+# SVRT
+
+from vignette_set import VignetteSet, CompressedVignetteSet
+
+######################################################################
+
+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('--deep_model',
+ action='store_true', default = False,
+ help = 'Use Afroze\'s Alexnet-like deep model')
+
+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()