######################################################################
+import problem
-class Problem:
- def generate_seq(self, nb_train_samples):
- pass
- def save_quizzes(self, input, result_dir, filename_prefix, logger):
- pass
-
- def direction_tokens(self):
- pass
-
-
-class Sky:
+class Sky(problem.Problem):
colors = torch.tensor(
[
[255, 255, 255],
result.append("".join([self.token2char[v] for v in s]))
return result
- def save_image(self, input, result_dir, filename, logger):
+ def save_image(self, input, result_dir, filename):
img = self.seq2img(input.to("cpu"))
image_name = os.path.join(result_dir, filename)
torchvision.utils.save_image(img.float() / 255.0, image_name, nrow=6, padding=4)
- logger(f"wrote {image_name}")
- def save_quizzes(self, input, result_dir, filename_prefix, logger):
- self.save_image(input, result_dir, filename_prefix + ".png", logger)
+ def save_quizzes(self, input, result_dir, filename_prefix):
+ self.save_image(input, result_dir, filename_prefix + ".png")
######################################################################