120 lines
4.6 KiB
Python
120 lines
4.6 KiB
Python
import argparse
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from typing import List, Tuple
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import xtrt_llm
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from xtrt_llm.vllm import EngineArgs, LLMEngine, RequestOutput, SamplingParams
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def create_test_prompts() -> List[Tuple[str, SamplingParams]]:
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"""Create a list of test prompts with their sampling parameters."""
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return [
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("A robot may not injure a human being",
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SamplingParams(temperature=0.0,
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logprobs=1,
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prompt_logprobs=1,
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max_tokens=50)),
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("To be or not to be,",
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SamplingParams(temperature=0.0,
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logprobs=1,
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prompt_logprobs=1,
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max_tokens=50)),
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("To be or not to be,",
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SamplingParams(temperature=0.0,
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logprobs=1,
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prompt_logprobs=1,
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max_tokens=50)),
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("A robot may not injure a human being",
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SamplingParams(temperature=0.0,
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logprobs=1,
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prompt_logprobs=1,
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max_tokens=50)),
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("To be or not to be,",
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SamplingParams(temperature=0.0,
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logprobs=1,
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prompt_logprobs=1,
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max_tokens=50)),
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("A robot may not injure a human being",
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SamplingParams(temperature=0.0,
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logprobs=1,
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prompt_logprobs=1,
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max_tokens=50)),
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("A robot may not injure a human being",
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SamplingParams(temperature=0.0,
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logprobs=1,
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prompt_logprobs=1,
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max_tokens=50)),
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("It is only with the heart that one can see rightly",
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SamplingParams(temperature=0.0,
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logprobs=1,
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prompt_logprobs=1,
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max_tokens=50)),
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("A robot may not injure a human being",
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SamplingParams(temperature=0.0,
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logprobs=1,
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prompt_logprobs=1,
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max_tokens=50)),
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("It is only with the heart that one can see rightly",
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SamplingParams(temperature=0.0,
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logprobs=1,
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prompt_logprobs=1,
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max_tokens=50)),
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("A robot may not injure a human being",
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SamplingParams(temperature=0.0,
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logprobs=1,
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prompt_logprobs=1,
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max_tokens=50)),
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("It is only with the heart that one can see rightly",
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SamplingParams(temperature=0.0,
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logprobs=1,
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prompt_logprobs=1,
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max_tokens=50)),
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# ("To be or not to be,",
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# SamplingParams(temperature=0.8, top_k=5, presence_penalty=0.2)),
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# ("What is the meaning of life?",
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# SamplingParams(n=2,
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# best_of=5,
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# temperature=0.8,
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# top_p=0.95,
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# frequency_penalty=0.1)),
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# ("It is only with the heart that one can see rightly",
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# SamplingParams(n=3, best_of=3, use_beam_search=True,
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# temperature=0.0)),
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]
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def process_requests(engine: LLMEngine,
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test_prompts: List[Tuple[str, SamplingParams]]):
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"""Continuously process a list of prompts and handle the outputs."""
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request_id = 0
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while test_prompts or engine.has_unfinished_requests():
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if test_prompts:
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prompt, sampling_params = test_prompts.pop(0)
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engine.add_request(str(request_id), prompt, sampling_params)
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request_id += 1
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request_outputs: List[RequestOutput] = engine.step()
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for request_output in request_outputs:
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if request_output.finished:
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print("end_request_output:", request_output)
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def initialize_engine(args: argparse.Namespace) -> LLMEngine:
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"""Initialize the LLMEngine from the command line arguments."""
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engine_args = EngineArgs.from_cli_args(args)
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return LLMEngine.from_engine_args(engine_args)
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def main(args: argparse.Namespace):
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"""Main function that sets up and runs the prompt processing."""
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engine = initialize_engine(args)
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test_prompts = create_test_prompts()
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process_requests(engine, test_prompts)
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(
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description='Demo on using the LLMEngine class directly')
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parser = EngineArgs.add_cli_args(parser)
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args = parser.parse_args()
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main(args)
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