init v0.11.0rc0

tests/ut/eplb/adaptor/test_abstract_adaptor.py

@@ -0,0 +1,73 @@
+import pytest
+
+from vllm_ascend.eplb.adaptor.abstract_adaptor import EplbAdaptor
+
+
+class DummyAdaptor(EplbAdaptor):
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self.args = kwargs
+
+    def get_rank_expert_workload(self):
+        return "workload"
+
+    def get_init_expert_map(self, num_moe_layers):
+        return {"layers": num_moe_layers}
+
+    def do_update_expert_map(self, layer_id, updated_expert_map):
+        return {"layer_id": layer_id, "map": updated_expert_map}
+
+    def do_update_expert_weight(self, layer_id, local_expert_to_replace,
+                                buffer_tensor_id):
+        return {
+            "layer_id": layer_id,
+            "replace": local_expert_to_replace,
+            "buffer": buffer_tensor_id,
+        }
+
+
+def test_base_class_methods_raise():
+    adaptor = EplbAdaptor()
+    with pytest.raises(NotImplementedError):
+        adaptor.get_rank_expert_workload()
+    with pytest.raises(NotImplementedError):
+        adaptor.get_init_expert_map(1)
+    with pytest.raises(NotImplementedError):
+        adaptor.do_update_expert_map(1, {})
+    with pytest.raises(NotImplementedError):
+        adaptor.do_update_expert_weight(1, "x", "y")
+
+
+def test_dummy_adaptor_init_and_args():
+    adaptor = DummyAdaptor(test_arg=123)
+    assert adaptor.args["test_arg"] == 123
+
+
+def test_get_rank_expert_workload():
+    adaptor = DummyAdaptor()
+    result = adaptor.get_rank_expert_workload()
+    assert result == "workload"
+
+
+def test_get_init_expert_map():
+    adaptor = DummyAdaptor()
+    result = adaptor.get_init_expert_map(5)
+    assert isinstance(result, dict)
+    assert result["layers"] == 5
+
+
+def test_do_update_expert_map():
+    adaptor = DummyAdaptor()
+    updated = {"expert": 1}
+    result = adaptor.do_update_expert_map(2, updated)
+    assert result["layer_id"] == 2
+    assert result["map"] == updated
+
+
+def test_do_update_expert_weight():
+    adaptor = DummyAdaptor()
+    result = adaptor.do_update_expert_weight(1, "expertA", "bufferX")
+    assert result["layer_id"] == 1
+    assert result["replace"] == "expertA"
+    assert result["buffer"] == "bufferX"