| 107 | |
| 108 | # lstm testing |
| 109 | class LSTMModel3(model.Model): |
| 110 | |
| 111 | def __init__(self, hidden_size): |
| 112 | super(LSTMModel3, self).__init__() |
| 113 | self.lstm = layer.CudnnRNN( |
| 114 | hidden_size=hidden_size, |
| 115 | batch_first=True, |
| 116 | # return_sequences=True, |
| 117 | use_mask=True) |
| 118 | self.l1 = layer.Linear(2) |
| 119 | self.optimizer = opt.SGD(0.1) |
| 120 | |
| 121 | def forward(self, x, seq_lengths): |
| 122 | y = self.lstm(x, seq_lengths=seq_lengths) |
| 123 | y = autograd.reshape(y, (y.shape[0], -1)) |
| 124 | y = self.l1(y) |
| 125 | return y |
| 126 | |
| 127 | |
| 128 | class LSTMModel2(model.Model): |
no outgoing calls