espnet2.asr.encoder.rnn_encoder.RNNEncoder

source

class espnet2.asr.encoder.rnn_encoder.RNNEncoder(input_size: int, rnn_type: str = 'lstm', bidirectional: bool = True, use_projection: bool = True, num_layers: int = 4, hidden_size: int = 320, output_size: int = 320, dropout: float = 0.0, subsample: Sequence[int] | None = (2, 2, 1, 1))

Bases: AbsEncoder

RNNEncoder class.

• Parameters:
  • input_size – The number of expected features in the input
  • output_size – The number of output features
  • hidden_size – The number of hidden features
  • bidirectional – If True becomes a bidirectional LSTM
  • use_projection – Use projection layer or not
  • num_layers – Number of recurrent layers
  • dropout – dropout probability

Initializes internal Module state, shared by both nn.Module and ScriptModule.

forward(xs_pad: Tensor, ilens: Tensor, prev_states: Tensor | None = None) → Tuple[Tensor, Tensor, Tensor]

Defines the computation performed at every call.

Should be overridden by all subclasses.

NOTE

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

output_size() → int