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L = []
m = 1
n = 10
for j in range(m):
for i in range(n):
t = Thread(target=simple_chat, args=(j*10+i, prompts[i], False)) # 切换True False
# t = Thread(target=simple_chat, args=(j*10+i, prompts[i], True))
t.start()
L.append(t)
for i in range(m*n):
L[i].join()
Is there an existing issue for this?
Current Behavior
我在两台服务器上测试API,一台是有A800 GPU(基于docker,独占GPU),另一台有3090 GPU(直接使用)
发现use_stream这个参数对结果的影响很大
当use_stream是False的时候,A800比3090快很多
10线程A800跑完约15秒,3090跑完约35秒
但是use_stream为True的时候
10线程A800跑完约45秒(是False的3倍),3090跑完约30秒,反而比A800快
30线程、100线程都类似
请问是怎么回事?
Expected Behavior
No response
Steps To Reproduce
python openai_api.py 启动api
然后发送请求
python openai_api_request2.py
是把python openai_api_request.py改了一下
主要改动如下:
Environment
Anything else?
No response
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