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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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69
tests/models/language/pooling_mteb_test/test_intfloat.py
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@@ -2,50 +2,55 @@
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import pytest
from tests.models.language.pooling.embed_utils import (
correctness_test_embed_models)
from tests.models.language.pooling.embed_utils import correctness_test_embed_models
from tests.models.utils import CLSPoolingEmbedModelInfo, EmbedModelInfo
from .mteb_utils import mteb_test_embed_models
MODELS = [
########## BertModel
CLSPoolingEmbedModelInfo("intfloat/e5-small",
architecture="BertModel",
mteb_score=0.742285423,
enable_test=True),
CLSPoolingEmbedModelInfo("intfloat/e5-base",
architecture="BertModel",
enable_test=False),
CLSPoolingEmbedModelInfo("intfloat/e5-large",
architecture="BertModel",
enable_test=False),
CLSPoolingEmbedModelInfo("intfloat/multilingual-e5-small",
architecture="BertModel",
enable_test=False),
CLSPoolingEmbedModelInfo(
"intfloat/e5-small",
architecture="BertModel",
mteb_score=0.742285423,
enable_test=True,
),
CLSPoolingEmbedModelInfo(
"intfloat/e5-base", architecture="BertModel", enable_test=False
),
CLSPoolingEmbedModelInfo(
"intfloat/e5-large", architecture="BertModel", enable_test=False
),
CLSPoolingEmbedModelInfo(
"intfloat/multilingual-e5-small", architecture="BertModel", enable_test=False
),
########## XLMRobertaModel
CLSPoolingEmbedModelInfo("intfloat/multilingual-e5-base",
architecture="XLMRobertaModel",
mteb_score=0.779325955,
enable_test=True),
CLSPoolingEmbedModelInfo("intfloat/multilingual-e5-large",
architecture="XLMRobertaModel",
enable_test=False),
CLSPoolingEmbedModelInfo("intfloat/multilingual-e5-large-instruct",
architecture="XLMRobertaModel",
enable_test=False),
CLSPoolingEmbedModelInfo(
"intfloat/multilingual-e5-base",
architecture="XLMRobertaModel",
mteb_score=0.779325955,
enable_test=True,
),
CLSPoolingEmbedModelInfo(
"intfloat/multilingual-e5-large",
architecture="XLMRobertaModel",
enable_test=False,
),
CLSPoolingEmbedModelInfo(
"intfloat/multilingual-e5-large-instruct",
architecture="XLMRobertaModel",
enable_test=False,
),
]
@pytest.mark.parametrize("model_info", MODELS)
def test_embed_models_mteb(hf_runner, vllm_runner,
model_info: EmbedModelInfo) -> None:
def test_embed_models_mteb(hf_runner, vllm_runner, model_info: EmbedModelInfo) -> None:
mteb_test_embed_models(hf_runner, vllm_runner, model_info)
@pytest.mark.parametrize("model_info", MODELS)
def test_embed_models_correctness(hf_runner, vllm_runner,
model_info: EmbedModelInfo,
example_prompts) -> None:
correctness_test_embed_models(hf_runner, vllm_runner, model_info,
example_prompts)
def test_embed_models_correctness(
hf_runner, vllm_runner, model_info: EmbedModelInfo, example_prompts
) -> None:
correctness_test_embed_models(hf_runner, vllm_runner, model_info, example_prompts)