Functions
Graph	LoadJSON (const std::string &json_str)
	Load a graph from JSON string, redirects to "LoadJSON" pass. More...

std::string	SaveJSON (Graph graph)
	Save a graph to json, redirects to "SaveJSON" pass. More...

std::string	PrintGraphIR (Graph graph)
	Print graph ir. More...

Graph	OrderMutation (Graph src)
	Add control flow dependencies between nodes. More...

Graph	InferShape (Graph graph, ShapeVector shape_inputs, std::string shape_attr_key="")
	Infer shapes in the graph given the information. More...

Graph	InferType (Graph graph, DTypeVector dtype_inputs, std::string dtype_attr_key="")
	Infer types in the graph given the information. More...

Graph	PlaceDevice (Graph graph, std::string device_group_attr_key, DeviceAssignMap device_assign_map, std::string device_copy_op)
	Place the devices for each operator in the graph. More...

Graph	Gradient (Graph graph, std::vector< NodeEntry > ys, std::vector< NodeEntry > xs, std::vector< NodeEntry > ys_out_grad, std::function< NodeEntry(std::vector< NodeEntry > &&inputs)> aggregate_fun=nullptr, std::function< int(const Node &node)> mirror_fun=nullptr, std::function< NodeEntry(const NodeEntry &src, const NodeEntry &like)> attr_hint_fun=nullptr, std::vector< const Op * > zero_ops=std::vector< const Op * >(), std::string copy_op_str=std::string())
	Get the gradient graph whose outputs are gradients of xs wrt to ys. More...

Function Documentation

Graph nnvm::pass::Gradient	(	Graph	graph,
		std::vector< NodeEntry >	ys,
		std::vector< NodeEntry >	xs,
		std::vector< NodeEntry >	ys_out_grad,
		std::function< NodeEntry(std::vector< NodeEntry > &&inputs)>	aggregate_fun = `nullptr`,
		std::function< int(const Node &node)>	mirror_fun = `nullptr`,
		std::function< NodeEntry(const NodeEntry &src, const NodeEntry &like)>	attr_hint_fun = `nullptr`,
		std::vector< const Op * >	zero_ops = `std::vector<const Op*>()`,
		std::string	copy_op_str = `std::string()`
	)

inline

Get the gradient graph whose outputs are gradients of xs wrt to ys.

Parameters

graph	The input graph.
ys	The entries we want to take gradient from.
xs	The input to take gradient with respect to.
ys_out_grad	The symbol for additional gradient to be propagate back to y.
aggregate_fun	Aggregation function applied to aggregate the inputs.
mirror_fun	Optional mirror function to do mirror optimization and save memory.
attr_hint_fun	Optional, hint function to output a node that like src, but its attr is same as like.
zero_ops	Optional, list of operators that outputs a single zero array. The first one must be zeros_like.
copy_op_str	Optional, name of the copy operation required to handle duplicates on the edge of the graph

Returns: A new graph, whose outputs correspond to inputs of xs.

Graph nnvm::pass::InferShape	(	Graph	graph,
		ShapeVector	shape_inputs,
		std::string	shape_attr_key = `""`
	)

inline

Infer shapes in the graph given the information.

Parameters

graph	The input graph.
shape_inputs	The shapes of input symbols to the graph.
shape_attr_key	The key to the node attribute that can indicate shape. This is the place where manual hint for shapes could be injected.

Returns: A graph with new attribute "shape" containing inferred shape of each NodeEntry. The index of ShapeVector is given by graph.indexed_graph().entry_id.

Graph nnvm::pass::InferType	(	Graph	graph,
		DTypeVector	dtype_inputs,
		std::string	dtype_attr_key = `""`
	)

inline

Infer types in the graph given the information.

Parameters

graph	The input graph.
dtype_inputs	The types of input symbols to the graph.
dtype_attr_key	The key to the node attribute that can indicate types. This is the place where manual hint for types could be injected.

Returns: A graph with new attribute "dtype" containing inferred type of each NodeEntry. The index of ShapeVector is given by graph.indexed_graph().entry_id.

Graph nnvm::pass::LoadJSON ( const std::string & json_str )

inline

Load a graph from JSON string, redirects to "LoadJSON" pass.

Parameters

json_str The json string.

Returns: Loaded graph.

Graph nnvm::pass::OrderMutation ( Graph src )

inline

Add control flow dependencies between nodes.

This function will enforce the correct order between write (mutable operators) and read (immutable operators) to sovle write-after-read and read-after-write problems.

Parameters

src	The input graph.

Returns: A graph with proper control flow dependencies added.

Graph nnvm::pass::PlaceDevice	(	Graph	graph,
		std::string	device_group_attr_key,
		DeviceAssignMap	device_assign_map,
		std::string	device_copy_op
	)

inline

Place the devices for each operator in the graph.

Current device placement is quite simple. Each operator is assigned to a "group" (stored in device_group_attr_key attribute). Each group is assigned to a device (stored in device_assign_map attribute). Operators will be placed to the device assigned to its group. Copy operators will be injected if cross device reference happens.

Parameters

graph	The input graph.
device_group_attr_key	The attribute name for hints of device group.
device_assign_map	The assignment map of device.
device_copy_op	The name of copy op to be inserted when cross device copy happened.

Returns: A graph with new attribute "device", cotaining device information of each node.

std::string nnvm::pass::PrintGraphIR ( Graph graph )

inline

Print graph ir.

Parameters

graph The graph to be printed

Returns: The graph ir string.

std::string nnvm::pass::SaveJSON ( Graph graph )

inline

Save a graph to json, redirects to "SaveJSON" pass.

Parameters

graph The graph to be saved as json format.

Returns: The json string.

Functions

Function Documentation