| 231 | class MotionEncoderBiGRUCo(nn.Module): |
| 232 | |
| 233 | def __init__(self, input_size, hidden_size, output_size): |
| 234 | super(MotionEncoderBiGRUCo, self).__init__() |
| 235 | |
| 236 | self.input_emb = nn.Linear(input_size, hidden_size) |
| 237 | self.gru = nn.GRU(hidden_size, |
| 238 | hidden_size, |
| 239 | batch_first=True, |
| 240 | bidirectional=True) |
| 241 | self.output_net = nn.Sequential( |
| 242 | nn.Linear(hidden_size * 2, hidden_size), nn.LayerNorm(hidden_size), |
| 243 | nn.LeakyReLU(0.2, inplace=True), nn.Linear(hidden_size, |
| 244 | output_size)) |
| 245 | |
| 246 | self.input_emb.apply(init_weight) |
| 247 | self.output_net.apply(init_weight) |
| 248 | self.hidden_size = hidden_size |
| 249 | self.hidden = nn.Parameter( |
| 250 | torch.randn((2, 1, self.hidden_size), requires_grad=True)) |
| 251 | |
| 252 | # input(batch_size, seq_len, dim) |
| 253 | def forward(self, inputs, m_lens): |