code: def _build_pos_and_neg_contribs(self):
      if self.verbose:
          print(
              "Heads-up: current implementation assumes maxpool layer "
              "is followed by a linear transformation (conv/dense layer)"
          )
      # placeholder; not used for linear layer, hence assumption above
      return tf.zeros_like(
          tensor=self.get_activation_vars(),
          name="dummy_pos_cont_" + str(self.get_name()),
      ), tf.zeros_like(
          tensor=self.get_activation_vars(),
          name="dummy_neg_cont_" + str(self.get_name()),
      )
  
imports: from __future__ import division
  from __future__ import print_function
  from __future__ import absolute_import
  from .core import *
  from .helper_functions import conv1d_transpose_via_conv2d
  from .convolutional import PaddingMode, DataFormat
  from .None import helper_functions
  import tensorflow
  from tensorflow.python.ops import nn_grad
label_desc: Use image node_id 4 for calling the GlobalMaxPool1D obj's underlying member method code with example usage: obj._build_pos_and_neg_contribs() and returns: tf,  tf