# How to initialize an array of Turing variables?

**URL:** <https://discourse.julialang.org/t/how-to-initialize-an-array-of-turing-variables/85205>\
**Category:** Probabilistic Programming\
**Tags:** turing\
**Created:** [August 2, 2022, 10:04pm UTC](https://discourse.julialang.org/t/how-to-initialize-an-array-of-turing-variables/85205 "2022-08-02T22:04:43Z")\
**Posts on this page:** 3\
**Page:** 1

<div class="post-metadata">

**Author:** ![jpm](https://avatars.discourse-cdn.com/v4/letter/j/b487fb/32.png) [@jpm](https://discourse.julialang.org/u/jpm)\
**Post date:** [August 2, 2022, 10:04pm UTC](https://discourse.julialang.org/t/how-to-initialize-an-array-of-turing-variables/85205/1 "2022-08-02T22:04:43Z")

</div>

I am new to Turing and in the process of translating a complex dynamical stochastic model from Stan to Turing. Instead of declaring individual variables (many of them arrays), I would like to include them in a dictionary, and here I am running into issues using the right type. How do I initialize dictionary and array using the correct type?  
This short piece of code demonstrates what I would like to achieve without having to declare `x`:

```julia
using Turing

@model function mwe_model()
    # unnecessary declaration of an extra variable to get type
    x ~ Normal(0.0, 1.0)
    T = typeof(x)
    
    stoch = Dict{String, T}();

    stoch["param1"] = Array{T}(undef, 1)
    stoch["param1"][1] ~ Normal(0.0, 1.0)
end

```

PS: I have tried setting the type explicitly which is less flexible and sometimes results in errors:

```julia
import ForwardDiff
using Turing

@model function mwe_model()
    T = ForwardDiff.Dual :: Type
    stoch = Dict{String, T}();

    # this creates an error
    stoch["param1"] = Array{T}(undef, 1)
    stoch["param1"][1] ~ Normal(0.0, 1.0)

    # this works:
    #stoch["param2"] = Array{T}(undef, 1, 1)
    #stoch["param2"][1, 1] ~ Normal(0.0, 1.0)
end

display(sample(mwe_model(), NUTS(), 1_000))

```

The code above terminates with an error: `LoadError: UndefRefError: access to undefined reference`. However, it appears to work when using the 2-dimensional array `stoch["param2"]` instead of `stoch["param1"]`. This is probably a bug, but I am most interested in a more flexible way to obtain the type without having to hard-code it.

---

<div class="post-metadata">

**Author:** ![jling](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/jling/32/212909_2.png) [@jling](https://discourse.julialang.org/u/jling)\
**Post date:** [August 2, 2022, 10:09pm UTC](https://discourse.julialang.org/t/how-to-initialize-an-array-of-turing-variables/85205/2 "2022-08-02T22:09:58Z")

</div>

you can either use loop for arraydist:  
[https://turing.ml/dev/docs/using-turing/guide#constructing-product-distributions-with-arraydist](https://turing.ml/dev/docs/using-turing/guide#constructing-product-distributions-with-arraydist)

---

<div class="post-metadata">

**Author:** ![jpm](https://avatars.discourse-cdn.com/v4/letter/j/b487fb/32.png) [@jpm](https://discourse.julialang.org/u/jpm)\
**Post date:** [August 3, 2022, 9:46pm UTC](https://discourse.julialang.org/t/how-to-initialize-an-array-of-turing-variables/85205/3 "2022-08-03T21:46:31Z")

</div>

Thanks for the tip. And – somewhat embarrassingly – for the last few weeks, I thought that the website [turing.ml](https://turing.ml) was down, when it just turned out that it is being blocked by my university’s VPN. Turning off the VPN, I found more useful information:

> Moreover, if the continuous random variable is to be sampled using a Hamiltonian sampler, the vector’s element type needs to either be: 1. `Real` to enable auto-differentiation through the model which uses special number types that are sub-types of `Real`, or 2. Some type parameter `T` defined in the model header using the type parameter syntax, …

I checked that `supertype(ForwardDiff.Dual)` is indeed `Real` and based on that, I would change my example code to something along the lines of:

```julia
@model function mwe_model()
    T = Real
    stoch = Dict{String, Array{T}}();

    stoch["param1"] ~ arraydist([Normal(0.0, 1.0) for i in 1:1])
end

```