A Class Reference

does bound shape inference given a C2 net. More...

Inheritance diagram for A:

Public Member Functions
int	forward ()
Public Member Functions inherited from torch::nn::Module
	Module (std::string name)
	Tells the base Module about the name of the submodule.
	Module ()
	Constructs the module without immediate knowledge of the submodule's name. More...
const std::string &	name () const noexcept
	Returns the name of the Module. More...
virtual std::shared_ptr< Module >	clone (const optional< Device > &device=nullopt) const
	Performs a recursive deep copy of the module and all its registered parameters, buffers and submodules. More...
void	apply (const ModuleApplyFunction &function)
	Applies the function to the Module and recursively to every submodule. More...
void	apply (const ConstModuleApplyFunction &function) const
	Applies the function to the Module and recursively to every submodule. More...
void	apply (const NamedModuleApplyFunction &function, const std::string &name_prefix=std::string())
	Applies the function to the Module and recursively to every submodule. More...
void	apply (const ConstNamedModuleApplyFunction &function, const std::string &name_prefix=std::string()) const
	Applies the function to the Module and recursively to every submodule. More...
void	apply (const ModulePointerApplyFunction &function) const
	Applies the function to the Module and recursively to every submodule. More...
void	apply (const NamedModulePointerApplyFunction &function, const std::string &name_prefix=std::string()) const
	Applies the function to the Module and recursively to every submodule. More...
std::vector< Tensor >	parameters (bool recurse=true) const
	Returns the parameters of this Module and if recurse is true, also recursively of every submodule. More...
OrderedDict< std::string, Tensor >	named_parameters (bool recurse=true) const
	Returns an OrderedDict with the parameters of this Module along with their keys, and if recurse is true also recursively of every submodule. More...
std::vector< Tensor >	buffers (bool recurse=true) const
	Returns the buffers of this Module and if recurse is true, also recursively of every submodule. More...
OrderedDict< std::string, Tensor >	named_buffers (bool recurse=true) const
	Returns an OrderedDict with the buffers of this Module along with their keys, and if recurse is true also recursively of every submodule. More...
std::vector< std::shared_ptr< Module > >	modules (bool include_self=true) const
	Returns the submodules of this Module (the entire submodule hierarchy) and if include_self is true, also inserts a shared_ptr to this module in the first position. More...
OrderedDict< std::string, std::shared_ptr< Module > >	named_modules (const std::string &name_prefix=std::string(), bool include_self=true) const
	Returns an OrderedDict of he submodules of this Module (the entire submodule hierarchy) and thei keys, and if include_self is true, also inserts a shared_ptr to this module in the first position. More...
std::vector< std::shared_ptr< Module > >	children () const
	Returns the direct submodules of this Module.
OrderedDict< std::string, std::shared_ptr< Module > >	named_children () const
	Returns an OrderedDict of the direct submodules of this Module and their keys. More...
virtual void	train (bool on=true)
	Enables "training" mode.
void	eval ()
	Calls train(false) to enable "eval" mode. More...
virtual bool	is_training () const noexcept
	True if the module is in training mode. More...
virtual void	to (torch::Device device, torch::Dtype dtype, bool non_blocking=false)
	Recursively casts all parameters to the given dtype and device. More...
virtual void	to (torch::Dtype dtype, bool non_blocking=false)
	Recursively casts all parameters to the given dtype. More...
virtual void	to (torch::Device device, bool non_blocking=false)
	Recursively moves all parameters to the given device. More...
virtual void	zero_grad ()
	Recursively zeros out the grad value of each registered parameter.
template<typename ModuleType >
ModuleType::ContainedType *	as () noexcept
	Attempts to cast this Module to the given ModuleType. More...
template<typename ModuleType >
const ModuleType::ContainedType *	as () const noexcept
	Attempts to cast this Module to the given ModuleType. More...
template<typename ModuleType , typename = torch::detail::disable_if_module_holder_t<ModuleType>>
ModuleType *	as () noexcept
	Attempts to cast this Module to the given ModuleType. More...
template<typename ModuleType , typename = torch::detail::disable_if_module_holder_t<ModuleType>>
const ModuleType *	as () const noexcept
	Attempts to cast this Module to the given ModuleType. More...
virtual void	save (serialize::OutputArchive &archive) const
	Serializes the Module into the given OutputArchive.
virtual void	load (serialize::InputArchive &archive)
	Deserializes the Module from the given InputArchive.
virtual void	pretty_print (std::ostream &stream) const
	Streams a pretty representation of the Module into the given stream. More...

Additional Inherited Members
Public Types inherited from torch::nn::Module
using	ModuleApplyFunction = std::function< void(Module &)>
using	ConstModuleApplyFunction = std::function< void(const Module &)>
using	NamedModuleApplyFunction = std::function< void(const std::string &, Module &)>
using	ConstNamedModuleApplyFunction = std::function< void(const std::string &, const Module &)>
using	ModulePointerApplyFunction = std::function< void(const std::shared_ptr< Module > &)>
using	NamedModulePointerApplyFunction = std::function< void(const std::string &, const std::shared_ptr< Module > &)>
Protected Member Functions inherited from torch::nn::Module
Tensor &	register_parameter (std::string name, Tensor tensor, bool requires_grad=true)
	Registers a parameter with this Module. More...
Tensor &	register_buffer (std::string name, Tensor tensor)
	Registers a buffer with this Module. More...
template<typename ModuleType >
std::shared_ptr< ModuleType >	register_module (std::string name, std::shared_ptr< ModuleType > module)
	Registers a submodule with this Module. More...
template<typename ModuleType >
std::shared_ptr< ModuleType >	register_module (std::string name, ModuleHolder< ModuleType > module_holder)
	Registers a submodule with this Module. More...

Detailed Description

does bound shape inference given a C2 net.

Depending on its type, each op have a maximum shape that it accepts. We define some initial bound for certain dimension, for example max batch size or max sequnce lookup size. And the inference will first infer the input size and then propagates the bound shape down the network. For now the variable part (bound part) is the first dimension of the shape, which usually corresponds to the batch size or sequence lookup size.

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

• caffe2/opt/bound_shape_inferencer.h
• test/cpp/api/static.cpp