OpenNN
Open-source neural networks library
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opennn::Flatten Class Referencefinal

Flatten layer that reshapes a multi-dimensional input into a single 1D feature vector. More...

#include <flatten_layer.h>

Inheritance diagram for opennn::Flatten:
[legend]

Public Member Functions

 Flatten (const Shape &={})
 Constructs a flatten layer for the given input shape.
 
Shape get_output_shape () const override
 Returns the flattened 1D output shape (product of input dimensions).
 
void set (const Shape &)
 Reconfigures the layer with a new input shape.
 
void set_input_shape (const Shape &new_input_shape) override
 Sets the input shape; subclasses override to derive dependent dimensions.
 
- Public Member Functions inherited from opennn::Layer
virtual ~Layer ()=default
 
const string & get_label () const
 
const string & get_name () const
 
LayerType get_type () const
 
virtual void set_output_shape (const Shape &)
 Sets the output shape; subclasses override when the output is user-configurable.
 
void set_label (string new_label)
 
Index get_parameters_number () const
 Returns the total number of trainable parameters owned by this layer.
 
const vector< Operator * > & get_operators () const
 
virtual vector< TensorSpecget_parameter_specs () const
 Returns the tensor specs of trainable parameters; subclasses override.
 
virtual vector< TensorSpecget_state_specs () const
 Returns the tensor specs of persistent state (e.g. running mean/variance).
 
virtual vector< TensorSpecget_forward_specs (Index batch_size) const
 Returns the tensor specs of the forward workspace; defaults to a single output tensor.
 
virtual vector< TensorSpecget_backward_specs (Index batch_size) const
 Returns the tensor specs of the backward workspace; empty for non-trainable layers.
 
virtual Shape get_input_shape () const
 Returns the input shape stored by the layer.
 
virtual ActivationOp::Function get_output_activation () const
 Returns the layer's output activation (Identity for most layers; overridden by Dense/Bounding).
 
Index get_inputs_number () const
 
Index get_outputs_number () const
 
virtual void forward_propagate (ForwardPropagation &fp, size_t layer, bool is_training) noexcept
 Runs the forward pass by chaining the layer's operators in order.
 
virtual void back_propagate (ForwardPropagation &fp, BackPropagation &bp, size_t i) const noexcept
 Runs the backward pass by chaining the layer's operators in reverse order.
 
virtual void from_JSON (const JsonDocument &document)
 Restores layer configuration and parameters from a JSON document.
 
virtual void read_JSON_body (const Json *)
 Subclass hook reading the body section of the layer's JSON node.
 
virtual void load_state_from_JSON (const JsonDocument &document)
 Restores persistent state (e.g. running statistics) from a JSON document.
 
virtual void to_JSON (JsonWriter &writer) const
 Serializes layer configuration and parameters to a JSON writer.
 
virtual void write_JSON_body (JsonWriter &) const
 Subclass hook writing the body section of the layer's JSON node.
 
virtual string write_expression (const vector< string > &, const vector< string > &) const
 Returns a human-readable mathematical expression for this layer (empty by default).
 
virtual void print () const
 Prints a human-readable summary of the layer to standard output.
 
bool get_is_trainable () const
 
Type get_compute_dtype () const
 
void set_compute_dtype (Type new_compute_dtype)
 Sets the compute dtype and notifies subclasses via on_compute_dtype_changed().
 
virtual void on_compute_dtype_changed ()
 Subclass hook invoked when the compute dtype changes; default is no-op.
 
virtual float * link_states (float *pointer)
 Binds the persistent-state region of the shared buffer to operator views.
 
float * link_gradients (float *pointer, vector< TensorView > &gradient_views)
 Binds the gradient slice of the shared buffer to operator gradient views.
 
vector< TensorView > & get_parameter_views ()
 
const vector< TensorView > & get_parameter_views () const
 
void redistribute_parameters_to_operators ()
 Re-binds operator parameter views after the parameter buffer has been resized or moved.
 

Additional Inherited Members

- Protected Types inherited from opennn::Layer
enum  Forward { Input , Output }
 
enum  Backward { OutputDelta , InputDelta }
 
- Protected Member Functions inherited from opennn::Layer
 Layer ()=default
 
 Layer (LayerType t, bool trainable=true)
 
float * link_views_to_operators (vector< TensorView > &views, float *pointer, vector< TensorSpec >(Operator::*specs_fn)() const, void(Operator::*link_fn)(span< const TensorView >))
 
- Protected Attributes inherited from opennn::Layer
string label = "my_layer"
 
LayerType layer_type = LayerType::Dense
 
bool is_trainable = true
 
Shape input_shape
 
Type compute_dtype = Type::FP32
 
vector< TensorViewparameters
 
vector< TensorViewstates
 
vector< Operator * > operators
 

Detailed Description

Flatten layer that reshapes a multi-dimensional input into a single 1D feature vector.

Constructor & Destructor Documentation

◆ Flatten()

opennn::Flatten::Flatten ( const Shape & = {})

Constructs a flatten layer for the given input shape.

Member Function Documentation

◆ get_output_shape()

Shape opennn::Flatten::get_output_shape ( ) const
inlineoverridevirtual

Returns the flattened 1D output shape (product of input dimensions).

Implements opennn::Layer.

◆ set()

void opennn::Flatten::set ( const Shape & )

Reconfigures the layer with a new input shape.

◆ set_input_shape()

void opennn::Flatten::set_input_shape ( const Shape & new_input_shape)
inlineoverridevirtual

Sets the input shape; subclasses override to derive dependent dimensions.

Reimplemented from opennn::Layer.