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Avoid direct comparison of floating point numbers (#21002)

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Signed-off-by: Max de Bayser <mbayser@br.ibm.com>
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Maximilien de Bayser 2025-07-16 01:12:14 -03:00 committed by GitHub
parent cfbcb9ed87
commit 6ebf313790
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5 changed files with 44 additions and 7 deletions
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6
tests/entrypoints/openai/test_classification.py
View File

@ -176,4 +176,8 @@ async def test_invocations(server: RemoteOpenAIServer):
invocation_output = invocation_response.json()
assert classification_output.keys() == invocation_output.keys()
assert classification_output["data"] == invocation_output["data"]
for classification_data, invocation_data in zip(
classification_output["data"], invocation_output["data"]):
assert classification_data.keys() == invocation_data.keys()
assert classification_data["probs"] == pytest.approx(
invocation_data["probs"], rel=0.01)

17
tests/entrypoints/openai/test_embedding.py
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@ -14,6 +14,7 @@ from vllm.transformers_utils.tokenizer import get_tokenizer
from ...models.language.pooling.embed_utils import (
run_embedding_correctness_test)
from ...models.utils import check_embeddings_close
from ...utils import RemoteOpenAIServer
MODEL_NAME = "intfloat/multilingual-e5-small"
@ -321,7 +322,13 @@ async def test_invocations(server: RemoteOpenAIServer,
invocation_output = invocation_response.json()
assert completion_output.keys() == invocation_output.keys()
assert completion_output["data"] == invocation_output["data"]
for completion_data, invocation_data in zip(completion_output["data"],
invocation_output["data"]):
assert completion_data.keys() == invocation_data.keys()
check_embeddings_close(embeddings_0_lst=[completion_data["embedding"]],
embeddings_1_lst=[invocation_data["embedding"]],
name_0="completion",
name_1="invocation")
@pytest.mark.asyncio
@ -355,4 +362,10 @@ async def test_invocations_conversation(server: RemoteOpenAIServer):
invocation_output = invocation_response.json()
assert chat_output.keys() == invocation_output.keys()
assert chat_output["data"] == invocation_output["data"]
for chat_data, invocation_data in zip(chat_output["data"],
invocation_output["data"]):
assert chat_data.keys() == invocation_data.keys()
check_embeddings_close(embeddings_0_lst=[chat_data["embedding"]],
embeddings_1_lst=[invocation_data["embedding"]],
name_0="chat",
name_1="invocation")

16
tests/entrypoints/openai/test_pooling.py
View File

@ -281,7 +281,13 @@ async def test_invocations(server: RemoteOpenAIServer):
invocation_output = invocation_response.json()
assert completion_output.keys() == invocation_output.keys()
assert completion_output["data"] == invocation_output["data"]
for completion_data, invocation_data in zip(completion_output["data"],
invocation_output["data"]):
assert completion_data.keys() == invocation_data.keys()
check_embeddings_close(embeddings_0_lst=completion_data["data"],
embeddings_1_lst=invocation_data["data"],
name_0="completion",
name_1="invocation")
@pytest.mark.asyncio
@ -314,4 +320,10 @@ async def test_invocations_conversation(server: RemoteOpenAIServer):
invocation_output = invocation_response.json()
assert chat_output.keys() == invocation_output.keys()
assert chat_output["data"] == invocation_output["data"]
for chat_data, invocation_data in zip(chat_output["data"],
invocation_output["data"]):
assert chat_data.keys() == invocation_data.keys()
check_embeddings_close(embeddings_0_lst=chat_data["data"],
embeddings_1_lst=invocation_data["data"],
name_0="chat",
name_1="invocation")

6
tests/entrypoints/openai/test_rerank.py
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@ -120,4 +120,8 @@ def test_invocations(server: RemoteOpenAIServer):
invocation_output = invocation_response.json()
assert rerank_output.keys() == invocation_output.keys()
assert rerank_output["results"] == invocation_output["results"]
for rerank_result, invocations_result in zip(rerank_output["results"],
invocation_output["results"]):
assert rerank_result.keys() == invocations_result.keys()
assert rerank_result["relevance_score"] == pytest.approx(
invocations_result["relevance_score"], rel=0.01)

6
tests/entrypoints/openai/test_score.py
View File

@ -215,4 +215,8 @@ class TestModel:
invocation_output = invocation_response.json()
assert score_output.keys() == invocation_output.keys()
assert score_output["data"] == invocation_output["data"]
for score_data, invocation_data in zip(score_output["data"],
invocation_output["data"]):
assert score_data.keys() == invocation_data.keys()
assert score_data["score"] == pytest.approx(
invocation_data["score"], rel=0.01)