Getting familiar with TensorFlow

tensor_overflow.py

import argparse
import tensorflow as tf
import sys

def flowfib(n):
    ''' f_n = f_n-1 + f_n-2
    
    Fails in a somewhat interesting way, showing that ints passed to constants are cast to 32 bit signed ints,
    causing overflow pretty early in fibonacci sequence.
    
    See for example f_48 = f_47 + f_46
    
    numpy.int32(1134903170) + numpy.int32(1836311903)
    __main__:1: RuntimeWarning: overflow encountered in int_scalars
    -1323752223
    
    '''    
    f = [tf.constant(0),tf.constant(1)]
    
    if n>2:
        for i in range(2,n):
            f_i = f[i-1] + f[i-2]
            f.append(f_i)
    
    with tf.Session() as sess:
        result = sess.run(f)
        print result

def constant_test():
    i1, i2, i3, i4 = (tf.constant(1.0),
                      tf.constant(2.0),
                      tf.constant(3.0),
                      tf.constant(4.0))
    
    j1, j2 = (tf.mul(i1,i2), tf.mul(i3,i4))
    
    k = tf.mul(j1,j2)
    
    with tf.Session() as sess:
        r = sess.run([k ,j1, j2])
        print r
        
def variable_test():
    
    counter_var = tf.Variable(0, name='counter')
    
    one_const = tf.constant(1)
    result = tf.add(counter_var, one_const)
    update = tf.assign(counter_var, result)
    
    init_operation = tf.initialize_all_variables()
    
    with tf.Session() as sess:
        
        sess.run(init_operation)
        
        for i in range(5):
            print "====="
            
            # counter_var is only updated when output of "update" is retrieved
            print "counter variable before update:"
            print sess.run([counter_var])
            
            print "counter variable retrieved at same time that we retrieve result of update op:"
            print sess.run([counter_var,update])
            
            print "variables that feed into result have not changed, thus retrieving result repeatedly will not yield any different value"
            print sess.run([result])
            print sess.run([result])
            print sess.run([result])
            
            
def feed_test(data_one, data_two):
    
    data_placeholder_one = tf.placeholder(tf.types.float32)
    data_placeholder_two = tf.placeholder(tf.types.float32)
    output = tf.mul(data_placeholder_one, data_placeholder_two)
    
    with tf.Session() as sess:
        print sess.run(
            [output],
            feed_dict={
                data_placeholder_one : data_one,
                data_placeholder_two : data_two
            })

def main(args):
    parser = argparse.ArgumentParser(
        description='Runs some simple TensorFlow examples.'
    )
    
    parser.add_argument('--constant-test',action='store_true')
    
    parser.add_argument('--variable-test',action='store_true')
    
    parser.add_argument('--feed-test',action='store_true')
    
    parser.add_argument('--fib-test',action='store_true')
    
    parsed_args = parser.parse_args(args)
    
    if parsed_args.constant_test:
        constant_test()
    elif parsed_args.variable_test:
        variable_test()
    elif parsed_args.feed_test:
        feed_test(10.0,20.0)
    elif parsed_args.fib_test:
        flowfib(50)

if __name__=='__main__':
    main(sys.argv[1:])