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/one_card/test_sampler.py
+++ b/tests/e2e/pull_request/one_card/test_sampler.py
@@ -0,0 +1,105 @@
+#
+# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
+# This file is a part of the vllm-ascend project.
+# Adapted from vllm/tests/entrypoints/llm/test_guided_generate.py
+# 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.
+#
+import gc
+import os
+
+import pytest
+import torch
+from vllm import LLM, SamplingParams
+
+from tests.e2e.conftest import ModelName, cleanup_dist_env_and_memory, model_cache
+
+os.environ["VLLM_BATCH_INVARIANT"] = "1"
+
+
+@pytest.mark.timeout(1000)
+@pytest.mark.model(
+    model_name=ModelName.QWEN3_06B,
+    quantization=None,
+    max_model_len=8192,
+    dtype="bfloat16",
+    gpu_memory_utilization=0.9,
+    enable_prefix_caching=False,
+    max_num_seqs=32,
+    tensor_parallel_size=1,
+    distributed_executor_backend="mp",
+    compilation_config={"cudagraph_mode": "FULL_DECODE_ONLY", "cudagraph_capture_sizes": [1, 32, 64]},
+)
+def test_qwen3_topk(vllm_runner) -> None:
+    example_prompts = [
+        "Hello, my name is",
+    ]
+    sampling_params = SamplingParams(max_tokens=5, temperature=0.0, top_k=50, top_p=0.9)
+    vllm_runner.generate(example_prompts, sampling_params)
+
+
+@pytest.mark.timeout(1000)
+@pytest.mark.model(
+    model_name=ModelName.QWEN3_06B,
+    quantization=None,
+    max_model_len=8192,
+    dtype="bfloat16",
+    gpu_memory_utilization=0.9,
+    enable_prefix_caching=False,
+    max_num_seqs=32,
+    tensor_parallel_size=1,
+    distributed_executor_backend="mp",
+    compilation_config={"cudagraph_mode": "FULL_DECODE_ONLY", "cudagraph_capture_sizes": [1, 32, 64]},
+)
+def test_qwen3_prompt_logprobs(vllm_runner) -> None:
+    example_prompts = [
+        "Hello, my name is",
+    ]
+    vllm_runner.generate_greedy_logprobs(example_prompts, max_tokens=5, num_logprobs=1)
+
+
+@pytest.mark.timeout(1000)
+def test_qwen3_exponential_overlap(monkeypatch: pytest.MonkeyPatch) -> None:
+    # enable_async_exponential is mutually exclusive with VLLM_BATCH_INVARIANT
+    # (see vllm_ascend/ascend_config.py). The module-level os.environ setting
+    # would silently disable async_exponential, so this test creates its own
+    # LLM instance with batch invariant mode turned off.
+    model_cache.clear()
+    gc.collect()
+    torch.npu.empty_cache()
+
+    monkeypatch.setenv("VLLM_BATCH_INVARIANT", "0")
+
+    llm = LLM(
+        model=ModelName.QWEN3_06B,
+        quantization=None,
+        max_model_len=8192,
+        dtype="bfloat16",
+        gpu_memory_utilization=0.9,
+        enable_prefix_caching=False,
+        max_num_seqs=32,
+        tensor_parallel_size=1,
+        distributed_executor_backend="mp",
+        compilation_config={"cudagraph_mode": "FULL_DECODE_ONLY", "cudagraph_capture_sizes": [1, 2, 4, 8]},
+        additional_config={"enable_async_exponential": True},
+    )
+
+    example_prompts = [
+        "Hello, my name is",
+    ]
+    sampling_params = SamplingParams(max_tokens=5, temperature=1.0, top_k=50, top_p=0.9)
+    llm.generate(example_prompts, sampling_params)
+
+    del llm
+    cleanup_dist_env_and_memory()