Fix up

qa/L0_device_memory_tracker/test.py

@@ -27,18 +27,39 @@
 
 import unittest
 import time
+from functools import partial
 
-import tritonclient.http as tritonclient
+import tritonclient.http as httpclient
+import tritonclient.grpc as grpcclient
 
 import nvidia_smi
 
 
+class UnifiedClientProxy:
+
+    def __init__(self, client):
+        self.client_ = client
+
+    def __getattr__(self, attr):
+        forward_attr = getattr(self.client_, attr)
+        if type(self.client_) == grpcclient.InferenceServerClient:
+            if attr == "get_model_config":
+                return lambda *args, **kwargs: forward_attr(
+                    *args, **kwargs, as_json=True)["config"]
+            elif attr == "get_inference_statistics":
+                return partial(forward_attr, as_json=True)
+        return forward_attr
+
+
 class MemoryUsageTest(unittest.TestCase):
 
     def setUp(self):
         nvidia_smi.nvmlInit()
         self.gpu_handle_ = nvidia_smi.nvmlDeviceGetHandleByIndex(0)
-        self.client_ = tritonclient.InferenceServerClient(url="localhost:8000")
+        self.http_client_ = httpclient.InferenceServerClient(
+            url="localhost:8000")
+        self.grpc_client_ = grpcclient.InferenceServerClient(
+            url="localhost:8001")
 
     def tearDown(self):
         nvidia_smi.nvmlShutdown()
@@ -55,7 +76,7 @@ def verify_recorded_usage(self, model_stat):
         recorded_gpu_usage = 0
         for usage in model_stat["memory_usage"]:
             if usage["type"] == "GPU":
-                recorded_gpu_usage += usage["byte_size"]
+                recorded_gpu_usage += int(usage["byte_size"])
         # unload and verify recorded usage
         before_total_usage = self.report_used_gpu_memory()
         self.client_.unload_model(model_stat["name"])
@@ -71,13 +92,15 @@ def verify_recorded_usage(self, model_stat):
             .format(model_stat["name"], usage_delta * 0.9, usage_delta * 1.1,
                     recorded_gpu_usage))
 
-    def test_onnx(self):
+    def test_onnx_http(self):
+        self.client_ = UnifiedClientProxy(self.http_client_)
         model_stats = self.client_.get_inference_statistics()["model_stats"]
         for model_stat in model_stats:
             if self.is_testing_backend(model_stat["name"], "onnxruntime"):
                 self.verify_recorded_usage(model_stat)
 
-    def test_plan(self):
+    def test_plan_grpc(self):
+        self.client_ = UnifiedClientProxy(self.grpc_client_)
         model_stats = self.client_.get_inference_statistics()["model_stats"]
         for model_stat in model_stats:
             if self.is_testing_backend(model_stat["name"], "tensorrt"):