LibtorchUtils Namespace Reference

Functions
template<typename DataType >
void	vectorToTensor (std::vector< DataType > &vector, torch::Tensor &tensor, const bool detach=false)
	Utility function that converts a standard vector to a torch::Tensor. More...
template<typename DataType >
void	tensorToVector (torch::Tensor &tensor, std::vector< DataType > &vector)
	Utility function that converts a torch::Tensor to a standard vector. More...
template void	vectorToTensor< Real > (std::vector< Real > &vector, torch::Tensor &tensor, const bool detach)
template void	tensorToVector< Real > (torch::Tensor &tensor, std::vector< Real > &vector)

Function Documentation

tensorToVector()

template<typename DataType >

void LibtorchUtils::tensorToVector	(	torch::Tensor &	tensor,
		std::vector< DataType > &	vector
	)

Utility function that converts a torch::Tensor to a standard vector.

Template Parameters

DataType

The type of data (float,double, etc.) which the vector is filled with

Parameters

tensor	The tensor which needs to be converted
vector	The output vector

Definition at line 44 of file LibtorchUtils.C.

{
  try
  {
    tensor.data_ptr<DataType>();
  }
  catch (const c10::Error & e)
  {
    mooseError(
        "Cannot cast tensor values to", MooseUtils::prettyCppType<DataType>(), "!\n", e.msg());
  }

  const auto & sizes = tensor.sizes();

  long int max_size = 0;
  for (const auto & dim_size : sizes)
    // We do this comparison because XCode complains if we use std::max
    max_size = dim_size > max_size ? dim_size : max_size;

  mooseAssert(max_size == tensor.numel(), "The given tensor should be one-dimensional!");
  vector = {tensor.data_ptr<DataType>(), tensor.data_ptr<DataType>() + tensor.numel()};
}

tensorToVector< Real >()

template void LibtorchUtils::tensorToVector< Real >	(	torch::Tensor &	tensor,
		std::vector< Real > &	vector
	)

vectorToTensor()

template<typename DataType >

void LibtorchUtils::vectorToTensor	(	std::vector< DataType > &	vector,
		torch::Tensor &	tensor,
		const bool	detach = false
	)

Utility function that converts a standard vector to a torch::Tensor.

Template Parameters

DataType

The type of data (float,double, etc.) which the vector is filled with

Parameters

vector	The vector that needs to be converted
tensor	The output tensor
detach	If the gradient information needs to be detached during the conversion

Definition at line 19 of file LibtorchUtils.C.

Referenced by LibtorchNeuralNetControl::prepareInputTensor().

{
  auto options = torch::TensorOptions();
  if constexpr (std::is_same<DataType, double>::value)
    options = torch::TensorOptions().dtype(at::kDouble);
  else if constexpr (std::is_same<DataType, float>::value)
    options = torch::TensorOptions().dtype(at::kFloat);
  else
    static_assert(Moose::always_false<DataType>,
                  "vectorToTensor is not implemented for the given data type!");

  // We need to clone here because from_blob() doesn't take ownership of the pointer so if it
  // vector goes out of scope before tensor, we get unwanted behavior
  tensor = torch::from_blob(vector.data(), {long(vector.size()), 1}, options).clone();

  if (detach)
    tensor.detach();
}

vectorToTensor< Real >()

template void LibtorchUtils::vectorToTensor< Real >	(	std::vector< Real > &	vector,
		torch::Tensor &	tensor,
		const bool	detach
	)