From: Francois Fleuret Date: Fri, 16 Jun 2017 12:13:59 +0000 (+0200) Subject: Added the command line arguments test_loaded_models. X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=commitdiff_plain;h=cefdf80cffc5f897dc728d68bf927f522e3e1608;p=pysvrt.git Added the command line arguments test_loaded_models. --- diff --git a/cnn-svrt.py b/cnn-svrt.py index 283f02b..5913345 100755 --- a/cnn-svrt.py +++ b/cnn-svrt.py @@ -73,6 +73,10 @@ parser.add_argument('--compress_vignettes', action='store_true', default = False, help = 'Use lossless compression to reduce the memory footprint') +parser.add_argument('--test_loaded_models', + action='store_true', default = False, + help = 'Should we compute the test error of models we load') + args = parser.parse_args() ###################################################################### @@ -217,9 +221,7 @@ for problem_number in range(1, 24): args.nb_train_batches, args.batch_size, cuda=torch.cuda.is_available()) - log_string('data_generation {:0.2f} samples / s'.format( - (train_set.nb_samples + test_set.nb_samples) / (time.time() - t)) - ) + log_string('data_generation {:0.2f} samples / s'.format(train_set.nb_samples / (time.time() - t))) train_model(model, train_set) torch.save(model.state_dict(), model_filename) @@ -234,23 +236,28 @@ for problem_number in range(1, 24): train_set.nb_samples) ) - if args.compress_vignettes: - test_set = CompressedVignetteSet(problem_number, - args.nb_test_batches, args.batch_size, - cuda=torch.cuda.is_available()) - else: - test_set = VignetteSet(problem_number, - args.nb_test_batches, args.batch_size, - cuda=torch.cuda.is_available()) + if need_to_train or args.test_loaded_models: - nb_test_errors = nb_errors(model, test_set) + t = time.time() - log_string('test_error {:d} {:.02f}% {:d} {:d}'.format( - problem_number, - 100 * nb_test_errors / test_set.nb_samples, - nb_test_errors, - test_set.nb_samples) - ) + if args.compress_vignettes: + test_set = CompressedVignetteSet(problem_number, + args.nb_test_batches, args.batch_size, + cuda=torch.cuda.is_available()) + else: + test_set = VignetteSet(problem_number, + args.nb_test_batches, args.batch_size, + cuda=torch.cuda.is_available()) + + log_string('data_generation {:0.2f} samples / s'.format(test_set.nb_samples / (time.time() - t))) + + nb_test_errors = nb_errors(model, test_set) + log_string('test_error {:d} {:.02f}% {:d} {:d}'.format( + problem_number, + 100 * nb_test_errors / test_set.nb_samples, + nb_test_errors, + test_set.nb_samples) + ) ######################################################################