I am new to python & tensorFlow, and I am following this MNIST tutorial on tensorFlow documentation.
In the first bit, I don't know what FLAGS = None does here. I searched in Google, and came back empty. Seems like this is too obvious to others?
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import argparse
import sys
from tensorflow.examples.tutorials.mnist import input_data
import tensorflow as tf
FLAGS = None
def main(_):
# Import data
mnist = input_data.read_data_sets(FLAGS.data_dir, one_hot=True)
So what is FLAGS and how it is used? e.g., FLAGS.data_dir
Any help would be appreciated!
This was the full code you're looking at: I'll explain:
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import argparse
import sys
from tensorflow.examples.tutorials.mnist import input_data
import tensorflow as tf
FLAGS = None #Adds a default value to FLAGS
def main(_): #Everything inside the function is not checked until it's called
mnist = input_data.read_data_sets(FLAGS.data_dir, one_hot=True) #FLAGS is not None anymore because it got changed below
x = tf.placeholder(tf.float32, [None, 784])
W = tf.Variable(tf.zeros([784, 10]))
b = tf.Variable(tf.zeros([10]))
y = tf.matmul(x, W) + b
y_ = tf.placeholder(tf.float32, [None, 10])
cross_entropy = tf.reduce_mean(
tf.nn.softmax_cross_entropy_with_logits(labels=y_, logits=y))
train_step = tf.train.GradientDescentOptimizer(0.5).minimize(cross_entropy)
sess = tf.InteractiveSession()
tf.global_variables_initializer().run()
# Train
for _ in range(1000):
batch_xs, batch_ys = mnist.train.next_batch(100)
sess.run(train_step, feed_dict={x: batch_xs, y_: batch_ys})
# Test trained model
correct_prediction = tf.equal(tf.argmax(y, 1), tf.argmax(y_, 1))
accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
print(sess.run(accuracy, feed_dict={x: mnist.test.images,
y_: mnist.test.labels}))
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--data_dir', type=str, default='/tmp/tensorflow/mnist/input_data',
help='Directory for storing input data')
FLAGS, unparsed = parser.parse_known_args() #Here it changed the value of FLAGS to the first thing returned from parser.parse_known_args()
tf.app.run(main=main, argv=[sys.argv[0]] + unparsed) #runs the app (calling main)
what was happening is that FLAGS got changed here:
FLAGS, unparsed = parser.parse_known_args()
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