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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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21
tests/models/quantization/test_mxfp4.py
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@@ -1,8 +1,8 @@
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
# flake8: noqa
"""Tests Quark mxfp4 models against ground truth generation
"""
"""Tests Quark mxfp4 models against ground truth generation"""
import pytest
from vllm import LLM, SamplingParams
@@ -11,13 +11,13 @@ MODELS = ["amd/Llama-2-7b-chat-hf-wmxfp4-amxfp4-kvfp8-scale-uint8"]
EXPECTED_STRS_MAP = {
"amd/Llama-2-7b-chat-hf-wmxfp4-amxfp4-kvfp8-scale-uint8": [
'\n### Key Features\n\n* **High-throughput Inference**: vLL',
'\nArtificial intelligence (AI) has evolved significantly since its inception in the 1',
'Artificial intelligence (AI) and human intelligence (HI) are two distinct concepts that have been',
'A neural network is a machine learning model inspired by the structure of the human brain. It consists of',
'\nTitle: The Dreaming Robot\n\nAs the sun set on the bustling metropol',
'\nThe COVID-19 pandemic has had a profound impact on global economic structures and business',
'The Mona Lisa painting, created by Leonardo da Vinci in the early 16th',
"\n### Key Features\n\n* **High-throughput Inference**: vLL",
"\nArtificial intelligence (AI) has evolved significantly since its inception in the 1",
"Artificial intelligence (AI) and human intelligence (HI) are two distinct concepts that have been",
"A neural network is a machine learning model inspired by the structure of the human brain. It consists of",
"\nTitle: The Dreaming Robot\n\nAs the sun set on the bustling metropol",
"\nThe COVID-19 pandemic has had a profound impact on global economic structures and business",
"The Mona Lisa painting, created by Leonardo da Vinci in the early 16th",
" everybody knows this proverbial saying, but did you know that it's not entirely accurate?",
]
}
@@ -38,4 +38,5 @@ def test_models(example_prompts, model_name) -> None:
output_str = output.outputs[0].text
expected_str = EXPECTED_STRS_MAP[model_name][i]
assert expected_str == output_str, (
f"Expected: {expected_str!r}\nvLLM: {output_str!r}")
f"Expected: {expected_str!r}\nvLLM: {output_str!r}"
)