54 lines
1.9 KiB
Python
54 lines
1.9 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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"""Tests for phi3v's multimodal preprocessing kwargs."""
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import pytest
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from vllm.multimodal import MULTIMODAL_REGISTRY
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from ....conftest import _ImageAssets
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from ...utils import build_model_context
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@pytest.mark.parametrize("model_id", ["microsoft/Phi-3.5-vision-instruct"])
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# yapf: disable
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@pytest.mark.parametrize(
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("mm_processor_kwargs", "expected_toks_per_img"),
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[
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({"num_crops": 4}, 757),
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({"num_crops": 16}, 1921),
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# the default num_crops of phi-3.5-vision is 4
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({}, 757),
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])
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# yapf: enable
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@pytest.mark.parametrize("num_imgs", [1, 2])
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@pytest.mark.parametrize("kwargs_on_init", [True, False])
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def test_processor_override(
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image_assets: _ImageAssets,
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model_id: str,
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mm_processor_kwargs: dict[str, int],
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expected_toks_per_img: int,
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num_imgs: int,
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kwargs_on_init: bool,
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):
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"""Ensure Phi3VMultiModalProcessor handles num_crops properly."""
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# Avoid initializing CUDA early
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from vllm.model_executor.models.phi3v import _IMAGE_TOKEN_ID
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ctx = build_model_context(
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model_id,
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mm_processor_kwargs=mm_processor_kwargs if kwargs_on_init else None,
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limit_mm_per_prompt={"image": num_imgs},
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)
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processor = MULTIMODAL_REGISTRY.create_processor(ctx.model_config)
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hf_processor_mm_kwargs = {} if kwargs_on_init else mm_processor_kwargs
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# Build the image str / prompt based on the number of images we pass
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img_str = "".join([f"<|image_{idx}|>\n" for idx in range(1, num_imgs + 1)])
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prompt = f"<|user|>\n{img_str}<|end|>\n<|assistant|>\n"
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mm_data = {"image": [image_assets[0].pil_image] * num_imgs}
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processed_inputs = processor.apply(prompt, mm_data, hf_processor_mm_kwargs)
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# Ensure we have the right number of placeholders per num_crops size
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img_tok_count = processed_inputs["prompt_token_ids"].count(_IMAGE_TOKEN_ID)
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assert img_tok_count == expected_toks_per_img * num_imgs
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