text: import tensorflow as tf
  
  hidden_layer_weights = [
      [0.1, 0.2, 0.4],
      [0.4, 0.6, 0.6],
      [0.5, 0.9, 0.1],
      [0.8, 0.2, 0.8]]
      
  out_weights = [
      [0.1, 0.6],
      [0.2, 0.1],
      [0.7, 0.9]]
  
  weights = [
      tf.Variable(hidden_layer_weights),
      tf.Variable(out_weights)]
      
  biases = [
      tf.Variable(tf.zeros(3)),
      tf.Variable(tf.zeros(2))]
  
  features = tf.Variable([[1.0, 2.0, 3.0, 4.0], [-1.0, -2.0, -3.0, -4.0], [11.0, 12.0, 13.0, 14.0]])
  
  hidden_layer = tf.add(tf.matmul(features, weights[0]), biases[0])
  hidden_layer = tf.nn.relu(hidden_layer)
  
  logits = tf.add(tf.matmul(hidden_layer, weights[1]), biases[1])
  
  with tf.Session() as session:
      session.run(tf.global_variables_initializer())
      
      print(session.run(logits))
  