Add Arm64 INT8 MoE test coverage (#25007)

This commit is contained in:
Mandepudi Rani Chowdary
2026-06-10 10:36:57 +08:00
committed by GitHub
parent 854d232a40
commit 7e3e616159
12 changed files with 245 additions and 17 deletions
+118
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@@ -0,0 +1,118 @@
"""Arm64 MoE test.
Tests fused_experts_cpu with W8A8 INT8 quantization, which is supported
on Arm64 via aarch64/moe.cpp (PR #16045). Additional quantization paths
(BF16, INT4) will be added here as Arm kernels land.
"""
from sglang.test.ci.ci_register import register_cpu_ci
register_cpu_ci(est_time=10, suite="base-b-test-cpu-arm64")
import itertools
import math
import os
import platform
import sys
import unittest
import torch
# Add parent dir (test/srt/cpu/) to path for utils import
sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
from sglang.srt.layers.amx_utils import CPUQuantMethod
from sglang.test.test_utils import CustomTestCase
kernel = torch.ops.sgl_kernel
IS_ARM64 = platform.machine().lower() in ("aarch64", "arm64")
torch.manual_seed(128)
from utils import (
precision,
torch_w8a8_per_column_fused_moe,
)
class TestFusedExpertsInt8(CustomTestCase):
M = [1, 6, 32, 64]
N = [256, 512]
K = [256, 512]
E = [8]
topk = [4]
def _int8_moe(self, M, N, K, E, topk):
dtype = torch.bfloat16
# Arm64 INT8 MoE currently uses the unpacked, out-of-place path.
prepack = not IS_ARM64
int8_factor_for_scale = 1e-2
int8_max = 127
int8_min = -128
a = torch.randn((M, K), dtype=dtype) / math.sqrt(K)
w1_fp32 = (torch.rand((E, 2 * N, K), dtype=torch.float32) - 0.5) * 2
w1 = (w1_fp32 * int8_max).clamp(min=int8_min, max=int8_max).to(torch.int8)
w2_fp32 = (torch.rand((E, K, N), dtype=torch.float32) - 0.5) * 2
w2 = (w2_fp32 * int8_max).clamp(min=int8_min, max=int8_max).to(torch.int8)
w1_s = torch.rand(E, 2 * N, device=w1_fp32.device) * int8_factor_for_scale
w2_s = torch.rand(E, K, device=w2_fp32.device) * int8_factor_for_scale
score = torch.randn((M, E), dtype=dtype)
score = torch.softmax(score, dim=-1, dtype=torch.float32)
topk_weight, topk_ids = torch.topk(score, topk)
ref_out = torch_w8a8_per_column_fused_moe(
a, w1, w2, w1_s, w2_s, topk_weight, topk_ids, topk
)
inplace = not IS_ARM64
packed_w1 = kernel.convert_weight_packed(w1) if prepack else w1
packed_w2 = kernel.convert_weight_packed(w2) if prepack else w2
out = kernel.fused_experts_cpu(
a,
packed_w1,
packed_w2,
topk_weight,
topk_ids.to(torch.int32),
inplace,
CPUQuantMethod.INT8_W8A8,
w1_s,
w2_s,
None,
None,
None,
prepack,
)
atol = rtol = precision[ref_out.dtype]
if IS_ARM64:
atol = rtol = 0.03
elif M > 35:
atol = rtol = 0.02
torch.testing.assert_close(ref_out, out, atol=atol, rtol=rtol)
def test_int8_moe(self):
for params in itertools.product(
self.M,
self.N,
self.K,
self.E,
self.topk,
):
with self.subTest(
M=params[0],
N=params[1],
K=params[2],
E=params[3],
topk=params[4],
):
self._int8_moe(*params)
if __name__ == "__main__":
unittest.main()
+1
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@@ -9,6 +9,7 @@ from sglang.test.ci.ci_register import register_cpu_ci
from sglang.test.test_utils import CustomTestCase
register_cpu_ci(est_time=10, suite="base-b-test-cpu")
register_cpu_ci(est_time=10, suite="base-b-test-cpu-arm64")
torch.manual_seed(1234)
+1
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@@ -7,6 +7,7 @@ from sglang.test.ci.ci_register import register_cpu_ci
from sglang.test.test_utils import CustomTestCase
register_cpu_ci(est_time=10, suite="base-b-test-cpu")
register_cpu_ci(est_time=10, suite="base-b-test-cpu-arm64")
torch.manual_seed(1234)
+1
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@@ -9,6 +9,7 @@ from sglang.test.ci.ci_register import register_cpu_ci
from sglang.test.test_utils import CustomTestCase
register_cpu_ci(est_time=10, suite="base-b-test-cpu")
register_cpu_ci(est_time=10, suite="base-b-test-cpu-arm64")
torch.manual_seed(1234)
+1
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@@ -7,6 +7,7 @@ from sglang.test.ci.ci_register import register_cpu_ci
from sglang.test.test_utils import CustomTestCase
register_cpu_ci(est_time=10, suite="base-b-test-cpu")
register_cpu_ci(est_time=10, suite="base-b-test-cpu-arm64")
torch.manual_seed(1234)
+1
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@@ -16,6 +16,7 @@ from sglang.test.ci.ci_register import register_cpu_ci
from sglang.test.test_utils import CustomTestCase
register_cpu_ci(est_time=10, suite="base-b-test-cpu")
register_cpu_ci(est_time=10, suite="base-b-test-cpu-arm64")
torch.manual_seed(1234)
@@ -8,6 +8,7 @@ from sglang.srt.server_args import ServerArgs
from sglang.test.ci.ci_register import register_cpu_ci
register_cpu_ci(est_time=10, suite="base-b-test-cpu")
register_cpu_ci(est_time=10, suite="base-b-test-cpu-arm64")
class TestServerArgsCPUBackend(unittest.TestCase):
+1
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@@ -14,6 +14,7 @@ from sglang.test.ci.ci_register import register_cpu_ci
from sglang.test.test_utils import CustomTestCase
register_cpu_ci(est_time=10, suite="base-b-test-cpu")
register_cpu_ci(est_time=10, suite="base-b-test-cpu-arm64")
# This is used by the Deepseek-V2 model
+1 -1
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@@ -29,7 +29,7 @@ HW_MAPPING = {
# (label-gated; pr-test-extra.yml). Tests are tagged per-commit regardless;
# pr-test-extra.yml's `run-ci-extra` PR label decides whether extra-* dispatches.
PER_COMMIT_SUITES = {
HWBackend.CPU: ["base-a-test-cpu", "base-b-test-cpu"],
HWBackend.CPU: ["base-a-test-cpu", "base-b-test-cpu", "base-b-test-cpu-arm64"],
HWBackend.AMD: [
"stage-a-test-1-gpu-small-amd",
"stage-b-test-1-gpu-small-amd",
+118
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@@ -0,0 +1,118 @@
"""Arm64 MoE test.
Tests fused_experts_cpu with W8A8 INT8 quantization, which is supported
on Arm64 via aarch64/moe.cpp (PR #16045). Additional quantization paths
(BF16, INT4) will be added here as Arm kernels land.
"""
from sglang.test.ci.ci_register import register_cpu_ci
register_cpu_ci(est_time=10, suite="per-commit-cpu-arm64")
import itertools
import math
import os
import platform
import sys
import unittest
import torch
# Add parent dir (test/srt/cpu/) to path for utils import
sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
from sglang.srt.layers.amx_utils import CPUQuantMethod
from sglang.test.test_utils import CustomTestCase
kernel = torch.ops.sgl_kernel
IS_ARM64 = platform.machine().lower() in ("aarch64", "arm64")
torch.manual_seed(128)
from utils import (
precision,
torch_w8a8_per_column_fused_moe,
)
class TestFusedExpertsInt8(CustomTestCase):
M = [1, 6, 32, 64]
N = [256, 512]
K = [256, 512]
E = [8]
topk = [4]
def _int8_moe(self, M, N, K, E, topk):
dtype = torch.bfloat16
# Arm64 INT8 MoE currently uses the unpacked, out-of-place path.
prepack = not IS_ARM64
int8_factor_for_scale = 1e-2
int8_max = 127
int8_min = -128
a = torch.randn((M, K), dtype=dtype) / math.sqrt(K)
w1_fp32 = (torch.rand((E, 2 * N, K), dtype=torch.float32) - 0.5) * 2
w1 = (w1_fp32 * int8_max).clamp(min=int8_min, max=int8_max).to(torch.int8)
w2_fp32 = (torch.rand((E, K, N), dtype=torch.float32) - 0.5) * 2
w2 = (w2_fp32 * int8_max).clamp(min=int8_min, max=int8_max).to(torch.int8)
w1_s = torch.rand(E, 2 * N, device=w1_fp32.device) * int8_factor_for_scale
w2_s = torch.rand(E, K, device=w2_fp32.device) * int8_factor_for_scale
score = torch.randn((M, E), dtype=dtype)
score = torch.softmax(score, dim=-1, dtype=torch.float32)
topk_weight, topk_ids = torch.topk(score, topk)
ref_out = torch_w8a8_per_column_fused_moe(
a, w1, w2, w1_s, w2_s, topk_weight, topk_ids, topk
)
inplace = not IS_ARM64
packed_w1 = kernel.convert_weight_packed(w1) if prepack else w1
packed_w2 = kernel.convert_weight_packed(w2) if prepack else w2
out = kernel.fused_experts_cpu(
a,
packed_w1,
packed_w2,
topk_weight,
topk_ids.to(torch.int32),
inplace,
CPUQuantMethod.INT8_W8A8,
w1_s,
w2_s,
None,
None,
None,
prepack,
)
atol = rtol = precision[ref_out.dtype]
if IS_ARM64:
atol = rtol = 0.03
elif M > 35:
atol = rtol = 0.02
torch.testing.assert_close(ref_out, out, atol=atol, rtol=rtol)
def test_int8_moe(self):
for params in itertools.product(
self.M,
self.N,
self.K,
self.E,
self.topk,
):
with self.subTest(
M=params[0],
N=params[1],
K=params[2],
E=params[3],
topk=params[4],
):
self._int8_moe(*params)
if __name__ == "__main__":
unittest.main()
-15
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@@ -45,20 +45,6 @@ suite_amd = {
}
# Keep the Arm64 bootstrap suite limited to hosted-runner-safe unit kernels.
# `test_extend.py`, `test_mamba.py`, and `test_mla.py` still hit the
# x86-specific BF16 BRGEMM/VNNI path on Arm and need dedicated fallbacks.
suite_arm64 = {
"per-commit-cpu-arm64": [
TestFile("cpu/test_activation.py"),
TestFile("cpu/test_decode.py"),
TestFile("cpu/test_norm.py"),
TestFile("cpu/test_qwen3.py"),
TestFile("cpu/test_rope.py"),
TestFile("cpu/test_server_args_backend.py"),
TestFile("cpu/test_topk.py"),
],
}
# Add Intel Xeon tests
suite_xeon = {
"per-commit-cpu": [
@@ -93,7 +79,6 @@ suite_xeon = {
suite_xpu = {}
suites.update(suite_amd)
suites.update(suite_arm64)
suites.update(suite_xeon)
suites.update(suite_xpu)