Created by: Termset

类似pytorch的代码如下：

class LSTMNet(nn.Module):
    def __init__(self, input_size, hidden_size,
                 num_layers=1,
                 bias=True,
                 batch_fisrt=True,
                 bidirectional=True):
        super(LSTMNet, self).__init__()

        self.lstm = nn.LSTM(
            input_size=input_size,
            hidden_size=hidden_size,
            num_layers=num_layers,
            bias=bias,
            batch_first=batch_fisrt,
            bidirectional=bidirectional
        )

    def forward(self, input, wh=None, wc=None):
        output, (hidden, cell) = self.lstm(input)
        return output

而使用paddlepaddle，layers.lstm()需要传入输入值，无法在init时候搭建lstm

class LSTMNet(parl.Model):
    def __init__(self, batch_size, hidden_size,
                 num_layers=1,
                 bidirectional=True):

        super(LSTMNet, self).__init__()
        self.bidirectional = bidirectional
        self.num_layers = num_layers
        self.hidden_size = hidden_size
        cell = layers.LSTMCell(hidden_size=hidden_size)
        self.batch_size = batch_size
        # output = layers.rnn(cell=cell, inputs=, )
        # output = layers.

    def forward(self, input):
        input.stop_gradient = False
        self.init_h = layers.fill_constant([self.num_layers * 2, self.batch_size, self.hidden_size], 'float32', 0.0)
        self.init_c = layers.fill_constant([self.num_layers * 2, self.batch_size, self.hidden_size], 'float32', 0.0)
        output, hidden, cell = layers.lstm(
            input=input,
            init_h=self.init_h,
            init_c=self.init_c,
            max_len=100,
            is_test=False,
            hidden_size=self.hidden_size,
            num_layers=self.num_layers,
            is_bidirec=self.bidirectional
        )
        return output

请问这个应该怎么写呢？