[Build] Add build info (#1386)

wangxiyuan · web-flow · commit 5968dff4e000 · 2025-06-27T09:14:43.000+08:00
Add static build_info py file to show soc and sleep mode info. It helps
to make the code clean and the error info will be more friendly for
users

This PR also added the unit test for vllm_ascend/utils.py

This PR also added the base test class for all ut in tests/ut/base.py

Signed-off-by: wangxiyuan &lt;wangxiyuan1007@gmail.com&gt;
diff --git a/.gitignore b/.gitignore
@@ -196,3 +196,5 @@ kernel_meta/
 
 # version file generated by setuptools-scm
 /vllm_ascend/_version.py
+# build info file generated by setup.py
+/vllm_ascend/_build_info.py
diff --git a/setup.py b/setup.py
@@ -27,6 +27,7 @@
 
 from setuptools import Extension, find_packages, setup
 from setuptools.command.build_ext import build_ext
+from setuptools.command.build_py import build_py
 from setuptools.command.develop import develop
 from setuptools.command.install import install
 from setuptools_scm import get_version
@@ -78,6 +79,30 @@ def __init__(self,
         self.cmake_lists_dir = os.path.abspath(cmake_lists_dir)
 
 
+class custom_build_info(build_py):
+
+    def run(self):
+        soc_version = envs.SOC_VERSION
+        if not soc_version:
+            raise ValueError(
+                "SOC version is not set. Please set SOC_VERSION environment variable."
+            )
+        if "310" in soc_version and not envs.COMPILE_CUSTOM_KERNELS:
+            raise ValueError(
+                "SOC version 310 only supports custom kernels. Please set COMPILE_CUSTOM_KERNELS=1 to enable custom kernels."
+            )
+
+        package_dir = os.path.join(ROOT_DIR, "vllm_ascend", "_build_info.py")
+        with open(package_dir, "w+") as f:
+            f.write('# Auto-generated file\n')
+            f.write(f"__soc_version__ = '{soc_version}'\n")
+            f.write(
+                f"__sleep_mode_enabled__ = {envs.COMPILE_CUSTOM_KERNELS}\n")
+        logging.info(
+            f"Generated _build_info.py with SOC version: {soc_version}")
+        super().run()
+
+
 class cmake_build_ext(build_ext):
     # A dict of extension directories that have been configured.
     did_config: Dict[str, bool] = {}
@@ -326,7 +351,11 @@ def _read_requirements(filename: str) -> List[str]:
     return requirements
 
 
-cmdclass = {"build_ext": cmake_build_ext, "install": custom_install}
+cmdclass = {
+    "build_py": custom_build_info,
+    "build_ext": cmake_build_ext,
+    "install": custom_install
+}
 
 setup(
     name="vllm_ascend",
diff --git a/tests/ut/base.py b/tests/ut/base.py
@@ -0,0 +1,12 @@
+import unittest
+
+from vllm_ascend.utils import adapt_patch
+
+
+class TestBase(unittest.TestCase):
+
+    def setUp(self):
+        # adapt patch by default.
+        adapt_patch(True)
+        adapt_patch()
+        super().setUp()
diff --git a/tests/ut/patch/worker/patch_common/test_patch_distributed.py b/tests/ut/patch/worker/patch_common/test_patch_distributed.py
@@ -0,0 +1,12 @@
+from tests.ut.base import TestBase
+
+
+class TestPatchDistributed(TestBase):
+
+    def test_GroupCoordinator_patched(self):
+        from vllm.distributed.parallel_state import GroupCoordinator
+
+        from vllm_ascend.patch.worker.patch_common.patch_distributed import \
+            GroupCoordinatorPatch
+
+        self.assertIs(GroupCoordinator, GroupCoordinatorPatch)
diff --git a/tests/ut/patch/worker/patch_common/test_patch_sampler.py b/tests/ut/patch/worker/patch_common/test_patch_sampler.py
diff --git a/tests/ut/test_utils.py b/tests/ut/test_utils.py
@@ -0,0 +1,251 @@
+import math
+import os
+import unittest
+from threading import Lock
+from unittest import mock
+
+import torch
+from vllm.config import (CompilationConfig, ModelConfig, ParallelConfig,
+                         VllmConfig)
+
+from vllm_ascend import utils
+
+
+class TestUtils(unittest.TestCase):
+
+    def test_is_310p(self):
+        utils._IS_310P = None
+        with mock.patch("vllm_ascend._build_info.__soc_version__",
+                        "Ascend310P3"):
+            self.assertTrue(utils.is_310p())
+        utils._IS_310P = None
+        with mock.patch("vllm_ascend._build_info.__soc_version__",
+                        "Ascend910P1"):
+            self.assertFalse(utils.is_310p())
+
+    def test_sleep_mode_enabled(self):
+        utils._SLEEP_MODE_ENABLED = None
+        with mock.patch("vllm_ascend._build_info.__sleep_mode_enabled__",
+                        True):
+            self.assertTrue(utils.sleep_mode_enabled())
+        utils._SLEEP_MODE_ENABLED = None
+        with mock.patch("vllm_ascend._build_info.__sleep_mode_enabled__",
+                        False):
+            self.assertFalse(utils.sleep_mode_enabled())
+
+    def test_nd_to_nz_2d(self):
+        # can be divided by 16
+        input_tensor = torch.randn(32, 64)
+        output = utils.nd_to_nz_2d(input_tensor)
+        self.assertEqual(output.shape[0], 1)
+        self.assertEqual(output.shape[1], 64 // 16)
+        self.assertEqual(output.shape[2], 32)
+        self.assertEqual(output.shape[3], 16)
+
+        # cannot be divided by 16
+        input_tensor = torch.randn(30, 62)
+        output = utils.nd_to_nz_2d(input_tensor)
+        self.assertEqual(output.shape[0], 1)
+        self.assertEqual(output.shape[1], math.ceil(62 / 16))
+        self.assertEqual(output.shape[2], 32)
+        self.assertEqual(output.shape[3], 16)
+
+        # pad to 16
+        input_tensor = torch.randn(8, 12)
+        output = utils.nd_to_nz_2d(input_tensor)
+        self.assertEqual(output.shape[0], 1)
+        self.assertEqual(output.shape[1], 1)  # 12->16, 16//16=1
+        self.assertEqual(output.shape[2], 16)  # 8->16
+        self.assertEqual(output.shape[3], 16)
+
+        # check if the output is contiguous
+        input_tensor = torch.randn(32, 64)
+        output = utils.nd_to_nz_2d(input_tensor)
+        self.assertTrue(output.is_contiguous())
+
+        # check if the output values are preserved
+        input_tensor = torch.tensor([[1, 2, 3, 4], [5, 6, 7, 8]])
+        output = utils.nd_to_nz_2d(input_tensor)
+        expected = torch.tensor(
+            [[[[1, 2, 3, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+               [5, 6, 7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+               [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+               [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+               [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+               [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+               [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+               [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+               [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+               [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+               [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+               [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+               [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+               [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+               [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+               [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]]])
+        self.assertTrue(torch.allclose(output, expected))
+
+    def test_aligned_16(self):
+        # align to 16
+        input_tensor = torch.randn(15, 64)
+        output_tensor = utils.aligned_16(input_tensor)
+        self.assertEqual(output_tensor.shape[0], 16)
+
+        # align to 16
+        input_tensor = torch.randn(16, 64)
+        output_tensor = utils.aligned_16(input_tensor)
+        self.assertEqual(output_tensor.shape[0], 16)
+        self.assertTrue(torch.equal(input_tensor, output_tensor))
+
+        # align to 32
+        input_tensor = torch.randn(17, 64)
+        output_tensor = utils.aligned_16(input_tensor)
+        self.assertEqual(output_tensor.shape[0], 32)
+
+    @mock.patch('importlib.util.find_spec')
+    @mock.patch('importlib.import_module')
+    def test_try_register_lib(self, mock_import_module, mock_find_spec):
+        # import OK
+        mock_find_spec.return_value = mock.MagicMock()
+        mock_import_module.return_value = mock.MagicMock()
+        lib_name = "existing_lib"
+        lib_info = "Library found and imported successfully"
+        utils.try_register_lib(lib_name, lib_info)
+        mock_find_spec.assert_called_once_with(lib_name)
+        mock_import_module.assert_called_once_with(lib_name)
+
+        # Can't find lib
+        mock_find_spec.return_value = None
+        lib_name = "non_existing_lib"
+        utils.try_register_lib(lib_name)
+        self.assertEqual(2, mock_find_spec.call_count)
+        self.assertEqual(1, mock_import_module.call_count)
+
+        # import error
+        mock_find_spec.return_value = mock.MagicMock()
+        mock_import_module.side_effect = ImportError("import error")
+        lib_name = "error_lib"
+        utils.try_register_lib(lib_name)
+        self.assertEqual(3, mock_find_spec.call_count)
+        self.assertEqual(2, mock_import_module.call_count)
+
+    def test_enable_custom_op(self):
+        result = utils.enable_custom_op()
+        self.assertTrue(result)
+
+        utils._CUSTOM_OP_ENABLED = None
+
+        with mock.patch('builtins.__import__') as mock_import_module:
+            mock_import_module.side_effect = ImportError("import error")
+            self.assertFalse(utils.enable_custom_op())
+
+    def test_find_hccl_library(self):
+        with mock.patch.dict(os.environ,
+                             {"HCCL_SO_PATH": "/path/to/hccl/libhccl.so"}):
+            self.assertEqual(utils.find_hccl_library(),
+                             "/path/to/hccl/libhccl.so")
+        with mock.patch("torch.version.cann", None):
+            self.assertRaises(ValueError, utils.find_hccl_library)
+        with mock.patch("torch.version.cann", "Ascend910"):
+            self.assertEqual(utils.find_hccl_library(), "libhccl.so")
+
+    def test_current_stream(self):
+        with mock.patch("torch.npu.current_stream") as mock_current_stream:
+            self.assertEqual(utils.current_stream(), mock_current_stream())
+
+    def test_vllm_version_is(self):
+        with mock.patch.dict(os.environ, {"VLLM_VERSION": "1.0.0"}):
+            with mock.patch("vllm.__version__", "1.0.0"):
+                self.assertTrue(utils.vllm_version_is("1.0.0"))
+                self.assertFalse(utils.vllm_version_is("2.0.0"))
+            with mock.patch("vllm.__version__", "2.0.0"):
+                self.assertTrue(utils.vllm_version_is("1.0.0"))
+                self.assertFalse(utils.vllm_version_is("2.0.0"))
+        with mock.patch("vllm.__version__", "1.0.0"):
+            self.assertTrue(utils.vllm_version_is("1.0.0"))
+            self.assertFalse(utils.vllm_version_is("2.0.0"))
+        with mock.patch("vllm.__version__", "2.0.0"):
+            self.assertTrue(utils.vllm_version_is("2.0.0"))
+            self.assertFalse(utils.vllm_version_is("1.0.0"))
+
+    def test_update_aclgraph_sizes(self):
+        # max_num_batch_sizes < len(original_sizes)
+        test_compilation_config = CompilationConfig(
+            cudagraph_capture_sizes=[i for i in range(150)])
+        model_path = os.path.join(os.path.dirname(__file__), "fake_weight")
+        test_model_config = ModelConfig(model=model_path, enforce_eager=True)
+        test_parallel_config = ParallelConfig()
+        test_vllm_config = VllmConfig(
+            model_config=test_model_config,
+            compilation_config=test_compilation_config,
+            parallel_config=test_parallel_config,
+        )
+        utils.update_aclgraph_sizes(test_vllm_config)
+        self.assertEqual(
+            147,
+            len(test_vllm_config.compilation_config.cudagraph_capture_sizes))
+        # max_num_batch_sizes >= len(original_sizes)
+        test_compilation_config = CompilationConfig(
+            cudagraph_capture_sizes=[1, 2, 3])
+        test_vllm_config = VllmConfig(
+            model_config=test_model_config,
+            compilation_config=test_compilation_config,
+            parallel_config=test_parallel_config,
+        )
+        utils.update_aclgraph_sizes(test_vllm_config)
+        self.assertEqual(
+            3,
+            len(test_vllm_config.compilation_config.cudagraph_capture_sizes))
+
+
+class TestProfileExecuteDuration(unittest.TestCase):
+
+    def setUp(self):
+        utils.ProfileExecuteDuration._instance = None
+        utils.ProfileExecuteDuration._observations = []
+        utils.ProfileExecuteDuration._lock = Lock()
+
+    def test_singleton_creation(self):
+        instance1 = utils.ProfileExecuteDuration()
+        self.assertIsNotNone(instance1)
+        self.assertIs(instance1, utils.ProfileExecuteDuration._instance)
+
+        instance2 = utils.ProfileExecuteDuration()
+        self.assertIs(instance1, instance2)
+
+    def test_thread_safety(self):
+        from threading import Thread
+
+        instances = []
+
+        def create_instance():
+            instances.append(utils.ProfileExecuteDuration())
+
+        threads = [Thread(target=create_instance) for _ in range(10)]
+        for t in threads:
+            t.start()
+        for t in threads:
+            t.join()
+
+        first_instance = instances[0]
+        for instance in instances[1:]:
+            self.assertIs(first_instance, instance)
+
+    def test_atexit_registration(self):
+        with mock.patch('atexit.register') as mock_register:
+            instance = utils.ProfileExecuteDuration()
+            mock_register.assert_called_once_with(instance.destroy)
+
+    def test_lock_usage(self):
+        original_lock = utils.ProfileExecuteDuration._lock
+
+        with mock.patch.object(utils.ProfileExecuteDuration,
+                               '_lock',
+                               wraps=original_lock) as mock_lock:
+            utils.ProfileExecuteDuration()
+            mock_lock.__enter__.assert_called()
+            mock_lock.__exit__.assert_called()
+
+    def test_observations_initialization(self):
+        instance = utils.ProfileExecuteDuration()
+        self.assertEqual(instance._observations, [])
diff --git a/vllm_ascend/device_allocator/camem.py b/vllm_ascend/device_allocator/camem.py
@@ -138,7 +138,6 @@ def get_instance() -> "CaMemAllocator":
         We cannot call the constructor directly.
         Call this method to get the instance.
         """
-        assert camem_available, "camem allocator is not available"
         if CaMemAllocator.instance is None:
             CaMemAllocator.instance = CaMemAllocator()
         return CaMemAllocator.instance
diff --git a/vllm_ascend/ops/fused_moe.py b/vllm_ascend/ops/fused_moe.py
@@ -155,7 +155,6 @@ def fused_experts_with_mc2(
     kwargs_mc2.update(stage1_kwargs)
 
     output = torch_npu.npu_moe_distribute_dispatch(**kwargs_mc2)
-    # comm_stream.wait_stream(torch.npu.current_stream())
     expand_x, dynamic_scale, expand_idx, expert_token_nums, ep_recv_counts = output[
         0:5]
 
diff --git a/vllm_ascend/patch/platform/patch_common/patch_distributed.py b/vllm_ascend/patch/platform/patch_common/patch_distributed.py
@@ -23,7 +23,7 @@
 import vllm.envs as envs
 from vllm.config import ParallelConfig
 
-from vllm_ascend.utils import NullHandle, is_310p
+from vllm_ascend.utils import is_310p
 
 
 def ascend_destroy_model_parallel():
@@ -66,6 +66,15 @@ def parallel_config_get_dp_port(self) -> int:
 ParallelConfig.get_next_dp_init_port = parallel_config_get_dp_port
 
 
+class NullHandle:
+
+    def __init__(self):
+        pass
+
+    def wait(self):
+        pass
+
+
 def communication_adaptation_310p():
 
     def broadcast310p(tensor, src, group=None, async_op=False):
diff --git a/vllm_ascend/utils.py b/vllm_ascend/utils.py
diff --git a/vllm_ascend/worker/worker_v1.py b/vllm_ascend/worker/worker_v1.py
