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3fa2c12185
Signed-off-by: wang.yuqi <noooop@126.com> Signed-off-by: Christian Pinto <christian.pinto@ibm.com> Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> Co-authored-by: Christian Pinto <christian.pinto@ibm.com>
61 lines
1.4 KiB
Python
61 lines
1.4 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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import pytest
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import torch
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from ....conftest import VllmRunner
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def generate_test_mm_data():
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mm_data = {
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"pixel_values": torch.full((6, 512, 512), 1.0, dtype=torch.float16),
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"location_coords": torch.full((1, 2), 1.0, dtype=torch.float16),
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}
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return mm_data
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def _run_test(
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vllm_runner: type[VllmRunner],
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model: str,
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) -> None:
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prompt = [
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{
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# This model deals with no text input
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"prompt_token_ids": [1],
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"multi_modal_data": generate_test_mm_data(),
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}
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for _ in range(10)
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]
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with vllm_runner(
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model,
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runner="pooling",
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dtype="half",
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enforce_eager=True,
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skip_tokenizer_init=True,
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enable_mm_embeds=True,
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# Limit the maximum number of sequences to avoid the
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# test going OOM during the warmup run
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max_num_seqs=32,
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default_torch_num_threads=1,
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) as vllm_model:
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vllm_model.llm.encode(prompt, pooling_task="plugin")
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MODELS = ["mgazz/Prithvi-EO-2.0-300M-TL-Sen1Floods11"]
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@pytest.mark.core_model
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@pytest.mark.parametrize("model", MODELS)
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def test_models_image(
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hf_runner,
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vllm_runner,
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image_assets,
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model: str,
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) -> None:
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_run_test(
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vllm_runner,
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model,
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)
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