first version using cmd line args for the parameters

waf_tools/limbo.py

@@ -13,10 +13,14 @@ except:
     json_ok = False
     print "WARNING simplejson not found some function may not work"
 
-
-def options(opt):
-    opt.add_option('--qsub', type='string', help='json file to submit to torque', dest='qsub')
-
+def add_create_options(opt):
+    opt.add_option('--dim_in', type='int', help='dim_in', dest='dim_in')
+    opt.add_option('--dim_out', type='int', help='dim_out', dest='dim_out')
+    opt.add_option('--bayes_opt_boptimizer_noise', type='float', help='bayes_opt_boptimizer_noise', dest='bayes_opt_boptimizer_noise')
+    opt.add_option('--bayes_opt_bobase_stats_enabled', action='store_true', help='bayes_opt_bobase_stats_enabled', dest='bayes_opt_bobase_stats_enabled')
+    opt.add_option('--init_randomsampling_samples', type='int', help='init_randomsampling_samples', dest='init_randomsampling_samples')
+    opt.add_option('--stop_maxiterations_iterations', type='int', help='stop_maxiterations_iterations', dest='stop_maxiterations_iterations')
+    
 
 def create_variants(bld, source, uselib_local,
                     uselib, variants, includes=". ../",
@@ -43,9 +47,12 @@ def create_variants(bld, source, uselib_local,
                     use=uselib_local,
                     defines=deff)
 
-def create_exp(name):
-    ws_tpl = """
-#! /usr/bin/env python
+def create_exp(name, opt):
+    if not os.path.exists('exp'):
+        os.makedirs('exp')
+    os.mkdir('exp/' + name)
+
+    ws_tpl = """#! /usr/bin/env python
 def configure(conf):
     pass
 
@@ -54,18 +61,116 @@ def options(opt):
 
 def build(bld):
     bld(features='cxx cxxprogram',
-        source='@exp.cpp',
+        source='@NAME.cpp',
         includes='. ../../src',
-        target='@exp',
+        target='@NAME',
         uselib='BOOST EIGEN TBB LIBCMAES NLOPT',
         use='limbo')
 """
-    if not os.path.exists('exp'):
-        os.makedirs('exp')
-    os.mkdir('exp/' + name)
-    wscript = open('exp/' + name + "/wscript", "w")
-    wscript.write(ws_tpl.replace('@exp', name))
-    os.system("cp src/tutorials/basic_example.cpp exp/" + name + "/" + name + ".cpp")
+    
+    ws_tpl = ws_tpl.replace('@NAME', name)
+    
+    ws = open('exp/' + name + "/wscript", "w")    
+    ws.write(ws_tpl)
+
+    cpp_tpl = """// please see the explanation in the documentation
+
+#include <iostream>
+
+// you can also include <limbo/limbo.hpp> but it will slow down the compilation
+#include <limbo/bayes_opt/boptimizer.hpp>
+
+using namespace limbo;
+
+struct Params {
+    struct bayes_opt_boptimizer : public defaults::bayes_opt_boptimizer {
+    @BAYES_OPT_BOPTIMIZER_NOISE};
+
+    // depending on which internal optimizer we use, we need to import different parameters
+#ifdef USE_LIBCMAES
+    struct opt_cmaes : public defaults::opt_cmaes {
+    };
+#elif defined(USE_NLOPT)
+    struct opt_nloptnograd : public defaults::opt_nloptnograd {
+    };
+#else
+    struct opt_gridsearch : public defaults::opt_gridsearch {
+    };
+#endif
+
+    struct bayes_opt_bobase : public defaults::bayes_opt_bobase {
+    @BAYES_OPT_BOBASE_STATS_ENABLED};
+
+    struct kernel_exp : public defaults::kernel_exp {
+    };
+
+    struct init_randomsampling : public defaults::init_randomsampling {
+    @INIT_RANDOMSAMPLING_SAMPLES};
+
+    struct stop_maxiterations : public defaults::stop_maxiterations {
+    @STOP_MAXITERATIONS_ITERATIONS};
+
+    // we use the default parameters for acqui_ucb
+    struct acqui_ucb : public defaults::acqui_ucb {
+    };
+};
+
+struct Eval {
+    // number of input dimension (x.size())
+    static constexpr size_t dim_in = @DIM_IN;
+    // number of dimenions of the result (res.size())
+    static constexpr size_t dim_out = @DIM_OUT;
+
+    // the function to be optimized
+    Eigen::VectorXd operator()(const Eigen::VectorXd& x) const
+    {
+        @CODE_RES_INIT
+
+        // YOUR CODE HERE
+
+        @CODE_RES_RETURN
+    }
+};
+
+int main()
+{
+    // we use the default acquisition function / model / stat / etc.
+    bayes_opt::BOptimizer<Params> boptimizer;
+    // run the evaluation
+    boptimizer.optimize(Eval());
+    // the best sample found
+    std::cout << "Best sample: " << @CODE_BEST_SAMPLE << " - Best observation: " << @CODE_BEST_OBS << std::endl;
+    return 0;
+}
+"""
+    cpp_params = {}    
+    cpp_params['BAYES_OPT_BOPTIMIZER_NOISE'] = '    BO_PARAM(double, noise, ' + str(opt.bayes_opt_boptimizer_noise) + ');\n    ' if opt.bayes_opt_boptimizer_noise and opt.bayes_opt_boptimizer_noise >= 0 else ''
+    cpp_params['BAYES_OPT_BOBASE_STATS_ENABLED'] = '' if opt.bayes_opt_bobase_stats_enabled else '    BO_PARAM(bool, stats_enabled, false);\n    '
+    cpp_params['INIT_RANDOMSAMPLING_SAMPLES'] = '    BO_PARAM(int, samples, ' + str(opt.init_randomsampling_samples) + ');\n    ' if opt.init_randomsampling_samples and opt.init_randomsampling_samples > 0  else ''
+    cpp_params['STOP_MAXITERATIONS_ITERATIONS'] = '    BO_PARAM(int, iterations, ' + str(opt.stop_maxiterations_iterations) + ');\n    ' if opt.stop_maxiterations_iterations and opt.stop_maxiterations_iterations > 0 else ''
+
+    cpp_params['DIM_IN'] = str(opt.dim_in) if opt.dim_in and opt.dim_in > 1 else '1'
+    cpp_params['DIM_OUT'] = str(opt.dim_out) if opt.dim_out and opt.dim_out > 1 else '1'
+
+    if opt.dim_in and opt.dim_in > 1:
+        cpp_params['CODE_BEST_SAMPLE'] = 'boptimizer.best_sample().transpose()'
+    else:
+        cpp_params['CODE_BEST_SAMPLE'] = 'boptimizer.best_sample()(0)'
+
+    if opt.dim_out and opt.dim_out > 1:
+        cpp_params['CODE_RES_INIT'] = 'Eigen::VectorXd res(' + str(opt.dim_in) + ')'
+        cpp_params['CODE_RES_RETURN'] = 'return res;'        
+        cpp_params['CODE_BEST_OBS'] = 'boptimizer.best_observation().transpose()'
+    else:
+        cpp_params['CODE_RES_INIT'] = 'double y = 0;'
+        cpp_params['CODE_RES_RETURN'] = '// return a 1-dimensional vector\n        return tools::make_vector(y);'        
+        cpp_params['CODE_BEST_OBS'] = 'boptimizer.best_observation()(0)'
+
+    for key, value in cpp_params.iteritems():
+        cpp_tpl = cpp_tpl.replace('@' + key, value)
+
+    cpp = open('exp/' + name + "/" + name + ".cpp", "w")
+    cpp.write(cpp_tpl)
 
 def summary(bld):
     lst = getattr(bld, 'utest_results', [])

wscript

@@ -29,6 +29,7 @@ def options(opt):
         opt.load('libcmaes')
 
         opt.add_option('--create', type='string', help='create a new exp', dest='create_exp')
+        limbo.add_create_options(opt)
         opt.add_option('--exp', type='string', help='exp(s) to build, separate by comma', dest='exp')
         opt.add_option('--qsub', type='string', help='config file (json) to submit to torque', dest='qsub')
         opt.add_option('--oar', type='string', help='config file (json) to submit to oar', dest='oar')
@@ -153,7 +154,7 @@ def run_benchmark(ctx):
 
 def shutdown(ctx):
     if ctx.options.create_exp:
-        limbo.create_exp(ctx.options.create_exp)
+        limbo.create_exp(ctx.options.create_exp, ctx.options)
     if ctx.options.qsub:
         limbo.qsub(ctx.options.qsub)
     if ctx.options.oar: