44 lines
1.3 KiB
Python
44 lines
1.3 KiB
Python
"""
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Usage:
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python3 offline_batch_inference.py --model meta-llama/Llama-3.1-8B-Instruct
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"""
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import argparse
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import dataclasses
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import sglang as sgl
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from sglang.srt.server_args import ServerArgs
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def main(
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server_args: ServerArgs,
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):
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# Sample prompts.
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prompts = [
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"Hello, my name is",
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"The president of the United States is",
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"The capital of France is",
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"The future of AI is",
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]
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# Create a sampling params object.
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sampling_params = {"temperature": 0.8, "top_p": 0.95}
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# Create an LLM.
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llm = sgl.Engine(**dataclasses.asdict(server_args))
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outputs = llm.generate(prompts, sampling_params)
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# Print the outputs.
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for prompt, output in zip(prompts, outputs):
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print("===============================")
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print(f"Prompt: {prompt}\nGenerated text: {output['text']}")
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# The __main__ condition is necessary here because we use "spawn" to create subprocesses
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# Spawn starts a fresh program every time, if there is no __main__, it will run into infinite loop to keep spawning processes from sgl.Engine
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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ServerArgs.add_cli_args(parser)
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args = parser.parse_args()
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server_args = ServerArgs.from_cli_args(args)
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main(server_args)
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