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. Details and code below. Thanks!
#
Wording of error: "julia(9849,0x7fff705d0300) malloc: *** error for object
0x7f96a332f408: incorrect checksum for freed object - object was probably
modified after being freed.
*** set a breakpoint in malloc_error_break to debug"
Julia Version: 0.4.1
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!);
