#!/usr/bin/python # Copyright 2022, 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 argparse import numpy as np import tritonhttpclient as httpclient from tritonclientutils import np_to_triton_dtype if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('-u', '--url', type=str, required=False, default='localhost:8000', help='Inference server URL. Default is localhost:8000.') FLAGS = parser.parse_args() model_name = "bls_fp32" shape = [16] with httpclient.InferenceServerClient(url=FLAGS.url) 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) result = response.get_response() output0_data = response.as_numpy("OUTPUT0") output1_data = response.as_numpy("OUTPUT1") print("INPUT0 ({}) + INPUT1 ({}) = OUTPUT0 ({})".format( input0_data, input1_data, output0_data)) print("INPUT0 ({}) - INPUT1 ({}) = OUTPUT1 ({})".format( input0_data, input1_data, output1_data)) if not np.allclose(input0_data + input1_data, output0_data): print("error: incorrect sum") sys.exit(1) if not np.allclose(input0_data - input1_data, output1_data): print("error: incorrect difference") sys.exit(1) print('\nPASS') sys.exit(0)