In [6]:

    

import tensorflow as tf 
import numpy as np


    

In [28]:

    

tf.reset_default_graph()

x = np.random.choice(2,10)
print('x:')
print(x)

res = tf.one_hot(x, 2)
ustack = tf.unstack(res, axis=1)


with tf.Session() as sess:
    print('one_hot:')
    print(res.eval())
    print('unstack:')
    print(sess.run(ustack))


    

    




x:
[1 0 1 0 1 1 0 0 0 1]
one_hot:
[[ 0.  1.]
 [ 1.  0.]
 [ 0.  1.]
 [ 1.  0.]
 [ 0.  1.]
 [ 0.  1.]
 [ 1.  0.]
 [ 1.  0.]
 [ 1.  0.]
 [ 0.  1.]]
unstack:
[array([ 0.,  1.], dtype=float32), array([ 1.,  0.], dtype=float32), array([ 0.,  1.], dtype=float32), array([ 1.,  0.], dtype=float32), array([ 0.,  1.], dtype=float32), array([ 0.,  1.], dtype=float32), array([ 1.,  0.], dtype=float32), array([ 1.,  0.], dtype=float32), array([ 1.,  0.], dtype=float32), array([ 0.,  1.], dtype=float32)]

In [30]:

    

mylist = [1,2,3]
for i in mylist:
    print(i)


    

    




1
2
3

In [31]:

    

mylist = [x*x for x in range(3)]
for i in mylist:
    print(i)


    

    




0
1
4

In [33]:

    

mygenerator = (x*x for x in range(3))
for i in mygenerator:
    print(i)


    

    




0
1
4

In [36]:

    

def create_generator():
    mylist = range(3)
    for i in mylist:
        yield i*i


    

In [40]:

    

mygenerator = create_generator()
print(mygenerator)
for i in mygenerator:
    print(i)


    

    




<generator object create_generator at 0x7f8d0ad3e5c8>
0
1
4

In [ ]: