# Starting the Tensorflow Session

with tf.Session() as sess:

# Initializing the Variables

sess.run(init)

# Iterating through all the epochs

for epoch in range(training_epochs):

# Feeding each data point into the optimizer using Feed Dictionary

for (_x, _y) in zip(x, y):

sess.run(optimizer, feed_dict = {X : _x, Y : _y})

# Displaying the result after every 50 epochs

if (epoch + 1) % 50 == 0:

# Calculating the cost a every epoch

c = sess.run(cost, feed_dict = {X : x, Y : y})

print("Epoch", (epoch + 1), ": cost =", c, "W =", sess.run(W), "b =", sess.run(b))

# Storing necessary values to be used outside the Session

training_cost = sess.run(cost, feed_dict ={X: x, Y: y})

weight = sess.run(W)

bias = sess.run(b)

输出：

Epoch: 50 cost = 5.8868036 W = 0.9951241 b = 1.2381054
Epoch: 100 cost = 5.7912707 W = 0.99812365 b = 1.0914398
Epoch: 150 cost = 5.7119675 W = 1.0008028 b = 0.96044314
Epoch: 200 cost = 5.6459413 W = 1.0031956 b = 0.8434396
Epoch: 250 cost = 5.590799 W = 1.0053328 b = 0.7389357
Epoch: 300 cost = 5.544608 W = 1.007242 b = 0.6455922
Epoch: 350 cost = 5.5057883 W = 1.008947 b = 0.56222
Epoch: 400 cost = 5.473066 W = 1.01047 b = 0.48775345
Epoch: 450 cost = 5.4453845 W = 1.0118302 b = 0.42124167
Epoch: 500 cost = 5.421903 W = 1.0130452 b = 0.36183488
Epoch: 550 cost = 5.4019217 W = 1.0141305 b = 0.30877414
Epoch: 600 cost = 5.3848577 W = 1.0150996 b = 0.26138115
Epoch: 650 cost = 5.370246 W = 1.0159653 b = 0.21905091
Epoch: 700 cost = 5.3576994 W = 1.0167387 b = 0.18124212
Epoch: 750 cost = 5.3468933 W = 1.0174294 b = 0.14747244
Epoch: 800 cost = 5.3375573 W = 1.0180461 b = 0.11730931
Epoch: 850 cost = 5.3294764 W = 1.0185971 b = 0.090368524
Epoch: 900 cost = 5.322459 W = 1.0190892 b = 0.0663058
Epoch: 950 cost = 5.3163586 W = 1.0195289 b = 0.044813324
Epoch: 1000 cost = 5.3110332 W = 1.0199214 b = 0.02561663