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[Bugfix] Fix Qwen2-VL LoRA weight loading (#11430)
Signed-off-by: Jee Jee Li <[email protected]>
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Original file line number | Diff line number | Diff line change |
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from typing import List | ||
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import pytest | ||
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import vllm | ||
from vllm.assets.image import ImageAsset | ||
from vllm.lora.request import LoRARequest | ||
from vllm.platforms import current_platform | ||
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MODEL_PATH = "Qwen/Qwen2-VL-7B-Instruct" | ||
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PROMPT_TEMPLATE = ( | ||
"<|im_start|>system\nYou are a helpful assistant.<|im_end|>" | ||
"\n<|im_start|>user\n<|vision_start|><|image_pad|><|vision_end|>" | ||
"What is in the image?<|im_end|>\n" | ||
"<|im_start|>assistant\n") | ||
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IMAGE_ASSETS = [ | ||
ImageAsset("stop_sign"), | ||
ImageAsset("cherry_blossom"), | ||
] | ||
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# After fine-tuning with LoRA, all generated content should start begin `A`. | ||
EXPECTED_OUTPUT = [ | ||
"A stop sign stands prominently in the foreground, with a traditional Chinese gate and a black SUV in the background, illustrating a blend of modern and cultural elements.", # noqa: E501 | ||
"A majestic skyscraper stands tall, partially obscured by a vibrant canopy of cherry blossoms, against a clear blue sky.", # noqa: E501 | ||
] | ||
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def do_sample(llm: vllm.LLM, lora_path: str, lora_id: int) -> List[str]: | ||
sampling_params = vllm.SamplingParams( | ||
temperature=0, | ||
max_tokens=5, | ||
) | ||
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inputs = [{ | ||
"prompt": PROMPT_TEMPLATE, | ||
"multi_modal_data": { | ||
"image": asset.pil_image | ||
}, | ||
} for asset in IMAGE_ASSETS] | ||
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outputs = llm.generate( | ||
inputs, | ||
sampling_params, | ||
lora_request=LoRARequest(str(lora_id), lora_id, lora_path) | ||
if lora_id else None, | ||
) | ||
# Print the outputs. | ||
generated_texts: List[str] = [] | ||
for output in outputs: | ||
prompt = output.prompt | ||
generated_text = output.outputs[0].text.strip() | ||
generated_texts.append(generated_text) | ||
print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}") | ||
return generated_texts | ||
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@pytest.mark.xfail(current_platform.is_rocm(), | ||
reason="Qwen2-VL dependency xformers incompatible with ROCm" | ||
) | ||
def test_qwen2vl_lora(qwen2vl_lora_files): | ||
llm = vllm.LLM( | ||
MODEL_PATH, | ||
max_num_seqs=2, | ||
enable_lora=True, | ||
max_loras=2, | ||
max_lora_rank=16, | ||
trust_remote_code=True, | ||
mm_processor_kwargs={ | ||
"min_pixels": 28 * 28, | ||
"max_pixels": 1280 * 28 * 28, | ||
}, | ||
max_model_len=4096, | ||
) | ||
output1 = do_sample(llm, qwen2vl_lora_files, lora_id=1) | ||
for i in range(len(EXPECTED_OUTPUT)): | ||
assert EXPECTED_OUTPUT[i].startswith(output1[i]) |
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