X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=main.py;h=00e19ac78f1695265286ce4e1160423468f753bd;hb=ce969e8372fb161d86be29042a20b044ee6efe2a;hp=8081850f2fc7e6a000a9fefb66fc34e6245390d5;hpb=4be66ea5e2814ed1f3ad650487e1a187e9a90cd1;p=picoclvr.git diff --git a/main.py b/main.py index 8081850..00e19ac 100755 --- a/main.py +++ b/main.py @@ -33,7 +33,7 @@ parser.add_argument( "--task", type=str, default="twotargets", - help="byheart, learnop, guessop, twotargets, addition, picoclvr, mnist, maze, snake, stack, expr, rpl", + help="byheart, learnop, guessop, twotargets, addition, picoclvr, mnist, maze, snake, stack, expr, rpl, grid", ) parser.add_argument("--log_filename", type=str, default="train.log", help=" ") @@ -89,13 +89,13 @@ parser.add_argument("--checkpoint_name", type=str, default="checkpoint.pth") ############################## # rpl options -parser.add_argument("--rpl_nb_starting_values", type=int, default=5) +parser.add_argument("--rpl_nb_starting_values", type=int, default=3) parser.add_argument("--rpl_max_input", type=int, default=9) -parser.add_argument("--rpl_prog_len", type=int, default=10) +parser.add_argument("--rpl_prog_len", type=int, default=8) -parser.add_argument("--rpl_nb_runs", type=int, default=8) +parser.add_argument("--rpl_nb_runs", type=int, default=5) parser.add_argument("--rpl_no_prog", action="store_true", default=False) @@ -249,10 +249,10 @@ default_task_args = { "nb_test_samples": 10000, }, "rpl": { - "model": "352M", + "model": "122M", "nb_epochs": 50, - "batch_size": 10, - "nb_train_samples": 2500000, + "batch_size": 5, + "nb_train_samples": 1000000, "nb_test_samples": 10000, }, "world": { @@ -262,6 +262,13 @@ default_task_args = { "nb_train_samples": 25000, "nb_test_samples": 1000, }, + "grid": { + "model": "37M", + "nb_epochs": 25, + "batch_size": 25, + "nb_train_samples": 250000, + "nb_test_samples": 10000, + }, } if args.task in default_task_args: @@ -505,6 +512,17 @@ elif args.task == "rpl": device=device, ) +elif args.task == "grid": + task = tasks.Grid( + nb_train_samples=args.nb_train_samples, + nb_test_samples=args.nb_test_samples, + batch_size=args.batch_size, + height=args.picoclvr_height, + width=args.picoclvr_width, + logger=log_string, + device=device, + ) + elif args.task == "world": task = tasks.World( nb_train_samples=args.nb_train_samples,