Created
February 16, 2022 13:59
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Gist for benchmarking GPT generating performance with same input (43 tokens)
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import aiohttp | |
import json | |
import asyncio | |
import datetime | |
import matplotlib.pyplot as plt | |
text = """ | |
Planning a project is one thing, but making sure deadlines are met and all tasks are completed is a whole other. Falling behind is easy when an entire sequence of events is dependent on the previous being successfully finished. | |
""" | |
sentenses = [s for s in text.split('\n') if s] | |
async def req(txt, gen_toks): | |
base = { | |
"text": txt, | |
"generate_tokens_limit": gen_toks, | |
"top_p": 0.7, | |
"top_k": 0, | |
"temperature": 1.0 | |
} | |
async with aiohttp.ClientSession() as session: | |
async with session.post( | |
'http://127.0.0.1:8080/generate/', | |
json=base | |
) as response: | |
resp = await response.text() | |
resp = json.loads(resp) | |
c = resp['completion'] | |
return c | |
REPEATS_PER_LENGTH = 3 | |
async def start(): | |
inp = sentenses[0] | |
res = [ | |
[], | |
[], | |
] | |
for gen_toks in range(100, 1900, 100): | |
t = datetime.datetime.now() | |
await asyncio.gather(*[req(inp, gen_toks) for _ in range(REPEATS_PER_LENGTH)]) | |
dur = (datetime.datetime.now() - t).total_seconds() | |
res[0].append( gen_toks ) | |
res[1].append( dur * 1.0 / REPEATS_PER_LENGTH ) | |
print('RES:\n', | |
" ".join([str(e) for e in res[0]]), | |
'\n', | |
" ".join([str(e) for e in res[1]]), | |
) | |
plt.plot(res[0], res[1]) | |
plt.xlabel('input char count') | |
plt.ylabel('time of 20 tokens gen') | |
plt.title('Speed of generation from input length') | |
plt.savefig('res.png', dpi=600) | |
asyncio.run(start()) |
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