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43721bc67f
Signed-off-by: Tahsin Tunan <tahsintunan@gmail.com> Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com> Co-authored-by: Nick Hill <nhill@redhat.com> Co-authored-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
38 lines
983 B
Python
38 lines
983 B
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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from vllm import LLM
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MODEL = "hmellor/tiny-random-LlamaForCausalLM"
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PROMPT = "Hello my name is Robert and I"
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@pytest.fixture(scope="module")
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def llm() -> LLM:
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return LLM(
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MODEL,
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enforce_eager=True,
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enable_prefix_caching=True,
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long_prefill_token_threshold=2,
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max_num_batched_tokens=6,
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max_num_seqs=3,
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block_size=16,
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)
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def test_concurrent_partial_prefill(llm):
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outputs = llm.generate([PROMPT] * 3)
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assert len(outputs) == 3
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for output in outputs:
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assert len(output.outputs) == 1
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def test_prefix_cache_stats_is_recorded(llm):
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# 17 tokens will make sure first 16 tokens are cached in a block
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input_tokens = {"prompt_token_ids": [101] * 17}
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_ = llm.generate([input_tokens])
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outputs = llm.generate([input_tokens])
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assert outputs[0].num_cached_tokens == 16
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