init v0.23.0

Signed-off-by: Sun Ruoxi <sunruoxi@4paradigm.com>
2026-08-27 15:11:51 +08:00
parent b582a8e7d1
commit 7f8a1b1f7a
2849 changed files with 712887 additions and 22001 deletions
--- a/tests/e2e/pull_request/four_card/test_pipeline_parallel.py
+++ b/tests/e2e/pull_request/four_card/test_pipeline_parallel.py
@@ -0,0 +1,146 @@
+# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
+# Copyright 2023 The vLLM team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# This file is a part of the vllm-ascend project.
+#
+import pytest
+
+from tests.e2e.conftest import DPVllmRunner, VllmRunner, wait_until_npu_memory_free
+from tests.e2e.model_utils import check_outputs_equal
+
+DS3 = "deepseek-ai/DeepSeek-V2-Lite-Chat"
+MODELS = [
+    DS3,
+]
+MOE_MODELS = [
+    DS3,
+]
+
+DATA_PARALLELS = [2]
+TENSOR_PARALLELS = [1]
+PIPELINE_PARALLELS = [2]
+DIST_EXECUTOR_BACKEND = ["mp", "ray"]
+
+prompts = [
+    "Hello, my name is",
+    "The future of AI is",
+]
+GOLDEN = [
+    (
+        [
+            17464,
+            11,
+            601,
+            1210,
+            317,
+            459,
+            6946,
+            29,
+            32,
+            1568,
+            32092,
+            535,
+            6946,
+            29,
+            285,
+            304,
+            6,
+            76,
+            245,
+            459,
+            6946,
+        ],
+        "Hello, my name is <strong>Alessandro</strong> and I'm a <strong",
+    ),
+    (
+        [
+            549,
+            3680,
+            280,
+            20838,
+            317,
+            6464,
+            11,
+            285,
+            359,
+            487,
+            82,
+            1872,
+            276,
+            330,
+            245,
+            2624,
+            12,
+            73309,
+            279,
+            254,
+            1843,
+        ],
+        "The future of AI is bright, and it’s going to be a game-changer in the world",
+    ),
+]
+
+
+@pytest.mark.parametrize("model", MODELS)
+@pytest.mark.parametrize("tp_size", TENSOR_PARALLELS)
+@pytest.mark.parametrize("pp_size", PIPELINE_PARALLELS)
+@pytest.mark.parametrize("distributed_executor_backend", DIST_EXECUTOR_BACKEND)
+@wait_until_npu_memory_free(target_free_percentage=0.6)
+def test_models_pp2_tp2(model: str, tp_size: int, pp_size: int, distributed_executor_backend: str) -> None:
+    with VllmRunner(
+        model,
+        tensor_parallel_size=tp_size,
+        pipeline_parallel_size=pp_size,
+        compilation_config={
+            "cudagraph_mode": "PIECEWISE",
+            "cudagraph_capture_sizes": [1, 2, 4],
+        },
+        distributed_executor_backend=distributed_executor_backend,
+        gpu_memory_utilization=0.7,
+        enable_expert_parallel=model in MOE_MODELS,
+    ) as vllm_model:
+        outputs = vllm_model.generate_greedy(prompts, 16)
+        check_outputs_equal(
+            outputs_0_lst=outputs,
+            outputs_1_lst=GOLDEN,
+            name_0=f"{model}-tp{tp_size}pp{pp_size}",
+            name_1="GOLDEN",
+        )
+
+
+@pytest.mark.parametrize("model", MODELS)
+@pytest.mark.parametrize("dp_size", DATA_PARALLELS)
+@pytest.mark.parametrize("pp_size", PIPELINE_PARALLELS)
+@pytest.mark.parametrize("distributed_executor_backend", DIST_EXECUTOR_BACKEND)
+@wait_until_npu_memory_free(target_free_percentage=0.6)
+def test_models_pp2_dp2(model: str, dp_size: int, pp_size: int, distributed_executor_backend: str) -> None:
+    with DPVllmRunner(
+        model,
+        data_parallel_size=dp_size,
+        pipeline_parallel_size=pp_size,
+        compilation_config={
+            "cudagraph_mode": "PIECEWISE",
+            "cudagraph_capture_sizes": [1, 2, 4],
+        },
+        distributed_executor_backend=distributed_executor_backend,
+        gpu_memory_utilization=0.7,
+        enable_expert_parallel=model in MOE_MODELS,
+    ) as vllm_model:
+        outputs = vllm_model.generate_greedy(prompts, 16)
+        check_outputs_equal(
+            outputs_0_lst=outputs,
+            outputs_1_lst=GOLDEN,
+            name_0=f"{model}-dp{dp_size}pp{pp_size}",
+            name_1="GOLDEN",
+        )