Crate candle_nn

Re-exports

• pub use activation::prelu;
• pub use activation::Activation;
• pub use activation::PReLU;
• pub use batch_norm::batch_norm;
• pub use batch_norm::BatchNorm;
• pub use batch_norm::BatchNormConfig;
• pub use conv::conv1d;
• pub use conv::conv1d_no_bias;
• pub use conv::conv2d;
• pub use conv::conv2d_no_bias;
• pub use conv::conv_transpose1d;
• pub use conv::conv_transpose1d_no_bias;
• pub use conv::conv_transpose2d;
• pub use conv::conv_transpose2d_no_bias;
• pub use conv::Conv1d;
• pub use conv::Conv1dConfig;
• pub use conv::Conv2d;
• pub use conv::Conv2dConfig;
• pub use conv::ConvTranspose1d;
• pub use conv::ConvTranspose1dConfig;
• pub use conv::ConvTranspose2d;
• pub use conv::ConvTranspose2dConfig;
• pub use embedding::embedding;
• pub use embedding::Embedding;
• pub use func::func;
• pub use func::func_t;
• pub use func::Func;
• pub use func::FuncT;
• pub use group_norm::group_norm;
• pub use group_norm::GroupNorm;
• pub use init::Init;
• pub use layer_norm::layer_norm;
• pub use layer_norm::rms_norm;
• pub use layer_norm::LayerNorm;
• pub use layer_norm::LayerNormConfig;
• pub use layer_norm::RmsNorm;
• pub use linear::linear;
• pub use linear::linear_b;
• pub use linear::linear_no_bias;
• pub use linear::Linear;
• pub use ops::Dropout;
• pub use optim::AdamW;
• pub use optim::Optimizer;
• pub use optim::ParamsAdamW;
• pub use optim::SGD;
• pub use rnn::gru;
• pub use rnn::lstm;
• pub use rnn::GRUConfig;
• pub use rnn::LSTMConfig;
• pub use rnn::GRU;
• pub use rnn::LSTM;
• pub use rnn::RNN;
• pub use sequential::seq;
• pub use sequential::Sequential;
• pub use var_builder::VarBuilder;
• pub use var_map::VarMap;

Modules

• activation
• batch_norm
  Batch Normalization.
• conv
  Convolution Layers.
• embedding
  Embedding Layer.
• encoding
  Encoding Utilities. (e.g., one-hot/cold encoding)
• func
  Layers defined by closures.
• group_norm
  Group Normalization.
• init
  Variable initialization.
• layer_norm
  Layer Normalization.
• linear
  Linear layer
• loss
• ops
• optim
  Various optimization algorithms.
• rnn
  Recurrent Neural Networks
• rotary_emb
• sequential
  A sequential layer used to chain multiple layers and closures.
• var_builder
  A VarBuilder is used to retrieve variables used by a model. These variables can either come from a pre-trained checkpoint, e.g. using VarBuilder::from_mmaped_safetensors, or initialized for training, e.g. using VarBuilder::from_varmap.
• var_map

Traits

• Module
• ModuleT