[텐서플로] 경사하강법 그래프 보기

 

import tensorflow.compat.v1 as tf
tf.disable_v2_behavior()
import matplotlib.pyplot as plt
class GradientDescent:
    @staticmethod
    def execute():
        X = [1., 2., 3.]
        Y = [1., 2., 3.]
        m = len(X)
        W = tf.placeholder(tf.float32)
        hypothesis = tf.multiply(X, W)
        cost = tf.reduce_mean(tf.pow(hypothesis - Y, 2)) / m
        W_val = []
        cost_val = []
        with tf.Session() as sess:
            init = tf.global_variables_initializer()
            sess.run(init)
            for i in range(-30, 50):
                W_val.append(i * 0.1)
                cost_val.append(sess.run(cost, {W: i * 0.1}))
            plt.plot(W_val, cost_val, 'ro')
            plt.ylabel('COST')
            plt.xlabel('W')
            plt.savefig('./data/result.svg')
            print('경사하강법 종료')
            return '종료'
if __name__ == '__main__':
    GradientDescent.execute()