X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=main.py;h=cd37b9441b21f6923da2e0df347c41d05de42dac;hb=0cba1df2952a9f9b88b6e7aacfcddc17fbc35186;hp=7b104bfa6db294ffbf1a53cb42aa28877e72f4b0;hpb=c797d1dc0243e6bf7a7e4a0d93bfcf13bf719163;p=picoclvr.git diff --git a/main.py b/main.py index 7b104bf..cd37b94 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=" ") @@ -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) @@ -62,7 +62,7 @@ parser.add_argument("--learning_rate_schedule", type=str, default="10: 2e-5,30: ######################################## -parser.add_argument("--model", type=str, default="37M") +parser.add_argument("--model", type=str, default=None) parser.add_argument("--dim_model", 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() @@ -171,84 +171,84 @@ if args.result_dir is None: ###################################################################### default_task_args = { + "addition": { + "model": "352M", + "batch_size": 25, + "nb_train_samples": 250000, + "nb_test_samples": 10000, + }, "byheart": { - "nb_epochs": 5, + "model": "37M", "batch_size": 25, "nb_train_samples": 50000, "nb_test_samples": 10000, }, - "learnop": { - "nb_epochs": 5, + "expr": { + "model": "352M", "batch_size": 25, - "nb_train_samples": 50000, + "nb_train_samples": 2500000, "nb_test_samples": 10000, }, - "guessop": { - "nb_epochs": 5, + "grid": { + "model": "37M", "batch_size": 25, - "nb_train_samples": 50000, + "nb_train_samples": 250000, "nb_test_samples": 10000, }, - "twotargets": { - "nb_epochs": 5, + "guessop": { + "model": "352M", "batch_size": 25, - "nb_train_samples": 50000, + "nb_train_samples": 1000000, "nb_test_samples": 10000, }, - "addition": { - "nb_epochs": 5, + "learnop": { + "model": "37M", "batch_size": 25, "nb_train_samples": 50000, "nb_test_samples": 10000, }, + "maze": { + "model": "37M", + "batch_size": 5, + "nb_train_samples": 100000, + "nb_test_samples": 10000, + }, "picoclvr": { - "nb_epochs": 25, + "model": "37M", "batch_size": 25, "nb_train_samples": 250000, "nb_test_samples": 10000, }, - "mnist": { - "nb_epochs": 25, - "batch_size": 10, - "nb_train_samples": 60000, - "nb_test_samples": 10000, - }, - "maze": { - "nb_epochs": 25, + "rpl": { + "model": "352M", "batch_size": 5, - "nb_train_samples": 250000, + "nb_train_samples": 2500000, "nb_test_samples": 10000, }, "snake": { - "nb_epochs": 5, + "model": "37M", "batch_size": 25, - "nb_train_samples": 50000, + "nb_train_samples": 250000, "nb_test_samples": 10000, }, "stack": { - "nb_epochs": 5, + "model": "37M", "batch_size": 25, "nb_train_samples": 100000, "nb_test_samples": 1000, }, - "expr": { - "nb_epochs": 40, + "twotargets": { + "model": "37M", "batch_size": 25, - "nb_train_samples": 1000000, + "nb_train_samples": 50000, "nb_test_samples": 10000, }, - "rpl": { - "nb_epochs": 40, - "batch_size": 25, - "nb_train_samples": 100000, + "mnist": { + "model": "37M", + "batch_size": 10, + "nb_train_samples": 60000, "nb_test_samples": 10000, }, - "world": { - "nb_epochs": 10, - "batch_size": 25, - "nb_train_samples": 25000, - "nb_test_samples": 1000, - }, } if args.task in default_task_args: @@ -492,12 +492,12 @@ 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, )