70 lines
1.6 KiB
Python
70 lines
1.6 KiB
Python
"""
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Usage:
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python3 -m sglang.launch_server --model-path /model/llama-classification
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python3 test_httpserver_classify.py
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"""
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import argparse
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import numpy as np
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import requests
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def get_logits(url, prompt):
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response = requests.post(
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url + "/generate",
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json={
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"text": prompt,
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"sampling_params": {
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"max_new_tokens": 0,
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},
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"return_logprob": True,
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},
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)
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return response.json()["meta_info"]["normalized_prompt_logprob"]
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def get_logits_batch(url, prompts):
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response = requests.post(
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url + "/generate",
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json={
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"text": prompts,
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"sampling_params": {
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"max_new_tokens": 0,
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},
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"return_logprob": True,
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},
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)
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ret = response.json()
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logits = np.array(
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list(
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ret[i]["meta_info"]["normalized_prompt_logprob"]
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for i in range(len(prompts))
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)
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)
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return logits
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument("--host", type=str, default="http://127.0.0.1")
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parser.add_argument("--port", type=int, default=30000)
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args = parser.parse_args()
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url = f"{args.host}:{args.port}"
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# A single request
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prompt = "This is a test prompt.<|eot_id|>"
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logits = get_logits(url, prompt)
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print(f"{logits=}")
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# A batch of requests
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prompts = [
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"This is a test prompt.<|eot_id|>",
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"This is another test prompt.<|eot_id|>",
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"This is a long long long long test prompt.<|eot_id|>",
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]
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logits = get_logits_batch(url, prompts)
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print(f"{logits=}")
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