X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=main.py;h=d961301b4115b20a19cc63f1432d605564597305;hb=4aa7e109b4c712643cdddc2480b66d8799f71d3f;hp=dbdf89d1b091c68f91e6afd0a9f2e4fa27f4aece;hpb=2ec38da6ecc9a0f24c20b6b1e04e17d0eb23bd7e;p=picoclvr.git diff --git a/main.py b/main.py index dbdf89d..d961301 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, qmlp", ) parser.add_argument("--log_filename", type=str, default="train.log", help=" ") @@ -46,7 +46,7 @@ parser.add_argument("--max_percents_of_test_in_train", type=int, default=1) ######################################## -parser.add_argument("--nb_epochs", type=int, default=None) +parser.add_argument("--nb_epochs", type=int, default=25) parser.add_argument("--batch_size", type=int, default=None) @@ -89,16 +89,21 @@ 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) +############################## +# grid options + +parser.add_argument("--grid_size", type=int, default=6) + ############################## # picoclvr options @@ -113,11 +118,11 @@ parser.add_argument("--picocvlr_prune_properties", type=str, default="none") ############################## # Maze options -parser.add_argument("--maze_height", type=int, default=23) +parser.add_argument("--maze_height", type=int, default=13) -parser.add_argument("--maze_width", type=int, default=39) +parser.add_argument("--maze_width", type=int, default=21) -parser.add_argument("--maze_nb_walls", type=int, default=45) +parser.add_argument("--maze_nb_walls", type=int, default=15) ############################## # Snake options @@ -154,11 +159,6 @@ parser.add_argument("--expr_result_max", type=int, default=99) parser.add_argument("--expr_input_file", type=str, default=None) -############################## -# World options - -parser.add_argument("--world_vqae_nb_epochs", type=int, default=25) - ###################################################################### args = parser.parse_args() @@ -171,97 +171,90 @@ if args.result_dir is None: ###################################################################### default_task_args = { + "addition": { + "model": "352M", + "batch_size": 25, + "nb_train_samples": 250000, + "nb_test_samples": 10000, + }, "byheart": { "model": "37M", - "nb_epochs": 5, "batch_size": 25, "nb_train_samples": 50000, "nb_test_samples": 10000, }, - "learnop": { - "model": "37M", - "nb_epochs": 5, + "expr": { + "model": "352M", "batch_size": 25, - "nb_train_samples": 50000, + "nb_train_samples": 2500000, "nb_test_samples": 10000, }, - "guessop": { - "model": "122M", - "nb_epochs": 5, + "grid": { + "model": "37M", "batch_size": 25, "nb_train_samples": 250000, "nb_test_samples": 10000, }, - "twotargets": { + "qmlp": { "model": "37M", - "nb_epochs": 5, + "batch_size": 10, + "nb_train_samples": 100000, + "nb_test_samples": 1000, + }, + "guessop": { + "model": "352M", "batch_size": 25, - "nb_train_samples": 50000, + "nb_train_samples": 1000000, "nb_test_samples": 10000, }, - "addition": { - "model": "122M", - "nb_epochs": 5, + "learnop": { + "model": "37M", "batch_size": 25, "nb_train_samples": 50000, "nb_test_samples": 10000, }, - "picoclvr": { + "maze": { "model": "37M", - "nb_epochs": 25, - "batch_size": 25, - "nb_train_samples": 250000, + "batch_size": 5, + "nb_train_samples": 100000, "nb_test_samples": 10000, }, - "mnist": { + "picoclvr": { "model": "37M", - "nb_epochs": 25, - "batch_size": 10, - "nb_train_samples": 60000, + "batch_size": 25, + "nb_train_samples": 250000, "nb_test_samples": 10000, }, - "maze": { - "model": "37M", - "nb_epochs": 25, + "rpl": { + "model": "352M", "batch_size": 5, - "nb_train_samples": 250000, + "nb_train_samples": 2500000, "nb_test_samples": 10000, }, "snake": { "model": "37M", - "nb_epochs": 5, "batch_size": 25, - "nb_train_samples": 50000, + "nb_train_samples": 250000, "nb_test_samples": 10000, }, "stack": { "model": "37M", - "nb_epochs": 5, "batch_size": 25, "nb_train_samples": 100000, "nb_test_samples": 1000, }, - "expr": { + "twotargets": { "model": "37M", - "nb_epochs": 40, "batch_size": 25, - "nb_train_samples": 1000000, + "nb_train_samples": 50000, "nb_test_samples": 10000, }, - "rpl": { + "mnist": { "model": "37M", - "nb_epochs": 40, - "batch_size": 25, - "nb_train_samples": 100000, + "batch_size": 10, + "nb_train_samples": 60000, "nb_test_samples": 10000, }, - "world": { - "model": "37M", - "nb_epochs": 10, - "batch_size": 25, - "nb_train_samples": 25000, - "nb_test_samples": 1000, - }, } if args.task in default_task_args: @@ -505,12 +498,22 @@ elif args.task == "rpl": device=device, ) -elif args.task == "world": - task = tasks.World( +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, - vqae_nb_epochs=args.world_vqae_nb_epochs, + size=args.grid_size, + logger=log_string, + device=device, + ) + +elif args.task == "qmlp": + task = tasks.QMLP( + nb_train_samples=args.nb_train_samples, + nb_test_samples=args.nb_test_samples, + batch_size=args.batch_size, + result_dir=args.result_dir, logger=log_string, device=device, )