Tensorflow - running total -

how can add number 5 after every iteration of loop?

i want this:

weight = 0.225  in range(10):     weight += 5     print (weight) 

here how trying in tensorflow never updates weight

import tensorflow tf def dummy(x):     weights['h0'] = tf.add(weights['h0'], 5)     res = tf.add(weights['h0'], x)     return res  # build computational graph = tf.placeholder('float', none) d = dummy(a) weights = {     'h0': tf.variable(tf.random_normal([1])) } # initialize variables init = tf.global_variables_initializer()  # create session , run graph tf.session() sess:     sess.run(init)     in range(10):         print (sess.run(d, feed_dict={a: [2]})) # close session sess.close() 

there's operation explicitly created adding value , assigning result input node: tf.assign_add

you should use instead of tf.assing + tf.add.

also, it's more important understand why previous code won't work.

weights['h0'] = tf.add(weights['h0'], 5) res = tf.add(weights['h0'], x) 

at fist line, you're defining node add, inputs weights['h0'] , 5 and you're assigning node python variable weights['h0'].

now, thus, weights['h0'] python variable holding tensorflow node.

in next line, you're defining add node, between previous node , x, , return node.

when graph evaluated, evaluate node pointed res, force evaluation of previous node (because res function of node holded weights['h0']).

the problem assignment @ line 1 python assignment , not tensorflow assignment. assign operation executed in python environment has no defined assign node tensorflow graph.

p.s: when use with you're defining context manager handles closing operations you. can remove sess.close() because executed automatically when exit context