[None][chore] Add tests for non-existent and completed request cancellation (#6840)

Signed-off-by: Aurelien Chartier <[email protected]>

Author: achartier

tests/integration/defs/triton_server/test_triton_llm.py

@@ -3726,6 +3726,12 @@ def test_llmapi_backend(E2E_MODEL_NAME, DECOUPLED_MODE, TRITON_MAX_BATCH_SIZE,
             output = venv_check_output(llm_backend_venv, run_cmd)
             assert 'Request is cancelled' in output
 
+            # Test request cancellation for non-existing request and completed request
+            run_cmd = [
+                f"{llm_backend_repo_root}/tools/tests/test_llmapi_cancel.py"
+            ]
+            output = venv_check_output(llm_backend_venv, run_cmd)
+
 
 @pytest.mark.parametrize("E2E_MODEL_NAME", ["ensemble", "tensorrt_llm_bls"])
 @pytest.mark.parametrize("ACCUMULATE_TOKEN", ["False"])

triton_backend/tools/tests/test_llmapi_cancel.py

@@ -0,0 +1,115 @@
+#!/usr/bin/env python
+# Copyright 2025, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions
+# are met:
+#  * Redistributions of source code must retain the above copyright
+#    notice, this list of conditions and the following disclaimer.
+#  * Redistributions in binary form must reproduce the above copyright
+#    notice, this list of conditions and the following disclaimer in the
+#    documentation and/or other materials provided with the distribution.
+#  * Neither the name of NVIDIA CORPORATION nor the names of its
+#    contributors may be used to endorse or promote products derived
+#    from this software without specific prior written permission.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
+# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+# PURPOSE ARE DISCLAIMED.  IN NO EVENT SHALL THE COPYRIGHT OWNER OR
+# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
+# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
+# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+import os
+import sys
+from functools import partial
+
+import numpy as np
+from tritonclient import grpc as grpcclient
+from tritonclient.utils import InferenceServerException
+
+sys.path.append(os.path.dirname(os.path.abspath(__file__)) + '/..')
+from llmapi_client import (UserData, _prepare_inputs, callback,
+                           prepare_stop_signals)
+
+if __name__ == "__main__":
+    input_data = np.array([
+        "The current time is",
+    ], dtype=object)
+    output_len = 100
+    inputs = _prepare_inputs(input_data, output_len)
+
+    stop_inputs = prepare_stop_signals()
+    request_id = 1
+    user_data = UserData()
+    with grpcclient.InferenceServerClient(
+            url="localhost:8001",
+            verbose=False,
+            ssl=False,
+            root_certificates=None,
+            private_key=None,
+            certificate_chain=None,
+    ) as triton_client:
+
+        # Send stop request for non-existing request
+        triton_client.async_infer(
+            "tensorrt_llm",
+            stop_inputs,
+            request_id=str(request_id),  # Request does not exist yet
+            callback=partial(callback, user_data),
+            parameters={'Streaming': False})
+
+        result = user_data._completed_requests.get()
+        assert isinstance(result, InferenceServerException)
+        assert result.status() == "StatusCode.CANCELLED"
+
+        # Send actual request
+        infer_response = triton_client.async_infer(
+            "tensorrt_llm",
+            inputs,
+            request_id=str(request_id),
+            callback=partial(callback, user_data),
+            parameters={'Streaming': False})
+
+        result = user_data._completed_requests.get()
+        print(
+            f'Output text: {result.as_numpy("text_output")[0].decode("utf-8")}')
+
+        # Cancel request after it is completed
+        infer_response.cancel()
+
+        # Send stop request for completed request
+        triton_client.async_infer("tensorrt_llm",
+                                  stop_inputs,
+                                  request_id=str(request_id),
+                                  callback=partial(callback, user_data),
+                                  parameters={'Streaming': False})
+
+        cancel_result = user_data._completed_requests.get()
+        assert isinstance(cancel_result, InferenceServerException)
+        assert cancel_result.status() == "StatusCode.CANCELLED"
+
+        # Send a second request to check if server is still healthy
+        infer_response_2 = triton_client.async_infer(
+            "tensorrt_llm",
+            inputs,
+            request_id=str(request_id + 1),
+            callback=partial(callback, user_data),
+            parameters={'Streaming': False})
+
+        # Get result of second request
+        result_2 = user_data._completed_requests.get()
+        print('Got completed request')
+
+        print(
+            f'Output text: {result_2.as_numpy("text_output")[0].decode("utf-8")}'
+        )
+
+        # Check that both results match
+        assert np.array_equal(result.as_numpy("text_output"),
+                              result_2.as_numpy("text_output"))