LSTM API

namespace lstm

Functions

LSTMConfig parse_config_json(const nlohmann::json &config)

Parse LSTM configuration from JSON.

Parameters:

config – JSON configuration object

Returns:

LSTMConfig

std::unique_ptr<ModelConfig> create_config(const nlohmann::json &config, double sampleRate)

Config parser for ConfigParserRegistry.

class LSTM : public nam::DSP
#include <lstm.h>

A multi-layer LSTM model.

A multi-layer LSTM processes audio frame-by-frame, maintaining hidden states across layers. Each layer processes the hidden state from the previous layer as input.

Public Functions

LSTM(const int in_channels, const int out_channels, const int num_layers, const int input_size, const int hidden_size, std::vector<float> &weights, const double expected_sample_rate = -1.0)

Constructor.

Parameters:

  • in_channels – Number of input channels

  • out_channels – Number of output channels

  • num_layers – Number of LSTM layers

  • input_size – Size of the input to each LSTM cell

  • hidden_size – Size of the hidden state in each LSTM cell

  • weights – Model weights vector

  • expected_sample_rate – Expected sample rate in Hz (-1.0 if unknown)

~LSTM() = default

Destructor.

virtual void process(NAM_SAMPLE **input, NAM_SAMPLE **output, const int num_frames) override

Process audio frames.

Parameters:

  • input – Input audio buffers

  • output – Output audio buffers

  • num_frames – Number of frames to process

class LSTMCell
#include <lstm.h>

A single LSTM cell.

Public Functions

LSTMCell(const int input_size, const int hidden_size, std::vector<float>::iterator &weights)

Constructor.

Parameters:

  • input_size – Size of the input vector

  • hidden_size – Size of the hidden state

  • weights – Iterator to the weights vector. Will be advanced as weights are consumed.

inline Eigen::VectorXf get_hidden_state() const

Get the current hidden state.

Returns:

Hidden state vector

void process_(const Eigen::VectorXf &x)

Process a single input vector.

Parameters:

x – Input vector

struct LSTMConfig : public nam::ModelConfig
#include <lstm.h>

Configuration for an LSTM model.

Public Functions

virtual std::unique_ptr<DSP> create(std::vector<float> weights, double sampleRate) override

Construct a DSP object from this configuration.

Parameters:

  • weights – Model weights (taken by value to allow move for WaveNet)

  • sampleRate – Expected sample rate in Hz

Returns:

Unique pointer to a DSP object

Public Members

int num_layers
int input_size
int hidden_size
int in_channels
int out_channels
class LSTM : public nam::DSP

A multi-layer LSTM model.

A multi-layer LSTM processes audio frame-by-frame, maintaining hidden states across layers. Each layer processes the hidden state from the previous layer as input.

Public Functions

LSTM(const int in_channels, const int out_channels, const int num_layers, const int input_size, const int hidden_size, std::vector<float> &weights, const double expected_sample_rate = -1.0)

Constructor.

Parameters:

  • in_channels – Number of input channels

  • out_channels – Number of output channels

  • num_layers – Number of LSTM layers

  • input_size – Size of the input to each LSTM cell

  • hidden_size – Size of the hidden state in each LSTM cell

  • weights – Model weights vector

  • expected_sample_rate – Expected sample rate in Hz (-1.0 if unknown)

~LSTM() = default

Destructor.

virtual void process(NAM_SAMPLE **input, NAM_SAMPLE **output, const int num_frames) override

Process audio frames.

Parameters:

  • input – Input audio buffers

  • output – Output audio buffers

  • num_frames – Number of frames to process

class LSTMCell

A single LSTM cell.

Public Functions

LSTMCell(const int input_size, const int hidden_size, std::vector<float>::iterator &weights)

Constructor.

Parameters:

  • input_size – Size of the input vector

  • hidden_size – Size of the hidden state

  • weights – Iterator to the weights vector. Will be advanced as weights are consumed.

inline Eigen::VectorXf get_hidden_state() const

Get the current hidden state.

Returns:

Hidden state vector

void process_(const Eigen::VectorXf &x)

Process a single input vector.

Parameters:

x – Input vector