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[CI/Build] Add inputs tests #5215

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Jun 4, 2024
Merged

[CI/Build] Add inputs tests #5215

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29856a1
Add inputs tests
DarkLight1337 Jun 3, 2024
d82b140
Fix tests for multimodal processor
DarkLight1337 Jun 3, 2024
b44e7c9
Fix images not being downloaded
DarkLight1337 Jun 3, 2024
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8 changes: 7 additions & 1 deletion .buildkite/test-pipeline.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -62,7 +62,6 @@ steps:
mirror_hardwares: [amd]

commands:
- pytest -v -s test_inputs.py
- pytest -v -s entrypoints -m llm
- pytest -v -s entrypoints -m openai

Expand All @@ -79,6 +78,13 @@ steps:
- 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

- 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
#mirror_hardwares: [amd]
command: pytest -v -s kernels --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
Expand Down
11 changes: 7 additions & 4 deletions tests/multimodal/test_processor.py
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Expand Up @@ -6,8 +6,10 @@
from vllm.multimodal import MULTIMODAL_REGISTRY
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):
MODEL_NAME = "llava-hf/llava-1.5-7b-hf"
IMAGE_HEIGHT = IMAGE_WIDTH = 33
Expand Down Expand Up @@ -36,16 +38,17 @@ def test_clip_image_processor(hf_images, dtype):
for image in hf_images:
hf_result = hf_processor.preprocess(
image,
return_tensors="np",
)
return_tensors="pt",
).to(dtype=_STR_DTYPE_TO_TORCH_DTYPE[dtype])
vllm_result = MULTIMODAL_REGISTRY.process_input(
ImagePixelData(image),
model_config=model_config,
vlm_config=vlm_config,
)

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()

assert hf_arr.shape == vllm_arr.shape, f"Failed for key={key}"
Expand Down
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