simple_http_infer_client.py

#!/usr/bin/env python
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import argparse
import sys

import gevent.ssl
import numpy as np
import tritonclient.http as httpclient
from tritonclient.utils import InferenceServerException


def test_infer(
    model_name,
    input0_data,
    input1_data,
    headers=None,
    request_compression_algorithm=None,
    response_compression_algorithm=None,
):
    inputs = []
    outputs = []
    inputs.append(httpclient.InferInput("INPUT0", [1, 16], "INT32"))
    inputs.append(httpclient.InferInput("INPUT1", [1, 16], "INT32"))

    # Initialize the data
    inputs[0].set_data_from_numpy(input0_data, binary_data=False)
    inputs[1].set_data_from_numpy(input1_data, binary_data=True)

    outputs.append(httpclient.InferRequestedOutput("OUTPUT0", binary_data=True))
    outputs.append(httpclient.InferRequestedOutput("OUTPUT1", binary_data=False))
    query_params = {"test_1": 1, "test_2": 2}
    results = triton_client.infer(
        model_name,
        inputs,
        outputs=outputs,
        query_params=query_params,
        headers=headers,
        request_compression_algorithm=request_compression_algorithm,
        response_compression_algorithm=response_compression_algorithm,
    )

    return results


def test_infer_no_outputs(
    model_name,
    input0_data,
    input1_data,
    headers=None,
    request_compression_algorithm=None,
    response_compression_algorithm=None,
):
    inputs = []
    inputs.append(httpclient.InferInput("INPUT0", [1, 16], "INT32"))
    inputs.append(httpclient.InferInput("INPUT1", [1, 16], "INT32"))

    # Initialize the data
    inputs[0].set_data_from_numpy(input0_data, binary_data=False)
    inputs[1].set_data_from_numpy(input1_data, binary_data=True)

    query_params = {"test_1": 1, "test_2": 2}
    results = triton_client.infer(
        model_name,
        inputs,
        outputs=None,
        query_params=query_params,
        headers=headers,
        request_compression_algorithm=request_compression_algorithm,
        response_compression_algorithm=response_compression_algorithm,
    )

    return results


if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.add_argument(
        "-v",
        "--verbose",
        action="store_true",
        required=False,
        default=False,
        help="Enable verbose output",
    )
    parser.add_argument(
        "-u",
        "--url",
        type=str,
        required=False,
        default="localhost:8000",
        help="Inference server URL. Default is localhost:8000.",
    )
    parser.add_argument(
        "-s",
        "--ssl",
        action="store_true",
        required=False,
        default=False,
        help="Enable encrypted link to the server using HTTPS",
    )
    parser.add_argument(
        "--key-file",
        type=str,
        required=False,
        default=None,
        help="File holding client private key. Default is None.",
    )
    parser.add_argument(
        "--cert-file",
        type=str,
        required=False,
        default=None,
        help="File holding client certificate. Default is None.",
    )
    parser.add_argument(
        "--ca-certs",
        type=str,
        required=False,
        default=None,
        help="File holding ca certificate. Default is None.",
    )
    parser.add_argument(
        "--insecure",
        action="store_true",
        required=False,
        default=False,
        help="Use no peer verification in SSL communications. Use with caution. Default is False.",
    )
    parser.add_argument(
        "-H",
        dest="http_headers",
        metavar="HTTP_HEADER",
        required=False,
        action="append",
        help="HTTP headers to add to inference server requests. "
        + 'Format is -H"Header:Value".',
    )
    parser.add_argument(
        "--request-compression-algorithm",
        type=str,
        required=False,
        default=None,
        help="The compression algorithm to be used when sending request body to server. Default is None.",
    )
    parser.add_argument(
        "--response-compression-algorithm",
        type=str,
        required=False,
        default=None,
        help="The compression algorithm to be used when receiving response body from server. Default is None.",
    )

    FLAGS = parser.parse_args()
    try:
        if FLAGS.ssl:
            ssl_options = {}
            if FLAGS.key_file is not None:
                ssl_options["keyfile"] = FLAGS.key_file
            if FLAGS.cert_file is not None:
                ssl_options["certfile"] = FLAGS.cert_file
            if FLAGS.ca_certs is not None:
                ssl_options["ca_certs"] = FLAGS.ca_certs
            ssl_context_factory = None
            if FLAGS.insecure:
                ssl_context_factory = gevent.ssl._create_unverified_context
            triton_client = httpclient.InferenceServerClient(
                url=FLAGS.url,
                verbose=FLAGS.verbose,
                ssl=True,
                ssl_options=ssl_options,
                insecure=FLAGS.insecure,
                ssl_context_factory=ssl_context_factory,
            )
        else:
            triton_client = httpclient.InferenceServerClient(
                url=FLAGS.url, verbose=FLAGS.verbose
            )
    except Exception as e:
        print("channel creation failed: " + str(e))
        sys.exit(1)

    model_name = "simple"

    # Create the data for the two input tensors. Initialize the first
    # to unique integers and the second to all ones.
    input0_data = np.arange(start=0, stop=16, dtype=np.int32)
    input0_data = np.expand_dims(input0_data, axis=0)
    input1_data = np.full(shape=(1, 16), fill_value=-1, dtype=np.int32)

    if FLAGS.http_headers is not None:
        headers_dict = {l.split(":")[0]: l.split(":")[1] for l in FLAGS.http_headers}
    else:
        headers_dict = None

    # Infer with requested Outputs
    results = test_infer(
        model_name,
        input0_data,
        input1_data,
        headers_dict,
        FLAGS.request_compression_algorithm,
        FLAGS.response_compression_algorithm,
    )
    print(results.get_response())

    statistics = triton_client.get_inference_statistics(
        model_name=model_name, headers=headers_dict
    )
    print(statistics)
    if len(statistics["model_stats"]) != 1:
        print("FAILED: Inference Statistics")
        sys.exit(1)

    # Validate the results by comparing with precomputed values.
    output0_data = results.as_numpy("OUTPUT0")
    output1_data = results.as_numpy("OUTPUT1")
    for i in range(16):
        print(
            str(input0_data[0][i])
            + " + "
            + str(input1_data[0][i])
            + " = "
            + str(output0_data[0][i])
        )
        print(
            str(input0_data[0][i])
            + " - "
            + str(input1_data[0][i])
            + " = "
            + str(output1_data[0][i])
        )
        if (input0_data[0][i] + input1_data[0][i]) != output0_data[0][i]:
            print("sync infer error: incorrect sum")
            sys.exit(1)
        if (input0_data[0][i] - input1_data[0][i]) != output1_data[0][i]:
            print("sync infer error: incorrect difference")
            sys.exit(1)

    # Infer without requested Outputs
    results = test_infer_no_outputs(
        model_name,
        input0_data,
        input1_data,
        headers_dict,
        FLAGS.request_compression_algorithm,
        FLAGS.response_compression_algorithm,
    )
    print(results.get_response())

    # Validate the results by comparing with precomputed values.
    output0_data = results.as_numpy("OUTPUT0")
    output1_data = results.as_numpy("OUTPUT1")
    for i in range(16):
        print(
            str(input0_data[0][i])
            + " + "
            + str(input1_data[0][i])
            + " = "
            + str(output0_data[0][i])
        )
        print(
            str(input0_data[0][i])
            + " - "
            + str(input1_data[0][i])
            + " = "
            + str(output1_data[0][i])
        )
        if (input0_data[0][i] + input1_data[0][i]) != output0_data[0][i]:
            print("sync infer error: incorrect sum")
            sys.exit(1)
        if (input0_data[0][i] - input1_data[0][i]) != output1_data[0][i]:
            print("sync infer error: incorrect difference")
            sys.exit(1)

    # Infer with incorrect model name
    try:
        _ = test_infer("wrong_model_name", input0_data, input1_data).get_response()
        print("expected error message for wrong model name")
        sys.exit(1)
    except InferenceServerException as ex:
        print(ex)
        if not (ex.message().startswith("Request for unknown model")):
            print("improper error message for wrong model name")
            sys.exit(1)