mdlearn.nn.modules.lstm_net

LSTMNet module.

Classes

LSTMNet(*args, **kwargs)

class mdlearn.nn.modules.lstm_net.LSTMNet(*args: Any, **kwargs: Any)
__init__(input_dim: int, neurons: List[int] = [32], bias: bool = True, dropout: float = 0.0)

LSTMNet module for easy StackedLSTM network creation. The returned tensor from the forward function, is the hidden state of the final LSTM layer.

Parameters

  • input_dim (int) – Dimension D of input tensor (N, D) where N is the length of the sequence and D is the dimension of each example.

  • neurons (List[int], default=[32]) – LSTM layers hidden_size.

  • bias (bool, default=True) – If False, then each layer does not use bias weights b_ih and b_hh.

  • dropout (float, default=0.0) – If non-zero, introduces a Dropout layer on the outputs of each LSTM layer except the last layer, with dropout probability equal to dropout.

Note

Bidirectional LSTMs are not currently supported in this module.

Raises

ValueError – neurons should specify atleast one layer.

forward(x: torch.Tensor) → torch.Tensor

Forward pass through LSTM network.

Parameters

x (torch.Tensor) – Input data of shape (B, N, D) where B is the batch size, N is the length of the sequence, and D is the dimension.

Returns

torch.Tensor – The output of the neural network with dimension (batch size, last neuron size).