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Convert formatting to use ruff instead of yapf + isort (#26247)

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Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-10-05 15:06:22 +01:00
committed by GitHub
parent 17edd8a807
commit d6953beb91
1508 changed files with 115244 additions and 94146 deletions
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12
tests/entrypoints/pooling/correctness/test_mteb_embed.py
View File

@@ -5,8 +5,11 @@ import os
import pytest
from tests.models.language.pooling_mteb_test.mteb_utils import (
MTEB_EMBED_TASKS, MTEB_EMBED_TOL, OpenAIClientMtebEncoder,
run_mteb_embed_task)
MTEB_EMBED_TASKS,
MTEB_EMBED_TOL,
OpenAIClientMtebEncoder,
run_mteb_embed_task,
)
from tests.utils import RemoteOpenAIServer
os.environ["VLLM_LOGGING_LEVEL"] = "WARNING"
@@ -17,10 +20,7 @@ MAIN_SCORE = 0.7422994752439667
@pytest.fixture(scope="module")
def server():
args = [
"--runner", "pooling", "--enforce-eager",
"--disable-uvicorn-access-log"
]
args = ["--runner", "pooling", "--enforce-eager", "--disable-uvicorn-access-log"]
with RemoteOpenAIServer(MODEL_NAME, args) as remote_server:
yield remote_server

20
tests/entrypoints/pooling/correctness/test_mteb_score.py
View File

@@ -5,8 +5,13 @@ import os
import pytest
from tests.models.language.pooling_mteb_test.mteb_utils import (
MTEB_RERANK_LANGS, MTEB_RERANK_TASKS, MTEB_RERANK_TOL,
RerankClientMtebEncoder, ScoreClientMtebEncoder, run_mteb_rerank)
MTEB_RERANK_LANGS,
MTEB_RERANK_TASKS,
MTEB_RERANK_TOL,
RerankClientMtebEncoder,
ScoreClientMtebEncoder,
run_mteb_rerank,
)
from tests.utils import RemoteOpenAIServer
os.environ["VLLM_LOGGING_LEVEL"] = "WARNING"
@@ -17,10 +22,7 @@ st_main_score = 0.33457
@pytest.fixture(scope="module")
def server():
args = [
"--runner", "pooling", "--enforce-eager",
"--disable-uvicorn-access-log"
]
args = ["--runner", "pooling", "--enforce-eager", "--disable-uvicorn-access-log"]
with RemoteOpenAIServer(MODEL_NAME, args) as remote_server:
yield remote_server
@@ -29,8 +31,7 @@ def server():
def test_mteb_score(server):
url = server.url_for("score")
encoder = ScoreClientMtebEncoder(MODEL_NAME, url)
vllm_main_score = run_mteb_rerank(encoder, MTEB_RERANK_TASKS,
MTEB_RERANK_LANGS)
vllm_main_score = run_mteb_rerank(encoder, MTEB_RERANK_TASKS, MTEB_RERANK_LANGS)
print("VLLM main score: ", vllm_main_score)
print("SentenceTransformer main score: ", st_main_score)
@@ -44,8 +45,7 @@ def test_mteb_score(server):
def test_mteb_rerank(server):
url = server.url_for("rerank")
encoder = RerankClientMtebEncoder(MODEL_NAME, url)
vllm_main_score = run_mteb_rerank(encoder, MTEB_RERANK_TASKS,
MTEB_RERANK_LANGS)
vllm_main_score = run_mteb_rerank(encoder, MTEB_RERANK_TASKS, MTEB_RERANK_LANGS)
print("VLLM main score: ", vllm_main_score)
print("SentenceTransformer main score: ", st_main_score)