code: def _extract_apply_in_data(inputs):
      if not inputs:
          return False, ()
  
      if chainerx.is_available():
          has_chainerx_array = False
  
          # Unwrap arrays
          arrays = []
          for x in inputs:
              if isinstance(x, variable.Variable):
                  if x._has_chainerx_array:
                      arrays.append(x._data[0])
                      has_chainerx_array = True
                  else:
                      arrays.append(x.array)
              else:  # x is ndarray
                  arrays.append(x)
                  if not has_chainerx_array:
                      if isinstance(x, chainerx.ndarray):
                          has_chainerx_array = True
          return has_chainerx_array, tuple(arrays)
      else:
          return False, tuple(
              [
                  x.array if isinstance(x, variable.Variable) else x
                  for x in inputs
              ]
          )
  
imports: import numpy
  import chainer
  from chainer import backend
  from chainer.backends import cuda
  from chainer.functions.activation import sigmoid
  from chainer.functions.activation import tanh
  from chainer.functions.array import concat
  from chainer.functions.array import split_axis
  from chainer.functions.connection import linear
  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 1 for calling a global function with example usage: _extract_apply_in_data(inputs) and returns: False,  , has_chainerx_array,  tuple, False,  tuple