[chore] update torch version to 2.9 (#12969)
Co-authored-by: Baizhou Zhang <sobereddiezhang@gmail.com>
This commit is contained in:
Fan Yin
@@ -1,143 +0,0 @@
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import unittest
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from types import SimpleNamespace
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from sglang.srt.utils import kill_process_tree
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from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
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from sglang.test.test_disaggregation_utils import get_rdma_devices_args
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from sglang.test.test_utils import (
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DEFAULT_MODEL_NAME_FOR_TEST_MLA,
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DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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DEFAULT_URL_FOR_TEST,
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CustomTestCase,
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popen_launch_server,
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)
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ib_devices = get_rdma_devices_args()
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class TestTP(CustomTestCase):
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extra_args = []
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@classmethod
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def setUpClass(cls):
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cls.model = DEFAULT_MODEL_NAME_FOR_TEST_MLA
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cls.base_url = DEFAULT_URL_FOR_TEST
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cls.process = popen_launch_server(
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cls.model,
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cls.base_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=[
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"--trust-remote-code",
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"--tp",
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"4",
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"--elastic-ep-backend",
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"mooncake",
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"--mooncake-ib-device",
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ib_devices,
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"--moe-a2a-backend",
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"deepep",
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"--deepep-mode",
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"low_latency",
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"--chunked-prefill-size",
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"512",
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"--cuda-graph-max-bs",
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"128",
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"--max-running-requests",
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"512",
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"--mem-fraction-static",
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"0.5",
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*cls.extra_args,
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],
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)
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@classmethod
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def tearDownClass(cls):
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kill_process_tree(cls.process.pid)
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def test_gsm8k(self):
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args = SimpleNamespace(
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num_shots=5,
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data_path=None,
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num_questions=200,
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max_new_tokens=512,
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parallel=128,
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host="http://127.0.0.1",
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port=int(self.base_url.split(":")[-1]),
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)
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metrics = run_eval_few_shot_gsm8k(args)
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print(metrics)
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self.assertGreater(metrics["accuracy"], 0.60)
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class TestPureDP(TestTP):
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extra_args = [
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"--tp",
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"4",
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"--enable-dp-attention",
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"--dp",
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"4",
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]
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class TestHybridDPTP(TestTP):
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extra_args = [
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"--tp",
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"4",
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"--enable-dp-attention",
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"--dp",
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"2",
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]
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class TestNoGatherdBuffer(TestTP):
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extra_args = [
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"--tp",
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"4",
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"--enable-dp-attention",
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"--dp",
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"4",
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"--moe-dense-tp-size",
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"1",
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]
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class TestTBO(TestTP):
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extra_args = [
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"--tp",
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"4",
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"--enable-dp-attention",
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"--dp",
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"4",
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"--moe-dense-tp-size",
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"1",
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"--enable-two-batch-overlap",
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]
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class TestMooncakeWitchEPLB(TestTP):
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extra_args = [
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"--tp",
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"4",
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"--enable-dp-attention",
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"--dp",
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"4",
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"--moe-dense-tp-size",
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"1",
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"--enable-two-batch-overlap",
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"--enable-eplb",
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"--ep-num-redundant-experts",
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"4",
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"--eplb-rebalance-num-iterations",
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"50",
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"--expert-distribution-recorder-buffer-size",
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"50",
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"--expert-distribution-recorder-mode",
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"stat",
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"--ep-dispatch-algorithm",
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"static",
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]
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if __name__ == "__main__":
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unittest.main()
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@@ -1,71 +0,0 @@
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# Copyright 2023-2025 SGLang Team
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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import multiprocessing as mp
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import unittest
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from utils import (
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CI_MULTI_LORA_MODELS,
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LoRAAdaptor,
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LoRAModelCase,
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run_lora_multiple_batch_on_model_cases,
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)
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from sglang.test.test_utils import CustomTestCase
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LORA_MODELS_QWEN3 = [
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LoRAModelCase(
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base="Qwen/Qwen3-4B",
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adaptors=[
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LoRAAdaptor(
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name="nissenj/Qwen3-4B-lora-v2",
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prefill_tolerance=3e-1,
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),
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LoRAAdaptor(
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name="y9760210/Qwen3-4B-lora_model",
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prefill_tolerance=3e-1,
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),
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],
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max_loras_per_batch=2,
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),
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]
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class TestLoRASpecDecoding(CustomTestCase):
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def test_qwen(self):
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run_lora_multiple_batch_on_model_cases(
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LORA_MODELS_QWEN3,
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attention_backend="triton",
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use_spec_decoding=True,
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disable_cuda_graph=True,
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enable_deterministic_inference=True,
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)
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def test_llama(self):
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run_lora_multiple_batch_on_model_cases(
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CI_MULTI_LORA_MODELS,
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attention_backend="triton",
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use_spec_decoding=True,
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disable_cuda_graph=True,
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enable_deterministic_inference=True,
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)
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if __name__ == "__main__":
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try:
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mp.set_start_method("spawn")
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except RuntimeError:
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pass
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unittest.main(warnings="ignore")
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@@ -485,6 +485,7 @@ def run_lora_multiple_batch_on_model_cases(
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attention_backend: str = "torch_native",
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disable_cuda_graph: bool = True,
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enable_deterministic_inference: bool = False,
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disable_radix_cache: bool = True,
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):
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for model_case in model_cases:
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for torch_dtype in TORCH_DTYPES:
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@@ -523,6 +524,7 @@ def run_lora_multiple_batch_on_model_cases(
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attention_backend=attention_backend,
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enable_deterministic_inference=enable_deterministic_inference,
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disable_cuda_graph=disable_cuda_graph,
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disable_radix_cache=disable_radix_cache,
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**spec_args,
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)
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@@ -17,7 +17,6 @@ suites = {
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TestFile("lora/test_lora_eviction.py", 240),
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TestFile("lora/test_lora_update.py", 600),
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TestFile("lora/test_lora_backend.py", 99),
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TestFile("lora/test_lora_spec_decoding.py", 150),
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TestFile("lora/test_multi_lora_backend.py", 60),
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TestFile("models/test_compressed_tensors_models.py", 42),
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TestFile("models/test_cross_encoder_models.py", 100),
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@@ -186,7 +185,8 @@ suites = {
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],
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"per-commit-4-gpu-deepep": [
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TestFile("ep/test_deepep_small.py", 531),
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TestFile("ep/test_mooncake_ep_small.py", 450),
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# TODO: Add it back after mooncake supports torch 2.9
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# TestFile("ep/test_mooncake_ep_small.py", 450),
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],
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"per-commit-8-gpu-h200-deepep": [
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TestFile("ep/test_deepep_large.py", 338),
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