73844a5b82ca5a3dd9837a3fbed434b06af360bd,thinc/layers/lstm.py,,forward,#Any#Any#Any#,83

Before Change

    model: Model[RNNState, RNNState], prevstate_inputs: RNNState, is_train: bool
) -> Tuple[RNNState, Callable]:
    (cell_tm1, hidden_tm1), inputs = prevstate_inputs
    weights = model.layers[0]
    W = weights.get_param("W")
    b = weights.get_param("b")
    nI = inputs.shape[1]
    hiddens, cells, gates = model.ops.lstm(W, b, cell_tm1, hidden_tm1, inputs)

After Change

    hiddens += h
    cells += c
    Y, cells, gates = model.ops.recurrent_lstm(W, b, hiddens, cells, X)
    Yp = Padded(Y, Xp.size_at_t, Xp.lengths, Xp.indices)

    def backprop(dYp: Padded) -> Padded:
        raise NotImplementedError

Instances