[ROCm][Quantization] Add Quark W4A8 (INT4-FP8) MoE CI coverage (#48050)

Signed-off-by: amd-sourjya <amd-sourjya@users.noreply.github.com>
Co-authored-by: amd-sourjya <amd-sourjya@users.noreply.github.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Andreas Karatzas <akaratza@amd.com>
This commit is contained in:
amd-sourjya
2026-07-23 21:56:40 -05:00
committed by GitHub
co-authored by amd-sourjya Cursor Andreas Karatzas
parent da54a5bf05
commit 80c9d5d5e0
+37 -1
View File
@@ -23,6 +23,7 @@ from vllm.model_executor.layers.quantization.quark.quark import ( # noqa: E501
QuarkW8A8Int8,
)
from vllm.model_executor.layers.quantization.quark.quark_moe import ( # noqa: E501
QuarkW4A8Fp8MoEMethod,
QuarkW8A8Int8MoEMethod,
)
from vllm.model_executor.layers.quantization.utils.quant_utils import (
@@ -31,9 +32,12 @@ from vllm.model_executor.layers.quantization.utils.quant_utils import (
from vllm.platforms import current_platform
if current_platform.is_rocm():
from vllm.platforms.rocm import on_gfx950
from vllm.platforms.rocm import on_gfx942, on_gfx950
else:
def on_gfx942() -> bool:
return False
def on_gfx950() -> bool:
return False
@@ -170,6 +174,38 @@ def test_quark_int8_w8a8_moe(vllm_runner, tp):
assert output
@pytest.mark.skipif(
not (on_gfx950() or on_gfx942()),
reason="Quark W4A8 (INT4-FP8) MoE requires the AITER kernel on gfx942/gfx950",
)
@pytest.mark.parametrize("tp", [1])
def test_quark_w4a8_fp8_moe(vllm_runner, monkeypatch, tp):
"""Test W4A8 (INT4 weight + FP8 activation) MoE with a tiny Qwen3 MoE model.
W4A8 dispatches through the AITER fused MoE kernel, so AITER must be on.
"""
monkeypatch.setenv("VLLM_ROCM_USE_AITER", "1")
monkeypatch.setenv("VLLM_ROCM_USE_AITER_MOE", "1")
model_path = "amd/tiny-qwen3-moe-w4a8"
with vllm_runner(
model_path,
enforce_eager=True,
tensor_parallel_size=tp,
gpu_memory_utilization=0.1,
) as llm:
def check_model(model):
moe = model.model.layers[0].mlp.experts
assert isinstance(moe._quant_method, QuarkW4A8Fp8MoEMethod), (
f"Expected QuarkW4A8Fp8MoEMethod, got {type(moe._quant_method)}"
)
llm.apply_model(check_model)
output = llm.generate_greedy("Hello", max_tokens=4)
assert output
def test_quark_fp8_parity(vllm_runner):
quark_model_id = "amd-quark/llama-tiny-fp8-quark-quant-method"
fp8_model_id = "amd-quark/llama-tiny-fp8-quant-method"