Loading fairseq/models/lstm.py +5 −0 Changes for fairseq/models/lstm.py: 5 added lines, 0 removed lines. Original line number Diff line number Diff line Loading @@ -122,6 +122,8 @@ class LSTMDecoder(FairseqIncrementalDecoder): for layer in range(num_layers) ]) self.attention = AttentionLayer(encoder_embed_dim, embed_dim) if embed_dim != out_embed_dim: self.additional_fc = Linear(embed_dim, out_embed_dim) self.fc_out = Linear(out_embed_dim, num_embeddings, dropout=dropout_out) def forward(self, input_tokens, encoder_out): Loading Loading @@ -197,6 +199,9 @@ class LSTMDecoder(FairseqIncrementalDecoder): attn_scores = attn_scores.transpose(0, 2) # project back to size of vocabulary if hasattr(self, 'additional_fc'): x = self.additional_fc(x) x = F.dropout(x, p=self.dropout_out, training=self.training) x = self.fc_out(x) return x, attn_scores Loading Loading
fairseq/models/lstm.py +5 −0 Changes for fairseq/models/lstm.py: 5 added lines, 0 removed lines. Original line number Diff line number Diff line Loading @@ -122,6 +122,8 @@ class LSTMDecoder(FairseqIncrementalDecoder): for layer in range(num_layers) ]) self.attention = AttentionLayer(encoder_embed_dim, embed_dim) if embed_dim != out_embed_dim: self.additional_fc = Linear(embed_dim, out_embed_dim) self.fc_out = Linear(out_embed_dim, num_embeddings, dropout=dropout_out) def forward(self, input_tokens, encoder_out): Loading Loading @@ -197,6 +199,9 @@ class LSTMDecoder(FairseqIncrementalDecoder): attn_scores = attn_scores.transpose(0, 2) # project back to size of vocabulary if hasattr(self, 'additional_fc'): x = self.additional_fc(x) x = F.dropout(x, p=self.dropout_out, training=self.training) x = self.fc_out(x) return x, attn_scores Loading