Hi, when i wanna try the demo proposed by goldsborough. I strike an error and hope someone could solve this. Thank you very much.
Enviroment:
gcc: 4.8.5
g++: 4.8.5
cuda: 9.0
system: ubuntu18.04
libtorch: https://download.pytorch.org/libtorch/nightly/cu90/libtorch-shared-with-deps-latest.zip
cmake: 3.13
Code: mnist_example.cpp
#include <torch/torch.h>
// Define a new Module.
struct Net : torch::nn::Module {
Net() {
// Construct and register two Linear submodules.
fc1 = register_module("fc1", torch::nn::Linear(8, 64));
fc2 = register_module("fc2", torch::nn::Linear(64, 1));
}
// Implement the Net's algorithm.
torch::Tensor forward(torch::Tensor x) {
// Use one of many tensor manipulation functions.
x = torch::relu(fc1->forward(x));
// bug fixed 1
x = torch::dropout(x, 0.5, true);
x = torch::sigmoid(fc2->forward(x));
return x;
}
// Use one of many "standard library" modules.
torch::nn::Linear fc1{nullptr}, fc2{nullptr};
};
// Create a new Net.
Net net;
// Create a multi-threaded data loader for the MNIST dataset.
auto data_loader =
torch::data::data_loader(torch::data::datasets::MNIST("./data"));
// Instantiate an SGD optimization algorithm to update our Net's parameters.
torch::optim::SGD optimizer(net.parameters(), 0.1);
int main() {
for (size_t epoch = 1; epoch <= 20; ++epoch) {
size_t batch_index = 0;
// Iterate the data loader to yield batches from the dataset.
for (auto batch : data_loader) {
// Reset gradients.
optimizer.zero_grad();
// Execute the model on the input data.
auto prediction = model.forward(batch.data);
// Compute a loss value to judge the prediction of our model.
auto loss = torch::binary_cross_entropy(prediction, batch.label);
// Compute gradients of the loss w.r.t. the parameters of our model.
loss.backward();
// Update the parameters based on the calculated gradients.
optimizer.step();
if (batch_index++ % 10 == 0) {
std::cout << "Epoch: " << epoch << " | Batch: " << batch_index
<< " | Loss: " << loss << std::endl;
// Serialize your model periodically as a checkpoint.
torch::save(net, "net.pt");
}
}
}
CMakeLists.txt
cmake_minimum_required(VERSION 3.0 FATAL_ERROR)
project(mnist_example)
find_package(Torch REQUIRED)
option(DOWNLOAD_MNIST "Download the MNIST dataset from the internet" ON)
if (DOWNLOAD_MNIST)
message(STATUS "Downloading MNIST dataset")
execute_process(
COMMAND python ${CMAKE_CURRENT_LIST_DIR}/download_mnist.py
-d ${CMAKE_BINARY_DIR}/data
ERROR_VARIABLE DOWNLOAD_ERROR)
if (DOWNLOAD_ERROR)
message(FATAL_ERROR "Error downloading MNIST dataset: ${DOWNLOAD_ERROR}")
endif()
endif()
add_executable(mnist_example mnist_example.cpp)
target_compile_features(mnist_example PUBLIC cxx_range_for)
target_link_libraries(mnist_example "${TORCH_LIBRARIES}")
set_property(TARGET mnist_example PROPERTY CXX_STANDARD 11)
download_mnist.py
The error is
-- Configuring done
-- Generating done
-- Build files have been written to: /home/samuel/gaodaiheng/pytorch_prac/PyTorch1.0/Cpp_usage/end2end_example/build
Scanning dependencies of target mnist_example
[ 50%] Building CXX object CMakeFiles/mnist_example.dir/mnist_mlp.cpp.o
/home/samuel/gaodaiheng/pytorch_prac/PyTorch1.0/Cpp_usage/end2end_example/mnist_mlp.cpp:30:3: error: ‘data_loader’ is not a member of ‘torch::data’
torch::data::data_loader(torch::data::datasets::MNIST("./data"));
^
/home/samuel/gaodaiheng/pytorch_prac/PyTorch1.0/Cpp_usage/end2end_example/mnist_mlp.cpp:30:3: note: suggested alternative:
/home/samuel/gaodaiheng/pytorch_prac/PyTorch1.0/Cpp_usage/end2end_example/mnist_mlp.cpp:29:6: note: ‘data_loader’
auto data_loader =
^
/home/samuel/gaodaiheng/pytorch_prac/PyTorch1.0/Cpp_usage/end2end_example/mnist_mlp.cpp: In function ‘int main()’:
/home/samuel/gaodaiheng/pytorch_prac/PyTorch1.0/Cpp_usage/end2end_example/mnist_mlp.cpp:38:24: error: unable to deduce ‘auto&&’ from ‘data_loader’
for (auto batch : data_loader) {
^
/home/samuel/gaodaiheng/pytorch_prac/PyTorch1.0/Cpp_usage/end2end_example/mnist_mlp.cpp:42:26: error: ‘model’ was not declared in this scope
auto prediction = model.forward(batch.data);
^
/home/samuel/gaodaiheng/pytorch_prac/PyTorch1.0/Cpp_usage/end2end_example/mnist_mlp.cpp:57:2: error: expected ‘}’ at end of input
}
^
In file included from /home/samuel/gaodaiheng/pytorch_prac/PyTorch1.0/Cpp_usage/end2end_example/libtorch_cpu/include/torch/csrc/api/include/torch/all.h:8:0,
from /home/samuel/gaodaiheng/pytorch_prac/PyTorch1.0/Cpp_usage/end2end_example/libtorch_cpu/include/torch/csrc/api/include/torch/torch.h:3,
from /home/samuel/gaodaiheng/pytorch_prac/PyTorch1.0/Cpp_usage/end2end_example/mnist_mlp.cpp:1:
/home/samuel/gaodaiheng/pytorch_prac/PyTorch1.0/Cpp_usage/end2end_example/libtorch_cpu/include/torch/csrc/api/include/torch/serialize.h: In instantiation of ‘void torch::save(const Value&, SaveToArgs&& ...) [with Value = Net; SaveToArgs = {const char (&)[7]}]’:
/home/samuel/gaodaiheng/pytorch_prac/PyTorch1.0/Cpp_usage/end2end_example/mnist_mlp.cpp:54:35: required from here
/home/samuel/gaodaiheng/pytorch_prac/PyTorch1.0/Cpp_usage/end2end_example/libtorch_cpu/include/torch/csrc/api/include/torch/serialize.h:39:11: error: no match for ‘operator<<’ (operand types are ‘torch::serialize::OutputArchive’ and ‘const Net’)
archive << value;
...
