[Misc] Clean up processor tests (#14771)
Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>
This commit is contained in:
@@ -96,14 +96,14 @@ def _run_check(
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tokenizer = processor.info.get_tokenizer()
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config = processor.info.get_hf_config()
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prompt = "<image>" * len(images)
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mm_data = {"image": images}
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total_expected_num_patches = sum(
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_get_expected_num_patches(config, image, len(images), min_num, max_num)
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for image in images)
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processed_inputs = processor.apply("<image>" * len(images), mm_data,
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mm_processor_kwargs)
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processed_inputs = processor.apply(prompt, mm_data, mm_processor_kwargs)
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# Ensure we have the right number of placeholders per num_crops size
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image_token_id = tokenizer.convert_tokens_to_ids("<IMG_CONTEXT>")
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@@ -152,9 +152,7 @@ def test_processor_override(
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}
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ctx = build_model_context(
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model_name=model_id,
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tokenizer_name=model_id,
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trust_remote_code=True,
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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": len(size_factors)},
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)
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@@ -9,10 +9,8 @@ from vllm.transformers_utils.tokenizer import cached_tokenizer_from_config
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from ....conftest import _ImageAssets
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from ...utils import build_model_context
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models = ["HuggingFaceM4/Idefics3-8B-Llama3"]
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@pytest.mark.parametrize("model", models)
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@pytest.mark.parametrize("model_id", ["HuggingFaceM4/Idefics3-8B-Llama3"])
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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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@@ -25,7 +23,7 @@ models = ["HuggingFaceM4/Idefics3-8B-Llama3"]
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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: str,
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model_id: str,
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mm_processor_kwargs: dict[str, object],
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expected_toks_per_img: int,
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num_imgs: int,
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@@ -36,9 +34,7 @@ def test_processor_override(
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# in this test and assume that the kwargs will be correctly expanded by
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# the partial when calling the custom input processor.
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ctx = build_model_context(
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model_name=model,
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tokenizer_name=model,
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trust_remote_code=True,
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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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@@ -56,14 +56,14 @@ def _run_check(
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tokenizer = processor.info.get_tokenizer()
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config = processor.info.get_hf_config()
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prompt = "<image>" * len(images)
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mm_data = {"image": images}
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total_expected_num_patches = sum(
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_get_expected_num_patches(config, image, len(images), min_num, max_num)
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for image in images)
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processed_inputs = processor.apply("<image>" * len(images), mm_data,
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mm_processor_kwargs)
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processed_inputs = processor.apply(prompt, mm_data, mm_processor_kwargs)
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# Ensure we have the right number of placeholders per num_crops size
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image_token_id = tokenizer.convert_tokens_to_ids("<IMG_CONTEXT>")
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@@ -109,9 +109,7 @@ def test_processor_override(
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}
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ctx = build_model_context(
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model_name=model_id,
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tokenizer_name=model_id,
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trust_remote_code=True,
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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": len(size_factors)},
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)
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@@ -36,8 +36,7 @@ def _validate_image_max_tokens_one(
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@pytest.mark.parametrize("model_id", ["llava-hf/llava-v1.6-mistral-7b-hf"])
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def test_processor_max_tokens(model_id):
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ctx = build_model_context(
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model_name=model_id,
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tokenizer_name=model_id,
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model_id,
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mm_processor_kwargs=None,
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limit_mm_per_prompt={"image": 1},
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)
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@@ -136,8 +135,7 @@ def _test_image_prompt_replacements(
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@pytest.mark.parametrize("num_imgs", [1, 2])
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def test_processor_prompt_replacements_regression(model_id, num_imgs):
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ctx = build_model_context(
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model_name=model_id,
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tokenizer_name=model_id,
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model_id,
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mm_processor_kwargs=None,
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limit_mm_per_prompt={"image": num_imgs},
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)
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@@ -166,8 +164,7 @@ def test_processor_prompt_replacements_regression(model_id, num_imgs):
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@pytest.mark.parametrize("num_imgs", [1])
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def test_processor_prompt_replacements_all(model_id, num_imgs):
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ctx = build_model_context(
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model_name=model_id,
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tokenizer_name=model_id,
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model_id,
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mm_processor_kwargs=None,
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limit_mm_per_prompt={"image": num_imgs},
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)
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@@ -37,8 +37,7 @@ def _validate_image_max_tokens_one(
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["llava-hf/llava-onevision-qwen2-0.5b-ov-hf"])
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def test_processor_max_tokens(model_id):
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ctx = build_model_context(
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model_name=model_id,
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tokenizer_name=model_id,
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model_id,
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mm_processor_kwargs=None,
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limit_mm_per_prompt={"image": 1},
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)
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@@ -136,8 +135,7 @@ def _test_image_prompt_replacements(
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@pytest.mark.parametrize("num_imgs", [1, 2])
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def test_processor_prompt_replacements_regression(model_id, num_imgs):
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ctx = build_model_context(
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model_name=model_id,
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tokenizer_name=model_id,
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model_id,
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mm_processor_kwargs=None,
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limit_mm_per_prompt={"image": num_imgs},
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)
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@@ -167,8 +165,7 @@ def test_processor_prompt_replacements_regression(model_id, num_imgs):
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@pytest.mark.parametrize("num_imgs", [1])
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def test_processor_prompt_replacements_all(model_id, num_imgs):
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ctx = build_model_context(
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model_name=model_id,
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tokenizer_name=model_id,
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model_id,
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mm_processor_kwargs=None,
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limit_mm_per_prompt={"image": num_imgs},
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)
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@@ -35,9 +35,7 @@ def test_processor_override(
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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_name=model_id,
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tokenizer_name=model_id,
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trust_remote_code=True,
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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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@@ -30,8 +30,7 @@ def test_processor_override(
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):
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"""Ensure Qwen2VLMultiModalProcessor handles min/max pixels properly."""
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ctx = build_model_context(
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model_name=model_id,
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tokenizer_name=model_id,
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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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