#i=0
#while(i<10) : i=i+1
#i = tf.constant(0)
#c = lambda i: tf.less(i, 10)
#b = lambda i: tf.add(i, 1)
#r = tf.while_loop(c, b, [i])

def sum(l=10) :
    #i=0; sum=0
    #while(i<10): i+=1; sum +=i
    #print(sum)
    i   = tf.constant(0)
    sum1 = tf.constant(0)
    def c(sum,i) :
        return tf.less(i, l)
    def b(sum,i) :
        i    =tf.add(i,1)
        sum =tf.add(sum,i)
        return [sum,i]
    sum1,i = tf.while_loop(c, b, [sum1,i]) 
    return sum1
#s=sum(100)
#with tf.Session() as sess:   print(sess.run(s))

nts=np.array([0,0,0,1,1,1,2,2,2,3,3,3])
nps=np.array([0,2,1,0,1,1,2,0,2,1,2,3])
labels=['ang','hap','neu','sad']
N=len(labels)
ts=tf.constant(nts)
ps=tf.constant(nps)
S=ts.get_shape()[0]
i=tf.constant(0)
cm = tf.Variable(tf.zeros(shape=(N,N)))
def c(cm,ts,ps,i) :
    return tf.less(i,S)
def b(cm,ts,ps,i) :
    t=ts[i]; p=ps[i];
    m= tf.add(cm[t,p],1)
    tf.assign(cm[t,p],m)
    i    =tf.add(i,1)
    return [cm,ts,ps,i]
res = tf.while_loop(c, b, [cm,ts,ps,i]) 

with tf.Session() as sess:   print(sess.run(res))

i=tf.constant(0)
while_condition = lambda i: tf.less(i, input_placeholder[1, 1])
def body(i):
   # do something here which you want to do in your loop
   # increment i
return [tf.add(i, 1)]
# do the loop:
r = tf.while_loop(while_condition, body, [i])

• import tensorflow as tf
  data=tf.placeholder(tf.float32, shape=[2, 3])
  def cond(data, output, i):
      return tf.less(i, tf.shape(data)[0]) #until batch size
  def body(data, output, i):
      output = output.write(i, tf.add(data[i], 10))
      return data, output, i + 1
  # TensorArray is a data structure that support dynamic writing
  output_ta = tf.TensorArray(dtype=tf.float32,
                 size=0,
                 dynamic_size=True,
                 element_shape=(data.get_shape()[1],))  #data sample shape
  _, output_op, _  = tf.while_loop(cond, body, [data, output_ta, 0])
  output_op = output_op.stack()
  with tf.Session() as sess:
      print(sess.run([data,output_op], feed_dict={data: [[1, 2, 3], [0, 0, 0]]}))
  [array([[1.,  2.,  3.],
          [0.,  0.,  0.]],  dtype=float32),
   array([[11., 12., 13.],
          [10., 10., 10.]], dtype=float32)]

 """