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Fix pooling, add return code in each test, add return code handling in test_all_tests script

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Signed-off-by: Micaela Verucchi <micaelaverucchi@gmail.com>
This commit is contained in:
Micaela Verucchi
2020-04-09 15:25:05 +02:00
parent ed0596a52c
commit 3502c5b676
31 changed files with 293 additions and 202 deletions
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tests/csresnext50-panet-spp/csresnext50-panet-spp.cpp
+11 -10
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@@ -342,15 +342,15 @@ int main()
tk::dnn::Activation a83(&net, tk::dnn::ACTIVATION_LEAKY);
//SPP
tk::dnn::Pooling p84(&net, 5, 5, 1, 1,0,0, tk::dnn::POOLING_MAX, false, true);
tk::dnn::Pooling p84(&net, 5, 5, 1, 1,0,0, tk::dnn::POOLING_MAX_FIXEDSIZE);
tk::dnn::Layer *r85_layers[1] = {&a83};
tk::dnn::Route r85(&net, r85_layers, 1);
tk::dnn::Pooling p86(&net, 9, 9, 1, 1,0,0, tk::dnn::POOLING_MAX, false, true);
tk::dnn::Pooling p86(&net, 9, 9, 1, 1,0,0, tk::dnn::POOLING_MAX_FIXEDSIZE);
tk::dnn::Layer *r87_layers[1] = {&a83};
tk::dnn::Route r87(&net, r87_layers, 1);
tk::dnn::Pooling p88(&net, 13, 13, 1, 1, 12, 12, tk::dnn::POOLING_MAX, false, true);
tk::dnn::Pooling p88(&net, 13, 13, 1, 1, 12, 12, tk::dnn::POOLING_MAX_FIXEDSIZE);
tk::dnn::Layer *r89_layers[4] = {&p88, &p86, &p84, &a83};
tk::dnn::Route r89(&net, r89_layers, 4);
//END SPP
@@ -536,18 +536,19 @@ int main()
for (int i = 0; i < 3; i++)
rt_out[i] = (dnnType *)netRT.buffersRT[i + 1];
int ret_cudnn = 0, ret_tensorrt = 0, ret_cudnn_tensorrt = 0;
for (int i = 0; i < 3; i++)
{
printCenteredTitle((std::string(" YOLO ") + std::to_string(i) + " CHECK RESULTS ").c_str(), '=', 30);
dnnType *out, *out_h;
int odim = out_dim[i].tot();
readBinaryFile(output_bins[i], odim, &out_h, &out);
std::cout << "CUDNN vs correct";
checkResult(odim, cudnn_out[i], out);
std::cout << "TRT vs correct";
checkResult(odim, rt_out[i], out);
std::cout << "CUDNN vs TRT ";
checkResult(odim, cudnn_out[i], rt_out[i]);
std::cout<<"CUDNN vs correct";
ret_cudnn |= checkResult(odim, cudnn_out[i], out) == 0 ? 0: ERROR_CUDNN;
std::cout<<"TRT vs correct";
ret_tensorrt |= checkResult(odim, rt_out[i], out) == 0 ? 0 : ERROR_TKDNN;
std::cout<<"CUDNN vs TRT ";
ret_cudnn_tensorrt |= checkResult(odim, cudnn_out[i], rt_out[i]) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
}
return 0;
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/dla34/dla34.cpp
+7 -7
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@@ -339,12 +339,12 @@ int main()
int odim = out_dim.tot();
readBinaryFile(output_bin, odim, &out_h, &out);
std::cout << "CUDNN vs correct";
checkResult(odim, cudnn_out, out);
std::cout << "TRT vs correct";
checkResult(odim, rt_out, out);
std::cout << "CUDNN vs TRT ";
checkResult(odim, cudnn_out, rt_out);
std::cout<<"CUDNN vs correct";
int ret_cudnn = checkResult(odim, cudnn_out, out) == 0 ? 0: ERROR_CUDNN;
std::cout<<"TRT vs correct";
int ret_tensorrt = checkResult(odim, rt_out, out) == 0 ? 0 : ERROR_TKDNN;
std::cout<<"CUDNN vs TRT ";
int ret_cudnn_tensorrt = checkResult(odim, cudnn_out, rt_out) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
return 0;
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/dla34_cnet/dla34_cnet.cpp
+9 -9
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@@ -501,6 +501,7 @@ int main()
tk::dnn::Layer *outs[3] = { hm, wh, reg };
int out_count = 1;
int ret_cudnn = 0, ret_tensorrt = 0, ret_cudnn_tensorrt = 0;
for(int i=0; i<3; i++) {
printCenteredTitle((std::string(" RESNET CHECK RESULTS ") + std::to_string(i) + " ").c_str(), '=', 30);
@@ -517,13 +518,12 @@ int main()
if(i==0)
out_count ++;
std::cout << "CUDNN vs correct";
checkResult(odim, cudnn_out, out);
std::cout << "TRT vs correct";
checkResult(odim, rt_out, out);
std::cout << "CUDNN vs TRT ";
checkResult(odim, cudnn_out, rt_out);
}
return 0;
std::cout<<"CUDNN vs correct";
ret_cudnn |= checkResult(odim, cudnn_out, out) == 0 ? 0: ERROR_CUDNN;
std::cout<<"TRT vs correct";
ret_tensorrt |= checkResult(odim, rt_out, out) == 0 ? 0 : ERROR_TKDNN;
std::cout<<"CUDNN vs TRT ";
ret_cudnn_tensorrt |= checkResult(odim, cudnn_out, rt_out) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
}
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/imuodom/imuodom.cpp
+4 -3
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@@ -51,6 +51,7 @@ int main() {
std::ofstream path("path.txt");
int ret_cudnn = 0;
for(int i=0; i<N; i++) {
std::cout<<"i: "<<i<<"\n";
//TIMER_START
@@ -65,9 +66,9 @@ int main() {
// Print real test
printCenteredTitle( (std::string(" CHECK RESULT ") + std::to_string(i) + " ").c_str() , '=');
ImuNet.odim0.print();
checkResult(ImuNet.odim0.tot(), out0, ImuNet.o0_d);
ret_cudnn |= checkResult(ImuNet.odim0.tot(), out0, ImuNet.o0_d) == 0 ? 0 : ERROR_CUDNN;
ImuNet.odim1.print();
checkResult(ImuNet.odim0.tot(), out1, ImuNet.o1_d);
ret_cudnn |= checkResult(ImuNet.odim0.tot(), out1, ImuNet.o1_d) == 0 ? 0 : ERROR_CUDNN;
i0_h += ImuNet.dim0.tot();
i1_h += ImuNet.dim1.tot();
@@ -77,5 +78,5 @@ int main() {
}
system("cat path.txt | gnuplot -p -e \"set datafile separator ' '; plot '-'\"");
return 0;
return ret_cudnn;
}
tests/mobilenetv2ssd/mobilenetv2ssd.cpp
+11 -9
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@@ -507,17 +507,19 @@ int main()
dnnType *out2, *out2_h;
int odim2 = out_dim2.tot();
readBinaryFile(output_bin2, odim2, &out2_h, &out2);
int ret_cudnn = 0, ret_tensorrt = 0, ret_cudnn_tensorrt = 0;
std::cout << "CUDNN vs correct" << std::endl;
checkResult(odim1, cudnn_out1, out1);
checkResult(odim2, cudnn_out2, out2);
ret_cudnn |= checkResult(odim1, cudnn_out1, out1) == 0 ? 0 : ERROR_CUDNN;
ret_cudnn |= checkResult(odim2, cudnn_out2, out2) == 0 ? 0 : ERROR_CUDNN;
std::cout << "TRT vs correct" << std::endl;
checkResult(odim1, rt_out1, out1);
checkResult(odim2, rt_out2, out2);
ret_tensorrt |= checkResult(odim1, rt_out1, out1) == 0 ? 0 : ERROR_TKDNN;
ret_tensorrt |= checkResult(odim2, rt_out2, out2) == 0 ? 0 : ERROR_TKDNN;
std::cout << "CUDNN vs TRT " << std::endl;
checkResult(odim1, cudnn_out1, rt_out1);
checkResult(odim2, cudnn_out2, rt_out2);
ret_cudnn_tensorrt |= checkResult(odim1, cudnn_out1, rt_out1) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
ret_cudnn_tensorrt |= checkResult(odim2, cudnn_out2, rt_out2) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
std::cout << "---------------------------------------------------" << std::endl;
std::cout << "Confidence CUDNN" << std::endl;
@@ -533,8 +535,8 @@ int main()
std::cout << "---------------------------------------------------" << std::endl;
std::cout << "CUDNN vs TRT " << std::endl;
checkResult(conf->output_dim.tot(), conf->dstData, rt_out3);
checkResult(loc->output_dim.tot(), loc->dstData, rt_out4);
ret_cudnn_tensorrt |= checkResult(conf->output_dim.tot(), conf->dstData, rt_out3) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
ret_cudnn_tensorrt |= checkResult(loc->output_dim.tot(), loc->dstData, rt_out4) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
return 0;
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/mobilenetv2ssd512/mobilenetv2ssd512.cpp
+11 -9
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@@ -506,17 +506,19 @@ int main()
dnnType *out2, *out2_h;
int odim2 = out_dim2.tot();
readBinaryFile(output_bin2, odim2, &out2_h, &out2);
int ret_cudnn = 0, ret_tensorrt = 0, ret_cudnn_tensorrt = 0;
std::cout << "CUDNN vs correct" << std::endl;
checkResult(odim1, cudnn_out1, out1);
checkResult(odim2, cudnn_out2, out2);
ret_cudnn |= checkResult(odim1, cudnn_out1, out1) == 0 ? 0 : ERROR_CUDNN;
ret_cudnn |= checkResult(odim2, cudnn_out2, out2) == 0 ? 0 : ERROR_CUDNN;
std::cout << "TRT vs correct" << std::endl;
checkResult(odim1, rt_out1, out1);
checkResult(odim2, rt_out2, out2);
ret_tensorrt |= checkResult(odim1, rt_out1, out1) == 0 ? 0 : ERROR_TKDNN;
ret_tensorrt |= checkResult(odim2, rt_out2, out2) == 0 ? 0 : ERROR_TKDNN;
std::cout << "CUDNN vs TRT " << std::endl;
checkResult(odim1, cudnn_out1, rt_out1);
checkResult(odim2, cudnn_out2, rt_out2);
ret_cudnn_tensorrt |= checkResult(odim1, cudnn_out1, rt_out1) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
ret_cudnn_tensorrt |= checkResult(odim2, cudnn_out2, rt_out2) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
std::cout << "---------------------------------------------------" << std::endl;
std::cout << "Confidence CUDNN" << std::endl;
@@ -532,8 +534,8 @@ int main()
std::cout << "---------------------------------------------------" << std::endl;
std::cout << "CUDNN vs TRT " << std::endl;
checkResult(conf->output_dim.tot(), conf->dstData, rt_out3);
checkResult(loc->output_dim.tot(), loc->dstData, rt_out4);
ret_cudnn_tensorrt |= checkResult(conf->output_dim.tot(), conf->dstData, rt_out3) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
ret_cudnn_tensorrt |= checkResult(loc->output_dim.tot(), loc->dstData, rt_out4) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
return 0;
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/resnet101/resnet101.cpp
+8 -8
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@@ -326,13 +326,13 @@ int main()
dnnType *out, *out_h;
int odim = out_dim.tot();
readBinaryFile(output_bin, odim, &out_h, &out);
std::cout << "CUDNN vs correct";
checkResult(odim, cudnn_out, out);
std::cout<<"CUDNN vs correct";
int ret_cudnn = checkResult(odim, cudnn_out, out) == 0 ? 0: ERROR_CUDNN;
std::cout<<"TRT vs correct";
int ret_tensorrt = checkResult(odim, rt_out, out) == 0 ? 0 : ERROR_TKDNN;
std::cout<<"CUDNN vs TRT ";
int ret_cudnn_tensorrt = checkResult(odim, cudnn_out, rt_out) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
std::cout << "TRT vs correct";
checkResult(odim, rt_out, out);
std::cout << "CUDNN vs TRT ";
checkResult(odim, cudnn_out, rt_out);
return 0;
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/resnet101_cnet/resnet101_cnet.cpp
+9 -8
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@@ -377,6 +377,7 @@ int main()
tk::dnn::Layer *outs[3] = { hm, wh, reg };
int out_count = 1;
int ret_cudnn = 0, ret_tensorrt = 0, ret_cudnn_tensorrt = 0;
for(int i=0; i<3; i++) {
printCenteredTitle((std::string(" RESNET CHECK RESULTS ") + std::to_string(i) + " ").c_str(), '=', 30);
@@ -397,12 +398,12 @@ int main()
if(i==0)
out_count ++;
std::cout << "CUDNN vs correct";
checkResult(odim, cudnn_out, out);
std::cout << "TRT vs correct";
checkResult(odim, rt_out, out);
std::cout << "CUDNN vs TRT ";
checkResult(odim, cudnn_out, rt_out);
}
std::cout<<"CUDNN vs correct";
ret_cudnn |= checkResult(odim, cudnn_out, out) == 0 ? 0: ERROR_CUDNN;
std::cout<<"TRT vs correct";
ret_tensorrt |= checkResult(odim, rt_out, out) == 0 ? 0 : ERROR_TKDNN;
std::cout<<"CUDNN vs TRT ";
ret_cudnn_tensorrt |= checkResult(odim, cudnn_out, rt_out) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
}
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/simple/test_simple.cpp
+8 -4
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@@ -62,8 +62,12 @@ int main() {
dnnType *out, *out_h;
int out_dim = net.getOutputDim().tot();
//readBinaryFile(output_bin, out_dim, &out_h, &out);
//std::cout<<"CUDNN vs correct"; checkResult(out_dim, out_data, out);
//std::cout<<"TRT vs correct"; checkResult(out_dim, out_data2, out);
std::cout<<"CUDNN vs TRT "; checkResult(out_dim, out_data, out_data2);
return 0;
// 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_TKDNN;
std::cout<<"CUDNN vs TRT ";
int ret_cudnn_tensorrt = checkResult(out_dim, out_data, out_data2) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
return ret_cudnn_tensorrt;
}
tests/yolo/yolo.cpp
+15 -10
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@@ -138,15 +138,20 @@ int main() {
dnnType *out, *out_h;
int out_dim = net.getOutputDim().tot();
readBinaryFile(output_bin, out_dim, &out_h, &out);
std::cout<<"CUDNN vs correct"; checkResult(out_dim, out_data, out);
std::cout<<"TRT vs correct"; checkResult(out_dim, out_data2, out);
std::cout<<"CUDNN vs TRT "; checkResult(out_dim, out_data, out_data2);
std::cout<<"\n\nDetected objects: \n";
dnnType *output_h = new dnnType[rI.output_dim.tot()];
checkCuda(cudaMemcpy(output_h, out_data2,
rI.output_dim.tot()*sizeof(dnnType), cudaMemcpyDeviceToHost));
rI.interpretData(output_h);
rI.showImageResult(input_h);
return 0;
// std::cout<<"\n\nDetected objects: \n";
// dnnType *output_h = new dnnType[rI.output_dim.tot()];
// checkCuda(cudaMemcpy(output_h, out_data2,
// rI.output_dim.tot()*sizeof(dnnType), cudaMemcpyDeviceToHost));
// rI.interpretData(output_h);
// rI.showImageResult(input_h);
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_TKDNN;
std::cout<<"CUDNN vs TRT ";
int ret_cudnn_tensorrt = checkResult(out_dim, out_data, out_data2) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/yolo3/yolo3.cpp
+8 -4
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@@ -82,14 +82,18 @@ int main() {
}
for(int i=0; i<3; i++) rt_out[i] = (dnnType*)netRT.buffersRT[i+1];
int ret_cudnn = 0, ret_tensorrt = 0, ret_cudnn_tensorrt = 0;
for(int i=0; i<3; i++) {
printCenteredTitle((std::string(" YOLO ") + std::to_string(i) + " CHECK RESULTS ").c_str(), '=', 30);
dnnType *out, *out_h;
int odim = out_dim[i].tot();
readBinaryFile(output_bins[i], odim, &out_h, &out);
std::cout<<"CUDNN vs correct"; checkResult(odim, cudnn_out[i], out);
std::cout<<"TRT vs correct"; checkResult(odim, rt_out[i], out);
std::cout<<"CUDNN vs TRT "; checkResult(odim, cudnn_out[i], rt_out[i]);
std::cout<<"CUDNN vs correct";
ret_cudnn |= checkResult(odim, cudnn_out[i], out) == 0 ? 0: ERROR_CUDNN;
std::cout<<"TRT vs correct";
ret_tensorrt |= checkResult(odim, rt_out[i], out) == 0 ? 0 : ERROR_TKDNN;
std::cout<<"CUDNN vs TRT ";
ret_cudnn_tensorrt |= checkResult(odim, cudnn_out[i], rt_out[i]) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
}
return 0;
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/yolo3_512/yolo3_512.cpp
+8 -4
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@@ -82,14 +82,18 @@ int main() {
}
for(int i=0; i<3; i++) rt_out[i] = (dnnType*)netRT.buffersRT[i+1];
int ret_cudnn = 0, ret_tensorrt = 0, ret_cudnn_tensorrt = 0;
for(int i=0; i<3; i++) {
printCenteredTitle((std::string(" YOLO ") + std::to_string(i) + " CHECK RESULTS ").c_str(), '=', 30);
dnnType *out, *out_h;
int odim = out_dim[i].tot();
readBinaryFile(output_bins[i], odim, &out_h, &out);
std::cout<<"CUDNN vs correct"; checkResult(odim, cudnn_out[i], out);
std::cout<<"TRT vs correct"; checkResult(odim, rt_out[i], out);
std::cout<<"CUDNN vs TRT "; checkResult(odim, cudnn_out[i], rt_out[i]);
std::cout<<"CUDNN vs correct";
ret_cudnn |= checkResult(odim, cudnn_out[i], out) == 0 ? 0: ERROR_CUDNN;
std::cout<<"TRT vs correct";
ret_tensorrt |= checkResult(odim, rt_out[i], out) == 0 ? 0 : ERROR_TKDNN;
std::cout<<"CUDNN vs TRT ";
ret_cudnn_tensorrt |= checkResult(odim, cudnn_out[i], rt_out[i]) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
}
return 0;
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/yolo3_512tp/yolo3_512tp.cpp
+8 -4
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@@ -80,14 +80,18 @@ int main() {
}
for(int i=0; i<3; i++) rt_out[i] = (dnnType*)netRT.buffersRT[i+1];
int ret_cudnn = 0, ret_tensorrt = 0, ret_cudnn_tensorrt = 0;
for(int i=0; i<3; i++) {
printCenteredTitle((std::string(" YOLO ") + std::to_string(i) + " CHECK RESULTS ").c_str(), '=', 30);
dnnType *out, *out_h;
int odim = out_dim[i].tot();
readBinaryFile(output_bins[i], odim, &out_h, &out);
std::cout<<"CUDNN vs correct"; checkResult(odim, cudnn_out[i], out);
std::cout<<"TRT vs correct"; checkResult(odim, rt_out[i], out);
std::cout<<"CUDNN vs TRT "; checkResult(odim, cudnn_out[i], rt_out[i]);
std::cout<<"CUDNN vs correct";
ret_cudnn |= checkResult(odim, cudnn_out[i], out) == 0 ? 0: ERROR_CUDNN;
std::cout<<"TRT vs correct";
ret_tensorrt |= checkResult(odim, rt_out[i], out) == 0 ? 0 : ERROR_TKDNN;
std::cout<<"CUDNN vs TRT ";
ret_cudnn_tensorrt |= checkResult(odim, cudnn_out[i], rt_out[i]) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
}
return 0;
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/yolo3_berkeley/yolo3_berkeley.cpp
+8 -4
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@@ -82,14 +82,18 @@ int main() {
}
for(int i=0; i<3; i++) rt_out[i] = (dnnType*)netRT.buffersRT[i+1];
int ret_cudnn = 0, ret_tensorrt = 0, ret_cudnn_tensorrt = 0;
for(int i=0; i<3; i++) {
printCenteredTitle((std::string(" YOLO ") + std::to_string(i) + " CHECK RESULTS ").c_str(), '=', 30);
dnnType *out, *out_h;
int odim = out_dim[i].tot();
readBinaryFile(output_bins[i], odim, &out_h, &out);
std::cout<<"CUDNN vs correct"; checkResult(odim, cudnn_out[i], out);
std::cout<<"TRT vs correct"; checkResult(odim, rt_out[i], out);
std::cout<<"CUDNN vs TRT "; checkResult(odim, cudnn_out[i], rt_out[i]);
std::cout<<"CUDNN vs correct";
ret_cudnn |= checkResult(odim, cudnn_out[i], out) == 0 ? 0: ERROR_CUDNN;
std::cout<<"TRT vs correct";
ret_tensorrt |= checkResult(odim, rt_out[i], out) == 0 ? 0 : ERROR_TKDNN;
std::cout<<"CUDNN vs TRT ";
ret_cudnn_tensorrt |= checkResult(odim, cudnn_out[i], rt_out[i]) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
}
return 0;
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/yolo3_coco4/yolo3_coco4.cpp
+8 -4
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@@ -80,14 +80,18 @@ int main() {
}
for(int i=0; i<3; i++) rt_out[i] = (dnnType*)netRT.buffersRT[i+1];
int ret_cudnn = 0, ret_tensorrt = 0, ret_cudnn_tensorrt = 0;
for(int i=0; i<3; i++) {
printCenteredTitle((std::string(" YOLO ") + std::to_string(i) + " CHECK RESULTS ").c_str(), '=', 30);
dnnType *out, *out_h;
int odim = out_dim[i].tot();
readBinaryFile(output_bins[i], odim, &out_h, &out);
std::cout<<"CUDNN vs correct"; checkResult(odim, cudnn_out[i], out);
std::cout<<"TRT vs correct"; checkResult(odim, rt_out[i], out);
std::cout<<"CUDNN vs TRT "; checkResult(odim, cudnn_out[i], rt_out[i]);
std::cout<<"CUDNN vs correct";
ret_cudnn |= checkResult(odim, cudnn_out[i], out) == 0 ? 0: ERROR_CUDNN;
std::cout<<"TRT vs correct";
ret_tensorrt |= checkResult(odim, rt_out[i], out) == 0 ? 0 : ERROR_TKDNN;
std::cout<<"CUDNN vs TRT ";
ret_cudnn_tensorrt |= checkResult(odim, cudnn_out[i], rt_out[i]) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
}
return 0;
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/yolo3_flir/yolo3_flir.cpp
+9 -4
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@@ -82,14 +82,19 @@ int main() {
}
for(int i=0; i<3; i++) rt_out[i] = (dnnType*)netRT.buffersRT[i+1];
int ret_cudnn = 0, ret_tensorrt = 0, ret_cudnn_tensorrt = 0;
for(int i=0; i<3; i++) {
printCenteredTitle((std::string(" YOLO ") + std::to_string(i) + " CHECK RESULTS ").c_str(), '=', 30);
dnnType *out, *out_h;
int odim = out_dim[i].tot();
readBinaryFile(output_bins[i], odim, &out_h, &out);
std::cout<<"CUDNN vs correct"; checkResult(odim, cudnn_out[i], out);
std::cout<<"TRT vs correct"; checkResult(odim, rt_out[i], out);
std::cout<<"CUDNN vs TRT "; checkResult(odim, cudnn_out[i], rt_out[i]);
std::cout<<"CUDNN vs correct";
ret_cudnn |= checkResult(odim, cudnn_out[i], out) == 0 ? 0: ERROR_CUDNN;
std::cout<<"TRT vs correct";
ret_tensorrt |= checkResult(odim, rt_out[i], out) == 0 ? 0 : ERROR_TKDNN;
std::cout<<"CUDNN vs TRT ";
ret_cudnn_tensorrt |= checkResult(odim, cudnn_out[i], rt_out[i]) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
}
return 0;
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/yolo3_tiny/yolo3_tiny.cpp
+10 -6
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@@ -55,7 +55,7 @@ int main() {
tk::dnn::Conv2d c10(&net, 512, 3, 3, 1, 1, 1, 1, c10_bin, true);
tk::dnn::Activation a10(&net, tk::dnn::ACTIVATION_LEAKY);
tk::dnn::Pooling p11(&net, 2, 2, 1, 1,0,0, tk::dnn::POOLING_MAX, false, true);
tk::dnn::Pooling p11(&net, 2, 2, 1, 1,0,0, tk::dnn::POOLING_MAX_FIXEDSIZE);
tk::dnn::Conv2d c12(&net, 1024, 3, 3, 1, 1, 1, 1, c12_bin, true);
tk::dnn::Activation a12(&net, tk::dnn::ACTIVATION_LEAKY);
@@ -118,9 +118,13 @@ int main() {
dnnType *out, *out_h;
int out_dim = net.getOutputDim().tot();
readBinaryFile(output_bin, out_dim, &out_h, &out);
std::cout<<"CUDNN vs correct"; checkResult(out_dim, out_data, out);
std::cout<<"TRT vs correct"; checkResult(out_dim, out_data2, out);
std::cout<<"CUDNN vs TRT "; checkResult(out_dim, out_data, out_data2);
return 0;
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_TKDNN;
std::cout<<"CUDNN vs TRT ";
int ret_cudnn_tensorrt = checkResult(out_dim, out_data, out_data2) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/yolo3_tiny512/yolo3_tiny512.cpp
+9 -6
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@@ -54,7 +54,7 @@ int main() {
tk::dnn::Conv2d c10(&net, 512, 3, 3, 1, 1, 1, 1, c10_bin, true);
tk::dnn::Activation a10(&net, tk::dnn::ACTIVATION_LEAKY);
tk::dnn::Pooling p11(&net, 2, 2, 1, 1,0,0, tk::dnn::POOLING_MAX, false, true);
tk::dnn::Pooling p11(&net, 2, 2, 1, 1,0,0, tk::dnn::POOLING_MAX_FIXEDSIZE);
tk::dnn::Conv2d c12(&net, 1024, 3, 3, 1, 1, 1, 1, c12_bin, true);
tk::dnn::Activation a12(&net, tk::dnn::ACTIVATION_LEAKY);
@@ -117,9 +117,12 @@ int main() {
dnnType *out, *out_h;
int out_dim = net.getOutputDim().tot();
readBinaryFile(output_bin, out_dim, &out_h, &out);
std::cout<<"CUDNN vs correct"; checkResult(out_dim, out_data, out);
std::cout<<"TRT vs correct"; checkResult(out_dim, out_data2, out);
std::cout<<"CUDNN vs TRT "; checkResult(out_dim, out_data, out_data2);
return 0;
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_TKDNN;
std::cout<<"CUDNN vs TRT ";
int ret_cudnn_tensorrt = checkResult(out_dim, out_data, out_data2) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/yolo3_tiny512tp/yolo3_tiny512tp.cpp
+10 -6
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@@ -52,7 +52,7 @@ int main() {
tk::dnn::Conv2d c10(&net, 512, 3, 3, 1, 1, 1, 1, c10_bin, true);
tk::dnn::Activation a10(&net, tk::dnn::ACTIVATION_LEAKY);
tk::dnn::Pooling p11(&net, 2, 2, 1, 1,0,0, tk::dnn::POOLING_MAX, false, true);
tk::dnn::Pooling p11(&net, 2, 2, 1, 1,0,0, tk::dnn::POOLING_MAX_FIXEDSIZE);
tk::dnn::Conv2d c12(&net, 1024, 3, 3, 1, 1, 1, 1, c12_bin, true);
tk::dnn::Activation a12(&net, tk::dnn::ACTIVATION_LEAKY);
@@ -115,9 +115,13 @@ int main() {
dnnType *out, *out_h;
int out_dim = net.getOutputDim().tot();
readBinaryFile(output_bin, out_dim, &out_h, &out);
std::cout<<"CUDNN vs correct"; checkResult(out_dim, out_data, out);
std::cout<<"TRT vs correct"; checkResult(out_dim, out_data2, out);
std::cout<<"CUDNN vs TRT "; checkResult(out_dim, out_data, out_data2);
return 0;
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_TKDNN;
std::cout<<"CUDNN vs TRT ";
int ret_cudnn_tensorrt = checkResult(out_dim, out_data, out_data2) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/yolo3_tinyNM512/yolo3_tinyNM512.cpp
+8 -5
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@@ -116,9 +116,12 @@ int main() {
dnnType *out, *out_h;
int out_dim = net.getOutputDim().tot();
readBinaryFile(output_bin, out_dim, &out_h, &out);
std::cout<<"CUDNN vs correct"; checkResult(out_dim, out_data, out);
std::cout<<"TRT vs correct"; checkResult(out_dim, out_data2, out);
std::cout<<"CUDNN vs TRT "; checkResult(out_dim, out_data, out_data2);
return 0;
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_TKDNN;
std::cout<<"CUDNN vs TRT ";
int ret_cudnn_tensorrt = checkResult(out_dim, out_data, out_data2) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/yolo_224/yolo_224.cpp
+16 -10
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@@ -136,15 +136,21 @@ int main() {
dnnType *out, *out_h;
int out_dim = net.getOutputDim().tot();
readBinaryFile(output_bin, out_dim, &out_h, &out);
std::cout<<"CUDNN vs correct"; checkResult(out_dim, out_data, out);
std::cout<<"TRT vs correct"; checkResult(out_dim, out_data2, out);
std::cout<<"CUDNN vs TRT "; checkResult(out_dim, out_data, out_data2);
std::cout<<"\n\nDetected objects: \n";
dnnType *output_h = new dnnType[rI.output_dim.tot()];
checkCuda(cudaMemcpy(output_h, out_data2,
rI.output_dim.tot()*sizeof(dnnType), cudaMemcpyDeviceToHost));
rI.interpretData(output_h);
rI.showImageResult(input_h);
return 0;
// std::cout<<"\n\nDetected objects: \n";
// dnnType *output_h = new dnnType[rI.output_dim.tot()];
// checkCuda(cudaMemcpy(output_h, out_data2,
// rI.output_dim.tot()*sizeof(dnnType), cudaMemcpyDeviceToHost));
// rI.interpretData(output_h);
// rI.showImageResult(input_h);
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_TKDNN;
std::cout<<"CUDNN vs TRT ";
int ret_cudnn_tensorrt = checkResult(out_dim, out_data, out_data2) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/yolo_berkeley/yolo_berkeley.cpp
+16 -10
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@@ -136,15 +136,21 @@ int main() {
dnnType *out, *out_h;
int out_dim = net.getOutputDim().tot();
readBinaryFile(output_bin, out_dim, &out_h, &out);
std::cout<<"CUDNN vs correct"; checkResult(out_dim, out_data, out);
std::cout<<"TRT vs correct"; checkResult(out_dim, out_data2, out);
std::cout<<"CUDNN vs TRT "; checkResult(out_dim, out_data, out_data2);
std::cout<<"\n\nDetected objects: \n";
dnnType *output_h = new dnnType[rI.output_dim.tot()];
checkCuda(cudaMemcpy(output_h, out_data2,
rI.output_dim.tot()*sizeof(dnnType), cudaMemcpyDeviceToHost));
rI.interpretData(output_h);
rI.showImageResult(input_h);
return 0;
// std::cout<<"\n\nDetected objects: \n";
// dnnType *output_h = new dnnType[rI.output_dim.tot()];
// checkCuda(cudaMemcpy(output_h, out_data2,
// rI.output_dim.tot()*sizeof(dnnType), cudaMemcpyDeviceToHost));
// rI.interpretData(output_h);
// rI.showImageResult(input_h);
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_TKDNN;
std::cout<<"CUDNN vs TRT ";
int ret_cudnn_tensorrt = checkResult(out_dim, out_data, out_data2) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/yolo_relu/yolo_relu.cpp
+15 -11
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@@ -136,16 +136,20 @@ int main() {
dnnType *out, *out_h;
int out_dim = net.getOutputDim().tot();
readBinaryFile(output_bin, out_dim, &out_h, &out);
std::cout<<"CUDNN vs correct"; checkResult(out_dim, out_data, out);
std::cout<<"TRT vs correct"; checkResult(out_dim, out_data2, out);
std::cout<<"CUDNN vs TRT "; checkResult(out_dim, out_data, out_data2);
std::cout<<"\n\nDetected objects: \n";
dnnType *output_h = new dnnType[rI.output_dim.tot()];
checkCuda(cudaMemcpy(output_h, out_data2,
rI.output_dim.tot()*sizeof(dnnType), cudaMemcpyDeviceToHost));
rI.interpretData(output_h, 608, 608);
rI.showImageResult(input_h);
// std::cout<<"\n\nDetected objects: \n";
// dnnType *output_h = new dnnType[rI.output_dim.tot()];
// checkCuda(cudaMemcpy(output_h, out_data2,
// rI.output_dim.tot()*sizeof(dnnType), cudaMemcpyDeviceToHost));
// rI.interpretData(output_h, 608, 608);
// rI.showImageResult(input_h);
return 0;
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_TKDNN;
std::cout<<"CUDNN vs TRT ";
int ret_cudnn_tensorrt = checkResult(out_dim, out_data, out_data2) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/yolo_tiny/yolo_tiny.cpp
+9 -4
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@@ -88,8 +88,13 @@ int main() {
dnnType *out, *out_h;
int out_dim = net.getOutputDim().tot();
readBinaryFile(output_bin, out_dim, &out_h, &out);
std::cout<<"CUDNN vs correct"; checkResult(out_dim, out_data, out);
std::cout<<"TRT vs correct"; checkResult(out_dim, out_data2, out);
std::cout<<"CUDNN vs TRT "; checkResult(out_dim, out_data, out_data2);
return 0;
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_TKDNN;
std::cout<<"CUDNN vs TRT ";
int ret_cudnn_tensorrt = checkResult(out_dim, out_data, out_data2) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}
tests/yolo_voc/yolo_voc.cpp
+15 -11
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@@ -138,15 +138,19 @@ int main() {
dnnType *out, *out_h;
int out_dim = net.getOutputDim().tot();
readBinaryFile(output_bin, out_dim, &out_h, &out);
std::cout<<"CUDNN vs correct"; checkResult(out_dim, out_data, out);
std::cout<<"TRT vs correct"; checkResult(out_dim, out_data2, out);
std::cout<<"CUDNN vs TRT "; checkResult(out_dim, out_data, out_data2);
std::cout<<"\n\nDetected objects: \n";
dnnType *output_h = new dnnType[rI.output_dim.tot()];
checkCuda(cudaMemcpy(output_h, out_data2,
rI.output_dim.tot()*sizeof(dnnType), cudaMemcpyDeviceToHost));
rI.interpretData(output_h);
rI.showImageResult(input_h);
return 0;
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_TKDNN;
std::cout<<"CUDNN vs TRT ";
int ret_cudnn_tensorrt = checkResult(out_dim, out_data, out_data2) == 0 ? 0 : ERROR_CUDNNvsTENSORRT;
// std::cout<<"\n\nDetected objects: \n";
// dnnType *output_h = new dnnType[rI.output_dim.tot()];
// checkCuda(cudaMemcpy(output_h, out_data2,
// rI.output_dim.tot()*sizeof(dnnType), cudaMemcpyDeviceToHost));
// rI.interpretData(output_h);
// rI.showImageResult(input_h);
return ret_cudnn | ret_tensorrt | ret_cudnn_tensorrt;
}