LSTM Language Model¶
LSTM Language Model¶
-
class
openspeech.models.lstm_lm.model.
LSTMLanguageModel
(configs: omegaconf.dictconfig.DictConfig, tokenizer: openspeech.tokenizers.tokenizer.Tokenizer)[source]¶ LSTM language model. Paper: http://www-i6.informatik.rwth-aachen.de/publications/download/820/Sundermeyer-2012.pdf
- Parameters
configs (DictConfig) – configuration set.
tokenizer (Tokenizer) – tokenizer is in charge of preparing the inputs for a model.
- Inputs:
- inputs (torch.FloatTensor): A input sequence passed to encoders. Typically for inputs this will be
a padded FloatTensor of size
(batch, seq_length, dimension)
.
- Returns
Result of model predictions.
- Return type
outputs (dict)
LSTM Language Model Configuration¶
-
class
openspeech.models.lstm_lm.configurations.
LSTMLanguageModelConfigs
(model_name: str = 'lstm_lm', num_layers: int = 3, hidden_state_dim: int = 512, dropout_p: float = 0.3, rnn_type: str = 'lstm', max_length: int = 128, teacher_forcing_ratio: float = 1.0, optimizer: str = 'adam')[source]¶ This is the configuration class to store the configuration of a
LSTMLanguageModel
.It is used to initiated an LSTMLanguageModel model.
Configuration objects inherit from :class: ~openspeech.dataclass.configs.OpenspeechDataclass.
- Parameters
model_name (str) – Model name (default: lstm_lm)
num_layers (int) – The number of lstm layers. (default: 3)
hidden_state_dim (int) – The hidden state dimension of model. (default: 512)
dropout_p (float) – The dropout probability of encoder. (default: 0.3)
rnn_type (str) – Type of rnn cell (rnn, lstm, gru) (default: lstm)
max_length (int) – Max decoding length. (default: 128)
teacher_forcing_ratio (float) – The ratio of teacher forcing. (default: 1.0)
optimizer (str) – Optimizer for training. (default: adam)