I'm using the Julia package LowRankModels (https://github.com/madeleineudell/LowRankModels.jl/tree/dataframe-ux) and coming across a malloc error when making a single innocuous change to my code.
For instance in the following sample code, changing a single parameter (the rank k) from 10 to 40 makes the model go from running smoothly to producing a malloc error. Would really appreciate any pointers towards what might be going on /any tips to debug this error. Thanks! Branch of LowRankModels: dataframe-ux Link to Data: https://dl.dropboxusercontent.com/u/24399038/GSS2014cleanestCV10.csv Julia code that reproduces the error: ###################### using DataFrames # branch of LowRankModels found at https://github.com/NandanaSengupta/LowRankModels.jl/tree/dataframe-ux using LowRankModels ### loading data table df = readtable("GSS2014cleanestCV10.csv"); # eliminate first (id) column df1 = df[:, 2:size(df)[2] ]; # vector of datatypes -- 3 types of columns: real, categorical and ordinal datatypes = Array(Symbol, size(df1)[2]) datatypes[1:23] = :real datatypes[24:54] = :ord datatypes[55:size(df1)[2]] = :cat ################## run GLRM AND cross_validate with rank k = 10 ############## ######## Runs without any error glrm_10 = GLRM(df1, 10, datatypes) srand(10) t1, t2, t3, t4 = cross_validate(glrm_10, nfolds = 5, params = Params(), init = init_svd!); ################## run GLRM AND cross_validate with rank k = 40 ############## ######## malloc error on cross_validate glrm_40 = GLRM(df1, 40, datatypes) #, prob_scale = false) srand(40) t1, t2, t3, t4 = cross_validate(glrm_40, nfolds = 5, params = Params(), init = init_svd!);
