libtorch

I want to run Libtorch (Pytorch C++ Frontend) in OpenFrameworks

╄→гoц情女王★ 提交于 2021-02-10 18:41:57
问题 All. I want to run Libtorch (Pytorch C++ Frontend) in OpenFrameworks. LibTorch Site: https://pytorch.org/tutorials/advanced/cpp_frontend.html If LibTorch runs in OpenFrameworks, it will be very powerful Deep Solution IDE (deep learning + GUI Production for OSX, Win10, & Linux). But I can’t include <torch/torch.h> in XCode. At CMake method, CMakeLists.txt is like this: cmake_minimum_required(VERSION 3.0 FATAL_ERROR) project(dcgan) find_package(Torch REQUIRED) add_executable(dcgan dcgan.cpp)

How to convert a list of tensors into a torch::Tensor?

我的未来我决定 提交于 2021-02-10 04:24:22
问题 I'm trying to convert the following Python code into its equivalent libtorch: tfm = np.float32([[A[0, 0], A[1, 0], A[2, 0]], [A[0, 1], A[1, 1], A[2, 1]] ]) In Pytorch we could simply use torch.stack or simply use a torch.tensor() like below: tfm = torch.tensor([[A_tensor[0,0], A_tensor[1,0],0], [A_tensor[0,1], A_tensor[1,1],0] ]) However, in libtorch, this doesn't hold, that is I can not simply do: auto tfm = torch::tensor ({{A.index({0,0}), A.index({1,0}), A.index({2,0})}, {A.index({0,1}), A

How to convert a list of tensors into a torch::Tensor?

二次信任 提交于 2021-02-10 04:21:37
问题 I'm trying to convert the following Python code into its equivalent libtorch: tfm = np.float32([[A[0, 0], A[1, 0], A[2, 0]], [A[0, 1], A[1, 1], A[2, 1]] ]) In Pytorch we could simply use torch.stack or simply use a torch.tensor() like below: tfm = torch.tensor([[A_tensor[0,0], A_tensor[1,0],0], [A_tensor[0,1], A_tensor[1,1],0] ]) However, in libtorch, this doesn't hold, that is I can not simply do: auto tfm = torch::tensor ({{A.index({0,0}), A.index({1,0}), A.index({2,0})}, {A.index({0,1}), A

How to convert a list of tensors into a torch::Tensor?

∥☆過路亽.° 提交于 2021-02-10 04:21:07
问题 I'm trying to convert the following Python code into its equivalent libtorch: tfm = np.float32([[A[0, 0], A[1, 0], A[2, 0]], [A[0, 1], A[1, 1], A[2, 1]] ]) In Pytorch we could simply use torch.stack or simply use a torch.tensor() like below: tfm = torch.tensor([[A_tensor[0,0], A_tensor[1,0],0], [A_tensor[0,1], A_tensor[1,1],0] ]) However, in libtorch, this doesn't hold, that is I can not simply do: auto tfm = torch::tensor ({{A.index({0,0}), A.index({1,0}), A.index({2,0})}, {A.index({0,1}), A

How to solve GTest and LibTorch linkage conflict

爷,独闯天下 提交于 2021-01-29 09:32:55
问题 This question follows my precedent one. I'm writing a C++ program with OpenCV, Torch and NumCpp. The program compiles and works fine for now, but I need to write unit tests. I've followed google's tutorial to build GTest and GMock inside my project, but it fails. When I don't link Torch libraries, that works. Error when linking GTest + Torch : /usr/bin/ld: CMakeFiles/TryGTest_test.dir/test/boxTest.cpp.o: in function `testing::AssertionResult testing::internal::CmpHelperEQFailure<int, int>