class_docstr: Note: is ACTUALLY a cross-correlation i.e. weights are not 'flipped'
class_docstr_tok: ["Note",":","is","ACTUALLY","a","cross-correlation","i.e",".","weights","are","not","'flipped","'"]
code: def _build_activation_vars(self, input_act_vars):
      if self.data_format == DataFormat.channels_first:
          input_act_vars = tf.transpose(
              a=input_act_vars, perm=[0, 2, 3, 1]
          )
  
      conv_without_bias = self._compute_conv_without_bias(
          x=input_act_vars, kernel=self.kernel
      )
      to_return = conv_without_bias + self.bias[None, None, None, :]
  
      if self.data_format == DataFormat.channels_first:
          to_return = tf.transpose(a=to_return, perm=[0, 3, 1, 2])
      return to_return
  
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 .None import helper_functions
  import tensorflow
label_desc: Use image node_id 3 for calling the Conv2D obj's underlying member method code with example usage: obj._build_activation_vars(input_act_vars) and returns: to_return