FlexNN 1
Fully connected neural network built from scratch with flexible n-layer design and multiple activations.
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FlexNN::Layers Namespace Reference

Classes

class  AvgPool1D
 
class  BatchNorm1D
 
struct  BatchNormParams
 Parameters for BatchNorm1D. More...
 
class  Conv1D
 
struct  Conv1DParams
 Parameters for a Conv1D layer. More...
 
class  Dense
 Fully-connected layer: Z = W*X + b, A = act(Z). More...
 
struct  DenseParams
 Parameters for a Dense layer. More...
 
class  Layer
 Type-erased layer — holds one concrete layer type. More...
 
class  MaxPool1D
 
struct  Pool1DParams
 Parameters for pooling layers (Max and Avg share this POD). More...
 

Enumerations

enum class  LayerType : uint8_t {
  Dense = 0 , Conv1D = 1 , BatchNorm1D = 2 , MaxPool1D = 3 ,
  AvgPool1D = 4
}
 Layer kind, stable on-wire (uint8_t). More...
 
enum class  DType : uint16_t { F32 = 0 }
 Data type for blobs in model.bin. More...
 

Enumeration Type Documentation

◆ DType

enum class FlexNN::Layers::DType : uint16_t
strong

Data type for blobs in model.bin.

v0.1 only F32 (float32 IEEE). Value 1 is reserved; importer must reject unknown values (e.g., !=0) with Status error.

Enumerator
F32 

float32 little-endian

◆ LayerType

enum class FlexNN::Layers::LayerType : uint8_t
strong

Layer kind, stable on-wire (uint8_t).

Do not reorder — model.bin stores this as 1 byte. New types are appended.

Enumerator
Dense 

Fully-connected: W[out×in], b[out].

Conv1D 

1D temporal convolution

BatchNorm1D 

Per-feature BatchNorm (gamma/beta/mean/var in aux)

MaxPool1D 

Max pooling, weightless.

AvgPool1D 

Average pooling, weightless.