Dnn.Components.GptTransformer Module Reference

Exported Modules
module	Dnn.Components.LayerNorm
module	Compute.DeviceTypeTraits
module	Dnn.TensorDataType
module	Dnn.RuntimeMode
module	Dnn.TensorTypes
module	Dnn.Components.GptBlock
module	Serialization.PretrainedReader
module	Logging.Logger
module	Serialization.Tensor
module	Dnn.TensorDataTypeTraits
module	Dnn.Components.Linear
module	Serialization.ModelArchive
module	Compute.ExecutionContextFactory
module	Dnn.Component
module	Compute.CpuMemoryResource
module	Compute.DeviceId
module	Dnn.Tensor
module	Compute.Device
module	Dnn.ComponentType
module	Dnn.ActivationType
module	Dnn.LanguageNetwork
module	Compute.ExecutionContext
module	Dnn.Components.Lpe
module	Serialization.Mode
module	Compute.DeviceType
module	Dnn.ITensor

Classes
class	Mila::Dnn::GptConfig
	Network-level configuration for GPT-style transformer networks. More...
class	Mila::Dnn::GptTransformer< TDeviceType, TPrecision >
	GPT-2 style transformer (decoder-only) for autoregressive token prediction. More...

Typedefs
using	ComponentPtr = typename NetworkBase::ComponentPtr
using	EncoderType = Lpe<TDeviceType, dtype_t::INT32, TPrecision>
using	LayerNormType = LayerNorm<TDeviceType, TPrecision>
using	LinearType = Linear<TDeviceType, TPrecision>
using	MR = typename DeviceTypeTraits<TDeviceType>::memory_resource
using	NetworkBase = LanguageNetwork<TDeviceType, TPrecision>
using	TensorType = Tensor<TPrecision, MR>
using	TokenIndexType = Tensor<dtype_t::INT32, MR>
using	TransformerBlockType = GptBlock<TDeviceType, TPrecision>

Functions
	GptTransformer (const std::string &name, const GptConfig &config, DeviceId device_id)
	Construct Gpt type transformer.
	~GptTransformer () override=default
TokenIndexType &	backward (const TokenIndexType &input, const TensorType &output_grad) override
static auto	createConfigFromMetadata (const PretrainedMetadata &metadata) -> GptConfig
	Create GptConfig from Mila metadata.
void	createGraph ()
TensorType &	decode (const TokenIndexType &input, int position) override
	Inference-only single-token decode pass.
TensorType &	forward (const TokenIndexType &input) override
	Load GptTransformer from archive.
static std::unique_ptr< GptTransformer< TDeviceType, TPrecision > >	fromPretrained (const std::filesystem::path &model_path, std::size_t batch_size, std::size_t seq_length, DeviceId device_id=DeviceId{ TDeviceType, 0 }, bool strict=true)
IExecutionContext *	getExecutionContext () const
MemoryStats	getMemoryStats () const override
	Return the current memory allocation breakdown for this component.
const ComponentType	getType () const override
	Get the component type identifier.
GptConfig	Mila::Dnn::GPT2_Large ()
	GPT-2 Large (774M parameters).
GptConfig	Mila::Dnn::GPT2_Medium ()
	GPT-2 Medium (345M parameters).
GptConfig	Mila::Dnn::GPT2_Small ()
	Usage Examples:
GptConfig	Mila::Dnn::GPT2_XL ()
	GPT-2 XL (1.5B parameters).
void	loadParameters (PretrainedModelReader &reader, bool strict)
	Initialize this transformer's components from a GPT-2 checkpoint.
void	onBuilding (const BuildContext &context) override
	Hook invoked by build() to allocate component buffers.
void	onTrainingModeChanging (TrainingMode training_mode) override
	Hook invoked when training mode is about to change.
std::pair< std::string, std::string >	parseParameterPath (const std::string &full_name) const
TensorType &	prefill (const TokenIndexType &input) override
	Inference prefill — process full prompt and return last-token logits.
void	save_ (ModelArchive &archive, SerializationMode) const override
	Hook for concrete classes to save type-specific state.
std::string	toString () const override
	Generate a human-readable description.
void	validateBuildContext (const BuildContext &context) const
void	validateInputShape (const shape_t &input_shape) const
void	zeroGradients () override
	Clear all model-owned gradients for this component.

Variables
int64_t	batch_size_ { 0 }
std::vector< TensorType * >	block_input_ptrs_
std::vector< TensorType * >	block_output_ptrs_
GptConfig	config_
shape_t	embedding_shape_
std::shared_ptr< EncoderType >	encoder_ { nullptr }
TensorType *	encoder_out_ptr_ { nullptr }
std::shared_ptr< LayerNormType >	final_layernorm_ { nullptr }
shape_t	leading_shape_
std::shared_ptr< LinearType >	lm_head_ { nullptr }
TensorType *	logits_ptr_ { nullptr }
TensorType *	normalized_ptr_ { nullptr }
shape_t	output_shape_
std::unique_ptr< IExecutionContext >	owned_context_ { nullptr }
int64_t	seq_length_ { 0 }
std::vector< std::shared_ptr< TransformerBlockType > >	transformer_blocks_

Files
file	/__w/Mila/Mila/Mila/Src/Dnn/Components/Transformers/Gpt/GptTransformer.ixx
file	/__w/Mila/Mila/Mila/Src/Dnn/Components/Transformers/Gpt/Gpt.Config.ixx
	Network-level configuration for GPT-style transformer networks.
file	/__w/Mila/Mila/Mila/Src/Dnn/Components/Transformers/Gpt/Gpt.Presets.ixx