simple_grpc_string_infer_client.py

#!/usr/bin/env python
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import argparse
import numpy as np

import tritonclient.grpc as grpcclient

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:8001',
                        help='Inference server URL. Default is localhost:8001.')

    FLAGS = parser.parse_args()
    try:
        triton_client = grpcclient.InferenceServerClient(url=FLAGS.url,
                                                         verbose=FLAGS.verbose)
    except Exception as e:
        print("context creation failed: " + str(e))
        sys.exit()

    model_name = 'simple_string'

    inputs = []
    outputs = []
    inputs.append(grpcclient.InferInput('INPUT0', [1, 16], "BYTES"))
    inputs.append(grpcclient.InferInput('INPUT1', [1, 16], "BYTES"))

    # Create the data for the two input tensors. Initialize the first
    # to unique integers and the second to all ones.
    in0 = np.arange(start=0, stop=16, dtype=np.int32)
    in0 = np.expand_dims(in0, axis=0)
    in1 = np.ones(shape=(1, 16), dtype=np.int32)
    expected_sum = np.add(in0, in1)
    expected_diff = np.subtract(in0, in1)

    in0n = np.array([str(x) for x in in0.reshape(in0.size)], dtype=object)
    input0_data = in0n.reshape(in0.shape)
    in1n = np.array([str(x) for x in in1.reshape(in1.size)], dtype=object)
    input1_data = in1n.reshape(in1.shape)

    # Initialize the data
    inputs[0].set_data_from_numpy(input0_data)
    inputs[1].set_data_from_numpy(input1_data)

    outputs.append(grpcclient.InferRequestedOutput('OUTPUT0'))
    outputs.append(grpcclient.InferRequestedOutput('OUTPUT1'))

    results = triton_client.infer(model_name=model_name,
                                  inputs=inputs,
                                  outputs=outputs)

    # Get the output arrays from the results
    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]))

        # Convert result from string to int to check result
        r0 = int(output0_data[0][i])
        r1 = int(output1_data[0][i])
        if expected_sum[0][i] != r0:
            print("error: incorrect sum")
            sys.exit(1)
        if expected_diff[0][i] != r1:
            print("error: incorrect difference")
            sys.exit(1)

    print('PASS: string')