code: def ConvRelu(incoming, num_filters, filter_size, name):
      """
      Add a convolution layer followed by a Relu layer.
      :param incoming:
      :param num_filters:
      :param filter_size:
      :param name:
      :return:
      """
      num_filters_from = incoming.get_shape().as_list()[3]
      with tf.compat.v1.variable_scope(name):
          conv_W = var_random(
              "W",
              tuple(filter_size) + (num_filters_from, num_filters),
              regularizable=True,
          )
  
          after_conv = tf.nn.conv2d(
              incoming,
              filters=conv_W,
              strides=(1, 1, 1, 1),
              padding="SAME",
          )
  
          return tf.nn.relu(after_conv)
  
file_path: attention-ocr/aocr/model/cnn.py
imports: from __future__ import absolute_import
  import numpy
  import tensorflow
label_desc: Use image node_id 4 for calling a global function with example usage: ConvRelu(incoming, num_filters, filter_size, name) and returns: tf