mxnet::Imperative Class Reference

runtime functions for NDArray More...

#include <imperative.h>

Collaboration diagram for mxnet::Imperative:

Classes
class	AGInfo
class	CachedOp

Public Member Functions
bool	is_training () const
	whether operator recording is on. More...
bool	set_is_training (bool is_train)
	turn on or turn off operator recording for autograd. More...
bool	is_recording () const
	whether operator recording is on. More...
bool	set_is_recording (bool is_recording)
	turn on or turn off operator recording for autograd. More...
void	RecordOp (nnvm::NodeAttrs &&attrs, const std::vector< NDArray * > &inputs, const std::vector< NDArray * > &outputs, const OpStatePtr &state=OpStatePtr(), std::vector< bool > *p_save_inputs=nullptr, std::vector< bool > *p_save_outputs=nullptr)
	to record operator, return corresponding node. More...
OpStatePtr	Invoke (const Context &default_ctx, const nnvm::NodeAttrs &attrs, const std::vector< NDArray * > &inputs, const std::vector< NDArray * > &outputs)
OpStatePtr	InvokeOp (const Context &ctx, const nnvm::NodeAttrs &attrs, const std::vector< NDArray * > &inputs, const std::vector< NDArray * > &outputs, const std::vector< OpReqType > &req, const DispatchMode dispatch_mode, OpStatePtr state=OpStatePtr())
void	MarkVariables (const std::vector< NDArray * > &variables, const std::vector< mx_uint > &grad_reqs, const std::vector< NDArray * > &gradients)
	mark variables for computing gradients. More...
std::vector< NDArray * >	Backward (const std::vector< NDArray * > &outputs, const std::vector< NDArray * > &ograds, const std::vector< NDArray * > &variables, bool is_train, bool retain_graph, bool create_graph)
	compute the gradient of outputs w.r.t variables. More...

Static Public Member Functions
static Imperative *	Get ()

Friends
class	NDArray

Detailed Description

runtime functions for NDArray

Member Function Documentation

std::vector<NDArray*> mxnet::Imperative::Backward	(	const std::vector< NDArray * > &	outputs,
		const std::vector< NDArray * > &	ograds,
		const std::vector< NDArray * > &	variables,
		bool	is_train,
		bool	retain_graph,
		bool	create_graph
	)

compute the gradient of outputs w.r.t variables.

static Imperative* mxnet::Imperative::Get ( )

static

Returns

AutogradRuntime singleton

OpStatePtr mxnet::Imperative::Invoke	(	const Context &	default_ctx,
		const nnvm::NodeAttrs &	attrs,
		const std::vector< NDArray * > &	inputs,
		const std::vector< NDArray * > &	outputs
	)

OpStatePtr mxnet::Imperative::InvokeOp	(	const Context &	ctx,
		const nnvm::NodeAttrs &	attrs,
		const std::vector< NDArray * > &	inputs,
		const std::vector< NDArray * > &	outputs,
		const std::vector< OpReqType > &	req,
		const DispatchMode	dispatch_mode,
		OpStatePtr	state = OpStatePtr()
	)

bool mxnet::Imperative::is_recording ( ) const

inline

whether operator recording is on.

bool mxnet::Imperative::is_training ( ) const

inline

whether operator recording is on.

void mxnet::Imperative::MarkVariables	(	const std::vector< NDArray * > &	variables,
		const std::vector< mx_uint > &	grad_reqs,
		const std::vector< NDArray * > &	gradients
	)

mark variables for computing gradients.

void mxnet::Imperative::RecordOp	(	nnvm::NodeAttrs &&	attrs,
		const std::vector< NDArray * > &	inputs,
		const std::vector< NDArray * > &	outputs,
		const OpStatePtr &	state = OpStatePtr(),
		std::vector< bool > *	p_save_inputs = nullptr,
		std::vector< bool > *	p_save_outputs = nullptr
	)

to record operator, return corresponding node.

bool mxnet::Imperative::set_is_recording ( bool  is_recording )

inline

turn on or turn off operator recording for autograd.

bool mxnet::Imperative::set_is_training ( bool  is_train )

inline

turn on or turn off operator recording for autograd.

Friends And Related Function Documentation

friend class NDArray

friend

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

• include/mxnet/imperative.h