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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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41
tests/models/quantization/test_gptq_marlin_24.py
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@@ -6,6 +6,7 @@ Note: GPTQ and Marlin_24 do not have bitwise correctness.
As a result, in this test, we just confirm that the top selected tokens of the
Marlin/GPTQ models are in the top 3 selections of each other.
"""
from dataclasses import dataclass
import pytest
@@ -24,15 +25,18 @@ class ModelPair:
model_pairs = [
# 4-bit, group_size == 128
ModelPair(model_marlin="alexm-nm/tinyllama-24-marlin24-4bit-g128",
model_gptq="alexm-nm/tinyllama-24-gptq-4bit-g128"),
ModelPair(
model_marlin="alexm-nm/tinyllama-24-marlin24-4bit-g128",
model_gptq="alexm-nm/tinyllama-24-gptq-4bit-g128",
),
# # 4-bit, group_size == channelwise
# ModelPair(model_marlin="alexm-nm/tinyllama-24-marlin24-4bit-channelwise",
# model_gptq="alexm-nm/tinyllama-24-gptq-4bit-channelwise"),
# 8-bit, group_size == 128
ModelPair(model_marlin="alexm-nm/tinyllama-24-marlin24-8bit-g128",
model_gptq="alexm-nm/tinyllama-24-gptq-8bit-g128"),
ModelPair(
model_marlin="alexm-nm/tinyllama-24-marlin24-8bit-g128",
model_gptq="alexm-nm/tinyllama-24-gptq-8bit-g128",
),
# # 8-bit, group_size == channelwise
# ModelPair(model_marlin="alexm-nm/tinyllama-24-marlin24-8bit-channelwise",
# model_gptq="alexm-nm/tinyllama-24-gptq-8bit-channelwise"),
@@ -40,10 +44,12 @@ model_pairs = [
@pytest.mark.flaky(reruns=2)
@pytest.mark.skipif(not is_quant_method_supported("gptq_marlin_24")
or current_platform.is_rocm()
or not current_platform.is_cuda(),
reason="Marlin24 is not supported on this GPU type.")
@pytest.mark.skipif(
not is_quant_method_supported("gptq_marlin_24")
or current_platform.is_rocm()
or not current_platform.is_cuda(),
reason="Marlin24 is not supported on this GPU type.",
)
@pytest.mark.parametrize("model_pair", model_pairs)
@pytest.mark.parametrize("dtype", ["half"])
@pytest.mark.parametrize("max_tokens", [8])
@@ -56,16 +62,19 @@ def test_models(
max_tokens: int,
num_logprobs: int,
) -> None:
with vllm_runner(model_pair.model_marlin,
dtype=dtype,
quantization="gptq_marlin_24") as marlin_24_model:
with vllm_runner(
model_pair.model_marlin, dtype=dtype, quantization="gptq_marlin_24"
) as marlin_24_model:
marlin_24_outputs = marlin_24_model.generate_greedy_logprobs(
example_prompts, max_tokens, num_logprobs)
example_prompts, max_tokens, num_logprobs
)
with vllm_runner(model_pair.model_gptq, dtype=dtype,
quantization="gptq") as gptq_model:
with vllm_runner(
model_pair.model_gptq, dtype=dtype, quantization="gptq"
) as gptq_model:
gptq_outputs = gptq_model.generate_greedy_logprobs(
example_prompts, max_tokens, num_logprobs)
example_prompts, max_tokens, num_logprobs
)
check_logprobs_close(
outputs_0_lst=gptq_outputs,