remove Variable

Tractables · Dec 23, 2023 · 86ad4b9 · 86ad4b9
1 parent 6ef8ea5
commit 86ad4b9
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Showing 3 changed files with 7 additions and 20 deletions.
diff --git a/src/autodiff/adnode.jl b/src/autodiff/adnode.jl
@@ -1,16 +1,9 @@
-export ADNode, ADMatrix, Variable, Var, ad_map, sigmoid, deriv_sigmoid, inverse_sigmoid
+export ADNode, ADMatrix, Var, ad_map, sigmoid, deriv_sigmoid, inverse_sigmoid
 
 import DirectedAcyclicGraphs: NodeType, DAG, children
 
 abstract type ADNode <: DAG end
 
-# We always differentiate with respect to Variables
-abstract type Variable <: ADNode end
-
-NodeType(::Type{<:Variable}) = Leaf()
-compute_leaf(x::Variable) = error("The value of $(x) should've been provided in `vals`!")
-backward(::Variable, _, _) = nothing
-
 ADNodeCompatible = Union{Real, AbstractMatrix{<:Real}}
 
 function add_deriv(derivs, n::ADNode, amount::ADNodeCompatible)
@@ -21,10 +14,12 @@ function add_deriv(derivs, n::ADNode, amount::ADNodeCompatible)
     end
 end
 
-
-struct Var <: Variable
+struct Var <: ADNode
     id::Any
 end
+NodeType(::Type{Var}) = Leaf()
+compute_leaf(x::Var) = error("The value of $(x) should've been provided in `vals`!")
+backward(::Var, _, _) = nothing
 function Base.show(io::IO, x::Var)
     print(io, "Var(")
     show(io, x.id)

diff --git a/src/autodiff/core.jl b/src/autodiff/core.jl
@@ -1,9 +1,9 @@
-export value, compute, differentiate, value, Valuation, Derivs, compute_one, variables
+export value, compute, differentiate, value, Valuation, Derivs, compute_one
 
 using DirectedAcyclicGraphs
 using DataStructures: DefaultDict
 
-Valuation = Dict{Variable, ADNodeCompatible}
+Valuation = Dict{Var, ADNodeCompatible}
 Derivs = Dict{ADNode, ADNodeCompatible}
 
 function compute_one(root, vals::Dict{ADNode, <:ADNodeCompatible})
@@ -51,7 +51,3 @@ function foreach_down(f::Function, roots)
         f(n)
     end
 end
-
-function variables(x::ADNode)
-    filter(node -> node isa Variable, x)
-end
diff --git a/src/inference/train_pr.jl b/src/inference/train_pr.jl
@@ -17,8 +17,6 @@ mutable struct LogPrExpander
     end
 end
 
-
-
 function expand_logprs(l::LogPrExpander, root::ADNode)::ADNode
     fl(x::LogPr) = expand_logprs(l, logprob(l.w, x.bool))
     fl(x::Var) = x
@@ -54,7 +52,6 @@ function bool_roots(root::ADNode)
     setdiff(keys(seen_bools), non_roots)
 end
 
-
 # Find the log-probabilities and the log-probability gradient of a BDD
 function add_scaled_dict!(
     x::AbstractDict{<:Any, <:Real},
@@ -66,7 +63,6 @@ function add_scaled_dict!(
     end
 end
 
-
 function step_pr!(
     var_vals::Valuation,
     loss::ADNode,