removes unused and useless code

common.jl

@@ -82,36 +82,6 @@ function create_pca_model(dist, file::String; nbits::Int)
     fit(PCAProjection, A, dim), SqL2Distance(), "PCA-$(dim)"
 end
 
-function create_binperms_model(dist, file::String; nbits::Int, nrefs::Int=2048)
-    A = h5open(file) do f
-        X = f["emb"]
-        m, n = size(X)
-        n2 = min(10^6, n ÷ 3)
-        X[:, 1:n2]
-    end
-
-    @show size(A) typeof(A)
-    refs = let
-        C = fft(dist, MatrixDatabase(A), nrefs) # select `nrefs` distant elements -- kcenters using farthest first traversal
-        MatrixDatabase(A[:, C.centers])
-    end
-
-    fit(BinPerms, dist, refs, nbits), BinaryHammingDistance(), "BinPerms-$nbits"
-end
-
-function create_heh_model(dist, file::String; nbits::Int)
-    A = h5open(file) do f
-        X = f["emb"]
-        m, n = size(X)
-        n2 = 2^15
-        X[:, 1:n2]
-    end
-
-    @show size(A) typeof(A)
-    #fit(highentropyhyperplanes, dist, matrixdatabase(a), nbits; sample_for_hyperplane_selection=2^16, k=4092, k2=1024), binaryhammingdistance(), "highentropyhyperplanes-$nbits"
-    fit(HighEntropyHyperplanes, dist, MatrixDatabase(A), nbits; minent=0.5,
-        sample_for_hyperplane_selection=2^13), BinaryHammingDistance(), "HighEntropyHyperplanes-$nbits"
-end
 
 
 function predict_h5(model::Union{PCAProjection,GaussianRandomProjection}, file::String; nbits, block::Int=10^5)
@@ -129,17 +99,3 @@ function predict_h5(model::Union{PCAProjection,GaussianRandomProjection}, file::
     end
 end
 
-function predict_h5(model::Union{BinPerms,HighEntropyHyperplanes}, file::String; nbits, block::Int=10^5)
-    h5open(file) do f
-        X = f["emb"]
-        m, n = size(X)
-        B = Matrix{UInt64}(undef, nbits ÷ 64, n)
-        for group in Iterators.partition(1:n, block)
-            @info "encoding $group of $n -- $(Dates.now())"
-            B[:, group] .= predict(model, MatrixDatabase(X[:, group])).matrix
-        end
-
-        StrideMatrixDatabase(B)
-    end
-end
-

eval.jl

@@ -22,7 +22,6 @@ function evaluate_results(gfile, resultfiles, k)
 end
 
 function print_results(f, D, gfile, files, task, dbsize)
-    println(f, gfile => files)
     show(f, "text/plain", gfile => files); println(f)
     show(f, "text/plain", D); println(f)
     p = lineplot(D.recall; ylim=(0, 1), title=String(D.algo[1]), ylabel="recall", xlabel="$(D.params[1]) to $(D.params[end])")

task3.jl

@@ -35,12 +35,9 @@ function task3(;
 
     mkpath(outdir) 
     dist = NormalizedCosineDistance()  # 1 - dot(·, ·)
-    #nbits = 8 * 4 * 128  # memory eq to 128 fp32 
     nbits = 8 * 4 * 128  # memory eq to 128 fp32 
-    #model, dist_proj, nick = create_binperms_model(dist, dfile; nbits)
     #model, dist_proj, nick = create_rp_model(dist, dfile; nbits)
     modelingtime = @elapsed model, dist_proj, nick = create_pca_model(dist, dfile; nbits)
-    #modelingtime = @elapsed model, dist_proj, nick = create_heh_model(dist, dfile; nbits)
     encdatabasetime = @elapsed db = predict_h5(model, dfile; nbits)
     encqueriestime = @elapsed queries = predict_h5(model, qfile; nbits)