X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=main.py;h=e18887b1998adc31da6c914519b2ba7ff049aece;hb=0f580d4facb4b4b485d0a38d62d06c0639715b77;hp=003028a819ccc5e8882435dbb817ca59aa128ba0;hpb=5aee50805cfad1dd49bbf30b30fe65b05e03de78;p=picoclvr.git diff --git a/main.py b/main.py index 003028a..e18887b 100755 --- a/main.py +++ b/main.py @@ -14,6 +14,7 @@ import torch, torchvision from torch import nn from torch.nn import functional as F +import ffutils import mygpt, tasks ###################################################################### @@ -34,8 +35,8 @@ parser = argparse.ArgumentParser( parser.add_argument( "--task", type=str, - default="picoclvr", - help="picoclvr, mnist, maze, snake, stack, expr", + default="sandbox", + help="sandbox, picoclvr, mnist, maze, snake, stack, expr, world", ) parser.add_argument("--log_filename", type=str, default="train.log", help=" ") @@ -110,7 +111,7 @@ parser.add_argument("--snake_nb_colors", type=int, default=5) parser.add_argument("--snake_length", type=int, default=200) ############################## -# Snake options +# Stack options parser.add_argument("--stack_nb_steps", type=int, default=100) @@ -125,7 +126,18 @@ parser.add_argument("--stack_fraction_values_for_train", type=float, default=0.7 parser.add_argument("--expr_nb_variables", type=int, default=5) -parser.add_argument("--expr_sequence_length", type=int, default=30) +parser.add_argument("--expr_sequence_length", type=int, default=40) + +parser.add_argument("--expr_operand_max", type=int, default=9) + +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) ###################################################################### @@ -139,6 +151,12 @@ if args.result_dir is None: ###################################################################### default_args = { + "sandbox": { + "nb_epochs": 10, + "batch_size": 25, + "nb_train_samples": 25000, + "nb_test_samples": 10000, + }, "picoclvr": { "nb_epochs": 25, "batch_size": 25, @@ -170,11 +188,17 @@ default_args = { "nb_test_samples": 1000, }, "expr": { - "nb_epochs": 50, + "nb_epochs": 40, "batch_size": 25, - "nb_train_samples": 250000, + "nb_train_samples": 1000000, "nb_test_samples": 10000, }, + "world": { + "nb_epochs": 10, + "batch_size": 25, + "nb_train_samples": 25000, + "nb_test_samples": 1000, + }, } if args.task in default_args: @@ -240,7 +264,16 @@ picoclvr_pruner_eval = ( ###################################################################### -if args.task == "picoclvr": +if args.task == "sandbox": + task = tasks.SandBox( + nb_train_samples=args.nb_train_samples, + nb_test_samples=args.nb_test_samples, + batch_size=args.batch_size, + logger=log_string, + device=device, + ) + +elif args.task == "picoclvr": task = tasks.PicoCLVR( nb_train_samples=args.nb_train_samples, nb_test_samples=args.nb_test_samples, @@ -305,7 +338,19 @@ elif args.task == "expr": nb_test_samples=args.nb_test_samples, nb_variables=args.expr_nb_variables, sequence_length=args.expr_sequence_length, + operand_max=args.expr_operand_max, + result_max=args.expr_result_max, + batch_size=args.batch_size, + device=device, + ) + +elif args.task == "world": + task = tasks.World( + 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, + logger=log_string, device=device, ) @@ -366,6 +411,20 @@ else: ###################################################################### +if args.task == "expr" and args.expr_input_file is not None: + task.produce_results( + nb_epochs_finished, + model, + args.result_dir, + log_string, + args.deterministic_synthesis, + args.expr_input_file, + ) + + exit(0) + +###################################################################### + nb_epochs = args.nb_epochs if args.nb_epochs > 0 else nb_epochs_default # Compute the entropy of the training tokens