@@ -456,13 +456,13 @@ SourceCodeMcCormick generated functions, we can make use of the massive parallel
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available using GPUs.
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``` julia
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- using JuMP, EAGO, SourceCodeMcCormick, CUDA
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+ using JuMP, EAGO, SourceCodeMcCormick, Symbolics, DocStringExtensions CUDA
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- # Import the ParBB algorithm (Note: path may vary depending on where
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- # this file is in relation to SourceCodeMcCormick)
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- include (joinpath (@__DIR__ , " ParBB" , " extension.jl" ))
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- include (joinpath (@__DIR__ , " ParBB" , " subroutines.jl" ))
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- include (joinpath (@__DIR__ , " ParBB" , " kernels.jl" ))
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+ # Import the ParBB algorithm
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+ BASE_FOLDER = dirname ( dirname ( pathof ( SourceCodeMcCormick)) )
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+ include (joinpath (BASE_FOLDER, " examples " , " ParBB" , " extension.jl" ))
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+ include (joinpath (BASE_FOLDER, " examples " , " ParBB" , " subroutines.jl" ))
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+ include (joinpath (BASE_FOLDER, " examples " , " ParBB" , " kernels.jl" ))
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# Weights associated with the hidden layer
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W1 = [ 0.54 - 1.97 0.09 - 2.14 1.01 - 0.58 0.45 0.26 ;
@@ -595,13 +595,13 @@ implementation. The following shows how SourceCodeMcCormick's new subgradient fe
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with ParBB.
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``` julia
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- using JuMP, EAGO, SourceCodeMcCormick, CUDA
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+ using JuMP, EAGO, SourceCodeMcCormick, Symbolics, DocStringExtensions, CUDA
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- # Import the ParBB algorithm (Note: path may vary depending on where
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- # this file is in relation to SourceCodeMcCormick)
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- include (joinpath (@__DIR__ , " ParBB" , " extension.jl" ))
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- include (joinpath (@__DIR__ , " ParBB" , " subroutines.jl" ))
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- include (joinpath (@__DIR__ , " ParBB" , " kernels.jl" ))
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+ # Import the ParBB algorithm
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+ BASE_FOLDER = dirname ( dirname ( pathof ( SourceCodeMcCormick)) )
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+ include (joinpath (BASE_FOLDER, " examples " , " ParBB" , " extension.jl" ))
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+ include (joinpath (BASE_FOLDER, " examples " , " ParBB" , " subroutines.jl" ))
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+ include (joinpath (BASE_FOLDER, " examples " , " ParBB" , " kernels.jl" ))
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# Weights associated with the hidden layer
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W1 = [ 0.54 - 1.97 0.09 - 2.14 1.01 - 0.58 0.45 0.26 ;
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