Struct burn::nn::Lstm

pub struct Lstm<B>
where
    B: Backend,
{
    pub input_gate: GateController<B>,
    pub forget_gate: GateController<B>,
    pub output_gate: GateController<B>,
    pub cell_gate: GateController<B>,
    pub d_hidden: usize,
}

The Lstm module. This implementation is for a unidirectional, stateless, Lstm.

Introduced in the paper: Long Short-Term Memory.

Should be created with LstmConfig.

Fields

input_gate: GateController<B>

The input gate regulates which information to update and store in the cell state at each time step.

forget_gate: GateController<B>

The forget gate is used to control which information to discard or keep in the memory cell at each time step.

output_gate: GateController<B>

The output gate determines which information from the cell state to output at each time step.

cell_gate: GateController<B>

The cell gate is used to compute the cell state that stores and carries information through time.

d_hidden: usize

The hidden state of the LSTM.

Implementations

impl<B> Lstm<B>

where B: Backend,

pub fn forward( &self, batched_input: Tensor<B, 3>, state: Option<LstmState<B, 2>>, ) -> (Tensor<B, 3>, LstmState<B, 2>)

Applies the forward pass on the input tensor. This LSTM implementation returns the state for each element in a sequence (i.e., across seq_length) and a final state.

Parameters:

• batched_input: The input tensor of shape [batch_size, sequence_length, input_size].
• state: An optional LstmState representing the initial cell state and hidden state. Each state tensor has shape [batch_size, hidden_size]. If no initial state is provided, these tensors are initialized to zeros.

Returns:

• output: A tensor represents the output features of LSTM. Shape: [batch_size, sequence_length, hidden_size]
• state: A LstmState represents the final states. Both state.cell and state.hidden have the shape [batch_size, hidden_size].

Trait Implementations

impl<B> AutodiffModule<B> for Lstm<B>

where B: Backend + AutodiffBackend, <B as AutodiffBackend>::InnerBackend: Backend,

type InnerModule = Lstm<<B as AutodiffBackend>::InnerBackend>

Inner module without auto-differentiation.

fn valid(&self) -> <Lstm<B> as AutodiffModule<B>>::InnerModule

Get the same module, but on the inner backend without auto-differentiation.

impl<B> Clone for Lstm<B>

where B: Backend,

fn clone(&self) -> Lstm<B>

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<B> Debug for Lstm<B>

where B: Debug + Backend,

fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Formats the value using the given formatter.

impl<B> Display for Lstm<B>

where B: Backend,

fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Formats the value using the given formatter.

impl<B> Module<B> for Lstm<B>

where B: Backend,

type Record = LstmRecord<B>

Type to save and load the module.

fn load_record(self, record: <Lstm<B> as Module<B>>::Record) -> Lstm<B>

Load the module state from a record.

fn into_record(self) -> <Lstm<B> as Module<B>>::Record

Convert the module into a record containing the state.

fn num_params(&self) -> usize

Get the number of parameters the module has, including all of its sub-modules.

fn visit<Visitor>(&self, visitor: &mut Visitor)

where Visitor: ModuleVisitor<B>,

Visit each tensor parameter in the module with a visitor.

fn map<Mapper>(self, mapper: &mut Mapper) -> Lstm<B>

where Mapper: ModuleMapper<B>,

Map each tensor parameter in the module with a mapper.

fn collect_devices( &self, devices: Vec<<B as Backend>::Device>, ) -> Vec<<B as Backend>::Device>

Return all the devices found in the underneath module tree added to the given vector without duplicates.

fn to_device(self, device: &<B as Backend>::Device) -> Lstm<B>

Move the module and all of its sub-modules to the given device.

fn fork(self, device: &<B as Backend>::Device) -> Lstm<B>

Fork the module and all of its sub-modules to the given device.

fn devices(&self) -> Vec<<B as Backend>::Device>

Return all the devices found in the underneath module tree without duplicates.

fn no_grad(self) -> Self

Each tensor in the module tree will not require grad.

fn save_file<FR, PB>( self, file_path: PB, recorder: &FR, ) -> Result<(), RecorderError>

where FR: FileRecorder<B>, PB: Into<PathBuf>,

Save the module to a file using the provided file recorder.

fn load_file<FR, PB>( self, file_path: PB, recorder: &FR, device: &<B as Backend>::Device, ) -> Result<Self, RecorderError>

where FR: FileRecorder<B>, PB: Into<PathBuf>,

Load the module from a file using the provided file recorder.

fn quantize_weights<C>(self, quantizer: &mut Quantizer<C>) -> Self

where C: Calibration,

Quantize the weights of the module.

impl<B> ModuleDisplay for Lstm<B>

where B: Backend,

fn custom_settings(&self) -> Option<DisplaySettings>

Custom display settings for the module.

fn custom_content(&self, content: Content) -> Option<Content>

Custom attributes for the module.

fn format(&self, passed_settings: DisplaySettings) -> String

Formats the module with provided display settings.

impl<B> ModuleDisplayDefault for Lstm<B>

where B: Backend,

fn content(&self, content: Content) -> Option<Content>

Attributes of the module used for display purposes.

fn num_params(&self) -> usize

Gets the number of the parameters of the module.