header only, deep learning framework with no dependencies other than libtorch
The current code works with libtorch1.3, but the latest is libtorch1.4.
Support for libtorch1.3 to libtorch1.4 is being promoted. Please wait. The current changes that we learned from the work It cannot be compiled with visual studio2015. visual studio2017 also requires updates to the latest patches.
with_bias-> bias
transposed seems to be abolished in
torch :: nn :: Conv2dOptions.
Instead Must be changed to
torch :: nn :: ConvTranspose2d.
torch :: nn :: FeatureDropout
also seems to be abolished. instead of Use
torch :: nn :: Dropout2d.
Other
torch :: Tensor & tensor = torch :: tensor ({vec [i]});
Is said to be a tensor and terminates abnormally.
torch :: Tensor & tensor = torch :: tensor (vec [i]);
Must be.
(/std:c++17)
std::byte compile error C2872
compile option -> /D _HAS_STD_BYTE=0
This project aims to be a wrapper for libtorch to make tiny-dnn compatible with GPU. tiny-dnn really great, but unfortunately it can not be calculated on a GPU. At first glance, this header-only framework aims to be used as written in tiny-dnn.
Include path settings
Libtorch_path/include
Libtorch_path/include/torch/csrc/api/include
cpp_torch_path
cpp_torch_path/include
Library path setting
Libtorch_path/lib
cpp_torch_path
Minimum include file
#include "cpp_torch.h"
progress
tiny_dnn
tiny_dnn::progress_display disp(train_images.size());
cpp_torch
cpp_torch::progress_display disp(train_images.size());
cpp_torch::progress_display disp(train_images.size());
data set download
What you can do is still limited.
options | description | default | |
---|---|---|---|
USE_WINDOWS | ON | ||
USE_COLOR_CONSOLE | ON | ||
USE_ZLIB | ON | ||
USE_IMAGE_UTIL | ON | ||
USE_OPENCV_UTIL | OpenCV >= 2.3 | OFF | ex. C:\dev\opencv-3.4.0 |
MNIS
CIFAR10
DCGAN
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This app was created with C # for GUI and C ++ only for core processing. Python is not required.
visual studio 2015,2017,2019
libtorch Please adapt the version of cuda to your environment
BSD 3-Clause License Copyright (c) 2013, Taiga Nomi
tiny_dnn was good, but unfortunately development has clearly stopped. Therefore, we created cpp_torch that can be used instead.
If you are building in C++, Even if Python or pytorch (libtorch) is changed Should work. Will the Python app function correctly next month? Is there a guarantee that customers will not update python, etc.?