def forward(
        self,
        x: torch.Tensor,
        freqs_cis: torch.Tensor,
    ):
        """Perform a forward pass through the TransformerBlock.

        Args:
            x (torch.Tensor): Input tensor.
            freqs_cis (torch.Tensor): Precomputed cosine and sine frequencies.

        Returns:
            torch.Tensor: Output tensor after applying attention and feedforward layers.

        """
        h = x + self.attention(self.attention_norm(x), freqs_cis)
        return h + self.feed_forward(self.ffn_norm(h))
Perform a forward pass through the TransformerBlock.

        Args:
            x (torch.Tensor): Input tensor.
            freqs_cis (torch.Tensor): Precomputed cosine and sine frequencies.

        Returns:
            torch.Tensor: Output tensor after applying attention and feedforward layers.

        
examples/pytorch/tensor_parallel/model.py