square_client.py

# Copyright 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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import sys
from functools import partial
import numpy as np
import queue

from tritonclient.utils import *
import tritonclient.grpc as grpcclient


class UserData:

    def __init__(self):
        self._completed_requests = queue.Queue()


def callback(user_data, result, error):
    if error:
        user_data._completed_requests.put(error)
    else:
        user_data._completed_requests.put(result)


# This client sends a 4 requests to the model with the
# input as: [4], [2], [0] and [1] respectively. In
# compliance with the behavior of square_int32 model,
# it will expect the 4 responses for the 1st request
# each with output [4], 2 responses for 2nd request
# each with output [2], no response for the 3rd request
# and finally 1 response for the 4th request with output
# [1]
model_name = "square_int32"
in_values = [4, 2, 0, 1]
inputs = [grpcclient.InferInput("IN", [1], np_to_triton_dtype(np.int32))]
outputs = [grpcclient.InferRequestedOutput("OUT")]

user_data = UserData()

with grpcclient.InferenceServerClient(url="localhost:8001",
                                      verbose=True) as triton_client:
    # Establish stream
    triton_client.start_stream(callback=partial(callback, user_data))

    # Send specified many requests in parallel
    for i in range(len(in_values)):
        in_data = np.array([in_values[i]], dtype=np.int32)
        inputs[0].set_data_from_numpy(in_data)

        triton_client.async_stream_infer(model_name=model_name,
                                         inputs=inputs,
                                         request_id=str(i),
                                         outputs=outputs)

    # Retrieve results...
    recv_count = 0
    expected_count = sum(in_values)
    result_dict = {}
    while recv_count < expected_count:
        data_item = user_data._completed_requests.get()
        if type(data_item) == InferenceServerException:
            raise data_item
        else:
            this_id = data_item.get_response().id
            if this_id not in result_dict.keys():
                result_dict[this_id] = []
            result_dict[this_id].append((recv_count, data_item))

        recv_count += 1

    # Validate results...
    for i in range(len(in_values)):
        this_id = str(i)
        if in_values[i] != 0 and this_id not in result_dict.keys():
            print("response for request id {} not received".format(this_id))
            sys.exit(1)
        elif in_values[i] == 0 and this_id in result_dict.keys():
            print("received unexpected response for request id {}".format(
                this_id))
            sys.exit(1)
        if in_values[i] != 0:
            if len(result_dict[this_id]) != in_values[i]:
                print("expected {} many responses for request id {}, got {}".
                      format(in_values[i], this_id, result_dict[this_id]))
                sys.exit(1)

        if in_values[i] != 0:
            result_list = result_dict[this_id]
            expected_data = np.array([in_values[i]], dtype=np.int32)
            for j in range(len(result_list)):
                this_data = result_list[j][1].as_numpy('OUT')
                if not np.array_equal(expected_data, this_data):
                    print("incorrect data: expected {}, got {}".format(
                        expected_data, this_data))
                    sys.exit(1)

    print('PASS: square_int32')
    sys.exit(0)