[VLM][Core] Support profiling with multiple multi-modal inputs per prompt (#7126)
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@@ -59,7 +59,7 @@ def test_models(hf_runner, vllm_runner, image_assets, model, size_factors,
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All the image fixtures for the test is under tests/images.
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For huggingface runner, we provide the PIL images as input.
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For vllm runner, we provide MultiModalData objects and corresponding
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vision language config as input.
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MultiModalConfig as input.
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Note, the text input is also adjusted to abide by vllm contract.
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The text output is sanitized to be able to compare with hf.
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"""
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@@ -49,7 +49,7 @@ def run_test(
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All the image fixtures for the test is under tests/images.
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For huggingface runner, we provide the PIL images as input.
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For vllm runner, we provide MultiModalDataDict objects
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and corresponding vision language config as input.
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and corresponding MultiModalConfig as input.
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Note, the text input is also adjusted to abide by vllm contract.
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The text output is sanitized to be able to compare with hf.
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"""
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@@ -117,7 +117,7 @@ def run_test(
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All the image fixtures for the test is under tests/images.
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For huggingface runner, we provide the PIL images as input.
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For vllm runner, we provide MultiModalDataDict objects
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and corresponding vision language config as input.
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and corresponding MultiModalConfig as input.
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Note, the text input is also adjusted to abide by vllm contract.
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The text output is sanitized to be able to compare with hf.
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"""
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@@ -69,7 +69,7 @@ def run_test(
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All the image fixtures for the test is under tests/images.
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For huggingface runner, we provide the PIL images as input.
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For vllm runner, we provide MultiModalDataDict objects
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and corresponding vision language config as input.
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and corresponding MultiModalConfig as input.
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Note, the text input is also adjusted to abide by vllm contract.
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The text output is sanitized to be able to compare with hf.
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"""
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@@ -177,7 +177,7 @@ def test_models(hf_runner, vllm_runner, image_assets, model, size_factors,
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All the image fixtures for the test is under tests/images.
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For huggingface runner, we provide the PIL images as input.
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For vllm runner, we provide MultiModalDataDict objects
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and corresponding vision language config as input.
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and corresponding MultiModalConfig as input.
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Note, the text input is also adjusted to abide by vllm contract.
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The text output is sanitized to be able to compare with hf.
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"""
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@@ -61,7 +61,7 @@ def run_test(
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All the image fixtures for the test is under tests/images.
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For huggingface runner, we provide the PIL images as input.
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For vllm runner, we provide MultiModalDataDict objects
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and corresponding vision language config as input.
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and corresponding MultiModalConfig as input.
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Note, the text input is also adjusted to abide by vllm contract.
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The text output is sanitized to be able to compare with hf.
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"""
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@@ -176,7 +176,7 @@ def run_multi_image_test(
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All the image fixtures for the test is under tests/images.
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For huggingface runner, we provide the PIL images as input.
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For vllm runner, we provide MultiModalDataDict objects
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and corresponding vision language config as input.
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and corresponding MultiModalConfig as input.
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Note, the text input is also adjusted to abide by vllm contract.
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The text output is sanitized to be able to compare with hf.
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"""
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@@ -197,6 +197,7 @@ def run_multi_image_test(
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with vllm_runner(model,
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max_model_len=4096,
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max_num_seqs=1,
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limit_mm_per_prompt={"image": len(images)},
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dtype=dtype,
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tensor_parallel_size=tensor_parallel_size,
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distributed_executor_backend=distributed_executor_backend,
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@@ -72,7 +72,7 @@ def run_test(
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All the image fixtures for the test is under tests/images.
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For huggingface runner, we provide the PIL images as input.
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For vllm runner, we provide MultiModalDataDict objects
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and corresponding vision language config as input.
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and corresponding MultiModalConfig as input.
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Note, the text input is also adjusted to abide by vllm contract.
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The text output is sanitized to be able to compare with hf.
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"""
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@@ -73,7 +73,7 @@ def run_test(
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All the image fixtures for the test is under tests/images.
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For huggingface runner, we provide the PIL images as input.
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For vllm runner, we provide MultiModalDataDict objects
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and corresponding vision language config as input.
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and corresponding MultiModalConfig as input.
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Note, the text input is also adjusted to abide by vllm contract.
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The text output is sanitized to be able to compare with hf.
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"""
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