text-generation-inference/integration-tests/models/test_no_repeat_ngram.py
2024-08-01 13:37:45 +02:00

62 lines
1.6 KiB
Python

import pytest
import requests
def bloom_560_handle(launcher):
with launcher("bigscience/bloom-560m") as handle:
yield handle
@pytest.fixture(scope="module")
async def bloom_560(bloom_560_handle):
await bloom_560_handle.health(240)
return bloom_560_handle.client
@pytest.mark.release
@pytest.mark.asyncio
async def test_bloom_560m(bloom_560):
base_url = bloom_560.base_url
prompt = "The cat sat on the mat. The cat"
repeated_2grams_control = await call_model(base_url, prompt, 0)
assert (
len(repeated_2grams_control) > 0
), "Expected to find repeated bi-grams in control case"
repeated_2grams_test = await call_model(base_url, prompt, 2)
assert (
len(repeated_2grams_test) == 0
), f"Expected no repeated bi-grams, but found: {repeated_2grams_test}"
async def call_model(base_url, prompt, n_grams):
data = {
"inputs": prompt,
"parameters": {
"max_new_tokens": 20,
"seed": 42,
"no_repeat_ngram_size": n_grams,
"details": True,
},
}
res = requests.post(f"{base_url}/generate", json=data)
res = res.json()
tokens = res["details"]["tokens"]
token_texts = [token["text"] for token in tokens]
# find repeated 2grams
ngrams = [tuple(token_texts[i : i + 2]) for i in range(len(token_texts) - 2 + 1)]
ngram_counts = {}
for ngram in ngrams:
if ngram in ngram_counts:
ngram_counts[ngram] += 1
else:
ngram_counts[ngram] = 1
repeated = [list(ngram) for ngram, count in ngram_counts.items() if count > 1]
return repeated