From: François Fleuret Date: Mon, 19 Jun 2023 17:04:52 +0000 (+0200) Subject: Update. X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=commitdiff_plain;h=d363acfa35249faaa1fc6574e50c1c59da277141;p=culture.git Update. --- diff --git a/main.py b/main.py index 24c21f5..3db87df 100755 --- a/main.py +++ b/main.py @@ -526,7 +526,7 @@ class TaskMaze(Task): self.width = width self.device = device - train_mazes, train_paths, train_policies = maze.create_maze_data( + train_mazes, train_paths, _ = maze.create_maze_data( nb_train_samples, height=height, width=width, @@ -534,9 +534,8 @@ class TaskMaze(Task): progress_bar=lambda x: tqdm.tqdm(x, dynamic_ncols=True, desc=f"data-train"), ) self.train_input = self.map2seq(train_mazes.to(device), train_paths.to(device)) - self.train_policies = train_policies.flatten(-2).to(device) - test_mazes, test_paths, test_policies = maze.create_maze_data( + test_mazes, test_paths, _ = maze.create_maze_data( nb_test_samples, height=height, width=width, @@ -544,9 +543,8 @@ class TaskMaze(Task): progress_bar=lambda x: tqdm.tqdm(x, dynamic_ncols=True, desc=f"data-test"), ) self.test_input = self.map2seq(test_mazes.to(device), test_paths.to(device)) - self.test_policies = test_policies.flatten(-2).to(device) - self.nb_codes = self.train_input.max() + 1 + self.nb_codes = max(self.train_input.max(), self.test_input.max()) + 1 def batches(self, split="train", nb_to_use=-1, desc=None): assert split in {"train", "test"} @@ -560,26 +558,6 @@ class TaskMaze(Task): ): yield batch - def policy_batches(self, split="train", nb_to_use=-1, desc=None): - assert split in {"train", "test"} - input = self.train_input if split == "train" else self.test_input - policies = self.train_policies if split == "train" else self.test_policies - input = input[:, : self.height * self.width] - policies = policies * (input != maze.v_wall)[:, None] - - if nb_to_use > 0: - input = input[:nb_to_use] - policies = policies[:nb_to_use] - - if desc is None: - desc = f"epoch-{split}" - for batch in tqdm.tqdm( - zip(input.split(self.batch_size), policies.split(self.batch_size)), - dynamic_ncols=True, - desc=desc, - ): - yield batch - def vocabulary_size(self): return self.nb_codes @@ -643,6 +621,42 @@ class TaskMaze(Task): model.train(t) +###################################################################### + +class TaskSnake(Task): + def __init__( + self, + nb_train_samples, + nb_test_samples, + batch_size, + height, + width, + nb_walls, + device=torch.device("cpu"), + ): + self.batch_size = batch_size + self.height = height + self.width = width + self.device = device + + # self.train_input = + # self.test_input = + + self.nb_codes = max(self.train_input.max(), self.train_input.max()) + 1 + + def batches(self, split="train", nb_to_use=-1, desc=None): + assert split in {"train", "test"} + input = self.train_input if split == "train" else self.test_input + if nb_to_use > 0: + input = input[:nb_to_use] + if desc is None: + desc = f"epoch-{split}" + for batch in tqdm.tqdm( + input.split(self.batch_size), dynamic_ncols=True, desc=desc + ): + yield batch + + ######################################################################