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module _Derivatives
using LinearAlgebra
using SparseArrays
using Base.Meta
using ForwardDiff
import Calculus
import MathOptInterface
const MOI = MathOptInterface
using ..JuMP
const TAG = :jump_tag
# Override basic math functions to return NaN instead of throwing errors.
# This is what NLP solvers expect, and
# sometimes the results aren't needed anyway,
# because the code may compute derivatives wrt constants.
import NaNMath: sin, cos, tan, asin, acos, acosh, atanh, log, log2, log10, lgamma, log1p, pow, sqrt
include("types.jl")
include("conversion.jl")
include("coloring.jl")
export Coloring
include("linearity.jl")
include("sparsity.jl")
include("forward.jl")
include("reverse.jl")
include("subexpressions.jl")
end # module
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