code: def _conv(name, x, filter_size, in_filters, out_filters, strides):
      """Convolution."""
      with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
          n = filter_size * filter_size * out_filters
          kernel = tf.get_variable(
              "DW",
              [filter_size, filter_size, in_filters, out_filters],
              tf.float32,
              initializer=tf.random_normal_initializer(
                  stddev=np.sqrt(2.0 / n)
              ),
          )
          return tf.nn.conv2d(x, kernel, strides, padding="SAME")
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow
  from cleverhans.serial import NoRefModel
label_desc: Use image node_id 5 for calling a global function with example usage: _conv(name, x, filter_size, in_filters, out_filters, strides) and returns: tf