+parser = argparse.ArgumentParser(
+ description='Dummy test of the flatland sequence generation.',
+ formatter_class=argparse.ArgumentDefaultsHelpFormatter
+)
+
+parser.add_argument('--seed',
+ type = int, default = 0,
+ help = 'Random seed, < 0 is no seeding')
+
+parser.add_argument('--width',
+ type = int, default = 80,
+ help = 'Image width')
+
+parser.add_argument('--height',
+ type = int, default = 80,
+ help = 'Image height')
+
+parser.add_argument('--nb_shapes',
+ type = int, default = 10,
+ help = 'Image height')
+
+parser.add_argument('--nb_sequences',
+ type = int, default = 1,
+ help = 'How many sequences to generate')
+
+parser.add_argument('--nb_images_per_sequences',
+ type = int, default = 3,
+ help = 'How many images per sequence')
+
+parser.add_argument('--randomize_colors',
+ action='store_true', default=False,
+ help = 'Should the shapes be of different colors')
+
+parser.add_argument('--randomize_shape_size',
+ action='store_true', default=False,
+ help = 'Should the shapes be of different size')
+
+args = parser.parse_args()
+
+if args.seed >= 0:
+ torch.manual_seed(args.seed)
+
+######################################################################
+
+def sequences_to_image(x, gap = 1, gap_color = (0, 128, 255)):