Add exclude_input_in_output option to vllm backend

ci/L0_backend_vllm/enabled_stream/enabled_stream_test.py

@@ -34,37 +34,118 @@
 sys.path.append("../../common")
 from test_util import AsyncTestResultCollector, create_vllm_request
 
+PROMPTS = ["The most dangerous animal is"]
+SAMPLING_PARAMETERS = {"temperature": "0", "top_p": "1"}
+
 
 class VLLMTritonStreamTest(AsyncTestResultCollector):
-    async def test_vllm_model_enabled_stream(self):
+    async def _test_vllm_model(
+        self,
+        prompts=PROMPTS,
+        sampling_parameters=SAMPLING_PARAMETERS,
+        stream=True,
+        exclude_input_in_output=None,
+        expected_output=None,
+    ):
         async with grpcclient.InferenceServerClient(
             url="localhost:8001"
         ) as triton_client:
             model_name = "vllm_opt"
-            stream = True
-            prompts = [
-                "The most dangerous animal is",
-                "The future of AI is",
-            ]
-            sampling_parameters = {"temperature": "0", "top_p": "1"}
 
             async def request_iterator():
                 for i, prompt in enumerate(prompts):
                     yield create_vllm_request(
-                        prompt, i, stream, sampling_parameters, model_name
+                        prompt,
+                        i,
+                        stream,
+                        sampling_parameters,
+                        model_name,
+                        exclude_input_in_output=exclude_input_in_output,
                     )
 
             response_iterator = triton_client.stream_infer(
                 inputs_iterator=request_iterator()
             )
-
+            final_response = []
             async for response in response_iterator:
                 result, error = response
-                self.assertIsNone(error, str(error))
-                self.assertIsNotNone(result, str(result))
-
+                self.assertIsNone(error, error)
+                self.assertIsNotNone(result, result)
                 output = result.as_numpy("text_output")
                 self.assertIsNotNone(output, "`text_output` should not be None")
+                final_response.append(str(output[0], encoding="utf-8"))
+            if expected_output is not None:
+                self.assertEqual(
+                    final_response,
+                    expected_output,
+                    'Expected to receive the following response: "{}",\
+                    but received "{}".'.format(
+                        expected_output, final_response
+                    ),
+                )
+
+    async def test_vllm_model_enabled_stream(self):
+        """
+        Verifying that request with multiple prompts runs successfully.
+        """
+        prompts = [
+            "The most dangerous animal is",
+            "The future of AI is",
+        ]
+
+        await self._test_vllm_model(prompts=prompts)
+
+    async def test_vllm_model_enabled_stream_exclude_input_in_output_default(self):
+        """
+        Verifying that streaming request returns only generated diffs, which
+        is default behaviour for `stream=True`.
+        """
+        expected_output = [
+            " the",
+            " one",
+            " that",
+            " is",
+            " most",
+            " likely",
+            " to",
+            " be",
+            " killed",
+            " by",
+            " a",
+            " car",
+            ".",
+            "\n",
+            "I",
+            "'m",
+        ]
+        await self._test_vllm_model(expected_output=expected_output)
+
+    async def test_vllm_model_enabled_stream_exclude_input_in_output_false(self):
+        """
+        Verifying that streaming request returns only generated diffs even if
+        `exclude_input_in_output` is set to False explicitly.
+        """
+        expected_output = [
+            " the",
+            " one",
+            " that",
+            " is",
+            " most",
+            " likely",
+            " to",
+            " be",
+            " killed",
+            " by",
+            " a",
+            " car",
+            ".",
+            "\n",
+            "I",
+            "'m",
+        ]
+        await self._test_vllm_model(
+            exclude_input_in_output=False, expected_output=expected_output
+        )
 
 
 if __name__ == "__main__":

ci/L0_backend_vllm/enabled_stream/test.sh

@@ -36,7 +36,7 @@ CLIENT_LOG="./enabled_stream_client.log"
 TEST_RESULT_FILE='test_results.txt'
 CLIENT_PY="./enabled_stream_test.py"
 SAMPLE_MODELS_REPO="../../../samples/model_repository"
-EXPECTED_NUM_TESTS=1
+EXPECTED_NUM_TESTS=3
 
 rm -rf models && mkdir -p models
 cp -r ${SAMPLE_MODELS_REPO}/vllm_model models/vllm_opt

ci/L0_backend_vllm/vllm_backend/test.sh

@@ -36,7 +36,7 @@ CLIENT_LOG="./vllm_backend_client.log"
 TEST_RESULT_FILE='test_results.txt'
 CLIENT_PY="./vllm_backend_test.py"
 SAMPLE_MODELS_REPO="../../../samples/model_repository"
-EXPECTED_NUM_TESTS=3
+EXPECTED_NUM_TESTS=6
 
 # Helpers =======================================
 function assert_curl_success {

ci/L0_backend_vllm/vllm_backend/vllm_backend_test.py

@@ -35,6 +35,13 @@
 sys.path.append("../../common")
 from test_util import TestResultCollector, UserData, callback, create_vllm_request
 
+PROMPTS = [
+    "The most dangerous animal is",
+    "The capital of France is",
+    "The future of AI is",
+]
+SAMPLING_PARAMETERS = {"temperature": "0", "top_p": "1"}
+
 
 class VLLMTritonBackendTest(TestResultCollector):
     def setUp(self):
@@ -60,8 +67,18 @@ def test_vllm_triton_backend(self):
         self.assertFalse(self.triton_client.is_model_ready(self.python_model_name))
 
         # Test vllm model and unload vllm model
-        self._test_vllm_model(send_parameters_as_tensor=True)
-        self._test_vllm_model(send_parameters_as_tensor=False)
+        self._test_vllm_model(
+            prompts=PROMPTS,
+            sampling_parameters=SAMPLING_PARAMETERS,
+            stream=False,
+            send_parameters_as_tensor=True,
+        )
+        self._test_vllm_model(
+            prompts=PROMPTS,
+            sampling_parameters=SAMPLING_PARAMETERS,
+            stream=False,
+            send_parameters_as_tensor=False,
+        )
         self.triton_client.unload_model(self.vllm_model_name)
 
     def test_model_with_invalid_attributes(self):
@@ -74,16 +91,90 @@ def test_vllm_invalid_model_name(self):
         with self.assertRaises(InferenceServerException):
             self.triton_client.load_model(model_name)
 
-    def _test_vllm_model(self, send_parameters_as_tensor):
-        user_data = UserData()
-        stream = False
+    def test_exclude_input_in_output_default(self):
+        """
+        Verifying default behavior for `exclude_input_in_output`
+        in non-streaming mode.
+        Expected result: prompt is returned with diffs.
+        """
+        self.triton_client.load_model(self.vllm_model_name)
         prompts = [
-            "The most dangerous animal is",
             "The capital of France is",
-            "The future of AI is",
         ]
-        number_of_vllm_reqs = len(prompts)
+        expected_output = [
+            b"The capital of France is the capital of the French Republic.\n\nThe capital of France is the capital"
+        ]
+        sampling_parameters = {"temperature": "0", "top_p": "1"}
+        self._test_vllm_model(
+            prompts,
+            sampling_parameters,
+            stream=False,
+            send_parameters_as_tensor=True,
+            expected_output=expected_output,
+        )
+        self.triton_client.unload_model(self.vllm_model_name)
+
+    def test_exclude_input_in_output_false(self):
+        """
+        Verifying behavior for `exclude_input_in_output` = False
+        in non-streaming mode.
+        Expected result: prompt is returned with diffs.
+        """
+        self.triton_client.load_model(self.vllm_model_name)
+        # Test vllm model and unload vllm model
+        prompts = [
+            "The capital of France is",
+        ]
+        expected_output = [
+            b"The capital of France is the capital of the French Republic.\n\nThe capital of France is the capital"
+        ]
+        sampling_parameters = {"temperature": "0", "top_p": "1"}
+        self._test_vllm_model(
+            prompts,
+            sampling_parameters,
+            stream=False,
+            send_parameters_as_tensor=True,
+            exclude_input_in_output=False,
+            expected_output=expected_output,
+        )
+        self.triton_client.unload_model(self.vllm_model_name)
+
+    def test_exclude_input_in_output_true(self):
+        """
+        Verifying behavior for `exclude_input_in_output` = True
+        in non-streaming mode.
+        Expected result: only diffs are returned.
+        """
+        self.triton_client.load_model(self.vllm_model_name)
+        # Test vllm model and unload vllm model
+        prompts = [
+            "The capital of France is",
+        ]
+        expected_output = [
+            b" the capital of the French Republic.\n\nThe capital of France is the capital"
+        ]
         sampling_parameters = {"temperature": "0", "top_p": "1"}
+        self._test_vllm_model(
+            prompts,
+            sampling_parameters,
+            stream=False,
+            send_parameters_as_tensor=True,
+            exclude_input_in_output=True,
+            expected_output=expected_output,
+        )
+        self.triton_client.unload_model(self.vllm_model_name)
+
+    def _test_vllm_model(
+        self,
+        prompts,
+        sampling_parameters,
+        stream,
+        send_parameters_as_tensor,
+        exclude_input_in_output=None,
+        expected_output=None,
+    ):
+        user_data = UserData()
+        number_of_vllm_reqs = len(prompts)
 
         self.triton_client.start_stream(callback=partial(callback, user_data))
         for i in range(number_of_vllm_reqs):
@@ -94,6 +185,7 @@ def _test_vllm_model(self, send_parameters_as_tensor):
                 sampling_parameters,
                 self.vllm_model_name,
                 send_parameters_as_tensor,
+                exclude_input_in_output=exclude_input_in_output,
             )
             self.triton_client.async_stream_infer(
                 model_name=self.vllm_model_name,
@@ -111,6 +203,15 @@ def _test_vllm_model(self, send_parameters_as_tensor):
 
             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()
 

ci/common/test_util.py

@@ -95,6 +95,7 @@ def create_vllm_request(
     sampling_parameters,
     model_name,
     send_parameters_as_tensor=True,
+    exclude_input_in_output=None,
 ):
     inputs = []
 
@@ -111,6 +112,10 @@ def create_vllm_request(
         inputs.append(grpcclient.InferInput("sampling_parameters", [1], "BYTES"))
         inputs[-1].set_data_from_numpy(sampling_parameters_data)
 
+    if exclude_input_in_output is not None:
+        inputs.append(grpcclient.InferInput("exclude_input_in_output", [1], "BOOL"))
+        inputs[-1].set_data_from_numpy(np.array([exclude_input_in_output], dtype=bool))
+
     outputs = [grpcclient.InferRequestedOutput("text_output")]
 
     return {