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[CI/Build] Replace math.isclose with pytest.approx (#18703)

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Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>
This commit is contained in:
Cyrus Leung
2025-05-26 17:05:17 +08:00
committed by GitHub
parent 61a45e7a72
commit 38b13dfe78
6 changed files with 22 additions and 31 deletions
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3
tests/models/language/pooling/mteb_utils.py
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@@ -1,5 +1,4 @@
# SPDX-License-Identifier: Apache-2.0
import math
from collections.abc import Sequence
import mteb
@@ -115,4 +114,4 @@ def mteb_test_embed_models(hf_runner,
print("SentenceTransformer:", model_dtype, st_main_score)
print("Difference:", st_main_score - vllm_main_score)
assert math.isclose(st_main_score, vllm_main_score, rel_tol=MTEB_EMBED_TOL)
assert st_main_score == pytest.approx(vllm_main_score, rel=MTEB_EMBED_TOL)

9
tests/models/language/pooling/test_gritlm.py
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@@ -2,7 +2,6 @@
from __future__ import annotations
import importlib.util
import math
from array import array
import openai
@@ -104,16 +103,16 @@ def get_test_data():
def validate_embed_output(q_rep: list[list[float]], d_rep: list[list[float]]):
cosine_sim_q0_d0 = 1 - cosine(q_rep[0], d_rep[0])
assert math.isclose(cosine_sim_q0_d0, 0.609, abs_tol=0.001)
assert cosine_sim_q0_d0 == pytest.approx(0.609, abs=0.001)
cosine_sim_q0_d1 = 1 - cosine(q_rep[0], d_rep[1])
assert math.isclose(cosine_sim_q0_d1, 0.101, abs_tol=0.001)
assert cosine_sim_q0_d1 == pytest.approx(0.101, abs=0.001)
cosine_sim_q1_d0 = 1 - cosine(q_rep[1], d_rep[0])
assert math.isclose(cosine_sim_q1_d0, 0.120, abs_tol=0.001)
assert cosine_sim_q1_d0 == pytest.approx(0.120, abs=0.001)
cosine_sim_q1_d1 = 1 - cosine(q_rep[1], d_rep[1])
assert math.isclose(cosine_sim_q1_d1, 0.534, abs_tol=0.001)
assert cosine_sim_q1_d1 == pytest.approx(0.534, abs=0.001)
def test_gritlm_offline_embedding(vllm_runner):

8
tests/models/language/pooling/test_jina.py
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@@ -1,6 +1,4 @@
# SPDX-License-Identifier: Apache-2.0
import math
import pytest
from vllm import PoolingParams
@@ -60,7 +58,7 @@ def test_llm_1_to_1(vllm_runner, hf_runner, model_name, dtype: str):
assert len(vllm_outputs) == 1
assert len(hf_outputs) == 1
assert math.isclose(hf_outputs[0], vllm_outputs[0], rel_tol=0.01)
assert hf_outputs[0] == pytest.approx(vllm_outputs[0], rel=0.01)
@pytest.mark.parametrize("dtype", ["half"])
@@ -78,8 +76,8 @@ def test_llm_1_to_N(vllm_runner, hf_runner, model_name, dtype: str):
assert len(vllm_outputs) == 10
assert len(hf_outputs) == 10
assert math.isclose(hf_outputs[0], vllm_outputs[0], rel_tol=0.01)
assert math.isclose(hf_outputs[1], vllm_outputs[1], rel_tol=0.01)
assert hf_outputs[0] == pytest.approx(vllm_outputs[0], rel=0.01)
assert hf_outputs[1] == pytest.approx(vllm_outputs[1], rel=0.01)
@pytest.fixture(scope="module", params=EMBEDDING_MODELS)

22
tests/models/language/pooling/test_scoring.py
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@@ -1,6 +1,4 @@
# SPDX-License-Identifier: Apache-2.0
import math
import pytest
import torch
import torch.nn.functional as F
@@ -45,7 +43,7 @@ def test_cross_encoder_1_to_1(vllm_runner, hf_runner, model_name):
assert len(vllm_outputs) == 1
assert len(hf_outputs) == 1
assert math.isclose(hf_outputs[0], vllm_outputs[0], rel_tol=0.01)
assert hf_outputs[0] == pytest.approx(vllm_outputs[0], rel=0.01)
def test_cross_encoder_1_to_N(vllm_runner, hf_runner, model_name):
@@ -64,8 +62,8 @@ def test_cross_encoder_1_to_N(vllm_runner, hf_runner, model_name):
assert len(vllm_outputs) == 2
assert len(hf_outputs) == 2
assert math.isclose(hf_outputs[0], vllm_outputs[0], rel_tol=0.01)
assert math.isclose(hf_outputs[1], vllm_outputs[1], rel_tol=0.01)
assert hf_outputs[0] == pytest.approx(vllm_outputs[0], rel=0.01)
assert hf_outputs[1] == pytest.approx(vllm_outputs[1], rel=0.01)
def test_cross_encoder_N_to_N(vllm_runner, hf_runner, model_name):
@@ -84,8 +82,8 @@ def test_cross_encoder_N_to_N(vllm_runner, hf_runner, model_name):
assert len(vllm_outputs) == 2
assert len(hf_outputs) == 2
assert math.isclose(hf_outputs[0], vllm_outputs[0], rel_tol=0.01)
assert math.isclose(hf_outputs[1], vllm_outputs[1], rel_tol=0.01)
assert hf_outputs[0] == pytest.approx(vllm_outputs[0], rel=0.01)
assert hf_outputs[1] == pytest.approx(vllm_outputs[1], rel=0.01)
@pytest.fixture(scope="module", params=EMBEDDING_MODELS)
@@ -112,7 +110,7 @@ def test_embedding_1_to_1(vllm_runner, hf_runner, emb_model_name):
assert len(vllm_outputs) == 1
assert len(hf_outputs) == 1
assert math.isclose(hf_outputs[0], vllm_outputs[0], rel_tol=0.01)
assert hf_outputs[0] == pytest.approx(vllm_outputs[0], rel=0.01)
def test_embedding_1_to_N(vllm_runner, hf_runner, emb_model_name):
@@ -140,8 +138,8 @@ def test_embedding_1_to_N(vllm_runner, hf_runner, emb_model_name):
assert len(vllm_outputs) == 2
assert len(hf_outputs) == 2
assert math.isclose(hf_outputs[0], vllm_outputs[0], rel_tol=0.01)
assert math.isclose(hf_outputs[1], vllm_outputs[1], rel_tol=0.01)
assert hf_outputs[0] == pytest.approx(vllm_outputs[0], rel=0.01)
assert hf_outputs[1] == pytest.approx(vllm_outputs[1], rel=0.01)
def test_embedding_N_to_N(vllm_runner, hf_runner, emb_model_name):
@@ -169,5 +167,5 @@ def test_embedding_N_to_N(vllm_runner, hf_runner, emb_model_name):
assert len(vllm_outputs) == 2
assert len(hf_outputs) == 2
assert math.isclose(hf_outputs[0], vllm_outputs[0], rel_tol=0.01)
assert math.isclose(hf_outputs[1], vllm_outputs[1], rel_tol=0.01)
assert hf_outputs[0] == pytest.approx(vllm_outputs[0], rel=0.01)
assert hf_outputs[1] == pytest.approx(vllm_outputs[1], rel=0.01)