code: def uncombine_initial_dims(tensor: torch.Tensor, original_size: torch.Size) -> torch.Tensor:
      
      if len(original_size) <= 2:
          return tensor
      else:
          view_args = list(original_size) + [tensor.size(-1)]
          return tensor.view(*view_args)
docs: Given a tensor of embeddings with shape
      (d1 * ... * dn, sequence_length, embedding_dim)
      and the original shape
      (d1, ..., dn, sequence_length),
      return the reshaped tensor of embeddings with shape
      (d1, ..., dn, sequence_length, embedding_dim).
      If original size is 1-d or 2-d, return it as is.