Inheritance diagram for torch::optim::Adagrad:

Public Member Functions
template<typename ParameterContainer >
	Adagrad (ParameterContainer &&parameters, const AdagradOptions &options)

void	step () override
	Adapted from https://github.com/pytorch/pytorch/blob/master/torch/optim/adagrad.py.

void	save (serialize::OutputArchive &archive) const override
	Serializes the optimizer state into the given `archive`.

void	load (serialize::InputArchive &archive) override
	Deserializes the optimizer state from the given `archive`.

Public Member Functions inherited from torch::optim::detail::OptimizerBase
	OptimizerBase (std::vector< Tensor > parameters)
	Constructs the `Optimizer` from a vector of parameters.

void	add_parameters (const std::vector< Tensor > &parameters)
	Adds the given vector of parameters to the optimizer's parameter list.

virtual void	zero_grad ()
	Zeros out the gradients of all parameters.

const std::vector< Tensor > &	parameters () const noexcept
	Provides a const reference to the parameters this optimizer holds.

std::vector< Tensor > &	parameters () noexcept
	Provides a reference to the parameters this optimizer holds.

size_t	size () const noexcept
	Returns the number of parameters referenced by the optimizer.

Additional Inherited Members
Protected Member Functions inherited from torch::optim::detail::OptimizerBase
template<typename T >
T &	buffer_at (std::vector< T > &buffers, size_t index)
	Accesses a buffer at the given index. More...

Tensor &	buffer_at (std::vector< Tensor > &buffers, size_t index)
	Accesses a buffer at the given index, converts it to the type of the parameter at the corresponding index (a no-op if they match). More...

Protected Attributes inherited from torch::optim::detail::OptimizerBase
std::vector< Tensor >	parameters_
	The parameters this optimizer optimizes.

Detailed Description

Definition at line 28 of file adagrad.h.

The documentation for this class was generated from the following files:

Public Member Functions