Manipulating matrix elements in tensorflow

Question

How can I do the following in tensorflow?

mat = [4,2,6,2,3] #
mat[2] = 0 # simple zero the 3rd element

I can't use the [] brackets because it only works on constants and not on variables. I cant use the slice function either because that returns a tensor and you can't assign to a tensor.

import tensorflow as tf
sess = tf.Session()
var1 = tf.Variable(initial_value=[2, 5, -4, 0])
assignZerosOP = (var1[2] = 0) # < ------ This is what I want to do

sess.run(tf.initialize_all_variables())

print sess.run(var1)
sess.run(assignZerosOP)
print sess.run(var1)

Will print

[2, 5, -4, 0] 
[2, 5, 0, 0])

Answer 1

You can't change a tensor - but, as you noted, you can change a variable.

There are three patterns you could use to accomplish what you want:

(a) Use tf.scatter_update to directly poke to the part of the variable you want to change.

import tensorflow as tf

a = tf.Variable(initial_value=[2, 5, -4, 0])
b = tf.scatter_update(a, [1], [9])
init = tf.initialize_all_variables()

with tf.Session() as s:
  s.run(init)
  print s.run(a)
  print s.run(b)
  print s.run(a)

[ 2 5 -4 0]

[ 2 9 -4 0]

[ 2 9 -4 0]

(b) Create two tf.slice()s of the tensor, excluding the item you want to change, and then tf.concat(0, [a, 0, b]) them back together.

(c) Create b = tf.zeros_like(a), and then use tf.select() to choose which items from a you want, and which zeros from b that you want.

I've included (b) and (c) because they work with normal tensors, not just variables.