models.whisper.modeling_whisper import sinusoids
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@@ -660,16 +659,6 @@ class WhisperProcessingInfo(BaseProcessingInfo):
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def get_hf_config(self) -> WhisperConfig:
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def get_hf_config(self) -> WhisperConfig:
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return self.ctx.get_hf_config(WhisperConfig)
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return self.ctx.get_hf_config(WhisperConfig)
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def get_hf_processor(self, **kwargs: object) -> WhisperProcessor:
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# HACK: Transformers 4.53.2 has issue with whisper tokenizer to
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# initialize processor. We use a monkeypatch to fix it here.
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# See: https://github.com/vllm-project/vllm/issues/20224
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processor_class = WhisperProcessor
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tokenizer_class = ("WhisperTokenizer", "WhisperTokenizerFast")
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if processor_class.tokenizer_class != tokenizer_class:
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processor_class.tokenizer_class = tokenizer_class
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return self.ctx.get_hf_processor(processor_class, **kwargs)
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def get_supported_mm_limits(self) -> Mapping[str, int | None]:
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def get_supported_mm_limits(self) -> Mapping[str, int | None]:
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return {"audio": 1}
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return {"audio": 1}
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