def linear_regression():
  x = tf.placeholder(tf.float32, shape=(None, ), name='x')
  y = tf.placeholder(tf.float32, shape=(None, ), name='y')

  with tf.variable_scope('lreg') as scope:
    w = tf.Variable(np.random.normal(), name='W')

    y_pred = tf.multiply(w, x)

    loss = tf.reduce_mean(tf.square(y_pred - y))

  return x, y, y_pred, loss