Say we already have define

```
a = mx.sym.Variable('a')
b = mx.sym.Variable('b')
c = a+b # name is _plus0_output
d = c/2
```

and we could calculate `c`

with

```
c.eval(a=mx.nd.array([2.0]),b=mx.nd.array([3.0]))
```

or

```
d.get_internals().eval(a=mx.nd.array([2.0]),b=mx.nd.array([3.0]))
```

to get both `c`

and `d`

.

but how could I calculate `d`

only via `c`

?

sometimes I’d like to use synthetic `c`

to check if the model is robust and in this case I could not get `a`

and `b`

.

I’d like to have something like

```
d.eval(_plus0_output=mx.nd.array([2.5]))
```

Is it possible?