def forward()

in src/modules/transformer_decoder.py [0:0]

• 36 lines of code
• 1 McCabe index (conditional complexity)

    def forward(self, x, encoder_out, encoder_padding_mask, incremental_state):

        # self attention
        residual = x
        x = self.maybe_layer_norm(0, x, before=True)
        x, _ = self.self_attn(
            query=x,
            key=x,
            value=x,
            mask_future_timesteps=True,
            incremental_state=incremental_state,
            need_weights=False,
        )
        x = F.dropout(x, p=self.dropout, training=self.training)
        x = residual + x
        x = self.maybe_layer_norm(0, x, after=True)

        residual = x
        x = self.maybe_layer_norm(1, x, before=True)

        x, attn = self.encoder_attn(
            query=x,
            key=encoder_out,
            value=encoder_out,
            key_padding_mask=encoder_padding_mask,
            incremental_state=incremental_state,
            static_kv=True,
        )

        x = F.dropout(x, p=self.dropout, training=self.training)
        x = residual + x
        x = self.maybe_layer_norm(1, x, after=True)

        residual = x
        x = self.maybe_layer_norm(-1, x, before=True)
        x = F.relu(self.fc1(x))
        x = F.dropout(x, p=self.relu_dropout, training=self.training)
        x = self.fc2(x)
        x = F.dropout(x, p=self.dropout, training=self.training)
        x = residual + x
        x = self.maybe_layer_norm(-1, x, after=True)
        return x