Minor updates

Author: yinggeh

ci/L0_backend_vllm/metrics_test/vllm_metrics_test.py

@@ -70,46 +70,17 @@ def get_metrics(self):
 
         return vllm_dict
 
-    def test_vllm_metrics(self):
-        # All vLLM metrics from tritonserver
-        expected_metrics_dict = {
-            "vllm:prompt_tokens_total": 0,
-            "vllm:generation_tokens_total": 0,
-        }
-
-        # Test vLLM metrics
-        self._test_vllm_model(
-            prompts=self.prompts,
-            sampling_parameters=self.sampling_parameters,
-            stream=False,
-            send_parameters_as_tensor=True,
-            model_name=self.vllm_model_name,
-        )
-        expected_metrics_dict["vllm:prompt_tokens_total"] = 18
-        expected_metrics_dict["vllm:generation_tokens_total"] = 48
-        self.assertEqual(self.get_metrics(), expected_metrics_dict)
-
-        self._test_vllm_model(
-            prompts=self.prompts,
-            sampling_parameters=self.sampling_parameters,
-            stream=False,
-            send_parameters_as_tensor=False,
-            model_name=self.vllm_model_name,
-        )
-        expected_metrics_dict["vllm:prompt_tokens_total"] = 36
-        expected_metrics_dict["vllm:generation_tokens_total"] = 96
-        self.assertEqual(self.get_metrics(), expected_metrics_dict)
-
-    def _test_vllm_model(
+    def vllm_async_stream_infer(
         self,
         prompts,
         sampling_parameters,
         stream,
         send_parameters_as_tensor,
-        exclude_input_in_output=None,
-        expected_output=None,
-        model_name="vllm_opt",
+        model_name,
     ):
+        """
+        Helper function to send async stream infer requests to vLLM.
+        """
         user_data = UserData()
         number_of_vllm_reqs = len(prompts)
 
@@ -122,7 +93,6 @@ def _test_vllm_model(
                 sampling_parameters,
                 model_name,
                 send_parameters_as_tensor,
-                exclude_input_in_output=exclude_input_in_output,
             )
             self.triton_client.async_stream_infer(
                 model_name=model_name,
@@ -132,26 +102,47 @@ def _test_vllm_model(
                 parameters=sampling_parameters,
             )
 
-        for i in range(number_of_vllm_reqs):
+        for _ in range(number_of_vllm_reqs):
             result = user_data._completed_requests.get()
             if type(result) is InferenceServerException:
                 print(result.message())
             self.assertIsNot(type(result), InferenceServerException, str(result))
 
             output = result.as_numpy("text_output")
             self.assertIsNotNone(output, "`text_output` should not be None")
-            if expected_output is not None:
-                self.assertEqual(
-                    output,
-                    expected_output[i],
-                    'Actual and expected outputs do not match.\n \
-                                  Expected "{}" \n Actual:"{}"'.format(
-                        output, expected_output[i]
-                    ),
-                )
 
         self.triton_client.stop_stream()
 
+    def test_vllm_metrics(self):
+        # All vLLM metrics from tritonserver
+        expected_metrics_dict = {
+            "vllm:prompt_tokens_total": 0,
+            "vllm:generation_tokens_total": 0,
+        }
+
+        # Test vLLM metrics
+        self.vllm_async_stream_infer(
+            prompts=self.prompts,
+            sampling_parameters=self.sampling_parameters,
+            stream=False,
+            send_parameters_as_tensor=True,
+            model_name=self.vllm_model_name,
+        )
+        expected_metrics_dict["vllm:prompt_tokens_total"] = 18
+        expected_metrics_dict["vllm:generation_tokens_total"] = 48
+        self.assertEqual(self.get_metrics(), expected_metrics_dict)
+
+        self.vllm_async_stream_infer(
+            prompts=self.prompts,
+            sampling_parameters=self.sampling_parameters,
+            stream=False,
+            send_parameters_as_tensor=False,
+            model_name=self.vllm_model_name,
+        )
+        expected_metrics_dict["vllm:prompt_tokens_total"] = 36
+        expected_metrics_dict["vllm:generation_tokens_total"] = 96
+        self.assertEqual(self.get_metrics(), expected_metrics_dict)
+
     def tearDown(self):
         self.triton_client.close()