Loading fairseq/models/fconv.py +4 −1 Changes for fairseq/models/fconv.py: 4 added lines, 1 removed line. Original line number Diff line number Diff line Loading @@ -279,8 +279,11 @@ class FConvDecoder(FairseqIncrementalDecoder): encoder_a, encoder_b = self._split_encoder_out(encoder_out, incremental_state) # embed tokens and combine with positional embeddings pos_embed = self.embed_positions(prev_output_tokens, incremental_state) if incremental_state is not None: prev_output_tokens = prev_output_tokens[:, -1:] x = self._embed_tokens(prev_output_tokens, incremental_state) x += self.embed_positions(prev_output_tokens, incremental_state) x += pos_embed x = F.dropout(x, p=self.dropout, training=self.training) target_embedding = x Loading Loading
fairseq/models/fconv.py +4 −1 Changes for fairseq/models/fconv.py: 4 added lines, 1 removed line. Original line number Diff line number Diff line Loading @@ -279,8 +279,11 @@ class FConvDecoder(FairseqIncrementalDecoder): encoder_a, encoder_b = self._split_encoder_out(encoder_out, incremental_state) # embed tokens and combine with positional embeddings pos_embed = self.embed_positions(prev_output_tokens, incremental_state) if incremental_state is not None: prev_output_tokens = prev_output_tokens[:, -1:] x = self._embed_tokens(prev_output_tokens, incremental_state) x += self.embed_positions(prev_output_tokens, incremental_state) x += pos_embed x = F.dropout(x, p=self.dropout, training=self.training) target_embedding = x Loading