From: François Fleuret Date: Mon, 23 Oct 2023 06:16:58 +0000 (+0200) Subject: Update. X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=commitdiff_plain;h=8d9cd6a2c09da2105ca17b04df94fcf84e8de954;p=culture.git Update. --- diff --git a/main.py b/main.py index 496a603..f4e4f5c 100755 --- a/main.py +++ b/main.py @@ -164,6 +164,8 @@ parser.add_argument("--expr_input_file", type=str, default=None) parser.add_argument("--mixing_hard", action="store_true", default=False) +parser.add_argument("--mixing_deterministic_start", action="store_true", default=False) + ###################################################################### args = parser.parse_args() @@ -416,7 +418,9 @@ elif args.task == "twotargets": elif args.task == "mixing": task = tasks.SandBox( - problem=problems.ProblemMixing(hard=args.mixing_hard), + problem=problems.ProblemMixing( + hard=args.mixing_hard, random_start=not args.mixing_deterministic_start + ), nb_train_samples=args.nb_train_samples, nb_test_samples=args.nb_test_samples, batch_size=args.batch_size, diff --git a/problems.py b/problems.py index 9321194..ac16df4 100755 --- a/problems.py +++ b/problems.py @@ -289,36 +289,38 @@ class ProblemAddition(Problem): class ProblemMixing(Problem): - def __init__(self, height=4, width=4, nb_time_steps=9, hard=False): + def __init__( + self, height=4, width=4, nb_time_steps=9, hard=False, random_start=True + ): self.height = height self.width = width self.nb_time_steps = nb_time_steps self.hard = hard + self.random_start = random_start def start_random(self, nb): y = torch.arange(self.height * self.width).reshape(1, -1).expand(nb, -1) - # m = (torch.rand(y.size()).sort(dim=-1).indices < y.size(1) // 2).long() + if self.random_start: + i = ( + torch.arange(self.height) + .reshape(1, -1, 1) + .expand(nb, self.height, self.width) + ) + j = ( + torch.arange(self.width) + .reshape(1, 1, -1) + .expand(nb, self.height, self.width) + ) - i = ( - torch.arange(self.height) - .reshape(1, -1, 1) - .expand(nb, self.height, self.width) - ) - j = ( - torch.arange(self.width) - .reshape(1, 1, -1) - .expand(nb, self.height, self.width) - ) + ri = torch.randint(self.height, (nb,)).reshape(nb, 1, 1) + rj = torch.randint(self.width, (nb,)).reshape(nb, 1, 1) - ri = torch.randint(self.height, (nb,)).reshape(nb, 1, 1) - rj = torch.randint(self.width, (nb,)).reshape(nb, 1, 1) + m = 1 - torch.logical_or(i == ri, j == rj).long().flatten(1) - m = 1 - torch.logical_or(i == ri, j == rj).long().flatten(1) + y = y * m + self.height * self.width * (1 - m) - y = (y * m + self.height * self.width * (1 - m)).reshape( - nb, self.height, self.width - ) + y = y.reshape(nb, self.height, self.width) return y