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[CI/Build] Add inputs tests (#5215)

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Cyrus Leung 2024-06-04 12:01:46 +08:00 committed by GitHub
parent a58f24e590
commit ec784b2526
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2 changed files with 14 additions and 5 deletions
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8
.buildkite/test-pipeline.yaml
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@ -62,7 +62,6 @@ steps:
mirror_hardwares: [amd] mirror_hardwares: [amd]
commands: commands:
- pytest -v -s test_inputs.py
- pytest -v -s entrypoints -m llm - pytest -v -s entrypoints -m llm
- pytest -v -s entrypoints -m openai - pytest -v -s entrypoints -m openai
@ -79,6 +78,13 @@ steps:
- python3 llava_example.py - python3 llava_example.py
- python3 tensorize_vllm_model.py --model facebook/opt-125m serialize --serialized-directory /tmp/ --suffix v1 && python3 tensorize_vllm_model.py --model facebook/opt-125m deserialize --path-to-tensors /tmp/vllm/facebook/opt-125m/v1/model.tensors - python3 tensorize_vllm_model.py --model facebook/opt-125m serialize --serialized-directory /tmp/ --suffix v1 && python3 tensorize_vllm_model.py --model facebook/opt-125m deserialize --path-to-tensors /tmp/vllm/facebook/opt-125m/v1/model.tensors
- label: Inputs Test
#mirror_hardwares: [amd]
commands:
- bash ../.buildkite/download-images.sh
- pytest -v -s test_inputs.py
- pytest -v -s multimodal
- label: Kernels Test %N - label: Kernels Test %N
#mirror_hardwares: [amd] #mirror_hardwares: [amd]
command: pytest -v -s kernels --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT command: pytest -v -s kernels --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT

11
tests/multimodal/test_processor.py
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@ -6,8 +6,10 @@ from vllm.config import ModelConfig, VisionLanguageConfig
from vllm.multimodal import MULTIMODAL_REGISTRY from vllm.multimodal import MULTIMODAL_REGISTRY
from vllm.multimodal.image import ImagePixelData from vllm.multimodal.image import ImagePixelData
from ..conftest import _STR_DTYPE_TO_TORCH_DTYPE
@pytest.mark.parametrize("dtype", ["half", "bfloat16", "float"])
@pytest.mark.parametrize("dtype", ["half", "float"])
def test_clip_image_processor(hf_images, dtype): def test_clip_image_processor(hf_images, dtype):
MODEL_NAME = "llava-hf/llava-1.5-7b-hf" MODEL_NAME = "llava-hf/llava-1.5-7b-hf"
IMAGE_HEIGHT = IMAGE_WIDTH = 33 IMAGE_HEIGHT = IMAGE_WIDTH = 33
@ -36,8 +38,8 @@ def test_clip_image_processor(hf_images, dtype):
for image in hf_images: for image in hf_images:
hf_result = hf_processor.preprocess( hf_result = hf_processor.preprocess(
image, image,
return_tensors="np", return_tensors="pt",
) ).to(dtype=_STR_DTYPE_TO_TORCH_DTYPE[dtype])
vllm_result = MULTIMODAL_REGISTRY.process_input( vllm_result = MULTIMODAL_REGISTRY.process_input(
ImagePixelData(image), ImagePixelData(image),
model_config=model_config, model_config=model_config,
@ -45,7 +47,8 @@ def test_clip_image_processor(hf_images, dtype):
) )
assert hf_result.keys() == vllm_result.keys() assert hf_result.keys() == vllm_result.keys()
for key, hf_arr in hf_result.items(): for key, hf_tensor in hf_result.items():
hf_arr: np.ndarray = hf_tensor.numpy()
vllm_arr: np.ndarray = vllm_result[key].numpy() vllm_arr: np.ndarray = vllm_result[key].numpy()
assert hf_arr.shape == vllm_arr.shape, f"Failed for key={key}" assert hf_arr.shape == vllm_arr.shape, f"Failed for key={key}"