For a more complete description, see: https://tinyurl.com/gpumode-trimul
You will be implementing a Triangle Multiplicative Update (TriMul) module that is a core operation
for AlphaFold3, Chai, Protenix, and other protein structure prediction models in BioML.

The TriMul operator operates over a 4D tensor of shape [B, N, N, C]. 

Your task:
- Implement the "outgoing" version of the TriMul operator from the AlphaFold3 paper.
- You will not have to compute or store gradients for this version. You will only need to implement the forward pass.

Input:
- `data`: Tuple of (input: torch.Tensor, weights: Dict[str, torch.Tensor], config: Dict)
  - input: Input tensor of shape [bs, seq_len, seq_len, dim]
  - mask: Mask tensor of shape [bs, seq_len, seq_len]
  - weights: Dictionary containing model weights
  - config: Dictionary containing model configuration parameters

Output:
- Tuple containing:
  - output: Processed tensor [bs, seq_len, seq_len, dim]
