code: def _stack_weight(ws):
      # TODO(unno): Input of the current LSTM implementation is shuffled
      w = stack.stack(ws, axis=1)
      shape = w.shape
      return reshape.reshape(w, (shape[0] * shape[1],) + shape[2:])
  
imports: import numpy
  import chainer
  from chainer import backend
  from chainer.backends import cuda
  from chainer.functions.array import reshape
  from chainer.functions.array import stack
  from chainer.functions.connection import linear
  from chainer.functions.rnn import lstm
  from chainer.functions.rnn import n_step_rnn
  from chainer.utils import argument
  from chainer import variable
  import chainerx
label_desc: Use image node_id 4 for calling a global function with example usage: _stack_weight(ws) and returns: reshape