Micaela Verucchi
74 lines
2.2 KiB
C++
74 lines
2.2 KiB
C++
#include<iostream>
|
|
#include "tkdnn.h"
|
|
|
|
const char *input_bin = "simple/input.bin";
|
|
const char *c0_bin = "simple/layers/conv1d_1.bin";
|
|
const char *l1_bin = "simple/layers/bidirectional_1.bin";
|
|
const char *l2_bin = "simple/layers/bidirectional_2.bin";
|
|
const char *output_bin = "simple/output.bin";
|
|
|
|
int main() {
|
|
|
|
// Network layout
|
|
tk::dnn::dataDim_t dim(1, 8, 1, 3);
|
|
tk::dnn::Network net(dim);
|
|
tk::dnn::Conv2d l0(&net, 4, 1, 2, 1, 1, 0, 0, c0_bin);
|
|
tk::dnn::LSTM l1(&net, 5, true, l1_bin);
|
|
tk::dnn::LSTM l2(&net, 5, false, l2_bin);
|
|
|
|
net.print();
|
|
|
|
net.print();
|
|
|
|
// Load input
|
|
dnnType *data;
|
|
dnnType *input_h;
|
|
readBinaryFile(input_bin, dim.tot(), &input_h, &data);
|
|
|
|
// Print input
|
|
std::cout<<"\n======= INPUT =======\n";
|
|
printDeviceVector(dim.tot(), data);
|
|
std::cout<<"\n";
|
|
|
|
//convert network to tensorRT
|
|
tk::dnn::NetworkRT netRT(&net, net.getNetworkRTName("simple"));
|
|
|
|
dnnType *out_data, *out_data2; // cudnn output, tensorRT output
|
|
|
|
tk::dnn::dataDim_t dim1 = dim; //input dim
|
|
printCenteredTitle(" CUDNN inference ", '=', 30); {
|
|
dim1.print();
|
|
TIMER_START
|
|
out_data = net.infer(dim1, data);
|
|
TIMER_STOP
|
|
dim1.print();
|
|
}
|
|
|
|
tk::dnn::dataDim_t dim2 = dim;
|
|
printCenteredTitle(" TENSORRT inference ", '=', 30); {
|
|
dim2.print();
|
|
TIMER_START
|
|
out_data2 = netRT.infer(dim2, data);
|
|
TIMER_STOP
|
|
dim2.print();
|
|
}
|
|
|
|
std::cout<<"\n======= CUDNN =======\n";
|
|
printDeviceVector(dim.tot(), out_data);
|
|
std::cout<<"\n======= TENSORRT =======\n";
|
|
printDeviceVector(dim.tot(), out_data2);
|
|
|
|
printCenteredTitle(" CHECK RESULTS ", '=', 30);
|
|
dnnType *out, *out_h;
|
|
int out_dim = net.getOutputDim().tot();
|
|
//readBinaryFile(output_bin, out_dim, &out_h, &out);
|
|
// std::cout<<"CUDNN vs correct";
|
|
// int ret_cudnn = checkResult(out_dim, out_data, out) == 0 ? 0: ERROR_CUDNN;
|
|
// std::cout<<"TRT vs correct";
|
|
// int ret_tensorrt = checkResult(out_dim, out_data2, out) == 0 ? 0 : ERROR_TENSORRT;
|
|
std::cout<<"CUDNN vs TRT ";
|
|
int ret_cudnn_tensorrt = checkResult(out_dim, out_data, out_data2) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
|
|
|
|
return ret_cudnn_tensorrt;
|
|
}
|