mirror of https://github.com/vllm-project/vllm.git
51 lines
1.6 KiB
Python
51 lines
1.6 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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from vllm import LLM, SamplingParams
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from vllm.v1.metrics.reader import Counter, Gauge, Histogram, Vector
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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 = SamplingParams(temperature=0.8, top_p=0.95)
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def main():
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# Create an LLM.
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llm = LLM(model="facebook/opt-125m", disable_log_stats=False)
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# Generate texts from the prompts.
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outputs = llm.generate(prompts, sampling_params)
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# Print the outputs.
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print("-" * 50)
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for output in outputs:
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prompt = output.prompt
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generated_text = output.outputs[0].text
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print(f"Prompt: {prompt!r}\nGenerated text: {generated_text!r}")
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print("-" * 50)
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# Dump all metrics
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for metric in llm.get_metrics():
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if isinstance(metric, Gauge):
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print(f"{metric.name} (gauge) = {metric.value}")
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elif isinstance(metric, Counter):
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print(f"{metric.name} (counter) = {metric.value}")
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elif isinstance(metric, Vector):
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print(f"{metric.name} (vector) = {metric.values}")
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elif isinstance(metric, Histogram):
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print(f"{metric.name} (histogram)")
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print(f" sum = {metric.sum}")
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print(f" count = {metric.count}")
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for bucket_le, value in metric.buckets.items():
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print(f" {bucket_le} = {value}")
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if __name__ == "__main__":
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main()
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