Fix error in example (#1176)

Author: james-atkins

docs/src/adjoints.md

@@ -68,7 +68,7 @@ julia> mygradient(sin, 0.5)
 
 The rest of this section contains more technical detail. It can be skipped if you only need an intuition for pullbacks; you generally won't need to worry about it as a user.
 
-If ``x`` and ``y`` are vectors, ``\frac{\partial y}{\partial x}`` becomes a Jacobian. Importantly, because we are implementing reverse mode we actually left-multiply the Jacobian, i.e. `v'J`, rather than the more usual `J*v`. Transposing `v` to a row vector and back `(v'J)'` is equivalent to `J'v` so our gradient rules actually implement the *adjoint* of the Jacobian. This is relevant even for scalar code: the adjoint for `y = sin(x)` is `x̄ = sin(x)'*ȳ`; the conjugation is usually moot but gives the correct behaviour for complex code. "Pullbacks" are therefore sometimes called "vector-Jacobian products" (VJPs), and we refer to the reverse mode rules themselves as "adjoints".
+If ``x`` and ``y`` are vectors, ``\frac{\partial y}{\partial x}`` becomes a Jacobian. Importantly, because we are implementing reverse mode we actually left-multiply the Jacobian, i.e. `v'J`, rather than the more usual `J*v`. Transposing `v` to a row vector and back `(v'J)'` is equivalent to `J'v` so our gradient rules actually implement the *adjoint* of the Jacobian. This is relevant even for scalar code: the adjoint for `y = sin(x)` is `x̄ = cos(x)'*ȳ`; the conjugation is usually moot but gives the correct behaviour for complex code. "Pullbacks" are therefore sometimes called "vector-Jacobian products" (VJPs), and we refer to the reverse mode rules themselves as "adjoints".
 
 Zygote has many adjoints for non-mathematical operations such as for indexing and data structures. Though these can still be seen as linear functions of vectors, it's not particularly enlightening to implement them with an actual matrix multiply. In these cases it's easiest to think of the adjoint as a kind of inverse. For example, the gradient of a function that takes a tuple to a struct (e.g. `y = Complex(a, b)`) will generally take a struct to a tuple (`(ȳ.re, ȳ.im)`). The gradient of a `getindex` `y = x[i...]` is a `setindex!` `x̄[i...] = ȳ`, etc.