Module nn 

Neural Network module - PyTorch-compatible neural network layers and containers

This module provides a modular structure for neural network components:

• module - Base PyModule class and core functionality
• linear - Linear/Dense layers
• container - Sequential, ModuleList, and other containers
• activation - Activation functions
• loss - Loss functions
• conv - Convolutional layers (Conv1d, Conv2d)
• normalization - Normalization layers (BatchNorm, LayerNorm)
• dropout - Dropout and regularization layers
• pooling - Pooling layers (MaxPool, AvgPool, AdaptivePool)

Re-exports

pub use container::PyModuleList;

pub use container::PySequential;

pub use conv::PyConv1d;

pub use conv::PyConv2d;

pub use dropout::PyAlphaDropout;

pub use dropout::PyDropout;

pub use dropout::PyDropout2d;

pub use dropout::PyDropout3d;

pub use linear::PyLinear;

pub use module::PyModule as PyNNModule;

pub use normalization::PyBatchNorm1d;

pub use normalization::PyBatchNorm2d;

pub use normalization::PyLayerNorm;

pub use pooling::PyAdaptiveAvgPool2d;

pub use pooling::PyAdaptiveMaxPool2d;

pub use pooling::PyAvgPool2d;

pub use pooling::PyMaxPool2d;

Modules

activation

Activation functions for neural networks

container

Neural network containers - Sequential, ModuleList, etc.

conv

Convolutional neural network layers

dropout

Dropout and regularization layers

linear

Linear (fully connected) neural network layer

loss

Loss functions for neural networks

module

Base neural network module - Foundation for all PyTorch-compatible layers

normalization

Normalization layers

pooling

Pooling layers

Functions

register_nn_module

Register the nn module with Python