test: Enhance Python gRPC streaming test to send multiple requests (#…

…7684)

qa/L0_python_api/testing_utils.py

@@ -26,6 +26,7 @@
 
 import os
 import queue
+from functools import partial
 from typing import Union
 
 import numpy as np
@@ -101,59 +102,36 @@ def send_and_test_inference_identity(frontend_client, url: str) -> bool:
     return input_data[0] == output_data[0].decode()
 
 
-# Sends a streaming inference request to test_model_repository/identity model
-# and verifies input == output
+# Sends multiple streaming requests to "delayed_identity" model with negligible delays,
+# and verifies the inputs matches outputs and the ordering is preserved.
 def send_and_test_stream_inference(frontend_client, url: str) -> bool:
-    model_name = "identity"
-
-    # Setting up the gRPC client stream
-    results = queue.Queue()
-    callback = lambda error, result: results.put(error or result)
-    client = frontend_client.InferenceServerClient(url=url)
-
-    client.start_stream(callback=callback)
-
-    # Preparing Input Data
-    text_input = "testing"
-    input_tensor = frontend_client.InferInput(
-        name="INPUT0", shape=[1], datatype="BYTES"
-    )
-    input_tensor.set_data_from_numpy(np.array([text_input.encode()], dtype=np.object_))
+    num_requests = 100
+    requests = []
+    for i in range(num_requests):
+        input0_np = np.array([[float(i) / 1000]], dtype=np.float32)
+        inputs = [frontend_client.InferInput("INPUT0", input0_np.shape, "FP32")]
+        inputs[0].set_data_from_numpy(input0_np)
+        requests.append(inputs)
 
-    # Sending Streaming Inference Request
-    client.async_stream_infer(
-        model_name=model_name, inputs=[input_tensor], enable_empty_final_response=True
-    )
-
-    # Looping through until exception thrown or request completed
-    completed_requests, num_requests = 0, 1
-    text_output, is_final = None, None
-    while completed_requests != num_requests:
-        result = results.get()
-        if isinstance(result, InferenceServerException):
-            if result.status() == "StatusCode.CANCELLED":
-                completed_requests += 1
-            raise result
-
-        # Processing Response
-        text_output = result.as_numpy("OUTPUT0")[0].decode()
+    responses = []
 
-        triton_final_response = result.get_response().parameters.get(
-            "triton_final_response", {}
-        )
+    def callback(responses, result, error):
+        responses.append({"result": result, "error": error})
 
-        is_final = False
-        if triton_final_response.HasField("bool_param"):
-            is_final = triton_final_response.bool_param
-
-        # Request Completed
-        if is_final:
-            completed_requests += 1
+    client = frontend_client.InferenceServerClient(url=url)
+    client.start_stream(partial(callback, responses))
+    for inputs in requests:
+        client.async_stream_infer("delayed_identity", inputs)
+    client.stop_stream()
+    teardown_client(client)
 
-    # Tearing down gRPC client stream
-    client.stop_stream(cancel_requests=True)
+    assert len(responses) == num_requests
+    for i in range(len(responses)):
+        assert responses[i]["error"] is None
+        output0_np = responses[i]["result"].as_numpy(name="OUTPUT0")
+        assert np.allclose(output0_np, [[float(i) / 1000]])
 
-    return is_final and (text_input == text_output)
+    return True  # test passed
 
 
 def send_and_test_generate_inference() -> bool: