(self, hidden_size, output_size)
| 374 | |
| 375 | class DecoderRNN(nn.Module): |
| 376 | def __init__(self, hidden_size, output_size): |
| 377 | super(DecoderRNN, self).__init__() |
| 378 | self.embedding = nn.Embedding(output_size, hidden_size) |
| 379 | self.gru = nn.GRU(hidden_size, hidden_size, batch_first=True) |
| 380 | self.out = nn.Linear(hidden_size, output_size) |
| 381 | |
| 382 | def forward(self, encoder_outputs, encoder_hidden, target_tensor=None): |
| 383 | batch_size = encoder_outputs.size(0) |