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Add options for eval and gradient required #78

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Add options for eval and gradient required #78

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a45983c
Add options for eval and gradient required
ElliottKasoar Dec 4, 2023
0d122fb
Remove c_bool requirement from Fortran
ElliottKasoar Dec 5, 2023
84b149b
Refactor setting eval
ElliottKasoar Dec 5, 2023
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58 changes: 25 additions & 33 deletions src/ctorch.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -43,9 +43,20 @@ constexpr auto get_device(torch_device_t device)
}
}

void set_is_training(torch_jit_script_module_t module, const bool is_training)
{
auto model = static_cast<torch::jit::script::Module*>(module);
if (is_training) {
model->train();
} else {
model->eval();
}
}

torch_tensor_t torch_zeros(int ndim, const int64_t* shape, torch_data_t dtype,
torch_device_t device)
torch_device_t device, const bool requires_grad)
{
torch::AutoGradMode enable_grad(requires_grad);
torch::Tensor* tensor = nullptr;
try {
// This doesn't throw if shape and dimensions are incompatible
Expand All @@ -66,8 +77,9 @@ torch_tensor_t torch_zeros(int ndim, const int64_t* shape, torch_data_t dtype,
}

torch_tensor_t torch_ones(int ndim, const int64_t* shape, torch_data_t dtype,
torch_device_t device)
torch_device_t device, const bool requires_grad)
{
torch::AutoGradMode enable_grad(requires_grad);
torch::Tensor* tensor = nullptr;
try {
// This doesn't throw if shape and dimensions are incompatible
Expand All @@ -88,8 +100,9 @@ torch_tensor_t torch_ones(int ndim, const int64_t* shape, torch_data_t dtype,
}

torch_tensor_t torch_empty(int ndim, const int64_t* shape, torch_data_t dtype,
torch_device_t device)
torch_device_t device, const bool requires_grad)
{
torch::AutoGradMode enable_grad(requires_grad);
torch::Tensor* tensor = nullptr;
try {
// This doesn't throw if shape and dimensions are incompatible
Expand All @@ -109,38 +122,12 @@ torch_tensor_t torch_empty(int ndim, const int64_t* shape, torch_data_t dtype,
return tensor;
}

/*
// Exposes the given data as a Tensor without taking ownership of the original
// data
torch_tensor_t torch_from_blob(void* data, int ndim, const int64_t* shape,
torch_data_t dtype, torch_device_t device)
{
torch::Tensor* tensor = nullptr;
try {
// This doesn't throw if shape and dimensions are incompatible
c10::IntArrayRef vshape(shape, ndim);
tensor = new torch::Tensor;
*tensor = torch::from_blob(
data, vshape,
torch::dtype(get_dtype(dtype))).to(get_device(device));
} catch (const torch::Error& e) {
std::cerr << "[ERROR]: " << e.msg() << std::endl;
delete tensor;
exit(EXIT_FAILURE);
} catch (const std::exception& e) {
std::cerr << "[ERROR]: " << e.what() << std::endl;
delete tensor;
exit(EXIT_FAILURE);
}
return tensor;
}

*/
// New version of torch_from_blob that uses strides
torch_tensor_t torch_from_blob(void* data, int ndim, const int64_t* shape,
const int64_t* strides, torch_data_t dtype,
torch_device_t device)
torch_device_t device, const bool requires_grad)
{
torch::AutoGradMode enable_grad(requires_grad);
torch::Tensor* tensor = nullptr;

try {
Expand Down Expand Up @@ -176,8 +163,11 @@ void torch_tensor_delete(torch_tensor_t tensor)
delete t;
}

torch_jit_script_module_t torch_jit_load(const char* filename)
torch_jit_script_module_t torch_jit_load(const char* filename,
const bool requires_grad,
const bool is_training)
{
torch::AutoGradMode enable_grad(requires_grad);
torch::jit::script::Module* module = nullptr;
try {
module = new torch::jit::script::Module;
Expand All @@ -191,14 +181,16 @@ torch_jit_script_module_t torch_jit_load(const char* filename)
delete module;
exit(EXIT_FAILURE);
}
set_is_training(module, is_training);

return module;
}

void torch_jit_module_forward(const torch_jit_script_module_t module,
const torch_tensor_t *inputs, const int nin,
torch_tensor_t output)
torch_tensor_t output, const bool requires_grad)
{
torch::AutoGradMode enable_grad(requires_grad);
// Here we cast the pointers we recieved in to Tensor objects
auto model = static_cast<torch::jit::script::Module*>(module);
auto in = reinterpret_cast<torch::Tensor* const*>(inputs);
Expand Down
28 changes: 21 additions & 7 deletions src/ctorch.h
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Original file line number Diff line number Diff line change
Expand Up @@ -38,29 +38,35 @@ typedef enum { torch_kCPU, torch_kCUDA } torch_device_t;
* @param shape of the Tensor
* @param data type of the elements of the Tensor
* @param device used (cpu, CUDA, etc.)
* @param whether gradient is required
*/
EXPORT_C torch_tensor_t torch_zeros(int ndim, const int64_t* shape,
torch_data_t dtype, torch_device_t device);
torch_data_t dtype, torch_device_t device,
const bool requires_grad);

/**
* Function to generate a Torch Tensor of ones
* @param number of dimensions of the Tensor
* @param shape of the Tensor
* @param data type of the elements of the Tensor
* @param device used (cpu, CUDA, etc.)
* @param whether gradient is required
*/
EXPORT_C torch_tensor_t torch_ones(int ndim, const int64_t* shape,
torch_data_t dtype, torch_device_t device);
torch_data_t dtype, torch_device_t device,
const bool requires_grad);

/**
* Function to generate an empty Torch Tensor
* @param number of dimensions of the Tensor
* @param shape of the Tensor
* @param data type of the elements of the Tensor
* @param device used (cpu, CUDA, etc.)
* @param whether gradient is required
*/
EXPORT_C torch_tensor_t torch_empty(int ndim, const int64_t* shape,
torch_data_t dtype, torch_device_t device);
torch_data_t dtype, torch_device_t device,
const bool requires_grad);

/**
* Function to create a Torch Tensor from memory location given extra information
Expand All @@ -70,13 +76,15 @@ EXPORT_C torch_tensor_t torch_empty(int ndim, const int64_t* shape,
* @param strides to take through data
* @param data type of the elements of the Tensor
* @param device used (cpu, CUDA, etc.)
* @param whether gradient is required
* @return Torch Tensor interpretation of the data pointed at
*/
EXPORT_C torch_tensor_t torch_from_blob(void* data, int ndim,
const int64_t* shape,
const int64_t* strides,
torch_data_t dtype,
torch_device_t device);
torch_device_t device,
const bool requires_grad);

/**
* Function to print out a Torch Tensor
Expand All @@ -93,12 +101,14 @@ EXPORT_C void torch_tensor_print(const torch_tensor_t tensor);
* @param shape of the Tensor
* @param data type of the elements of the Tensor
* @param device used (cpu, CUDA, etc.)
* @param whether gradient is required
* @return Torch Tensor interpretation of the data pointed at
*/
EXPORT_C torch_tensor_t torch_from_blob_f(void* data, int ndim,
const int64_t* shape,
torch_data_t dtype,
torch_device_t device);
torch_device_t device,
const bool requires_grad);

/**
* Function to delete a Torch Tensor to clean up
Expand All @@ -113,20 +123,24 @@ EXPORT_C void torch_tensor_delete(torch_tensor_t tensor);
/**
* Function to load in a Torch model from a TorchScript file and store in a Torch Module
* @param filename where TorchScript description of model is stored
* @param whether gradient is required
* @param whether model is being trained
* @return Torch Module loaded in from file
*/
EXPORT_C torch_jit_script_module_t torch_jit_load(const char* filename);
EXPORT_C torch_jit_script_module_t torch_jit_load(const char* filename,
const bool requires_grad, const bool is_training);

/**
* Function to run the `forward` method of a Torch Module
* @param Torch Module containing the model
* @param vector of Torch Tensors as inputs to the model
* @param number of input Tensors in the input vector
* @param the output Tensor from running the model
* @param whether gradient is required
*/
EXPORT_C void torch_jit_module_forward(const torch_jit_script_module_t module,
const torch_tensor_t *inputs, const int nin,
torch_tensor_t output);
torch_tensor_t output, const bool requires_grad);

/**
* Function to delete a Torch Module to clean up
Expand Down
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