Struct Sequential 

pub struct Sequential { /* private fields */ }

Sequential model

Implementations

impl Sequential

pub fn new() -> Self

Create new sequential model

pub fn name(self, name: impl Into<String>) -> Self

Set model name

pub fn add(&mut self, layer: Box<dyn KerasLayer>)

Add layer to model

pub fn build(&mut self, input_shape: Vec<usize>) -> Result<()>

Build the model with given input shape

pub fn compile( self, loss: LossFunction, optimizer: OptimizerType, metrics: Vec<MetricType>, ) -> Self

Compile the model

pub fn summary(&self) -> ModelSummary

Get model summary

pub fn predict(&self, inputs: &ArrayD<f64>) -> Result<ArrayD<f64>>

Forward pass (predict)

pub fn fit( &mut self, X: &ArrayD<f64>, y: &ArrayD<f64>, epochs: usize, batch_size: Option<usize>, validation_data: Option<(&ArrayD<f64>, &ArrayD<f64>)>, callbacks: Vec<Box<dyn Callback>>, ) -> Result<TrainingHistory>

Train the model

pub fn evaluate( &self, X: &ArrayD<f64>, y: &ArrayD<f64>, batch_size: Option<usize>, ) -> Result<HashMap<String, f64>>

Evaluate the model

impl Sequential

pub fn export_onnx( &self, path: &str, input_shape: &[usize], options: Option<ExportOptions>, ) -> Result<()>

Export to ONNX format