linear_regression.py

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')
    b = tf.Variable(np.random.normal(), name='b')
		
    y_pred = tf.add(tf.multiply(w, x), b)

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

  return x, y, y_pred, loss