examples/custom_metrics/client.py - main - rnekrasov/python_backend

examples/custom_metrics/client.py
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27 июн 2023, 06:57
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# Copyright 2023, 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 sys

import numpy as np
import requests
import tritonclient.http as httpclient
from tritonclient.utils import *

model_name = "custom_metrics"
shape = [4]


def get_metrics():
    metrics_url = "http://localhost:8002/metrics"
    r = requests.get(metrics_url)
    r.raise_for_status()
    return r.text


with httpclient.InferenceServerClient("localhost:8000") as client:
    input0_data = np.random.rand(*shape).astype(np.float32)
    input1_data = np.random.rand(*shape).astype(np.float32)
    inputs = [
        httpclient.InferInput(
            "INPUT0", input0_data.shape, np_to_triton_dtype(input0_data.dtype)
        ),
        httpclient.InferInput(
            "INPUT1", input1_data.shape, np_to_triton_dtype(input1_data.dtype)
        ),
    ]

    inputs[0].set_data_from_numpy(input0_data)
    inputs[1].set_data_from_numpy(input1_data)

    outputs = [
        httpclient.InferRequestedOutput("OUTPUT0"),
        httpclient.InferRequestedOutput("OUTPUT1"),
    ]

    response = client.infer(model_name, inputs, request_id=str(1), outputs=outputs)

    output0_data = response.as_numpy("OUTPUT0")
    output1_data = response.as_numpy("OUTPUT1")

    if not np.allclose(input0_data + input1_data, output0_data):
        print("custom_metrics example error: incorrect sum")
        sys.exit(1)

    if not np.allclose(input0_data - input1_data, output1_data):
        print("custom_metrics example error: incorrect difference")
        sys.exit(1)

    metrics = get_metrics()
    patterns = [
        "# HELP requests_process_latency_ns Cumulative time spent processing requests",
        "# TYPE requests_process_latency_ns counter",
        'requests_process_latency_ns{model="custom_metrics",version="1"}',
    ]
    for pattern in patterns:
        if pattern not in metrics:
            print(
                "custom_metrics example error: missing pattern '{}' in metrics".format(
                    pattern
                )
            )
            sys.exit(1)
        else:
            print(
                "custom_metrics example: found pattern '{}' in metrics".format(pattern)
            )

    print("PASS: custom_metrics")
    sys.exit(0)