Class List

Here are the classes, structs, unions and interfaces with brief descriptions:

[detail level 1234567]

NMila	Mila main API namespace
NCore
CRandomGenerator	Singleton class providing centralized random number generation
NData
CBpeTokenizer	Unified BPE tokenizer targeting GPT-2, Llama 3.x, and Mistral model families
CBpeTrainer	Corpus accumulator and trainer for BPE vocabularies
CBpeVocabulary	Unified Byte Pair Encoding (BPE) vocabulary
CPairHash
CPairViewHash
CBpeVocabularyConfig	Configuration for the BPE vocabulary
CCharTokenizer	Character-level tokenizer
CCharTrainer	Character-level tokenizer trainer
CCharVocabulary	Character vocabulary for tokenization
CCharVocabularyConfig	Configuration for Character-level tokenizer training
CDataLoader	Device-agnostic data loader interface using abstract tensor data types
CMilaFileHeader	Common file header for Mila data files
CSerializationMetadata	Type-safe metadata container for component serialization
CSpecialTokens	Configuration for special tokens across all tokenizer types
CTokenizer
CTokenizerTrainer	Abstract interface for training tokenizer vocabularies from text corpora
CTokenizerVocabulary	Generic tokenizer vocabulary interface
CTokenSequenceLoader	Token sequence loader for autoregressive language models
CTokenSequenceLoaderConfig	Configuration for StreamingSequenceLoader behavior
CTrainerFactory	Factory for creating tokenizer trainers and loading vocabularies
NDnn
NCompute
NCpu
CFillOps	CPU specialization of TensorOps for initialization operations
CMathOps	CPU specialization of TensorOps for mathematical operations
CTransferOps	CPU specialization of TensorOps for transfer operations
CZeroOps
NCuda
NDetail
Ccuda_structural_kernels
Ccuda_structural_kernels< float >
Ccuda_structural_kernels< nv_bfloat16 >
NGelu
NDetail
Ccuda_gelu_impl
Ccuda_gelu_impl< float >
Ccuda_gelu_impl< half >
CCudaGeluOp	CUDA implementation of the GELU activation function for neural networks
CCudaGeluOpRegistrar	Class responsible for registering the CudaGeluOp operation
NGqa
NDetail
Ccuda_gqa_kernels
Ccuda_gqa_kernels< float >
Ccuda_gqa_kernels< nv_bfloat16 >
CCudaGqaOp	CUDA Grouped-Query Attention operation
CCudaGroupedQueryAttentionOpRegistrar
NLayerNorm
NDetail
Ccuda_layernorm_impl	CUDA kernel dispatcher for LayerNorm operations
Ccuda_layernorm_impl< float >
Ccuda_layernorm_impl< half >
CCudaLayerNormOp	CUDA implementation of Layer Normalization
CCudaLayerNormOpRegistrar
NLinear
NDetail
Ccuda_matmul_impl	CUDA kernel dispatcher for Linear operations
Ccuda_matmul_impl< float >
Ccuda_matvec_impl	CUDA kernel dispatcher for matrix-vector multiply (M=1 decode path)
Ccuda_matvec_impl< float, float >
Ccuda_matvec_impl< nv_bfloat16, __nv_fp8_e4m3 >
Ccuda_matvec_impl< nv_bfloat16, nv_bfloat16 >
CCudaLinearOp	CUDA Linear operation with compile-time weight quantization policy dispatch
CCudaLinearOpRegistrar
NLpe
NDetail
Ccuda_lpe_impl	CUDA kernel dispatcher for Lpe forward, backward, and positional decode
Ccuda_lpe_impl< float >	FP32 specialization of the Lpe CUDA kernel dispatcher
Ccuda_lpe_impl< half >	FP16 specialization of the Lpe CUDA kernel dispatcher
CCudaLpeOp	CUDA implementation of the Lpe (token + positional embedding) operation
CCudaLpeOpRegistrar
NMatMulBiasGelu
CCudaMatMulBiasGeluOp	CUDA implementation of the fused MatMul-Bias-GELU operation
CCudaMatMulBiasGeluOpRegistrar	Class responsible for registering the CudaMatMulBiasGeluOp operation
NMultiHeadAttention
NDetail
Ccuda_mha_kernels	CUDA kernel dispatcher for attention non-matmul operations
Ccuda_mha_kernels< float >
Ccuda_mha_kernels< half >
CCudaMultiHeadAttentionOp	CUDA implementation of Multi-Head Attention using column-major cuBLASLt optimization
CCudaMultiHeadAttentionOpRegistrar
NResidual
NDetail	CUDA residual kernel dispatch implementations
Ccuda_residual_impl
Ccuda_residual_impl< float >
Ccuda_residual_impl< nv_bfloat16 >
CCudaResidualOp	CUDA Residual operation implementing the BinaryOperation interface
CCudaResidualOpRegistrar
NRmsNorm
NDetail
Ccuda_rmsnorm_impl	CUDA kernel dispatcher for RMSNorm operations
Ccuda_rmsnorm_impl< float >
Ccuda_rmsnorm_impl< nv_bfloat16 >
CCudaRmsNormOp	CUDA implementation of RMS Normalization
CCudaRmsNormOpRegistrar
NRope
NDetail
Ccuda_rope_impl	CUDA kernel dispatcher for RoPE forward, backward, cache build, and positional decode
Ccuda_rope_impl< __nv_bfloat16 >
Ccuda_rope_impl< float >
CCudaRopeOp	CUDA implementation of the Rope (rotary positional embedding) operation
CCudaRopeOpRegistrar
CRopeCacheRegistry	Process-wide shared cache for RoPE cos/sin frequency tables
CAcquireResult
CCacheEntry
CCacheKey
CCacheKeyHash
NSoftmax
NDetail	Namespace for CUDA softmax implementation details
Ccuda_softmax_impl
Ccuda_softmax_impl< float >
Ccuda_softmax_impl< half >
CCudaSoftmaxOp	CUDA implementation of Softmax operation using abstract TensorDataType API
CCudaSoftmaxOpRegistrar	Class responsible for registering the CudaSoftmaxOp operation
NSoftmaxCrossEntropy
NDetail	Namespace for CUDA fused softmax cross entropy implementation details
Ccuda_softmax_crossentropy_impl	CUDA kernel dispatcher for SoftmaxCrossEntropy operations
Ccuda_softmax_crossentropy_impl< float >
Ccuda_softmax_crossentropy_impl< half >
CCudaSoftmaxCrossEntropyOp	Fused CUDA implementation of Softmax + CrossEntropy using abstract TensorDataType API
CCudaSoftmaxCrossEntropyOpRegistrar	Registrar for fused Softmax+CrossEntropy CUDA operation
NSwiglu
NDetail
Ccuda_swiglu_impl
Ccuda_swiglu_impl< __nv_bfloat16 >
Ccuda_swiglu_impl< float >
CCudaSwigluOp
CCudaSwigluOpRegistrar
NTokenEmbedding
NDetail
Ccuda_token_embedding_impl
Ccuda_token_embedding_impl< __nv_bfloat16 >
Ccuda_token_embedding_impl< float >
CCudaTokenEmbeddingOp
CCudaTokenEmbeddingOpRegistrar
CCublasLtLinearPlan	RAII wrapper owning cuBLASLt descriptors for a Linear matmul
CCublasLtMatMulPlan	RAII wrapper owning cuBLASLt descriptors and the selected heuristic algorithm
CCublasLtPlanCache	Generic plan cache keyed on batch size bucket
CCudaDataTypeTraits	Compile-time mapping from TensorDataType -> cudaDataType_t
CCudaDataTypeTraits< TensorDataType::BF16 >
CCudaDataTypeTraits< TensorDataType::FP16 >
CCudaDataTypeTraits< TensorDataType::FP32 >
CCudaDataTypeTraits< TensorDataType::FP8_E4M3 >
CCudaDataTypeTraits< TensorDataType::FP8_E5M2 >
CCudaDataTypeTraits< TensorDataType::INT32 >
CCudaDataTypeTraits< TensorDataType::INT8 >
CFillOps	CUDA specialization of TensorOps for initialization operations
CMathOps	CUDA specialization of TensorOps for mathematical operations
CRandomOps
CStructuralOps
CTensorDataTypeMap	Compile-time mapping from abstract TensorDataType -> CUDA native device type
CTensorDataTypeMap< TensorDataType::BF16 >	Maps TensorDataType::BF16 to CUDA __nv_bfloat16
CTensorDataTypeMap< TensorDataType::FP16 >	Maps TensorDataType::FP16 to CUDA __half
CTensorDataTypeMap< TensorDataType::FP32 >	Maps TensorDataType::FP32 to CUDA float
CTensorDataTypeMap< TensorDataType::FP4_E2M1 >	Maps TensorDataType::FP4_E2M1 to std::uint8_t
CTensorDataTypeMap< TensorDataType::FP4_E3M0 >	Maps TensorDataType::FP4_E3M0 to std::uint8_t
CTensorDataTypeMap< TensorDataType::FP8_E4M3 >	Maps TensorDataType::FP8_E4M3 to CUDA __nv_fp8_e4m3
CTensorDataTypeMap< TensorDataType::FP8_E5M2 >	Maps TensorDataType::FP8_E5M2 to CUDA __nv_fp8_e5m2
CTensorDataTypeMap< TensorDataType::INT16 >	Maps TensorDataType::INT16 to std::int16_t
CTensorDataTypeMap< TensorDataType::INT32 >	Maps TensorDataType::INT32 to std::int32_t
CTensorDataTypeMap< TensorDataType::INT8 >	Maps TensorDataType::INT8 to std::int8_t
CTensorDataTypeMap< TensorDataType::UINT16 >	Maps TensorDataType::UINT16 to std::uint16_t
CTensorDataTypeMap< TensorDataType::UINT32 >	Maps TensorDataType::UINT32 to std::uint32_t
CTensorDataTypeMap< TensorDataType::UINT8 >	Maps TensorDataType::UINT8 to std::uint8_t
CTransferOps	CUDA specialization of TensorOps for tensor transfer operations
CZeroOps
Calways_false
CBinaryOperation
CCpuAdamWOptimizer	CPU-specific AdamW optimizer implementation
CCpuAttentionOp	CPU implementation of Multi-Head Attention operation
CCpuAttentionOpRegistrar
CCpuCrossEntropyOp	CPU implementation of the cross entropy loss operation for neural networks
CCpuCrossEntropyOpRegistrar	Class responsible for registering the CpuCrossEntropyOp operation
CCpuDevice	Class representing a CPU compute device
CCpuDeviceRegistrar	CPU device plugin for device-agnostic registration
CCpuEncoderOp	CPU implementation of the Encoder operation
CCpuEncoderOpRegistrar	Registrar for CpuEncoderOp operation
CCpuGeluOp	CPU implementation of GELU activation operation using abstract TensorDataType
CCpuGeluOpRegistrar	Class responsible for registering CPU GELU operations
CCpuLayerNormOp	CPU implementation of Layer Normalization using abstract TensorDataType API
CCpuLayerNormOpRegistrar
CCpuLinearOp	CPU implementation of Linear operation using abstract TensorDataType API
CCpuLinearOpRegistrar
CCpuMemoryResource	CPU memory resource for host-accessible memory allocation
CCpuResidualOp	CPU Residual operation (FP32) implementing BinaryOperation interface
CCpuResidualOpRegistrar	Registrar for CPU Residual operation (FP32)
CCpuSoftmaxCrossEntropyOp	Fused CPU implementation of Softmax + CrossEntropy using abstract TensorDataType API
CCpuSoftmaxCrossEntropyOpRegistrar	Registrar for fused Softmax+CrossEntropy operation
CCpuSoftmaxOp	CPU implementation of Softmax using abstract TensorDataType API
CCpuSoftmaxOpRegistrar
CCublasLtError
CCudaAdamWOptimizer	CUDA-specific AdamW optimizer implementation
CCudaBadAlloc
CCudaDataTypeMap	Helper struct to map C++ types to CUDA data types for cuBLASLt
CCudaDataTypeMap< __nv_bfloat16 >
CCudaDataTypeMap< float >
CCudaDataTypeMap< half >
CCudaDevice	Class representing a CUDA compute device instance
CCudaDeviceMemoryResource	CUDA device memory resource for GPU-accessible memory allocation
CCudaDeviceProps	Wrapper for CUDA device properties with cached values
CCudaDeviceRegistrar	CUDA device registrar for device-agnostic registration
CCudaError	Exception class for CUDA runtime errors
CCudaManagedMemoryResource	CUDA managed memory resource for unified host/device accessible memory
CCudaPinnedMemoryResource	CUDA pinned memory resource for fast host/device transfer memory
CCudaTimer	GPU-accurate interval timer using a CUDA event pair
CDevice	Abstract interface for compute device implementations
CDeviceAccessible
CDeviceConstructionKey	Construction key for device factories
CDeviceId	Lightweight identifier for a compute device
CDeviceRegistrar	Device-agnostic registrar for automatic device discovery and registration
CDeviceRegistry	Registry of discovered compute devices with lazy instantiation
CDeviceTypeTraits
CDeviceTypeTraits< DeviceType::Cpu >	DeviceTypeTraits specialization for the CPU device
CDeviceTypeTraits< DeviceType::Cuda >	DeviceTypeTraits specialization for the CUDA device
CExecutionContext	Templated execution context for device-specific operations
CExecutionContext< DeviceType::Cpu >	CPU execution context specialization
CExecutionContext< DeviceType::Cuda >	CUDA execution context specialization
CExecutionContext< DeviceType::Metal >	Metal execution context specialization
CExecutionContext< DeviceType::Vulkan >	Vulkan execution context specialization
CGqaState	Non-owning pointers to shared transient GQA scratch buffers
CHostAccessible
CIExecutionContext	Type-erased execution context interface
CIKvCacheLifecycle	Capability interface for KV-cache state management
CIKvInference	Compute interface for attention operations that maintain a KV cache
CIPackedKvInference	KV-cache inference interface for packed-QKV MHA backends
CIPositionalDecode	Capability interface for position-dependent unary operations
CIPositionalPairedOp	Capability interface for position-dependent paired operations
CLinearOpTypeMap< DeviceType::Cpu, TensorDataType::FP32 >
CMemoryResource	Clean memory resource abstraction for device-specific memory allocation
CMemoryResourceTraits	Memory resource traits for compile-time dispatch optimization
CMemoryResourceTraits< CpuMemoryResource >	CPU-specific memory resource traits providing detailed CPU backend characteristics
CMemoryResourceTraits< CudaDeviceMemoryResource >	CUDA device memory resource traits providing detailed GPU backend characteristics
CMemoryResourceTraits< CudaManagedMemoryResource >	CUDA managed memory resource traits providing unified memory characteristics
CMemoryResourceTraits< CudaPinnedMemoryResource >	CUDA pinned memory resource traits providing fast transfer characteristics
CMemoryStats	Global memory statistics for all TrackedMemoryResource instances
CMetalDevice	Class representing a Metal compute device instance
CMetalDevicePlugin	Metal device plugin for device-agnostic registration
CMetalMemoryResource	Stub implementation for non-Apple platforms
COperation
COperationRegistry	Central registry for typed, device-aware compute operations
CTypeID	Composite key for registry lookup
CTypeIDHash
COperationsRegistrar	Class to manage compute operations initialization
COperationTraits	Primary traits template for unified compile-time operation dispatch
COperationTraits< OperationType::CrossEntropyOp, DeviceType::Cuda, TensorDataType::BF16, void >
COperationTraits< OperationType::CrossEntropyOp, DeviceType::Cuda, TensorDataType::FP32, void >
COperationTraits< OperationType::GeluOp, DeviceType::Cpu, TensorDataType::FP32, void >
COperationTraits< OperationType::GeluOp, DeviceType::Cuda, TensorDataType::BF16, void >
COperationTraits< OperationType::GeluOp, DeviceType::Cuda, TensorDataType::FP32, void >
COperationTraits< OperationType::GroupedQueryAttentionOp, DeviceType::Cuda, TensorDataType::BF16, NoKvCompression >	Unquantized BF16 path. No KV cache compression. Standard inference precision
COperationTraits< OperationType::GroupedQueryAttentionOp, DeviceType::Cuda, TensorDataType::FP32, NoKvCompression >	Unquantized FP32 path. No KV cache compression
COperationTraits< OperationType::LinearOp, DeviceType::Cpu, TensorDataType::FP32, NoWeightQuant >
COperationTraits< OperationType::LinearOp, DeviceType::Cuda, TensorDataType::BF16, NoWeightQuant >	Unquantized BF16 path. Standard inference precision
COperationTraits< OperationType::LinearOp, DeviceType::Cuda, TensorDataType::BF16, PerChannelFp8<> >	FP8 per-channel quantized BF16 path. Requires SM >= 8.0 (Ampere+)
COperationTraits< OperationType::LinearOp, DeviceType::Cuda, TensorDataType::BF16, PerGroupFp4< 128 > >	FP4 E2M1 per-group quantized BF16 path. W4A16 fused GEMM with E2M1 decode, group_size=128. Requires SM >= 8.0
COperationTraits< OperationType::LinearOp, DeviceType::Cuda, TensorDataType::BF16, PerGroupFp4< 64 > >	FP4 E2M1 per-group quantized BF16 path. W4A16 fused GEMM with E2M1 decode, group_size=64. Requires SM >= 8.0
COperationTraits< OperationType::LinearOp, DeviceType::Cuda, TensorDataType::BF16, PerGroupInt4< 128 > >	INT4 per-group quantized BF16 path. W4A16 fused GEMM, group_size=128. Requires SM >= 8.0
COperationTraits< OperationType::LinearOp, DeviceType::Cuda, TensorDataType::BF16, PerGroupInt4< 64 > >	INT4 per-group quantized BF16 path. W4A16 fused GEMM, group_size=64. Requires SM >= 8.0
COperationTraits< OperationType::LinearOp, DeviceType::Cuda, TensorDataType::FP32, NoWeightQuant >	Unquantized FP32 path. Retained for validation and reference
COperationTraits< OperationType::LpeOp, DeviceType::Cpu, TensorDataType::FP32, void >
COperationTraits< OperationType::LpeOp, DeviceType::Cuda, TensorDataType::BF16, void >
COperationTraits< OperationType::LpeOp, DeviceType::Cuda, TensorDataType::FP32, void >
COperationTraits< OperationType::MultiHeadAttentionOp, DeviceType::Cpu, TensorDataType::FP32, void >
COperationTraits< OperationType::MultiHeadAttentionOp, DeviceType::Cuda, TensorDataType::BF16, void >
COperationTraits< OperationType::MultiHeadAttentionOp, DeviceType::Cuda, TensorDataType::FP32, void >
COperationTraits< OperationType::ResidualOp, DeviceType::Cpu, TensorDataType::FP32, void >
COperationTraits< OperationType::ResidualOp, DeviceType::Cuda, TensorDataType::BF16, void >
COperationTraits< OperationType::ResidualOp, DeviceType::Cuda, TensorDataType::FP32, void >
COperationTraits< OperationType::RmsNormOp, DeviceType::Cuda, TensorDataType::BF16, void >
COperationTraits< OperationType::RmsNormOp, DeviceType::Cuda, TensorDataType::FP32, void >
COperationTraits< OperationType::RopeOp, DeviceType::Cuda, TensorDataType::BF16, void >
COperationTraits< OperationType::RopeOp, DeviceType::Cuda, TensorDataType::FP32, void >
COperationTraits< OperationType::SoftmaxOp, DeviceType::Cpu, TensorDataType::FP32, void >
COperationTraits< OperationType::SoftmaxOp, DeviceType::Cuda, TensorDataType::BF16, void >
COperationTraits< OperationType::SoftmaxOp, DeviceType::Cuda, TensorDataType::FP32, void >
COperationTraits< OperationType::SwigluOp, DeviceType::Cuda, TensorDataType::BF16, void >
COperationTraits< OperationType::SwigluOp, DeviceType::Cuda, TensorDataType::FP32, void >
COperationTraits< OperationType::TokenEmbeddingOp, DeviceType::Cuda, TensorDataType::BF16, void >
COperationTraits< OperationType::TokenEmbeddingOp, DeviceType::Cuda, TensorDataType::FP32, void >
COptimizer	Abstract base class for parameter optimizers
CPairedOperation	Abstract base for paired operations: two inputs -> two outputs
CTrackedMemoryResource	A memory resource wrapper that tracks allocation and deallocation statistics
CUnaryOperation
CVulkanDevice	Class representing a Vulkan compute device instance
CVulkanMemoryResource	Stub implementation for platforms without Vulkan support
NDetail
Cmlp_activation_impl
Cmlp_activation_impl< ActivationType::Gelu, TDeviceType, TPrecision >
Cmlp_activation_impl< ActivationType::Swiglu, TDeviceType, TPrecision >
NExtensibility
CIModulePlugin
CPluginInfo	Get plugin metadata
CPluginManager	Manages loading and querying of module plugins
CPluginEntry
NOptimizers
CAdamWConfig	Configuration for AdamW optimizer
CAdamWOptimizer	Device-agnostic AdamW optimizer
CSerializationMetadata	Type-safe metadata container for component serialization
NQuant
NKvCache
CNoKvCompression
CPerChannelKvFp8	Symmetric per-head per-token FP8 KV cache compression policy
NWeight
CNoWeightQuant
CPerChannelFp8
CPerGroupFp4
CPerGroupInt4
NSerialization
CArchiveSerializer	Interface for hierarchical archive serializers
CITensorBlob	Type-erased interface for a serialized tensor blob
CModelArchive	ModelArchive provides high-level helpers for component serialization
CScopedScope
CPretrainedMetadata	Metadata for pretrained model
CPretrainedModelReader	Reader for Mila pretrained binary format
CSerializationMetadata	Type-safe metadata container for component serialization
CSerializer	Minimal base interface for model serialization backends
CTensorBlob	Concrete tensor blob owning a TensorBuffer-backed raw byte buffer
CTensorBlobMetadata	Metadata for a tensor blob in pretrained model format
CTensorMetadata	Metadata describing a tensor in serialized form
CZipSerializer	ZIP archive serializer built on miniz
NVisualization
CBlockVisualizer
CColorLUT
CFramebuffer
CLayerNormVisualizer
CMLPVisualizer
CModuleVisualizer
CRect
CRGB
CVisualizerContext
CAxisPartition	Information about axis partitioning of a tensor
CBufferedTokenStreamer	Buffers BufSize tokens before forwarding a contiguous span to Sink
CBuildContext	Build-time context for Component::build()
CComponent	Abstract base class for neural network components
CComponentConfig	Abstract base for component configuration objects
CComponentFactory	Factory for reconstructing components from serialized archives
CCompositeComponent	A component that contains and manages child components
CConstantLRScheduler	Constant learning-rate scheduler
CCosineLRScheduler	Cosine annealing scheduler
CCpuTensorDataTypeTraits	CPU-specific traits for abstract tensor data types
CCrossEntropyConfig	Configuration for fused SoftmaxCrossEntropy loss
Cdependent_false
CDropout	Dropout regularization module for neural networks
CDropoutConfig	Configuration class for Dropout module
CFusedComponent	DEPRECATED
CGelu	Gaussian Error Linear Unit (GELU) activation component
CGeluConfig	Configuration class for GELU module
CGenerateParams
CGenerationStatistics	Statistics captured during a single generateStreaming() call
CGptBlock	Transformer encoder block as a composite component
CGptBlockConfig	Configuration class for GPT transformer blocks
CGptConfig	Network-level configuration for GPT-style transformer networks
CGptModel	GPT inference model
CGptTransformer	GPT-2 style transformer (decoder-only) for autoregressive token prediction
CGqaConfig	Configuration class for the Grouped-Query Attention module
CGroupedQueryAttention	Grouped-Query Attention module that accepts concatenated QKV input
CITensor	Abstract interface providing essential tensor information and data access
CLanguageModel
CLanguageModelConfig	CRTP base configuration for all deployable Mila language models
CLanguageNetwork
CLayerNorm	Device-templated Layer Normalization component
CLayerNormConfig
CLearningRateScheduler	Abstract base for learning-rate schedulers
CLinear	Device-templated fully connected (linear) component
CLinearConfig	Configuration object for a Linear (fully connected) layer
CLinearLRScheduler	Linear decay scheduler
CLlamaBlock
CLlamaConfig	Network-level configuration for LLaMA-style transformer networks
CLlamaModel	LLaMA 3 compatible inference model
CLlamaModelConfig	Deployment configuration for Llama language models
CLlamaTransformer	LLaMA-style transformer (decoder-only) for autoregressive token prediction
CLoss	Abstract base class for neural network loss functions
CLpe	Encoder module for token and positional embeddings (device-templated)
CLpeConfig	Configuration class for the Learned Positional Encoder
CMemoryStats	Memory allocation breakdown for a single component
CMLP	Multi-Layer Perceptron (MLP) composite component
CMLPConfig	Configuration class for the Multi-Layer Perceptron (MLP) block
CModel
CModelConfig	Abstract base configuration for all deployable Mila models
CMultiAxisPartition	Multi-axis partition for normalization over trailing dimensions
CMultiHeadAttention	Multi-Head Attention module that accepts concatenated QKV input
CMultiHeadAttentionConfig	Configuration class for Attention module
CNetwork	Root composite network container
CNetworkFactory	Factory registry for Network deserialization
CResidual	Device-templated Residual connection component
CResidualConfig	Configuration class for Residual connection component
CRmsNorm	Device-templated RMS Normalization component
CRmsNormConfig
CRope	Device-templated RoPE component
CRopeConfig
CSerializationMetadata	Type-safe metadata container for component serialization
CSoftmax	Softmax activation module (device-templated)
CSoftmaxConfig	Configuration class for Softmax module
CSoftmaxCrossEntropy	Fused SoftmaxCrossEntropy loss module (device-templated)
CSwiglu	SwiGLU activation component
CSwigluConfig
CTensor	Device-aware N-dimensional tensor
CTensorBuffer	Device-agnostic buffer for storing tensor data with abstract type system
CTensorDataTypeMap	Primary template for mapping concrete C++ types to TensorDataType
CTensorDataTypeMap< __nv_fp8_e4m3 >
CTensorDataTypeMap< __nv_fp8_e5m2 >
CTensorDataTypeMap< float >	Concrete type mapping for float (FP32)
CTensorDataTypeMap< half >
CTensorDataTypeMap< nv_bfloat16 >
CTensorDataTypeMap< std::int16_t >	Concrete type mapping for 16-bit signed integer
CTensorDataTypeMap< std::int32_t >	Concrete type mapping for 32-bit signed integer
CTensorDataTypeMap< std::int8_t >	Concrete type mapping for 8-bit signed integer
CTensorDataTypeMap< std::uint16_t >	Concrete type mapping for 16-bit unsigned integer
CTensorDataTypeMap< std::uint32_t >	Concrete type mapping for 32-bit unsigned integer
CTensorDataTypeMap< std::uint8_t >	Concrete type mapping for 8-bit unsigned integer
CTensorDataTypeTraits	Compile-time traits for TensorDataType enumeration values
CTensorDataTypeTraits< TensorDataType::BF16 >	Traits specialization for 16-bit brain floating point
CTensorDataTypeTraits< TensorDataType::FP16 >	Traits specialization for 16-bit half precision floating point
CTensorDataTypeTraits< TensorDataType::FP32 >	Traits specialization for 32-bit IEEE 754 floating point
CTensorDataTypeTraits< TensorDataType::FP4_E2M1 >	Traits specialization for 4-bit floating point with E2M1 format
CTensorDataTypeTraits< TensorDataType::FP4_E3M0 >	Traits specialization for 4-bit floating point with E3M0 format
CTensorDataTypeTraits< TensorDataType::FP8_E4M3 >	Traits specialization for 8-bit floating point with E4M3 format
CTensorDataTypeTraits< TensorDataType::FP8_E5M2 >	Traits specialization for 8-bit floating point with E5M2 format
CTensorDataTypeTraits< TensorDataType::INT16 >	Traits specialization for 16-bit signed integer
CTensorDataTypeTraits< TensorDataType::INT32 >	Traits specialization for 32-bit signed integer
CTensorDataTypeTraits< TensorDataType::INT8 >	Traits specialization for 8-bit signed integer
CTensorDataTypeTraits< TensorDataType::UINT16 >	Traits specialization for 16-bit unsigned integer
CTensorDataTypeTraits< TensorDataType::UINT32 >	Traits specialization for 32-bit unsigned integer
CTensorDataTypeTraits< TensorDataType::UINT8 >	Traits specialization for 8-bit unsigned integer
CTensorHostTypeMap	Maps abstract TensorDataType to host-compatible C++ type and TensorDataType
CTensorHostTypeMap< TensorDataType::BF16 >	Host type for 16-bit brain floating point
CTensorHostTypeMap< TensorDataType::FP16 >	Host type for 16-bit half precision floating point
CTensorHostTypeMap< TensorDataType::FP32 >	Host type for 32-bit IEEE 754 floating point
CTensorHostTypeMap< TensorDataType::FP8_E4M3 >	Host type for 8-bit floating point with E4M3 format
CTensorHostTypeMap< TensorDataType::FP8_E5M2 >	Host type for 8-bit floating point with E5M2 format
CTensorHostTypeMap< TensorDataType::INT16 >	Host type for 16-bit signed integer
CTensorHostTypeMap< TensorDataType::INT32 >	Host type for 32-bit signed integer
CTensorHostTypeMap< TensorDataType::INT8 >	Host type for 8-bit signed integer
CTensorHostTypeMap< TensorDataType::UINT16 >	Host type for 16-bit unsigned integer
CTensorHostTypeMap< TensorDataType::UINT32 >	Host type for 32-bit unsigned integer
CTensorHostTypeMap< TensorDataType::UINT8 >	Host type for 8-bit unsigned integer
CTensorOps	Device-dispatched TensorOps interface template
CTensorOps< Compute::DeviceType::Cpu >
CTensorOps< Compute::DeviceType::Cuda >
CTensorShape	Fixed-capacity inline shape descriptor for N-dimensional tensors
CTokenEmbedding	Pure token embedding component (device-templated)
CTokenEmbeddingConfig	Configuration for the TokenEmbedding component
CUniqueIdGenerator	Thread-safe generator for unique tensor identifiers
CVulkanTensorTraits	Vulkan-specific traits for abstract tensor data types
NLogging
CConsoleSink	Thread-safe logging sink that writes formatted records to the console
CFileSink	Thread-safe logging sink that writes formatted records to a file
CLogger	Abstract logging interface and static facade
CNullSink	A logging sink that silently discards all records
NProfiling
CNvtxRange
NUtils
CStepLogger
CVersion	Semantic Version data
Nstd
Chash< Mila::Dnn::Compute::DeviceId >	Hash specialization for DeviceId
CCudaException
CMyCustomLayerPlugin