code: def setUp(self):
      self.input_layer1 = layers.Input(batch_shape=(None, 1, 1, 1))
      self.input_layer2 = layers.Input(batch_shape=(None, 1, 1, 1))
      self.concat_layer = layers.Concat(axis=1)
      self.concat_layer.set_inputs(
          [self.input_layer1, self.input_layer2]
      )
      self.flatten_layer = layers.Flatten()
      self.flatten_layer.set_inputs(self.concat_layer)
      self.dense_layer = layers.Dense(
          kernel=np.array([([1, 2])]).T,
          bias=[1],
          dense_mxts_mode=DenseMxtsMode.Linear,
      )
      self.dense_layer.set_inputs(self.flatten_layer)
      self.dense_layer.build_fwd_pass_vars()
  
      self.input_layer1.reset_mxts_updated()
      self.input_layer2.reset_mxts_updated()
      self.dense_layer.set_scoring_mode(layers.ScoringMode.OneAndZeros)
      self.dense_layer.set_active()
      self.input_layer1.update_mxts()
      self.input_layer2.update_mxts()
  
      self.inp1 = np.arange(2).reshape((2, 1, 1, 1)) + 1
      self.inp2 = np.arange(2).reshape((2, 1, 1, 1)) + 1
  
file_path: deeplift/tests/layers/test_concat.py
imports: from __future__ import division
  from __future__ import print_function
  from __future__ import absolute_import
  import unittest
  from unittest import skip
  import sys
  import os
  import numpy
  import deeplift.layers
  from deeplift.layers import DenseMxtsMode
  from deeplift.util import compile_func
label_desc: Use image node_id 1 for calling the TestConcat obj's underlying member method code with example usage: obj.setUp() without return types