def __init__(self, input_size, hidden_size, output_size, k, bias=True):
super(MRNNFixD, self).__init__()
self.k = k
self.input_size = input_size
self.output_size = output_size
self.b_d = Parameter(torch.Tensor(torch.zeros(1, input_size)),
requires_grad=True)
self.mrnn_cell = layers.MRNNFixDCell(input_size, hidden_size,
output_size, k)
def __init__(self,
input_size,
hidden_size,
output_size,
k,
dropout,
bias=True):
super(MRNNFixD, self).__init__()
self.k = k
self.input_size = input_size
self.output_size = output_size
self.hidden_size = hidden_size
self.bd1 = Parameter(torch.Tensor(torch.zeros(1, input_size)),
requires_grad=True)
self.dropout = nn.Dropout(dropout)
self.mrnn_cell_1 = layers.MRNNFixDCell(input_size, hidden_size,
hidden_size, k)
self.lstm_cell_2 = nn.LSTMCell(hidden_size, hidden_size)
self.hidden2output = nn.Linear(hidden_size, output_size)