TensorFlow學習筆記

1、擬合直線

# import the library

import tensorflow as tf
import numpy as np
# prepare train data
train_x = np.linspace(-1, 1, 100)
#temp1 = *train_x,
#temp2 = *train_x.shape,#*argc 解包，把陣列開啟
#te*** = train_x.shape,
train_y = 2 * train_x + np.random.randn(*train_x.shape) * 0.33 + 10
# define the model
x = tf.placeholder("float")
y = tf.placeholder("float")
w = tf.variable(0.0, name="weght")
b = tf.variable(0.0, name="bias")
loss = tf.square(y - tf.multiply(x, w) - b)
#loss = tf.square(y - tf.mul(x, w) - b)
train_op = tf.train.gradientdescentoptimizer(0.01).minimize(loss)
# create session to run
with tf.session() as sess:
sess.run(tf.initialize_all_variables())
epoch = 1
for i in range(10):
for (x, y) in zip(train_x, train_y):
_, w_value, b_value = sess.run([train_op, w, b], feed_dict=)
print("epoch: {}, w: {}, b: {}".format(epoch, w_value, b_value))
epoch += 1

除錯這段**遇到了幾個問題

*train_x.shape中 * 的意思表示將乙個陣列解壓，比如a = [1,  2,  3]，那*a則是  1,  2,  3，把陣列開啟了，這麼用是因為randn函式的引數需求

tf.mul執行報錯，需要改為tf.multiply

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