sethaxen

sethaxen

using DynamicPPL

# utilities for working with Turing model parameter names using only the DynamicPPL API

"""
    flattened_varnames_list(model::DynamicPPL.Model) -> Vector{Symbol}

Get a vector of varnames as `Symbol`s with one-to-one correspondence to the
flattened parameter vector. 

sethaxen

using Distances, Distributions, OptimalTransport, LinearAlgebra, Random

struct PowEuclidean{T} <: Distances.PreMetric
    p::T
end

(m::PowEuclidean)(a, b) = Distances.Euclidean()(a, b)^m.p

# for measures μ and ν with support ℝᵈ, approximate empirical p-wasserstein distance
# between matrices x and y of random points whose columns are respectively drawn from 

sethaxen

# Using Manifolds.jl, follow-up to https://github.com/JuliaManifolds/Manifolds.jl/pull/249
using LinearAlgebra
using Manifolds
using Test

# parallel transport of a point (p,X) ∈ T GL(n) along the
# geodesic curve γ on GL(n) with the left-GL(n)-invariant metric
# from section A.2 of https://arxiv.org/abs/1603.05868v1

function geodesic_flow!(M::GeneralLinear, q, Y, p, X, t::Real = 1)

sethaxen

# rrule for expv(t, A, v) = exp(t * A) * v
# Use OrdinaryDiffEq to solve adjoint system for pullback
# Since OrdinaryDiffEq depends on ExponentialUtilities, it doesn't make sense
# to include this code there

using Pkg
Pkg.add(["ChainRulesCore", "ChainRulesTestUtils", "ExponentialUtilities", "FiniteDifferences", "OrdinaryDiffEq", "Test", "LinearAlgebra"])

using ChainRulesCore, ChainRulesTestUtils, FiniteDifferences, OrdinaryDiffEq, Test, LinearAlgebra, Random
using FiniteDifferences: rand_tangent

sethaxen

using FiniteDifferences, LinearAlgebra, Zygote, Random, Test

# adapted from ChainRulesTestUtils.rrule_test
function pullback_test(
    f,
    ȳ,
    xx̄s::Tuple{Any,Any}...;
    rtol = 1e-9,
    atol = 1e-9,
    fkwargs = NamedTuple(),

sethaxen