🤖 Format .jl files

Author: amontoison

src/ADNLPProblems/hs248.jl

@@ -7,9 +7,7 @@ function hs248(; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) wher
   x0 = T[-0.1, -1, 0.1]
   lcon = T[-1; 1]
   ucon = T[Inf; 1]
-  A = T[
-    1 -2
-  ]
+  A = T[1 -2]
   function c!(cx, x)
     cx[1] = x[1]^2 + x[2]^2 + x[3]^2
     return cx

src/ADNLPProblems/hs251.jl

@@ -8,9 +8,7 @@ function hs251(; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) wher
   x0 = T[10, 10, 10]
   lvar = T[0, 0, 0]
   uvar = T[42, 42, 42]
-  A = T[
-    -1 -2 -2
-  ]
+  A = T[-1 -2 -2]
   lcon = T[-72]
   ucon = T[Inf]
   return ADNLPModels.ADNLPModel(f, x0, lvar, uvar, sparse(A), lcon, ucon, name = "hs251"; kwargs...)

src/ADNLPProblems/hs253.jl

@@ -13,9 +13,7 @@ function hs253(; n::Int = default_nvar, type::Type{T} = Float64, kwargs...) wher
   x0 = T[0, 2, 0]
   lvar = T[0, 0, 0]
   uvar = T[Inf, Inf, Inf]
-  A = T[
-    -3 0 -3
-  ]
+  A = T[-3 0 -3]
   lcon = T[-30]
   ucon = T[Inf]
   return ADNLPModels.ADNLPModel(f, x0, lvar, uvar, sparse(A), lcon, ucon, name = "hs253"; kwargs...)