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[Misc] Fix the size of batched_dummy_mm_inputs in profile_run (#20434)

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Signed-off-by: bk-201 <joy25810@foxmail.com>
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B-201 2025-07-09 11:15:44 +08:00 committed by GitHub
parent 9e0ef888f0
commit 6bbf1795b7
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2 changed files with 9 additions and 6 deletions
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3
tests/models/registry.py
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@ -412,7 +412,8 @@ _MULTIMODAL_EXAMPLE_MODELS = {
hf_overrides={"architectures": ["QwenVLForConditionalGeneration"]}), # noqa: E501
"Qwen2AudioForConditionalGeneration": _HfExamplesInfo("Qwen/Qwen2-Audio-7B-Instruct"), # noqa: E501
"Qwen2VLForConditionalGeneration": _HfExamplesInfo("Qwen/Qwen2-VL-2B-Instruct"), # noqa: E501
"Qwen2_5_VLForConditionalGeneration": _HfExamplesInfo("Qwen/Qwen2.5-VL-3B-Instruct"), # noqa: E501
"Qwen2_5_VLForConditionalGeneration": _HfExamplesInfo("Qwen/Qwen2.5-VL-3B-Instruct", # noqa: E501
max_model_len=4096),
"Qwen2_5OmniModel": _HfExamplesInfo("Qwen/Qwen2.5-Omni-3B"),
"Qwen2_5OmniForConditionalGeneration": _HfExamplesInfo("Qwen/Qwen2.5-Omni-7B-AWQ"), # noqa: E501
"SkyworkR1VChatModel": _HfExamplesInfo("Skywork/Skywork-R1V-38B"),

12
vllm/v1/worker/gpu_model_runner.py
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@ -2219,8 +2219,8 @@ class GPUModelRunner(LoRAModelRunnerMixin):
encoder_budget = min(self.max_num_encoder_input_tokens,
self.encoder_cache_size)
max_num_mm_items_encoder_budget = cdiv(encoder_budget,
max_tokens_per_mm_item)
max_num_mm_items_encoder_budget = encoder_budget // \
max_tokens_per_mm_item
# Check how many items of this modality can be supported by
# the decoder budget.
@ -2233,8 +2233,10 @@ class GPUModelRunner(LoRAModelRunnerMixin):
max_num_mm_items_decoder_budget = self.max_num_reqs * \
max_mm_items_per_req
max_num_mm_items = min(max_num_mm_items_encoder_budget,
max_num_mm_items_decoder_budget)
max_num_mm_items = max(
1,
min(max_num_mm_items_encoder_budget,
max_num_mm_items_decoder_budget))
logger.info(
"Encoder cache will be initialized with a budget of %s tokens,"
@ -2244,7 +2246,7 @@ class GPUModelRunner(LoRAModelRunnerMixin):
# Create dummy batch of multimodal inputs.
dummy_mm_kwargs = self.mm_registry.get_decoder_dummy_data(
model_config=self.model_config,
seq_len=self.max_num_tokens,
seq_len=max_tokens_per_mm_item,
mm_counts={
dummy_data_modality: 1
},