tensorflow-條件循環控制（4）
#!/usr/bin/env python2 # -*- coding: utf-8 -*- """ Created on Thu Sep 6 10:16:37 2018 @author: myhaspl """ import tensorflow as tf import tensorflow as tf n = 10 x = tf.constant(0) c = lambda i, x: i < n b = lambda i, x: (tf.Print(i + 1, [i],"i:"), tf.Print(x + 1, [x], "x:")) i, out = tf.while_loop(c, b, (0, x)) with tf.Session() as sess: print(sess.run([i,out]))
i:[0]x:[0]
x:[1]
i:[1]
i:[2]
x:[2]
i:[3]
x:[3]
i:[4]
x:[4]
i:[5]
x:[5]
i:[6]
x:[6]
i:[7]
i:[8]x:[7]
i:[9]
x:[8]
x:[9]
[10, 10]
>>
觀察上面例子，x和i是並行計算的，以至於在i為8時，x還是7
i:[6]
x:[6]
i:[7]
i:[8]x:[7]
下面的例子將x設為列表，每次叠代對列表的每個元素加1
#!/usr/bin/env python2 # -*- coding: utf-8 -*- """ Created on Thu Sep 6 10:16:37 2018 @author: myhaspl """ import tensorflow as tf import tensorflow as tf n = 10 x = tf.constant(list(range(n))) c = lambda i, x: i < n b = lambda i, x: (tf.Print(i + 1, [i],"i:"), tf.Print(x + 1, [x], "x:")) i, out = tf.while_loop(c, b, (0, x)) with tf.Session() as sess: print(sess.run([i,out]))
i:[0]
x:[0 1 2...]i:[1]
x:[1 2 3...]i:[2]
x:[2 3 4...]
i:[3]
x:[3 4 5...]
i:[4]
x:[4 5 6...]
x:[5 6 7...]i:[5]
x:[6 7 8...]i:[6]
x:[7 8 9...]i:[7]
x:[8 9 10...]
i:[8]
i:[9]
x:[9 10 11...]
[10, array([10, 11, 12, 13, 14, 15, 16, 17, 18, 19], dtype=int32)]
因為一個循環叠代中的循環計數器依賴於前一個叠代中的值循環計數器本身不能並行遞增。
#!/usr/bin/env python2 # -*- coding: utf-8 -*- """ Created on Thu Sep 6 10:16:37 2018 @author: myhaspl """ import tensorflow as tf def b(i): return tf.Print(i + 2, [i],"i:") def c(i): return tf.less(i,n) n = tf.constant(10) i = tf.constant(0) res = tf.while_loop(c, b, [i]) with tf.Session() as sess: print sess.run(res)
i:[0]
i:[2]
i:[4]
i:[6]
i:[8]
10
i這個計算器本身，每次叠代增加，因此依賴於前一個叠代中的值。因此，如果我們只想要計數器i的最終值（我們在行打印（sess.run(i))，那麽x永遠不會遞增，但是計數器i將在單個線程上更新。如下所示：
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Thu Sep 6 10:16:37 2018
@author: myhaspl
"""
import tensorflow as tf
def b(i,x):
return (tf.Print(i + 2, [i],"i:"),tf.Print(x + 1, [x],"x:"))
def c(i,x):
return tf.less(i,n)
n = 10
i = 0
x = tf.constant(list(range(n)))
i,out = tf.while_loop(c, b, (i,x))
with tf.Session() as sess:
print sess.run(i) i:[0]
i:[2]
i:[4]
i:[6]
i:[8]
10
相反，如果我們希望輸出值（我們在行打印（sess.run(out））上打印），那麽計數器可以在自己的線程上遞增，而x可以在單獨的線程上並行遞增。
註意：因為i每次遞增2，所以x只會遞增5次，每次增加1
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Thu Sep 6 10:16:37 2018
@author: myhaspl
"""
import tensorflow as tf
def b(i,x):
return (tf.Print(i + 2, [i],"i:"),tf.Print(x + 1, [x],"x:"))
def c(i,x):
return tf.less(i,n)
n = 10
i = 0
x = tf.constant(list(range(n)))
i,out = tf.while_loop(c, b, (i,x))
with tf.Session() as sess:
print sess.run(out) i:[0]
x:[0 1 2...]i:[2]
x:[1 2 3...]i:[4]
i:[6]x:[2 3 4...]
x:[3 4 5...]
i:[8]
x:[4 5 6...]
[ 5 6 7 8 9 10 11 12 13 14]
在極端情況下，可以想象，遞增計數器的線程在x遞增一次之前一直運行到完成。唯一不可能發生的事情是線程更新x永遠不可能超過計數器線程，因為遞增x的線程取決於計數器的值。下面模擬了這種情況（i>6時，x更新遞增）
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Thu Sep 6 10:16:37 2018
@author: myhaspl
"""
import tensorflow as tf
def b(i,x):
i=tf.Print(i + 1, [i],"i:")
x=tf.cond(i<=5,lambda: tf.Print(x,[x],"x:"),lambda: tf.Print(x + 1, [x],"x:"))
return (i,x)
def c(i,x):
return tf.less(i,n)
n = 10
i = 0
x = 0
i,out = tf.while_loop(c, b, (i,x))
with tf.Session() as sess:
print sess.run(out) i:[0]
x:[0]
i:[1]
x:[0]
i:[2]
x:[0]
i:[3]
x:[0]
i:[4]
i:[5]
i:[6]x:[0]
x:[0]
i:[7]
x:[1]
i:[8]
i:[9]
x:[2]
x:[3]
x:[4]
5
組合tf.cond與tf.while_loop
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Thu Sep 6 10:16:37 2018
@author: myhaspl
@email:[email protected]
二分法猜數字
"""
import tensorflow as tf
def body(a,b,guessnum,num):
center = tf.div(tf.add(a, b),2)
a,b,num= tf.cond(guessnum>center, lambda: (center,b,center), lambda: (a,center,center))
return (tf.Print(a,[a],"a:"),tf.Print(b,[b],"b:"),guessnum,num)
def c(a,b,guessnum,num):
return tf.not_equal(guessnum,num)
guessnum = tf.constant(71)
mynum = tf.constant(-1)
a = tf.constant(0)
b = tf.constant(100)
a,b,guessnum,num = tf.while_loop(c, body, (a,b,guessnum,mynum))
with tf.Session() as sess:
print sess.run(num) b:[100]
a:[50]
a:[50]
b:[75]
b:[75]
a:[62]
b:[75]
a:[68]
a:[68]
b:[71]
71
tensorflow-條件循環控制（4）