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Caffe2 - C++ API
A deep learning, cross platform ML framework
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Caffe2 - C++ API
A deep learning, cross platform ML framework
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Applies a linear transformation with optional bias. More...
#include <linear.h>
Public Member Functions | |
| LinearImpl (int64_t in, int64_t out) | |
| LinearImpl (LinearOptions options) | |
| void | reset () override |
reset() must perform initialization of all members with reference semantics, most importantly parameters, buffers and submodules. More... | |
| void | pretty_print (std::ostream &stream) const override |
Pretty prints the Linear module into the given stream. | |
| Tensor | forward (const Tensor &input) |
Transforms the input tensor by multiplying with the weight and optionally adding the bias, if with_bias is true in the options. More... | |
 Public Member Functions inherited from torch::nn::Cloneable< LinearImpl > | |
| std::shared_ptr< Module > | clone (const optional< Device > &device=nullopt) const override |
Performs a recursive "deep copy" of the Module, such that all parameters and submodules in the cloned module are different from those in the original module. More... | |
| 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... | |
| 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. | |
Data Fields | |
| LinearOptions | options |
| The options used to configure this module. | |
| Tensor | weight |
| The learned weight. | |
| Tensor | bias |
| The learned bias. 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... | |
Transforms the input tensor by multiplying with the weight and optionally adding the bias, if with_bias is true in the options.
Definition at line 37 of file linear.cpp.
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overridevirtual |
reset() must perform initialization of all members with reference semantics, most importantly parameters, buffers and submodules.
Implements torch::nn::Cloneable< LinearImpl >.
Definition at line 17 of file linear.cpp.
| Tensor torch::nn::LinearImpl::bias |
1.8.11
