I have a source code shows error whenever I try to run it. I've been tried to fix this many times but I couldn't find out the error. The console keep show this:
File "C:\Users\My Documents\LiClipse Workspace\ANN.py", line 51
print session.run(cost, feed_dict={X: x_data, Y: y_data})
^
SyntaxError: invalid syntax
But still, I can't see any error..
Below are the chunk of code:
import tensorflow as tf
import numpy as np
from pip._vendor.requests.packages.urllib3.connectionpool import xrange
x_data = np.array([
[0,0], [0,1], [1,0], [1,1]
])
y_data = np.array([
[0],[1], [1], [0]
])
n_input = 2
n_hidden = 10
n_output = 1
learning_rate = 0.1
epochs = 1000
X = tf.placeholder(tf.float32)
Y = tf.placeholder(tf.float32)
W1 = tf.Variable(tf.random_uniform([n_input, n_hidden], -1.0, 1.0))
W2 = tf.Variable(tf.random_uniform([n_hidden, n_output], -1.0, 1.0))
b1 = tf.Variable(tf.zeros([n_hidden]), name="Bias1")
b2= tf.Variable(tf.zeros([n_output]), name="Bias2")
L2 = tf.sigmoid(tf.matmul(X, W1) + b1)
hy = tf.sigmoid(tf.matmul(L2, W2) + b2)
cost = tf.reduce_mean(-Y*tf.log(hy) - (1-Y)*tf.log(1-hy))
optimizer = tf.train.GradientDescentOptimizer(learning_rate).minimize(cost)
init = tf.initialize_all_variables()
with tf.Session() as session:
session.run(init)
for step in xrange(epochs):
session.run(optimizer, feed_dict={X: x_data, Y: y_data})
if step % 100 == 0:
#print (cost)
print session.run(cost, feed_dict={X: x_data, Y: y_data})
answer = tf.equal(tf.floor(hy + 0.5), Y)
accuracy = tf.reduce_mean(tf.cast(answer, "float"))
print session.run([hy], feed_dict={X: x_data, Y: y_data})
print "Accuracy: ", accuracy.eval({X: x_data, Y: y_data}) * 100, "%"
Can anyone tell me where I did wrongly? Thanks in advance!
