62 lines
1.8 KiB
Python
62 lines
1.8 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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"""A basic correctness check for TPUs
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Run `pytest tests/v1/tpu/test_basic.py`.
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"""
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from __future__ import annotations
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from typing import TYPE_CHECKING
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import pytest
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from vllm.platforms import current_platform
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if TYPE_CHECKING:
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from tests.conftest import VllmRunner
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MODELS = [
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"Qwen/Qwen2.5-1.5B-Instruct",
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# TODO: Enable this models with v6e
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# "Qwen/Qwen2-7B-Instruct",
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# "meta-llama/Llama-3.1-8B",
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]
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TENSOR_PARALLEL_SIZES = [1]
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# TODO: Enable when CI/CD will have a multi-tpu instance
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# TENSOR_PARALLEL_SIZES = [1, 4]
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@pytest.mark.skipif(not current_platform.is_tpu(),
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reason="This is a basic test for TPU only")
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@pytest.mark.parametrize("model", MODELS)
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@pytest.mark.parametrize("max_tokens", [5])
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@pytest.mark.parametrize("tensor_parallel_size", TENSOR_PARALLEL_SIZES)
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def test_models(
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vllm_runner: type[VllmRunner],
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monkeypatch: pytest.MonkeyPatch,
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model: str,
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max_tokens: int,
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tensor_parallel_size: int,
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) -> None:
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prompt = "The next numbers of the sequence " + ", ".join(
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str(i) for i in range(1024)) + " are:"
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example_prompts = [prompt]
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with monkeypatch.context() as m:
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m.setenv("VLLM_USE_V1", "1")
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with vllm_runner(
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model,
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# Note: max_num_batched_tokens == 1024 is needed here to
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# actually test chunked prompt
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max_num_batched_tokens=1024,
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max_model_len=8196,
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gpu_memory_utilization=0.7,
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max_num_seqs=16,
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tensor_parallel_size=tensor_parallel_size) as vllm_model:
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vllm_outputs = vllm_model.generate_greedy(example_prompts,
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max_tokens)
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output = vllm_outputs[0][1]
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assert "1024" in output
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