code: def main():
      """
      You can also run these commands manually to generate the pb file
      1. git clone https://github.com/tensorflow/models.git
      2. export PYTHONPATH=Path_to_your_model_folder
      3. python temporal_convolution.py
      """
      tf.set_random_seed(1024)
      input_width = 32
      input_channel = 3
      inputs = tf.Variable(
          tf.random_uniform((1, input_width, input_channel)),
          name="input",
      )
      inputs = tf.identity(inputs, "input_node")
      filter_width = 4
      output_channels = 6
      filters = tf.Variable(
          tf.random_uniform(
              (filter_width, input_channel, output_channels)
          )
      )
      conv_out = tf.nn.conv1d(
          inputs, filters, stride=1, padding="VALID"
      )
      bias = tf.Variable(tf.zeros([output_channels]))
  
      output = tf.nn.tanh(tf.nn.bias_add(conv_out, bias), name="output")
  
      net_outputs = map(
          lambda x: tf.get_default_graph().get_tensor_by_name(x),
          argv[2].split(","),
      )
      run_model(net_outputs, argv[1], backward=(argv[3] == "True"))
  
imports: import tensorflow
  from sys import argv
  from util import run_model
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types