lbann::categorical_random_layer< TensorDataType, T_layout, Dev > Class Template Reference
Random categorical outputs. More...
#include <categorical_random.hpp>
Inheritance diagram for lbann::categorical_random_layer< TensorDataType, T_layout, Dev >:
Collaboration diagram for lbann::categorical_random_layer< TensorDataType, T_layout, Dev >:
Public Member Functions | |
| categorical_random_layer (lbann_comm *comm) | |
| categorical_random_layer * | copy () const override |
| Copy function. This function dynamically allocates memory for a layer instance and instantiates a copy. The caller is responsible for deallocating the instance. More... | |
| std::string | get_type () const override |
| Get the layer type's name. More... | |
| data_layout | get_data_layout () const override |
| Get data layout of the data tensors. We assume that the data layouts of the previous activations, activations, previous error signals, and error signals are the same. Each concrete layer that is templated on its data layout should override this function to return its template parameter. More... | |
| El::Device | get_device_allocation () const override |
| Get the device allocation for the data tensors. We assume that the decice allocation of the previous activations, activations, previous error signals, and error signals are the same. Each concrete layer that is templated on its device allocation should override this function to return its template parameter. More... | |
| bool | can_run_inplace () const override |
| If True, the computation can run in-place (feeding each input activations tensor as the corresponding output activations) More... | |
| int | get_backprop_requirements () const override |
| Returns the necessary tensors for computing backpropagation. More... | |
Serialization | |
| template<typename ArchiveT > | |
| void | serialize (ArchiveT &ar) |
 Public Member Functions inherited from lbann::data_type_layer< TensorDataType > | |
| data_type_layer (lbann_comm *, bool persistent_error_signals=false) | |
| virtual | ~data_type_layer ()=default |
| std::string | get_datatype_name () const override |
| void | forward_prop () final |
| void | summarize_matrices (lbann_summary &summarizer, int step) override |
| void | check_setup () override |
| const OutputAbsDistMatrixType & | get_activations (const Layer &child) const override |
| OutputAbsDistMatrixType & | get_activations (int child_index=0) |
| const OutputAbsDistMatrixType & | get_activations (int child_index=0) const |
| const InputAbsDistMatrixType & | get_error_signals (const Layer &parent) const override |
| InputAbsDistMatrixType & | get_error_signals (int parent_index=0) |
| const InputAbsDistMatrixType & | get_error_signals (int parent_index=0) const |
| El::Int | current_output_mini_batch_size () const override |
| El::Int | infer_mini_batch_size_from_parents_or_default_to_current () const override |
| OutputAbsDistMatrixType & | get_temp_grad () |
| InputAbsDistMatrixType & | get_branch_tag_input (int tag) |
| std::vector< std::unique_ptr< InputAbsDistMatrixType > > & | get_branch_tag_input_vector () |
| std::vector< std::unique_ptr< OutputAbsDistMatrixType > > & | get_all_activations () |
| std::vector< std::unique_ptr< InputAbsDistMatrixType > > & | get_all_prev_activations () |
| std::vector< std::unique_ptr< OutputAbsDistMatrixType > > & | get_all_prev_error_signals () |
| std::vector< std::unique_ptr< InputAbsDistMatrixType > > & | get_all_error_signals () |
| OutputAbsMatrixType & | get_local_activations (int child_index=0) |
| const OutputAbsMatrixType & | get_local_activations (int child_index=0) const |
| InputAbsMatrixType & | get_local_error_signals (int parent_index=0) |
| const InputAbsMatrixType & | get_local_error_signals (int parent_index=0) const |
| void | set_keep_error_signals (bool) override |
| Set whether to keep or dynamically reallocate error signals. More... | |
| El::mpi::Comm & | get_subgrid_comm () |
| void | serialize (ArchiveT &ar) |
| Public Member Functions inherited from lbann::Layer | |
| void | write_proto (lbann_data::Layer &proto) const |
| Write layer to proto file. More... | |
| lbann_comm * | get_comm () const |
| int | get_grid_tag () const noexcept |
| Identifying tag for process grid. More... | |
| void | set_grid_tag (int tag) |
| Set process grid. More... | |
| bool | runs_inplace () const |
| If true, the layer will run in-place (the input and output activations point to the same tensor). Value is set during graph setup (in setup_pointers) based on layer traits and neighboring layers. More... | |
| bool | distconv_enabled () const |
| Indicate whether distconv is enabled. More... | |
| Layer () | |
| virtual | ~Layer ()=default |
| void | set_name (const std::string name) |
| Set the layer instance's name. Each layer in a model should have a unique, preferably human-readable, name. More... | |
| void | set_model (model *m) |
| Set the model that manages this layer. More... | |
| std::string | get_name () const |
| Get the layer instance's name. More... | |
| model * | get_model () const noexcept |
| Get a reference to the model that manages this layer. More... | |
| virtual description | get_description () const |
| Human-readable description. More... | |
| int | get_expected_num_parent_layers () const noexcept |
| Get expected number of parent layers. A negative value indicates no limit. More... | |
| int | get_expected_num_child_layers () const noexcept |
| Get expected number of child layers. A negative value indicates no limit. More... | |
| ParallelStrategy & | get_parallel_strategy () noexcept |
| Get the parallel strategy for the layer. More... | |
| ParallelStrategy const & | get_parallel_strategy () const noexcept |
| Get the parallel strategy for the layer. More... | |
| bool | using_gpus () const noexcept |
| Whether the layer is using a GPU implementation. More... | |
| void | back_prop () |
| Backward propagation step. Given the objective function gradients w.r.t. the output tensors, compute the gradients w.r.t. the input tensors and w.r.t. the weights. This is essentially an application of the chain rule. More... | |
| bool | update () |
| Update step. Update the layer's internal members. Note that the optimization step for the weights happens elsewhere. More... | |
| virtual void | setup (size_t max_mini_batch_size, const std::vector< El::Grid *> &grids) |
| Setup layer members. More... | |
| void | summarize_stats (lbann_summary &summarizer, int step) |
| void | reset_counters () |
| Reset layer stat counters. More... | |
| void | set_communication_flag (SubGraphCommunication type) |
| SubGraphCommunication | get_communication_flag () |
| void | set_num_spliting_groups (El::Int spliting_groups) |
| El::Int | get_num_spliting_groups () const |
| std::shared_ptr< El::Grid > | get_mygrid () const |
| void | reset_inter_subgrid_vc_comm (std::shared_ptr< El::mpi::Comm > mpi_comm) |
| void | set_subgraph_parallelism_execution () |
| bool | subgraph_parallelism_execution () const noexcept |
| void | set_run_layer_in_subgraph () |
| bool | get_run_layer_in_subgraph () const noexcept |
| const Layer & | get_parent_layer (size_t index=0) const |
| const Layer & | get_child_layer (size_t index=0) const |
| std::vector< const Layer * > | get_parent_layers () const |
| std::vector< const Layer * > | get_child_layers () const |
| size_t | find_parent_layer_index (const Layer &l) const |
| size_t | find_child_layer_index (const Layer &l) const |
| int | get_num_parents () const noexcept |
| Get number of parent layers. More... | |
| int | get_num_children () const noexcept |
| Get number of child layers. More... | |
| void | add_parent_layer (ViewingLayerPtr parent) |
| Add a parent layer. More... | |
| void | add_child_layer (ViewingLayerPtr child) |
| Add a child layer. More... | |
| void | replace_parent_layer (ViewingLayerPtr l, size_t index) |
| void | replace_child_layer (ViewingLayerPtr l, size_t index) |
| void | clear_parent_layers () |
| Remove pointers to parent layers. More... | |
| void | clear_child_layers () |
| Remove pointers to child layers. More... | |
| ViewingLayerPtr | get_parent_layer_pointer (size_t index) const |
| ViewingLayerPtr | get_child_layer_pointer (size_t index) const |
| virtual std::vector< ViewingLayerPtr > | get_layer_pointers () |
| List of pointers to other layers. More... | |
| virtual void | set_layer_pointers (std::vector< ViewingLayerPtr > layers) |
| Set list of pointers to other layers. More... | |
| std::vector< ViewingWeightsPtr > | get_weights_pointers () const |
| List of pointers to weights. More... | |
| void | set_weights_pointers (std::vector< ViewingWeightsPtr > ptrs) |
| Set list of pointers to weights. More... | |
| void | replace_weights (Layer const &other_layer) |
| Replace weights with another Layer's weights. More... | |
| std::vector< int > | get_input_dims (size_t input_index=0) const |
| Get input tensor dimensions. More... | |
| int | get_input_size (size_t input_index=0) const |
| Get input tensor size. More... | |
| std::vector< int > | get_output_dims (size_t output_index=0) const |
| Get output tensor dimensions. More... | |
| int | get_output_size (size_t output_index=0) const |
| Get output tensor size. More... | |
| void | set_output_dims (std::vector< int > dims, size_t output_index=0) |
| Set output tensor dimensions. More... | |
| El::Int | infer_mini_batch_size_from_parents () const |
| void | set_hint_layer (ViewingLayerPtr l) |
| Set hint layer. More... | |
| const Layer * | get_hint_layer () const |
| Get hint layer. More... | |
| void | freeze () |
| void | unfreeze () |
| bool | is_frozen () const |
| template<typename ArchiveT > | |
| void | serialize (ArchiveT &ar) |
Protected Member Functions | |
| void | write_specific_proto (lbann_data::Layer &proto) const final |
| categorical_random_layer () | |
| void | fp_compute () override |
| Apply layer operation. Called by the 'forward_prop' function. Given the input tensors, the output tensors are populated with computed values. More... | |
| Protected Member Functions inherited from lbann::data_type_layer< TensorDataType > | |
| InputAbsDistMatrixType & | get_prev_activations (int parent_index=0) |
| const InputAbsDistMatrixType & | get_prev_activations (int parent_index=0) const |
| OutputAbsDistMatrixType & | get_prev_error_signals (int child_index=0) |
| const OutputAbsDistMatrixType & | get_prev_error_signals (int child_index=0) const |
| const InputAbsMatrixType & | get_local_prev_activations (int parent_index=0) const |
| const OutputAbsMatrixType & | get_local_prev_error_signals (int child_index=0) const |
| void | setup_matrices (const std::vector< El::Grid * > &grids) override |
| void | setup_data (size_t max_mini_batch_size) override |
| void | fp_setup_inputs () override |
| void | fp_setup_outputs () override |
| void | bp_setup_gradient_wrt_inputs () override |
| void | bp_compute () override |
| InputAbsDistMatrixType const & | weights_values (size_t idx) const |
| Get the values matrix for a specific weights object. More... | |
| weights & | master_weights (size_t idx) |
| Get a specific master weights object. More... | |
| weights const & | master_weights (size_t idx) const |
| data_type_layer (data_type_layer &&other)=default | |
| Protected lifecycle functions. More... | |
| data_type_layer (data_type_layer const &other) | |
| data_type_layer & | operator= (data_type_layer &&other)=default |
| data_type_layer & | operator= (data_type_layer const &other) |
| Protected Member Functions inherited from lbann::Layer | |
| void | setup_grid () |
| Setup process grid. More... | |
| virtual void | setup_pointers () |
| Setup layer pointers. Called by the 'setup' function. Pointers to parent/child layers are assumed to be already initialized. More... | |
| virtual void | setup_dims () |
| Setup tensor dimensions Called by the 'setup' function. If there are any input tensors, the base method sets all uninitialized output tensor dimensions equal to the first input tensor dimensions. More... | |
| virtual void | setup_gpu () |
| Setup GPU objects. Called by the 'setup' function if the layer is on GPUs. More... | |
| virtual bool | update_compute () |
| Perform the computation for the update step. Returns false if the layer must reset for a new training epoch. More... | |
| Layer (Layer &&other)=default | |
| Layer (Layer const &other) | |
| Layer & | operator= (Layer &&other)=default |
| Layer & | operator= (Layer const &other) |
| void | add_weights (ViewingWeightsPtr w) |
| size_t | num_weights () const noexcept |
| bool | has_weights () const noexcept |
| bool | has_weights (size_t idx) const noexcept |
| void | set_num_weights (size_t n) |
| void | set_weights (size_t idx, ViewingWeightsPtr w) |
| weights const & | get_weights (size_t idx) const |
| weights & | get_weights (size_t idx) |
| void | add_as_gradient_source () |
| void | remove_as_gradient_source () |
Friends | |
| class | cereal::access |
Additional Inherited Members | |
| Public Types inherited from lbann::data_type_layer< TensorDataType > | |
| using | InputAbsDistMatrixType = El::AbstractDistMatrix< TensorDataType > |
| The tensor type expected in this object. More... | |
| using | OutputAbsDistMatrixType = El::AbstractDistMatrix< TensorDataType > |
| using | InputAbsDistMatReadProxyType = El::AbstractDistMatrixReadDeviceProxy< TensorDataType, D > |
| The proxy tensor type expected in this object. More... | |
| using | OutputAbsDistMatReadProxyType = El::AbstractDistMatrixReadDeviceProxy< TensorDataType, D > |
| using | InputAbsMatrixType = El::AbstractMatrix< TensorDataType > |
| The local tensor type expected in this object. More... | |
| using | OutputAbsMatrixType = El::AbstractMatrix< TensorDataType > |
| using | WeightsProxyType = weights_proxy< TensorDataType > |
| The proxy type for weights used by this object. More... | |
| Protected Attributes inherited from lbann::Layer | |
| int | m_expected_num_parent_layers = 1 |
| int | m_expected_num_child_layers = 1 |
| Expected number of child layers. A negative value indicates no limit. More... | |
| model * | m_model = nullptr |
| Reference to model managing this layer. More... | |
| bool | m_frozen |
| Avoid back prop if frozen. More... | |
| EvalType | m_fp_time |
| Time spent in forward propagation. More... | |
| EvalType | m_fp_compute_time |
| Time spent in the forward propagation computation. More... | |
| EvalType | m_bp_time |
| Time spent in backward propagation. More... | |
| EvalType | m_bp_compute_time |
| Time spent in the backward propagation computation. More... | |
| EvalType | m_update_time |
| Time spent in updates. More... | |
| std::string | m_name |
| Layer instance's name. Each layer in a model should have a unique, preferably human-readable, name. More... | |
| bool | m_runs_inplace = false |
| If true, the layer will run in-place (the input and output activations point to the same tensor). Value is set during graph setup (in setup_pointers) based on layer traits and neighboring layers. More... | |
| int | m_grid_tag = -1 |
| Identifying tag for process grid. More... | |
| SubGraphCommunication | subgraph_communication_method = PT2PT |
| bool | m_subgraph_parallelism_execution = false |
| bool | run_layer_in_subgraph = false |
| std::unique_ptr< std::set< int > > | m_subgrid_ranks |
| El::Int | m_num_spliting_groups = 1 |
| std::shared_ptr< El::mpi::Comm > | m_interSubGridVCComm |
Detailed Description
template<typename TensorDataType, data_layout T_layout = data_layout::DATA_PARALLEL, El::Device Dev = El::Device::CPU>
class lbann::categorical_random_layer< TensorDataType, T_layout, Dev >
Random categorical outputs.
Inputs are probability distributions and outputs are one-hot vectors. An input entry is the probability that the corresponding output entry is one.
- Todo:
- Remove.
Definition at line 47 of file categorical_random.hpp.
Constructor & Destructor Documentation
◆ categorical_random_layer() [1/2]
template<typename TensorDataType , data_layout T_layout = data_layout::DATA_PARALLEL, El::Device Dev = El::Device::CPU>
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inline |
Definition at line 56 of file categorical_random.hpp.
◆ categorical_random_layer() [2/2]
template<typename TensorDataType , data_layout T_layout = data_layout::DATA_PARALLEL, El::Device Dev = El::Device::CPU>
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inlineprotected |
Definition at line 83 of file categorical_random.hpp.
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Member Function Documentation
◆ can_run_inplace()
template<typename TensorDataType , data_layout T_layout = data_layout::DATA_PARALLEL, El::Device Dev = El::Device::CPU>
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inlineoverridevirtual |
If True, the computation can run in-place (feeding each input activations tensor as the corresponding output activations)
Reimplemented from lbann::Layer.
Definition at line 75 of file categorical_random.hpp.
◆ copy()
template<typename TensorDataType , data_layout T_layout = data_layout::DATA_PARALLEL, El::Device Dev = El::Device::CPU>
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inlineoverridevirtual |
Copy function. This function dynamically allocates memory for a layer instance and instantiates a copy. The caller is responsible for deallocating the instance.
Implements lbann::Layer.
Definition at line 59 of file categorical_random.hpp.
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◆ fp_compute()
template<typename TensorDataType , data_layout T_layout = data_layout::DATA_PARALLEL, El::Device Dev = El::Device::CPU>
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overrideprotectedvirtual |
Apply layer operation. Called by the 'forward_prop' function. Given the input tensors, the output tensors are populated with computed values.
Implements lbann::Layer.
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◆ get_backprop_requirements()
template<typename TensorDataType , data_layout T_layout = data_layout::DATA_PARALLEL, El::Device Dev = El::Device::CPU>
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inlineoverridevirtual |
Returns the necessary tensors for computing backpropagation.
Reimplemented from lbann::Layer.
Definition at line 76 of file categorical_random.hpp.
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◆ get_data_layout()
template<typename TensorDataType , data_layout T_layout = data_layout::DATA_PARALLEL, El::Device Dev = El::Device::CPU>
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inlineoverridevirtual |
Get data layout of the data tensors. We assume that the data layouts of the previous activations, activations, previous error signals, and error signals are the same. Each concrete layer that is templated on its data layout should override this function to return its template parameter.
Implements lbann::Layer.
Definition at line 73 of file categorical_random.hpp.
◆ get_device_allocation()
template<typename TensorDataType , data_layout T_layout = data_layout::DATA_PARALLEL, El::Device Dev = El::Device::CPU>
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inlineoverridevirtual |
Get the device allocation for the data tensors. We assume that the decice allocation of the previous activations, activations, previous error signals, and error signals are the same. Each concrete layer that is templated on its device allocation should override this function to return its template parameter.
Implements lbann::Layer.
Definition at line 74 of file categorical_random.hpp.
◆ get_type()
template<typename TensorDataType , data_layout T_layout = data_layout::DATA_PARALLEL, El::Device Dev = El::Device::CPU>
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inlineoverridevirtual |
Get the layer type's name.
A layer type name should be brief, unique, and human-readable description of the layer's mathematical operation that is recognizable to ML practitioners (e.g., "Convolution", "ReLU")
Implements lbann::Layer.
Definition at line 72 of file categorical_random.hpp.
◆ serialize()
template<typename TensorDataType , data_layout T_layout = data_layout::DATA_PARALLEL, El::Device Dev = El::Device::CPU>
template<typename ArchiveT >
| void lbann::categorical_random_layer< TensorDataType, T_layout, Dev >::serialize | ( | ArchiveT & | ar | ) |
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◆ write_specific_proto()
template<typename TensorDataType , data_layout T_layout = data_layout::DATA_PARALLEL, El::Device Dev = El::Device::CPU>
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finalprotectedvirtual |
Add layer specific data to prototext
Implements lbann::Layer.
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Friends And Related Function Documentation
◆ cereal::access
template<typename TensorDataType , data_layout T_layout = data_layout::DATA_PARALLEL, El::Device Dev = El::Device::CPU>
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friend |
Definition at line 82 of file categorical_random.hpp.
The documentation for this class was generated from the following file:
