initial_params working incorrectly and differently in v0.34.0 and v0.33.0

[evolbeginner]

Minimal working example

using Turing, Distributions, MCMCChains

@model function constrained_uniform(n)
    Z ~ Uniform(10, 20)
    #println(Z)
    X = Vector{Float64}(undef, n)    
    for i in 1:n
        X[i] ~ Uniform(0, Z)
    end  
end

n = 2
initial_z = 15
#initial_x = sort(collect(range(0, stop=n/2, length=n)))
initial_x = [0.2,0.5]
initial_params = (X = initial_x, Z = initial_z)

println("Initial Parameters: ", initial_params)

chain = sample(constrained_uniform(n), NUTS(), 1000; thinning=20, discard_initial=200, initial_params=[initial_z,initial_x])
#chain = sample(constrained_uniform(n), NUTS(), 1000; thinning=20, discard_initial=200, initial_params=initial_params)

println(chain)

Description

I want to sample Z ~ Unif(10,20) and X ~ Unif(0,Z) for two iid Xs.

When initial_params is not set, there's nothing wrong. However, if initial_params=initial_params, then it produces errors.

v0.33.0:

• chain = sample(constrained_uniform(n), NUTS(), 1000; thinning=20, discard_initial=200, initial_params=[initial_z,initial_x]):
  correct
• chain = sample(constrained_uniform(n), NUTS(), 1000; thinning=20, discard_initial=200, initial_params=initial_params):
  ArgumentError: Uniform: the condition a < b is not satisfied.

v0.34.0:

• chain = sample(constrained_uniform(n), NUTS(), 1000; thinning=20, discard_initial=200, initial_params=[initial_z,initial_x])

ERROR: MethodError: no method matching set_values!!(::DynamicPPL.TypedVarInfo{@NamedTuple{…}, Float64}, ::Vector{Any}, ::DynamicPPL.Sampler{NUTS{…}})

Closest candidates are:
  set_values!!(::DynamicPPL.AbstractVarInfo, ::NamedTuple, ::AbstractMCMC.AbstractSampler)
   @ DynamicPPL ~/.julia/packages/DynamicPPL/aKhfc/src/sampler.jl:169
  set_values!!(::DynamicPPL.AbstractVarInfo, ::AbstractVector{<:Union{Missing, Real}}, ::AbstractMCMC.AbstractSampler)
   @ DynamicPPL ~/.julia/packages/DynamicPPL/aKhfc/src/sampler.jl:145

• chain = sample(constrained_uniform(n), NUTS(), 1000; thinning=20, discard_initial=200, initial_params=initial_params)

ERROR: KeyError: key X not found
Stacktrace:
  [1] getindex(h::Dict{AbstractPPL.VarName{:X, Accessors.IndexLens{…}}, Int64}, key::AbstractPPL.VarName{:X, typeof(identity)})
    @ Base ./dict.jl:498

I think in Turing v0.34.0 NamedTuple has to be used for initial_params however I had some difficulties to make it work. Could anyone pls help me on this issue? Thank you!

Julia version info

versioninfo()

Julia Version 1.10.2
Commit bd47eca2c8a (2024-03-01 10:14 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 128 × Intel(R) Xeon(R) Platinum 8362 CPU @ 2.80GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-15.0.7 (ORCJIT, icelake-server)
Threads: 1 default, 0 interactive, 1 GC (on 128 virtual cores)

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]st --manifest

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[sunxd3]

Thank you for bringing up this issue. To clarify, initial_params should be an AbstractVector{<:Union{Real, Missing}}. For example, the following code should work as expected:

chain = sample(
    constrained_uniform(n),
    NUTS(),
    1000;
    thinning=20,
    discard_initial=200,
    initial_params=[initial_z, initial_x...], # vcat to flatten
)

When initial_params is a NamedTuple, the initialization is somewhat limited. The error occurs because from model's perspective (as in the VarInfo), X doesn't exist, but rather X[1], x[2].... Currently, there is no direct way to initialize individual components like X[i] (although we can and should add ways to support this).

For this specific model, if the definition is as follows:

@model function constrained_uniform(n)
    Z ~ Uniform(10, 20)
    X ~ filldist(Uniform(0, Z), n)
end

then initializing with NamedTuple should work

chain = sample(
    constrained_uniform(n),
    NUTS(),
    1000;
    thinning=20,
    discard_initial=200,
    initial_params=initial_params,
)

I hope this helps resolve the issue. Please let us know if this works on your end. Additionally, I’ve created TuringLang/DynamicPPL.jl#774 to track potential improvements.

[yebai]

Thanks, @sunxd3. Can you improve the error message as you suggested in TuringLang/DynamicPPL.jl#774 as a fix for this issue?

[evolbeginner]

Thanks so much @sunxd3! I also found using filldist is consistent with named tuple. I see the trick in providing initial_params. I am so grateful for the prompt help and detailed interpretation from all of you!! To this end, I'm closing this thread.