run.py

def run():
  x_batch, y_batch = generate_dataset()
  x, y, y_pred, loss = linear_regression()

  optimizer = tf.train.GradientDescentOptimizer(0.1)
  train_op = optimizer.minimize(loss)

  with tf.Session() as session:
    session.run(tf.global_variables_initializer())
    feed_dict = {x: x_batch, y: y_batch}
		
    for i in range(30):
      session.run(train_op, feed_dict)
      print(i, "loss:", loss.eval(feed_dict))

    print('Predicting')
    y_pred_batch = session.run(y_pred, {x : x_batch})

  plt.scatter(x_batch, y_batch)
  plt.plot(x_batch, y_pred_batch, color='red')
  plt.xlim(0, 2)
  plt.ylim(0, 2)
  plt.savefig('plot.png')

if __name__ == "__main__":
  run()