Gated feed-forward (GatedMLP) composite component. More...

Inheritance diagram for Mila::Dnn::GatedMLP< TDeviceType, TPrecision, TGate >:

Public Types
using	ComponentPtr = typename CompositeComponentBase::ComponentPtr
using	CompositeComponentBase = CompositeComponent<TDeviceType, TPrecision>
using	LinearType = Linear<TDeviceType, TPrecision>
using	MR = typename DeviceTypeTraits<TDeviceType>::memory_resource
using	SwigluType = Swiglu<TDeviceType, TPrecision, TGate>
using	TensorType = Tensor<TPrecision, MR>
Public Types inherited from Mila::Dnn::CompositeComponent< TDeviceType, TPrecision >
using	ComponentBase = Component<TDeviceType, TPrecision>
using	ComponentPtr = std::shared_ptr<Component<TDeviceType, TPrecision>>

Public Member Functions
	GatedMLP (const std::string &name, const GatedMLPConfig &config, std::optional< DeviceId > device_id=std::nullopt)
TensorType &	backward (const TensorType &input, const TensorType &output_grad)
TensorType &	decode (const TensorType &input) const
	Single-token inference convenience with no gradient capture.
TensorType &	forward (const TensorType &input)
	Forward pass: fc_gate_up -> gate -> fc_down.
MemoryStats	getMemoryStats () const override
	Return the current memory allocation breakdown for this component.
const ComponentType	getType () const override
	Get the component type identifier.
std::string	toString () const override
	Generate a human-readable description.
void	zeroGradients () override
	Clear all model-owned gradients for this component.
Public Member Functions inherited from Mila::Dnn::CompositeComponent< TDeviceType, TPrecision >
	CompositeComponent (CompositeComponent &&) noexcept=default
	CompositeComponent (const CompositeComponent &)=delete
	CompositeComponent (const std::string &name)
	Construct composite component with name.
CompositeComponent &	addComponent (ComponentPtr component)
	Add a pre-constructed child component (chainable).
size_t	childCount () const noexcept
	Get the number of direct children.
void	clearComponents ()
	Clear all child components.
ComponentPtr	findComponent (const std::string &path) const
	Resolve a dot-separated component path within this composite.
ComponentPtr	getComponent (const std::string &name) const
	Retrieve a direct child component by name.
const std::vector< ComponentPtr > &	getComponents () const
	Get all child components in insertion order.
DeviceId	getDeviceId () const override
	Get the compute device for this composite.
std::vector< ITensor * >	getGradients () const override
	Get all parameter gradients from all children.
std::vector< ITensor * >	getParameters () const override
	Get all parameters from all children.
bool	hasChildren () const noexcept
	Check if this composite has any children.
bool	hasComponent (const std::string &name) const
	Check if a named child component exists.
CompositeComponent &	operator= (CompositeComponent &&) noexcept=default
CompositeComponent &	operator= (const CompositeComponent &)=delete
dim_t	parameterCount () const override
	Count parameters across all children.
bool	removeComponent (const std::string &name)
void	saveFlatTensors (Serialization::SafeTensorsWriter &writer, const std::string &prefix, Serialization::TensorSavePass pass) const override
	Recurse into children, extending the flat dotted prefix.
void	synchronize () override
	Synchronize all child components.
ComponentPtr	tryFindComponent (const std::string &path) const
	Try to resolve a dot-separated component path within this composite.
Public Member Functions inherited from Mila::Dnn::Component< TDeviceType, TPrecision >
	Component (const std::string &name)
	Construct component with required name identifier.
virtual void	build (const BuildContext &context) final
	Build the component with the provided BuildContext (canonical overload).
const std::string	getName () const
	Get the component's name identifier.
virtual std::vector< std::string >	getParameterNames () const
	List all available parameter names for this component.
virtual MemoryStats	getRequiredMemory (const BuildContext &context) const
	Report what build( context ) would allocate, without allocating it.
TrainingMode	getTrainingMode () const noexcept
	The current runtime behavioral mode of this Component.
virtual bool	isBuilt () const final
	Returns true if build() has completed successfully.
virtual void	loadParameter (const std::string &, const Serialization::ITensorBlob &)
	Load a parameter from serialized tensor data.
void	setTrainingMode (TrainingMode mode)
	Set the runtime behavioral mode for this Component.

Protected Member Functions
void	onBuilding (const BuildContext &context) override
	Build child graph with the gated shape contract.
void	onTrainingModeChanging (TrainingMode training_mode) override
	Hook invoked when training mode is about to change.
Protected Member Functions inherited from Mila::Dnn::CompositeComponent< TDeviceType, TPrecision >
template<typename TComponent>
std::shared_ptr< TComponent >	getComponentAs (const std::string &name) const
	Retrieve a typed child component by name.
void	load_ (ModelArchive &archive, SerializationMode mode) override
	Restore children from their nested scopes, mirroring save_().
void	onExecutionContextSet () override
	Hook invoked after ExecutionContext is set.
virtual void	optimize ()
	Virtual hook for graph optimization after construction.
void	requireSerializableParameters () const override
	No-op override: a composite names no parameters of its own.
void	save_ (ModelArchive &archive, SerializationMode mode) const override
Protected Member Functions inherited from Mila::Dnn::Component< TDeviceType, TPrecision >
IExecutionContext *	getExecutionContext () const
	Get the shared execution context.
bool	hasExecutionContext () const noexcept
	Check if execution context has been set.
template<TensorDataType TParameterPrecision, typename TMemoryResource>
void	loadParameterFromBlob (const std::string &param_name, const Serialization::ITensorBlob &blob, Tensor< TParameterPrecision, TMemoryResource > &target, const shape_t &expected_shape)
	Load a tensor blob into a parameter tensor with validation.
template<TensorDataType TParameterPrecision, typename TMemoryResource>
void	saveParameterToArchive (ModelArchive &archive, const std::string &parameter_name, const Tensor< TParameterPrecision, TMemoryResource > &parameter) const
	Write one parameter tensor into the archive under "tensors/<name>".
template<TensorDataType TParameterPrecision, typename TMemoryResource>
void	saveParameterToWriter (Serialization::SafeTensorsWriter &writer, const std::string &flat_name, const Tensor< TParameterPrecision, TMemoryResource > &parameter, Serialization::TensorSavePass pass) const
	Drive one parameter through one pass of a flat safetensors save.
void	setExecutionContext (IExecutionContext *context)
	Set the execution context for this component.

Additional Inherited Members
Static Public Member Functions inherited from Mila::Dnn::Component< TDeviceType, TPrecision >
static constexpr DeviceType	getDeviceType ()
	Compile-time device type for this component instance.
static constexpr TensorDataType	getPrecision () noexcept
	Compile-time tensor precision for this component instance.
Protected Types inherited from Mila::Dnn::Component< TDeviceType, TPrecision >
using	HostStagingMemoryResource
	Host memory a device-resident parameter stages through.
Protected Attributes inherited from Mila::Dnn::Component< TDeviceType, TPrecision >
BuildContext	build_context_ { shape_t{ 1 }, RuntimeMode::Training }
	The BuildContext stored at build time.

Detailed Description

template<DeviceType TDeviceType, TensorDataType TPrecision, ActivationType TGate = ActivationType::Silu>
requires PrecisionSupportedOnDevice<TPrecision, TDeviceType>
class Mila::Dnn::GatedMLP< TDeviceType, TPrecision, TGate >

Gated feed-forward (GatedMLP) composite component.

Device-templated composite implementing the gated FFN used by Llama and the GLU family, and the single-expert reference for a future MoE layer: Input -> fc_gate_up Linear(in -> 2H, fused) -> Swiglu gate (2H -> H) -> fc_down Linear(H -> in) -> Output

The gate is the SwiGLU sub-structure (SiLU on the gate half, multiplied by the up half). The gate function is exposed as the TGate template parameter for forward compatibility with the activation unification; until the gate op is generalized, only SiLU is realizable (see Specifications/FfnAndMoE.md s7, s13).

MoE-readiness seams (FfnAndMoE.md s9): the injected-context path is the norm (owned-context construction is a standalone convenience); forward operates on the trailing feature dimension so it is valid for both [B, T, in] and gathered [num_tokens, in] layouts.

Template Parameters

TDeviceType	Device type for execution.
TPrecision	Tensor data precision. Must be supported on the device.
TGate	Gate activation: Silu (SwiGLU) or Gelu (GeGLU, Gemma).

Member Function Documentation

◆ forward()

template<DeviceType TDeviceType, TensorDataType TPrecision, ActivationType TGate = ActivationType::Silu>

TensorType & Mila::Dnn::GatedMLP< TDeviceType, TPrecision, TGate >::forward ( const TensorType & input )

inline

Forward pass: fc_gate_up -> gate -> fc_down.

Captures non-owning pointers to child-owned intermediates for backward().

Parameters

input Input tensor [..., in_features].

Returns: Reference to the final fc_down output (owned by that child).

◆ getMemoryStats()

template<DeviceType TDeviceType, TensorDataType TPrecision, ActivationType TGate = ActivationType::Silu>

MemoryStats Mila::Dnn::GatedMLP< TDeviceType, TPrecision, TGate >::getMemoryStats ( ) const

inlineoverridevirtual

Return the current memory allocation breakdown for this component.

Reflects allocations at the moment of the call. The returned stats naturally track the component lifecycle:

After construction – nothing; construction allocates none After build( Inference ) – parameters + T=1 state buffers After build( Training ) – parameters + T=full state buffers After setTrainingMode( Train ) – parameters + state + gradients

For CompositeComponent and Network, the returned stats are the recursive aggregate of all child components.

May be called at any time – no lifecycle preconditions.

Returns: MemoryStats reflecting current allocations.

Implements Mila::Dnn::Component< TDeviceType, TPrecision >.

◆ getType()

template<DeviceType TDeviceType, TensorDataType TPrecision, ActivationType TGate = ActivationType::Silu>

const ComponentType Mila::Dnn::GatedMLP< TDeviceType, TPrecision, TGate >::getType ( ) const

inlineoverridevirtual

Get the component type identifier.

Used for serialization and runtime type identification.

Returns: Component type enum value.

Implements Mila::Dnn::Component< TDeviceType, TPrecision >.

◆ onBuilding()

template<DeviceType TDeviceType, TensorDataType TPrecision, ActivationType TGate = ActivationType::Silu>

void Mila::Dnn::GatedMLP< TDeviceType, TPrecision, TGate >::onBuilding ( const BuildContext & context )

inlineoverrideprotectedvirtual

Build child graph with the gated shape contract.

fc_gate_up receives the input shape; the gate and fc_down receive the fused 2H and the gated H shapes respectively.

Reimplemented from Mila::Dnn::Component< TDeviceType, TPrecision >.

◆ onTrainingModeChanging()

template<DeviceType TDeviceType, TensorDataType TPrecision, ActivationType TGate = ActivationType::Silu>

void Mila::Dnn::GatedMLP< TDeviceType, TPrecision, TGate >::onTrainingModeChanging ( TrainingMode training_mode )

inlineoverrideprotectedvirtual

Hook invoked when training mode is about to change.

Propagates the new mode to all child components. The hook runs with the Component's training mutex held; it MUST NOT call setTrainingMode().

Parameters

training_mode New training mode (Normal or Eval)

Reimplemented from Mila::Dnn::CompositeComponent< TDeviceType, TPrecision >.

◆ toString()

template<DeviceType TDeviceType, TensorDataType TPrecision, ActivationType TGate = ActivationType::Silu>

std::string Mila::Dnn::GatedMLP< TDeviceType, TPrecision, TGate >::toString ( ) const

inlineoverridevirtual

Generate a human-readable description.

Returns: String representation showing children

Reimplemented from Mila::Dnn::CompositeComponent< TDeviceType, TPrecision >.

◆ zeroGradients()

template<DeviceType TDeviceType, TensorDataType TPrecision, ActivationType TGate = ActivationType::Silu>

void Mila::Dnn::GatedMLP< TDeviceType, TPrecision, TGate >::zeroGradients ( )

inlineoverridevirtual

Clear all model-owned gradients for this component.

Default implementation is a no-op. Composite components should override to recurse to children. Leaf components should override to zero their parameter and activation gradients using device-aware helpers.

Reimplemented from Mila::Dnn::Component< TDeviceType, TPrecision >.

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

Mila/Src/Dnn/Components/FFN/GatedMLP/GatedMLP.ixx

Public Types

Public Member Functions

Protected Member Functions

Additional Inherited Members

Detailed Description

Member Function Documentation

◆ forward()

◆ getMemoryStats()

◆ getType()

◆ onBuilding()

◆ onTrainingModeChanging()

◆ toString()

◆ zeroGradients()