def forward()

in inference/model.py [0:0]

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

    def forward(self, x: torch.Tensor, start_pos: int, freqs_cis: torch.Tensor, mask: Optional[torch.Tensor]) -> torch.Tensor:
        """
        Forward pass for the Transformer block.

        Args:
            x (torch.Tensor): Input tensor.
            start_pos (int): Starting position in the sequence.
            freqs_cis (torch.Tensor): Precomputed complex exponential values for rotary embeddings.
            mask (Optional[torch.Tensor]): Mask tensor to exclude certain positions from attention.

        Returns:
            torch.Tensor: Output tensor after block computation.
        """
        x = x + self.attn(self.attn_norm(x), start_pos, freqs_cis, mask)
        x = x + self.ffn(self.ffn_norm(x))
        return x