class_docstr: Concatenates all inputs by their last dimension. The resulting tensor last dim will be
  the sum of the last dimension of all input tensors.
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docstr: Args:
      input_list (List[torch.Tensor]): a list of tensors of shape
          (batch_size, seq_len, feature_dim).
  
  Returns:
      Tensor of shape (batch_size, seq_len, sum(feature_dims)) where sum(feature_dims)
          is the sum of all input feature_dims.
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code: def forward(self, input_list: List[torch.Tensor]) -> torch.Tensor:
      """
      Args:
          input_list (List[torch.Tensor]): a list of tensors of shape
              (batch_size, seq_len, feature_dim).
  
      Returns:
          Tensor of shape (batch_size, seq_len, sum(feature_dims)) where sum(feature_dims)
              is the sum of all input feature_dims.
      """
      return torch.cat(input_list, dim=-1)
  
imports: from typing import Callable, List
  import torch
  import torch.nn
label_desc: Use image node_id 3 for calling the ConcatFusion obj's underlying member method code with example usage: obj.forward(input_list) and returns: torch