I am facing a problem and I cannot seem to find the solution anywhere else, so I decided to post my question here (I have basic knowledge of tensorflow but quite new):

I wrote a simple code in python to illustrate what I want to do.

```
import tensorflow as tf
def generated_dict():
graph = {'input': tf.Variable(2)}
graph['layer_1'] = tf.square(graph['input'])
graph['layer_2'] = tf.add(graph['input'], graph['layer_1'])
return graph
graph = generated_dict()
print("boo = " + str(graph['layer_2']))
graph['input'].assign(tf.constant(3))
print("far = " + str(graph['layer_2']))
```

On this sample code, I would like tensorflow to update the whole dictionary when I assign a new input value by doing `graph['input'].assign(tf.constant(3))`

. Basically, right now I obtain

```
boo = tf.Tensor(6, shape=(), dtype=int32) # 2²+2
far = tf.Tensor(6, shape=(), dtype=int32) # 2²+2
```

which is normal because of eager execution of my code. However I would like the dictionary to update its values with my new input and to get :

```
boo = tf.Tensor(6, shape=(), dtype=int32) #2²+2
far = tf.Tensor(12, shape=(), dtype=int32) #3²+3
```

I have the feeling I should be using tf.function() but I am not sure how I should proceed with it. I tried `graph = tf.function(generated_graph)()`

but I did not help.

Any help will be greatly appreciated.

Source: Python Questions