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[AMD] Fix Janus-Pro crash and add Kimi-K2.5 nightly test (#18269)

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This commit is contained in:
Michael
2026-02-10 22:33:13 -08:00
committed by GitHub
parent cd90346a2b
commit d84d2063d3
4 changed files with 250 additions and 10 deletions
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.github/workflows/nightly-test-amd.yml
+39 -9
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@@ -31,10 +31,10 @@ on:
- 'nightly-8-gpu-deepseek-v31'
- 'nightly-8-gpu-deepseek-v32'
- 'nightly-8-gpu-deepseek-v32-mtp'
- 'nightly-8-gpu-kimi-k2'
- 'nightly-8-gpu-kimi-k25'
# MI35x jobs
- 'nightly-test-1-gpu-mi35x'
- 'nightly-8-gpu-mi35x-kimi-k2'
- 'nightly-8-gpu-mi35x-kimi-k25'
- 'nightly-accuracy-8-gpu-mi35x'
- 'nightly-8-gpu-mi35x-grok1-int4'
- 'nightly-8-gpu-mi35x-grok2'
@@ -494,6 +494,36 @@ jobs:
echo "$(<github_summary.md )" >> $GITHUB_STEP_SUMMARY || true
exit ${TEST_EXIT_CODE:-0}
# 8-GPU Kimi-K2.5 (Accuracy)
nightly-8-gpu-kimi-k25:
if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') && (inputs.job_filter == '' || inputs.job_filter == 'all' || inputs.job_filter == 'nightly-8-gpu-kimi-k25')
runs-on: linux-mi325-gpu-8
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
ref: ${{ inputs.ref || github.ref }}
- name: Setup docker
run: |
touch github_summary.md
bash scripts/ci/amd/amd_ci_start_container.sh
env:
GITHUB_WORKSPACE: ${{ github.workspace }}
- name: Install dependencies
run: bash scripts/ci/amd/amd_ci_install_dependency.sh
- name: Accuracy Test (8-GPU Kimi-K2.5)
timeout-minutes: 120
run: |
> github_summary.md # Clear summary file
bash scripts/ci/amd/amd_ci_exec.sh -w /sglang-checkout/test \
-e GITHUB_STEP_SUMMARY="/sglang-checkout/github_summary.md" \
python3 run_suite.py --hw amd --suite nightly-amd-accuracy-8-gpu-kimi-k25 --nightly --timeout-per-file 3600 || TEST_EXIT_CODE=$?
echo "$(<github_summary.md )" >> $GITHUB_STEP_SUMMARY || true
exit ${TEST_EXIT_CODE:-0}
# ============================================== MI35x Tests ==============================================
# MI35x 1-GPU tests - platform-agnostic tests that may work on CDNA4 (gfx950)
nightly-test-1-gpu-mi35x:
@@ -794,9 +824,9 @@ jobs:
echo "$(<github_summary.md )" >> $GITHUB_STEP_SUMMARY || true
exit ${TEST_EXIT_CODE:-0}
# MI35x 8-GPU Kimi-K2 (Accuracy)
nightly-8-gpu-mi35x-kimi-k2:
if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') && (inputs.job_filter == '' || inputs.job_filter == 'all' || inputs.job_filter == 'nightly-8-gpu-mi35x-kimi-k2')
# MI35x 8-GPU Kimi-K2.5 (Accuracy)
nightly-8-gpu-mi35x-kimi-k25:
if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') && (inputs.job_filter == '' || inputs.job_filter == 'all' || inputs.job_filter == 'nightly-8-gpu-mi35x-kimi-k25')
runs-on: linux-mi35x-gpu-8
steps:
- name: Checkout code
@@ -817,13 +847,13 @@ jobs:
# Install tabulate for run_suite.py (missing in MI35x container)
bash scripts/ci/amd/amd_ci_exec.sh pip install tabulate
- name: Accuracy Test MI35x (8-GPU Kimi-K2)
- name: Accuracy Test MI35x (8-GPU Kimi-K2.5)
timeout-minutes: 180
run: |
> github_summary.md # Clear summary file
bash scripts/ci/amd/amd_ci_exec.sh -w /sglang-checkout/test \
-e GITHUB_STEP_SUMMARY="/sglang-checkout/github_summary.md" \
python3 run_suite.py --hw amd --suite nightly-amd-accuracy-8-gpu-mi35x-kimi-k2 --nightly --timeout-per-file 7200 || TEST_EXIT_CODE=$?
python3 run_suite.py --hw amd --suite nightly-amd-accuracy-8-gpu-mi35x-kimi-k25 --nightly --timeout-per-file 7200 || TEST_EXIT_CODE=$?
echo "$(<github_summary.md )" >> $GITHUB_STEP_SUMMARY || true
exit ${TEST_EXIT_CODE:-0}
@@ -878,7 +908,7 @@ jobs:
- nightly-8-gpu-deepseek-v31
- nightly-8-gpu-deepseek-v32
- nightly-8-gpu-deepseek-v32-mtp
- nightly-8-gpu-kimi-k2
- nightly-8-gpu-kimi-k25
# MI35x jobs
- nightly-test-1-gpu-mi35x
- nightly-accuracy-8-gpu-mi35x
@@ -887,7 +917,7 @@ jobs:
- nightly-8-gpu-mi35x-deepseek-r1-mxfp4
- nightly-accuracy-8-gpu-mi35x-deepseek-v32
- nightly-accuracy-8-gpu-mi35x-deepseek-v32-mtp
- nightly-8-gpu-mi35x-kimi-k2
- nightly-8-gpu-mi35x-kimi-k25
# MI35x perf jobs excluded from check - perf failures don't block CI
# - nightly-perf-8-gpu-mi35x-deepseek-v32-basic
# - nightly-perf-8-gpu-mi35x-deepseek-v32-mtp
python/sglang/srt/models/deepseek_janus_pro.py
+1 -1
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@@ -1955,7 +1955,7 @@ class MultiModalityCausalLM(MultiModalityPreTrainedModel):
self.language_model = LlamaForCausalLM(
language_config, quant_config=quant_config
)
self.logits_processor = LogitsProcessor(config)
self.logits_processor = LogitsProcessor(language_config)
def get_image_feature(self, items: List[MultimodalDataItem]) -> torch.Tensor:
pixel_values = torch.concat([item.feature for item in items], dim=0)
test/registered/amd/accuracy/mi30x/test_kimi_k25_eval_amd.py
+104
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@@ -0,0 +1,104 @@
"""AMD Kimi-K2.5 GSM8K Completion Evaluation Test (8-GPU)
Tests moonshotai/Kimi-K2.5 with GSM8K few-shot benchmark on MI325.
Registry: nightly-amd-accuracy-8-gpu-kimi-k25 suite
"""
import os
import unittest
from types import SimpleNamespace
import requests
from sglang.srt.utils import kill_process_tree
from sglang.test.ci.ci_register import register_amd_ci
from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
from sglang.test.test_utils import (
DEFAULT_URL_FOR_TEST,
CustomTestCase,
is_in_ci,
popen_launch_server,
write_github_step_summary,
)
# Register for AMD CI - Kimi K2.5 accuracy test (~60 min)
register_amd_ci(
est_time=3600, suite="nightly-amd-accuracy-8-gpu-kimi-k25", nightly=True
)
KIMI_K25_MODEL_PATH = "moonshotai/Kimi-K2.5"
SERVER_LAUNCH_TIMEOUT = 3600
ACCURACY_THRESHOLD = 0.92
TP_SIZE = 8
class TestKimiK25EvalAMD(CustomTestCase):
"""Kimi-K2.5 GSM8K Completion Evaluation Test for AMD MI325."""
@classmethod
def setUpClass(cls):
cls.model = KIMI_K25_MODEL_PATH
cls.base_url = DEFAULT_URL_FOR_TEST
other_args = [
"--tp",
str(TP_SIZE),
"--decode-attention-backend",
"triton",
"--prefill-attention-backend",
"aiter",
"--trust-remote-code",
"--model-loader-extra-config",
'{"enable_multithread_load": true}',
]
env = os.environ.copy()
env["SGLANG_USE_AITER"] = "1"
env["SGLANG_ROCM_FUSED_DECODE_MLA"] = "0"
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=SERVER_LAUNCH_TIMEOUT,
other_args=other_args,
env=env,
)
@classmethod
def tearDownClass(cls):
kill_process_tree(cls.process.pid)
def test_kimi_k25_gsm8k_accuracy(self):
"""Test Kimi-K2.5 with GSM8K few-shot completion benchmark."""
requests.get(self.base_url + "/flush_cache")
args = SimpleNamespace(
num_shots=8,
data_path=None,
num_questions=1319,
parallel=1319,
max_new_tokens=512,
host="http://127.0.0.1",
port=int(self.base_url.split(":")[-1]),
)
metrics = run_eval_few_shot_gsm8k(args)
acc = metrics["accuracy"]
passed = acc >= ACCURACY_THRESHOLD
status = "✅ PASS" if passed else "❌ FAIL"
print(f" accuracy={acc:.3f} threshold={ACCURACY_THRESHOLD} {status}")
if is_in_ci():
summary = "### Kimi-K2.5 Model (MI325)\n\n"
summary += "| Model | TP | Accuracy | Threshold | Status |\n"
summary += "| ----- | -- | -------- | --------- | ------ |\n"
summary += f"| {KIMI_K25_MODEL_PATH} | {TP_SIZE} | {acc:.3f} | {ACCURACY_THRESHOLD} | {status} |\n"
write_github_step_summary(summary)
self.assertGreaterEqual(
acc,
ACCURACY_THRESHOLD,
f"Kimi-K2.5 accuracy {acc:.3f} below threshold {ACCURACY_THRESHOLD}",
)
if __name__ == "__main__":
unittest.main()
test/registered/amd/accuracy/mi35x/test_kimi_k25_eval_mi35x.py
+106
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@@ -0,0 +1,106 @@
"""MI35x Kimi-K2.5 GSM8K Completion Evaluation Test (8-GPU)
Tests moonshotai/Kimi-K2.5 with GSM8K few-shot benchmark on MI35x.
Registry: nightly-amd-accuracy-8-gpu-mi35x-kimi-k25 suite
"""
import os
import unittest
from types import SimpleNamespace
import requests
from sglang.srt.utils import kill_process_tree
from sglang.test.ci.ci_register import register_amd_ci
from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
from sglang.test.test_utils import (
DEFAULT_URL_FOR_TEST,
CustomTestCase,
is_in_ci,
popen_launch_server,
write_github_step_summary,
)
# Register for AMD CI - Kimi K2.5 accuracy test on MI35x (~60 min)
register_amd_ci(
est_time=3600, suite="nightly-amd-accuracy-8-gpu-mi35x-kimi-k25", nightly=True
)
KIMI_K25_MODEL_PATH = "moonshotai/Kimi-K2.5"
SERVER_LAUNCH_TIMEOUT = 3600
ACCURACY_THRESHOLD = 0.92
TP_SIZE = 8
class TestKimiK25EvalMI35x(CustomTestCase):
"""Kimi-K2.5 GSM8K Completion Evaluation Test for AMD MI35x."""
@classmethod
def setUpClass(cls):
cls.base_url = DEFAULT_URL_FOR_TEST
def test_kimi_k25_gsm8k_accuracy(self):
"""Test Kimi-K2.5 with GSM8K few-shot completion benchmark."""
other_args = [
"--tp",
str(TP_SIZE),
"--decode-attention-backend",
"triton",
"--prefill-attention-backend",
"aiter",
"--trust-remote-code",
"--model-loader-extra-config",
'{"enable_multithread_load": true}',
"--watchdog-timeout",
"1200",
]
env = os.environ.copy()
env["SGLANG_USE_AITER"] = "1"
env["SGLANG_ROCM_FUSED_DECODE_MLA"] = "0"
process = popen_launch_server(
KIMI_K25_MODEL_PATH,
self.base_url,
timeout=SERVER_LAUNCH_TIMEOUT,
other_args=other_args,
env=env,
)
try:
requests.get(self.base_url + "/flush_cache")
args = SimpleNamespace(
num_shots=8,
data_path=None,
num_questions=1319,
parallel=1319,
max_new_tokens=512,
host="http://127.0.0.1",
port=int(self.base_url.split(":")[-1]),
)
metrics = run_eval_few_shot_gsm8k(args)
acc = metrics["accuracy"]
passed = acc >= ACCURACY_THRESHOLD
status = "✅ PASS" if passed else "❌ FAIL"
print(f" accuracy={acc:.3f} threshold={ACCURACY_THRESHOLD} {status}")
if is_in_ci():
summary = "### Kimi-K2.5 Model (MI35x)\n\n"
summary += "| Model | TP | Accuracy | Threshold | Status |\n"
summary += "| ----- | -- | -------- | --------- | ------ |\n"
summary += f"| {KIMI_K25_MODEL_PATH} | {TP_SIZE} | {acc:.3f} | {ACCURACY_THRESHOLD} | {status} |\n"
write_github_step_summary(summary)
self.assertGreaterEqual(
acc,
ACCURACY_THRESHOLD,
f"Kimi-K2.5 accuracy {acc:.3f} below threshold {ACCURACY_THRESHOLD}",
)
finally:
kill_process_tree(process.pid)
if __name__ == "__main__":
unittest.main()