if(argc !=2) { std::cerr<<"usage: example-app <path-to-exported-script-module>\n";return-1; } torch::jit::getProfilingMode()=false; torch::jit::getExecutorMode()=false; torch::jit::setGraphExecutorOptimize(false);//Deserialize the ScriptModule from a file using torch::jit::load()...
if (argc != 2) { std::cerr << "usage: example-app <path-to-exported-script-module>\n"; return -1; } torch::jit::getProfilingMode() = false; torch::jit::getExecutorMode() = false; torch::jit::setGraphExecutorOptimize(false); // Deserialize the ScriptModule from a file using to...
ENABLE_JIT_PROFILING Support Model Instance Group Kind The PyTorch backend supports the following kinds of Model Instance Groups where the input tensors are placed as follows: KIND_GPU: Inputs are prepared on the GPU device associated with the model instance. KIND_CPU: Inputs are prepared on ...
1 #include <torch/script.h> // One-stop header.2 #include <iostream> 3 #include <memory> 4 5 #include <iostream> 6 #include "torch/script.h"7 #include "torch/torch.h"8 #include "torchvision/vision.h"9 #include "torchvision/ROIAlign.h"10 #include "torchvision/ROIPool.h"11 #...
std::cerr << "usage: example-app <path-to-exported-script-module>\n"; return -1; } torch::jit::getProfilingMode() = false; torch::jit::getExecutorMode() = false; torch::jit::setGraphExecutorOptimize(false); // Deserialize the ScriptModule from a file using torch::jit::load(). ...