# print 'Test only' # res = run_classify(context, labels_test) # acc_hist.append([0, res]) # print res # M = process_parameters_auto(context) d=et.mksavedir() et.globaldata.context = context et.save() et.save(context, 'context.pkl') et.save(sys.argv, 'sysargv.pkl') et.save(M,'M.pkl') et.save(spkcnt,'spkcnt.pkl') et.save(bestM,'bestM.pkl') et.save(acc_hist, 'acc_hist.pkl') et.annotate('res',text=str(acc_hist)) textannotate('last_res',text=str(acc_hist)) textannotate('last_dir',text=d) # # # #
nsat.run_c_nsat(fname_train) print(('Run took {0} seconds'.format(time.time() - t0))) for j in range(setup.ncores): #train->test shutil.copy(exp_name + '/_shared_mem_core_{0}.dat'.format(j), exp_name_test + '/_wgt_table_core_{0}.dat'.format(j)) #train->train shutil.copy(exp_name + '/_shared_mem_core_{0}.dat'.format(j), exp_name + '/_wgt_table_core_{0}.dat'.format(j)) if test_every > 0: if i % test_every == test_every - 1: nsat.run_c_nsat(fname_test) acc, slout = test_accuracy(c_nsat_reader_test, targets=targets_classify[:N_test], pop=pop_out, sim_ticks=sim_ticks_test, duration=t_sample_test) pip.append([i, acc]) print(exp_name) print(pip) try: import experimentTools as et d = et.mksavedir(pre='Results_Scripts/') et.save(pip, 'pip.pkl') et.annotate('res', text=str(pip)) except ImportError: print('saving disabled due to missing experiment tools')