[CI] enable custom ops build (#466)

### What this PR does / why we need it?
This PR enable custom ops build  by default. 

### Does this PR introduce _any_ user-facing change?

Yes, users now install vllm-ascend from source will trigger custom ops
build step.

### How was this patch tested?
By image build and e2e CI

---------

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>

tests/singlecard/test_offline_inference.py

@@ -0,0 +1,58 @@
+#
+# 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.
+#
+"""Compare the short outputs of HF and vLLM when using greedy sampling.
+
+Run `pytest tests/test_offline_inference.py`.
+"""
+import os
+
+import pytest
+import vllm  # noqa: F401
+from conftest import VllmRunner
+
+import vllm_ascend  # noqa: F401
+
+MODELS = [
+    "Qwen/Qwen2.5-0.5B-Instruct",
+]
+os.environ["PYTORCH_NPU_ALLOC_CONF"] = "max_split_size_mb:256"
+
+
+@pytest.mark.parametrize("model", MODELS)
+@pytest.mark.parametrize("dtype", ["half", "float16"])
+@pytest.mark.parametrize("max_tokens", [5])
+def test_models(model: str, dtype: str, max_tokens: int) -> None:
+    # 5042 tokens for gemma2
+    # gemma2 has alternating sliding window size of 4096
+    # we need a prompt with more than 4096 tokens to test the sliding window
+    prompt = "The following numbers of the sequence " + ", ".join(
+        str(i) for i in range(1024)) + " are:"
+    example_prompts = [prompt]
+
+    with VllmRunner(model,
+                    max_model_len=8192,
+                    dtype=dtype,
+                    enforce_eager=False,
+                    gpu_memory_utilization=0.7) as vllm_model:
+        vllm_model.generate_greedy(example_prompts, max_tokens)
+
+
+if __name__ == "__main__":
+    import pytest
+    pytest.main([__file__])