Mila::Dnn::LlamaConfig Class Reference

Network-level configuration for LLaMA-style transformer networks. More...

Inheritance diagram for Mila::Dnn::LlamaConfig:

Public Member Functions
	LlamaConfig (dim_t embedding_dim, dim_t num_layers)
	Construct a LLaMA network configuration.
void	fromMetadata (const SerializationMetadata &meta) override
	Populate configuration from provided metadata.
dim_t	getHiddenDimension () const noexcept
dim_t	getMaxSequenceLength () const noexcept
dim_t	getModelDim () const noexcept
dim_t	getNumHeads () const noexcept
dim_t	getNumKVHeads () const noexcept
dim_t	getNumLayers () const noexcept
float	getRMSNormEpsilon () const noexcept
float	getRoPEScalingFactor () const noexcept
float	getRoPETheta () const noexcept
dim_t	getVocabSize () const noexcept
SerializationMetadata	toMetadata () const override
	Convert configuration into a SerializationMetadata object.
std::string	toString () const override
	Produce a short, human-readable summary of the configuration.
bool	useBias () const noexcept
void	validate () const override
	Validate configuration parameters.
template<typename Self>
decltype(auto)	withBias (this Self &&self, bool use_bias)
template<typename Self>
decltype(auto)	withHiddenDimension (this Self &&self, dim_t hidden_dim)
template<typename Self>
decltype(auto)	withMaxSequenceLength (this Self &&self, dim_t max_seq_len)
	Sets the trained maximum sequence length for this model.
template<typename Self>
decltype(auto)	withNumHeads (this Self &&self, dim_t num_heads)
template<typename Self>
decltype(auto)	withNumKVHeads (this Self &&self, dim_t num_kv_heads)
template<typename Self>
decltype(auto)	withRoPEScalingFactor (this Self &&self, float scale_factor)
template<typename Self>
decltype(auto)	withRoPETheta (this Self &&self, float theta)
template<typename Self>
decltype(auto)	withVocabularyLength (this Self &&self, dim_t vocab_size)
Public Member Functions inherited from Mila::Dnn::ComponentConfig
virtual	~ComponentConfig ()=default
	Virtual destructor for polymorphic base.

Detailed Description

Network-level configuration for LLaMA-style transformer networks.

Exposes only the settings needed at network scope: vocabulary, number of layers, embedding dimension, and max sequence length.

Constructor & Destructor Documentation

LlamaConfig()

Mila::Dnn::LlamaConfig::LlamaConfig ( dim_t embedding_dim, dim_t num_layers )

inline

Construct a LLaMA network configuration.

Parameters

embedding_dim	Model embedding dimension. Must be > 0.
num_layers	Number of transformer layers. Must be > 0.

Member Function Documentation

fromMetadata()

void Mila::Dnn::LlamaConfig::fromMetadata ( const SerializationMetadata & meta )

inlineoverridevirtual

Populate configuration from provided metadata.

Implementations should read available keys and leave missing keys at their current/default values to preserve forward/backward compatibility.

Parameters

meta	Metadata to read configuration values from.

Implements Mila::Dnn::ComponentConfig.

toMetadata()

SerializationMetadata Mila::Dnn::LlamaConfig::toMetadata ( ) const

inlineoverridevirtual

Convert configuration into a SerializationMetadata object.

Implementations should include any fields required to fully reconstruct the configuration via fromMetadata.

Returns

SerializationMetadata Metadata representation of the config.

Implements Mila::Dnn::ComponentConfig.

toString()

std::string Mila::Dnn::LlamaConfig::toString ( ) const

inlineoverridevirtual

Produce a short, human-readable summary of the configuration.

Implementations should return a compact, single-line description suitable for logging and debugging.

Returns

std::string Human-readable summary of the configuration.

Implements Mila::Dnn::ComponentConfig.

validate()

void Mila::Dnn::LlamaConfig::validate ( ) const

inlineoverridevirtual

Validate configuration parameters.

Called by callers to ensure the configuration represents a valid, constructible component. Implementations must throw std::invalid_argument (or a derived exception) when validation fails.

Exceptions

std::invalid_argument

If the configuration is invalid.

Implements Mila::Dnn::ComponentConfig.

withMaxSequenceLength()

template<typename Self>

decltype(auto) Mila::Dnn::LlamaConfig::withMaxSequenceLength ( this Self && self, dim_t max_seq_len )

inline

Sets the trained maximum sequence length for this model.

This value is sourced from the pretrained model metadata and represents the architectural ceiling on context length – the furthest position for which RoPE embeddings were trained.

This is not a deployment parameter. The runtime context length is a deployment decision carried by BuildContext, and must not exceed this value. LlamaModel::fromPretrained() enforces that invariant.

Template Parameters

Self	Deduced type of the builder ( supports both lvalue and rvalue chains ).

Parameters

max_seq_len

The trained maximum sequence length. Must be > 0.

Exceptions

std::invalid_argument

if max_seq_len is zero or negative.

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

• Mila/Src/Dnn/Components/Transformers/LlaMa/Llama.Config.ixx