+parser = argparse.ArgumentParser(
+ description = 'Simple convnet test on the SVRT.',
+ formatter_class = argparse.ArgumentDefaultsHelpFormatter
+)
+
+parser.add_argument('--nb_train_batches',
+ type = int, default = 1000,
+ help = 'How many samples for train')
+
+parser.add_argument('--nb_test_batches',
+ type = int, default = 100,
+ help = 'How many samples for test')
+
+parser.add_argument('--nb_epochs',
+ type = int, default = 50,
+ help = 'How many training epochs')
+
+parser.add_argument('--batch_size',
+ type = int, default = 100,
+ help = 'Mini-batch size')
+
+parser.add_argument('--log_file',
+ type = str, default = 'default.log',
+ help = 'Log file name')
+
+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 errors of loaded models')
+
+args = parser.parse_args()
+
+######################################################################
+
+log_file = open(args.log_file, 'w')
+pred_log_t = None
+
+print(Fore.RED + 'Logging into ' + args.log_file + Style.RESET_ALL)
+
+def log_string(s):
+ global pred_log_t
+
+ t = time.time()
+
+ if pred_log_t is None:
+ elapsed = 'start'
+ else:
+ elapsed = '+{:.02f}s'.format(t - pred_log_t)
+
+ pred_log_t = t
+
+ s = Fore.BLUE + time.ctime() + ' ' + Fore.GREEN + elapsed + Style.RESET_ALL + ' ' + s
+ log_file.write(s + '\n')
+ log_file.flush()
+ print(s)