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Fix triton head num #1482

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Sep 21, 2024
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6 changes: 6 additions & 0 deletions .github/workflows/pr-test.yml
Original file line number Diff line number Diff line change
Expand Up @@ -233,6 +233,12 @@ jobs:
run: |
cd test/srt
python3 test_moe_eval_accuracy_large.py

- name: Evaluate MLA Accuracy (TP=2)
timeout-minutes: 10
run: |
cd test/srt
python3 -m unittest test_mla.TestMLA.test_mmlu

finish:
needs: [
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4 changes: 3 additions & 1 deletion python/sglang/srt/layers/attention_backend.py
Original file line number Diff line number Diff line change
Expand Up @@ -346,7 +346,9 @@ def __init__(self, model_runner: ModelRunner):

self.decode_attention_fwd = decode_attention_fwd
self.extend_attention_fwd = extend_attention_fwd
self.num_head = model_runner.model_config.num_attention_heads
self.num_head = (
model_runner.model_config.num_attention_heads // model_runner.tp_size
)

if global_server_args_dict.get("triton_attention_reduce_in_fp32", False):
self.reduce_dtype = torch.float32
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1 change: 1 addition & 0 deletions python/sglang/test/test_utils.py
Original file line number Diff line number Diff line change
Expand Up @@ -25,6 +25,7 @@
DEFAULT_FP8_MODEL_NAME_FOR_TEST = "neuralmagic/Meta-Llama-3.1-8B-FP8"
DEFAULT_MODEL_NAME_FOR_TEST = "meta-llama/Meta-Llama-3.1-8B-Instruct"
DEFAULT_MOE_MODEL_NAME_FOR_TEST = "mistralai/Mixtral-8x7B-Instruct-v0.1"
DEFAULT_MLA_MODEL_NAME_FOR_TEST = "deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct"
DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH = 600
DEFAULT_MODEL_NAME_FOR_NIGHTLY_EVAL_TP1 = "meta-llama/Meta-Llama-3.1-8B-Instruct,mistralai/Mistral-7B-Instruct-v0.3,deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct,google/gemma-2-27b-it"
DEFAULT_MODEL_NAME_FOR_NIGHTLY_EVAL_TP2 = "meta-llama/Meta-Llama-3.1-70B-Instruct,mistralai/Mixtral-8x7B-Instruct-v0.1,Qwen/Qwen2-57B-A14B-Instruct"
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44 changes: 44 additions & 0 deletions test/srt/test_mla.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,44 @@
import unittest
from types import SimpleNamespace

from sglang.srt.utils import kill_child_process
from sglang.test.run_eval import run_eval
from sglang.test.test_utils import (
DEFAULT_MLA_MODEL_NAME_FOR_TEST,
DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
DEFAULT_URL_FOR_TEST,
popen_launch_server,
)


class TestMLA(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.model = DEFAULT_MLA_MODEL_NAME_FOR_TEST
cls.base_url = DEFAULT_URL_FOR_TEST
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
other_args=["--tp", "2", "--trust-remote-code"],
)

@classmethod
def tearDownClass(cls):
kill_child_process(cls.process.pid)

def test_mmlu(self):
args = SimpleNamespace(
base_url=self.base_url,
model=self.model,
eval_name="mmlu",
num_examples=64,
num_threads=32,
)

metrics = run_eval(args)
assert metrics["score"] >= 0.5


if __name__ == "__main__":
unittest.main()
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