RxInfer Perfetto demo.jl

RxInfer Perfetto demo.jl

import Pkg; Pkg.activate(); Pkg.resolve(); Pkg.instantiate()

using Revise
using RxInfer, StableRNGs, Plots
using Markdown

## Inference example


@model function iid_estimation(y)
    μ  ~ Normal(mean = 0.0, precision = 0.1)
    τ  ~ Gamma(shape = 1.0, rate = 1.0)
    y .~ Normal(mean = μ, precision = τ)
end

# Specify mean-field constraint over the joint variational posterior
constraints = @constraints begin
    q(μ, τ) = q(μ)q(τ)
end

# Specify initial posteriors for variational iterations
initialization = @initialization begin
    q(μ) = vague(NormalMeanPrecision)
    q(τ) = vague(GammaShapeRate)
end

begin
	hidden_μ       = 3.1415
	hidden_τ       = 2.7182
	distribution   = NormalMeanPrecision(hidden_μ, hidden_τ)
	rng            = StableRNG(42)
	n_observations = 600
	dataset        = rand(rng, distribution, n_observations)
end

results = infer(
    model          = iid_estimation(),
    data           = (y = dataset, ),
    constraints    = constraints,
    iterations     = 4,
    initialization = initialization,
	trace          = true
)

## Getting traces from RxInfer

trace = results.model.metadata[:trace]

events = RxInfer.tracedevents(trace)

## View with Perfetto

RxInfer.perfetto_open(events)

RxInfer.perfetto_view(events)