code: def reshape_hidden_states_to_3d(hidden_states):
      """
      Turn hidden_states from (layer, batch, position, d_model)
      to a tensor  (layer, d_model, batch + position).
      Args:
          hidden_states: the hidden states return by the language model. A list of tensors. Its shape:
              (layer, batch, position, d_model)
      returns:
          hidden_states: tensor in the shape (layer, d_model, batch + position)
      """
      hs = hidden_states
  
      # Turn from a list of tensors into a tensor
      if isinstance(hs, tuple):
          hs = torch.stack(hs)
  
      # Merge the batch and position dimensions
      hs = hs.reshape((hs.shape[0], -1, hs.shape[-1]))
  
      return hs
  
label_desc: Use image node_id 1 for calling a global function with example usage: reshape_hidden_states_to_3d(hidden_states) and returns: hs