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simple_http_string_infer_client.cc
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simple_http_string_infer_client.cc
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// Copyright (c) 2020-2021, NVIDIA CORPORATION. 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.
#include <unistd.h>
#include <iostream>
#include <string>
#include "http_client.h"
namespace tc = triton::client;
#define FAIL_IF_ERR(X, MSG) \
{ \
tc::Error err = (X); \
if (!err.IsOk()) { \
std::cerr << "error: " << (MSG) << ": " << err << std::endl; \
exit(1); \
} \
}
namespace {
void
ValidateShapeAndDatatype(
const std::string& name, std::shared_ptr<tc::InferResult> result)
{
std::vector<int64_t> shape;
FAIL_IF_ERR(result->Shape(name, &shape), "unable to get shape for " + name);
// Validate shape
if ((shape.size() != 2) || (shape[0] != 1) || (shape[1] != 16)) {
std::cerr << "error: received incorrect shapes for " << name << std::endl;
exit(1);
}
std::string datatype;
FAIL_IF_ERR(
result->Datatype(name, &datatype), "unable to get datatype for " + name);
// Validate datatype
if (datatype.compare("BYTES") != 0) {
std::cerr << "error: received incorrect datatype for " << name << ": "
<< datatype << std::endl;
exit(1);
}
}
void
Usage(char** argv, const std::string& msg = std::string())
{
if (!msg.empty()) {
std::cerr << "error: " << msg << std::endl;
}
std::cerr << "Usage: " << argv[0] << " [options]" << std::endl;
std::cerr << "\t-v" << std::endl;
std::cerr << "\t-u <URL for inference service>" << std::endl;
std::cerr << "\t-H <HTTP header>" << std::endl;
std::cerr << std::endl;
std::cerr
<< "For -H, header must be 'Header:Value'. May be given multiple times."
<< std::endl;
exit(1);
}
} // namespace
int
main(int argc, char** argv)
{
bool verbose = false;
std::string url("localhost:8000");
tc::Headers http_headers;
// Parse commandline...
int opt;
while ((opt = getopt(argc, argv, "vu:H:")) != -1) {
switch (opt) {
case 'v':
verbose = true;
break;
case 'u':
url = optarg;
break;
case 'H': {
std::string arg = optarg;
std::string header = arg.substr(0, arg.find(":"));
http_headers[header] = arg.substr(header.size() + 1);
break;
}
case '?':
Usage(argv);
break;
}
}
// We use a simple model that takes 2 input tensors of 16 strings
// each and returns 2 output tensors of 16 strings each. The input
// strings must represent integers. One output tensor is the
// element-wise sum of the inputs and one output is the element-wise
// difference.
std::string model_name = "simple_string";
std::string model_version = "";
// Create a InferenceServerHttpClient instance to communicate with the
// server using http protocol.
std::unique_ptr<tc::InferenceServerHttpClient> client;
FAIL_IF_ERR(
tc::InferenceServerHttpClient::Create(&client, url, verbose),
"unable to create http client");
// Create the data for the two input tensors. Initialize the first
// to unique integers and the second to all ones. The input tensors
// are the string representation of these values.
std::vector<std::string> input0_data(16);
std::vector<std::string> input1_data(16);
std::vector<int32_t> expected_sum(16);
std::vector<int32_t> expected_diff(16);
for (size_t i = 0; i < 16; ++i) {
input0_data[i] = std::to_string(i);
input1_data[i] = std::to_string(1);
expected_sum[i] = i + 1;
expected_diff[i] = i - 1;
}
std::vector<int64_t> shape{1, 16};
// Initialize the inputs with the data.
tc::InferInput* input0;
tc::InferInput* input1;
FAIL_IF_ERR(
tc::InferInput::Create(&input0, "INPUT0", shape, "BYTES"),
"unable to get INPUT0");
std::shared_ptr<tc::InferInput> input0_ptr;
input0_ptr.reset(input0);
FAIL_IF_ERR(
tc::InferInput::Create(&input1, "INPUT1", shape, "BYTES"),
"unable to get INPUT1");
std::shared_ptr<tc::InferInput> input1_ptr;
input1_ptr.reset(input1);
FAIL_IF_ERR(
input0_ptr->AppendFromString(input0_data),
"unable to set data for INPUT0");
FAIL_IF_ERR(
input1_ptr->AppendFromString(input1_data),
"unable to set data for INPUT1");
// Generate the outputs to be requested.
tc::InferRequestedOutput* output0;
tc::InferRequestedOutput* output1;
FAIL_IF_ERR(
tc::InferRequestedOutput::Create(&output0, "OUTPUT0"),
"unable to get OUTPUT0");
std::shared_ptr<tc::InferRequestedOutput> output0_ptr;
output0_ptr.reset(output0);
FAIL_IF_ERR(
tc::InferRequestedOutput::Create(&output1, "OUTPUT1"),
"unable to get OUTPUT1");
std::shared_ptr<tc::InferRequestedOutput> output1_ptr;
output1_ptr.reset(output1);
// The inference settings. Will be using default for now.
tc::InferOptions options(model_name);
options.model_version_ = model_version;
std::vector<tc::InferInput*> inputs = {input0_ptr.get(), input1_ptr.get()};
std::vector<const tc::InferRequestedOutput*> outputs = {output0_ptr.get(),
output1_ptr.get()};
tc::InferResult* results;
FAIL_IF_ERR(
client->Infer(&results, options, inputs, outputs, http_headers),
"unable to run model");
std::shared_ptr<tc::InferResult> results_ptr;
results_ptr.reset(results);
// Validate the results...
ValidateShapeAndDatatype("OUTPUT0", results_ptr);
ValidateShapeAndDatatype("OUTPUT1", results_ptr);
// Get the result data
std::vector<std::string> result0_data;
std::vector<std::string> result1_data;
FAIL_IF_ERR(
results_ptr->StringData("OUTPUT0", &result0_data),
"unable to get data for OUTPUT0");
if (result0_data.size() != 16) {
std::cerr << "error: received incorrect number of strings for OUTPUT0: "
<< result0_data.size() << std::endl;
exit(1);
}
FAIL_IF_ERR(
results_ptr->StringData("OUTPUT1", &result1_data),
"unable to get data for OUTPUT1");
if (result1_data.size() != 16) {
std::cerr << "error: received incorrect number of strings for OUTPUT1: "
<< result1_data.size() << std::endl;
exit(1);
}
for (size_t i = 0; i < 16; ++i) {
std::cout << input0_data[i] << " + " << input0_data[i] << " = "
<< result0_data[i] << std::endl;
std::cout << input0_data[i] << " - " << input1_data[i] << " = "
<< result1_data[i] << std::endl;
if (expected_sum[i] != std::stoi(result0_data[i])) {
std::cerr << "error: incorrect sum" << std::endl;
exit(1);
}
if (expected_diff[i] != std::stoi(result1_data[i])) {
std::cerr << "error: incorrect difference" << std::endl;
exit(1);
}
}
// Get full response
std::cout << results_ptr->DebugString() << std::endl;
std::cout << "PASS : String Infer" << std::endl;
return 0;
}