init v0.23.0

Signed-off-by: Sun Ruoxi <sunruoxi@4paradigm.com>

tests/e2e/pull_request/one_card/test_camem.py

@@ -0,0 +1,57 @@
+#
+# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
+# This file is a part of the vllm-ascend project.
+# Adapted from vllm/tests/basic_correctness/test_basic_correctness.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 os
+from unittest.mock import patch
+
+import torch
+from vllm import SamplingParams
+from vllm.utils.mem_constants import GiB_bytes
+
+from tests.e2e.conftest import VllmRunner
+from tests.e2e.utils import fork_new_process_for_each_test
+
+
+@fork_new_process_for_each_test
+@patch.dict(os.environ, {"VLLM_ASCEND_ENABLE_NZ": "0"})
+def test_end_to_end():
+    free, total = torch.npu.mem_get_info()
+    used_bytes_baseline = total - free  # in case other process is running
+
+    prompt = "How are you?"
+    sampling_params = SamplingParams(temperature=0, max_tokens=10)
+
+    with VllmRunner("Qwen/Qwen3-0.6B", enable_sleep_mode=True, cudagraph_capture_sizes=[1, 2, 4, 8]) as runner:
+        output = runner.model.generate(prompt, sampling_params)
+        # the benefit of `llm.sleep(level=2)` is mainly CPU memory usage,
+        # which is difficult to measure in the test. therefore, we only
+        # test sleep level 1 here.
+        runner.model.sleep(level=1)
+
+        free_gpu_bytes_after_sleep, total = torch.npu.mem_get_info()
+        used_bytes = total - free_gpu_bytes_after_sleep - used_bytes_baseline
+        # now the memory usage should be less than the model weights
+        # (0.5B model, 1GiB weights)
+        assert used_bytes < 1 * GiB_bytes
+
+        runner.model.wake_up()
+        output2 = runner.model.generate(prompt, sampling_params)
+
+    # cmp output
+    assert output[0].outputs[0].text == output2[0].outputs[0].text