From: François Fleuret Date: Sat, 26 Aug 2023 10:06:19 +0000 (+0200) Subject: Update. X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=commitdiff_plain;h=6681907dcc86bf6e159925814d419f522e0e3300;p=picoclvr.git Update. --- diff --git a/grid.py b/grid.py index 60baedf..268f4ee 100755 --- a/grid.py +++ b/grid.py @@ -220,11 +220,17 @@ if __name__ == "__main__": # print(f"{len(samples) / (end_time - start_time):.02f} samples per second") start_scene, scene, questions = grid_factory.generate_scene_and_questions() + print() print("-- Original scene -----------------------------") + print() grid_factory.print_scene(start_scene) + print() print("-- Transformed scene --------------------------") + print() grid_factory.print_scene(scene) + print() print("-- Sequence -----------------------------------") + print() print(questions) ###################################################################### diff --git a/tasks.py b/tasks.py index cbc8e6b..d787c59 100755 --- a/tasks.py +++ b/tasks.py @@ -1426,7 +1426,7 @@ import grid class Grid(Task): # Make a tensor from a list of strings - def tensorize(self, descr): + def str2tensor(self, descr): token_descr = [s.strip().split(" ") for s in descr] l = max([len(s) for s in token_descr]) token_descr = [s + ["#"] * (l - len(s)) for s in token_descr] @@ -1434,7 +1434,7 @@ class Grid(Task): return torch.tensor(id_descr, device=self.device) # Make a list of strings from a tensor - def detensorize(self, x): + def tensor2str(self, x): return [" ".join([self.id2token[t.item()] for t in r]) for r in x] # trim all the tensors in the tuple z to remove as much token from @@ -1499,8 +1499,8 @@ class Grid(Task): self.t_false = self.token2id["false"] # Tokenize the train and test sets - self.train_input = self.tensorize(self.train_descr) - self.test_input = self.tensorize(self.test_descr) + self.train_input = self.str2tensor(self.train_descr) + self.test_input = self.str2tensor(self.test_descr) def batches(self, split="train"): assert split in {"train", "test"} @@ -1519,9 +1519,11 @@ class Grid(Task): correct = self.test_input[:1000] result = correct.clone() ar_mask = torch.logical_or(result == self.t_true, result == self.t_false).long() - result *= 1 - ar_mask + result *= 1 - ar_mask # paraaaaanoiaaaaaaa + + logger(f"----------------------------------------------------------") - for e in self.detensorize(result[:10]): + for e in self.tensor2str(result[:10]): logger(f"test_before {e}") masked_inplace_autoregression( @@ -1533,8 +1535,12 @@ class Grid(Task): device=self.device, ) - for e in self.detensorize(result[:10]): - logger(f"test_after {e}") + logger(f"----------------------------------------------------------") + + for e in self.tensor2str(result[:10]): + logger(f"test_after {e}") + + logger(f"----------------------------------------------------------") nb_total = ar_mask.sum().item() nb_correct = ((correct == result).long() * ar_mask).sum().item()