+ def generate_quizzes(self, nb, model_for_generation, min_ave_seq_logproba):
+ c_quizzes = torch.empty(
+ nb, self.train_w_quizzes.size(1), device=self.device, dtype=torch.int64
+ )
+
+ ar_mask_prompt = torch.zeros(c_quizzes.size(), device=self.device)
+ ar_mask_prompt[:, : ar_mask_prompt.size(1) // 2 + 1] = 1
+ ar_mask_solve = 1 - ar_mask_prompt
+ seq_logproba = torch.empty(ar_mask_prompt.size(0), device=self.device)
+
+ warnings.warn("noise injection", RuntimeWarning)
+ temperature = 1
+ noise_std = torch.rand(1).item()
+ self.logger(f"{noise_std=}")
+ mygpt.set_noise_injection(model_for_generation, noise_std)
+
+ masked_inplace_autoregression(
+ model=model_for_generation,
+ batch_size=self.batch_size,
+ input=c_quizzes,
+ ar_mask=ar_mask_prompt,
+ seq_logproba=seq_logproba,
+ temperature=temperature,
+ deterministic_synthesis=False,
+ # progress_bar_desc="sampling c_quizzes",
+ device=self.device,
+ )
+
+ ave_seq_logproba = seq_logproba.mean()
+
+ masked_inplace_autoregression(
+ model=model_for_generation,
+ batch_size=self.batch_size,
+ input=c_quizzes,
+ ar_mask=ar_mask_solve,
+ seq_logproba=seq_logproba,
+ temperature=temperature,
+ deterministic_synthesis=True,
+ # progress_bar_desc="sampling c_quizzes",
+ device=self.device,
+ )
+
+ mygpt.set_noise_injection(model_for_generation, 0.0)
+
+ return c_quizzes, seq_logproba.mean()
+
+ ######################################################################
+
+ def create_c_quizzes(
+ self,
+ nb,
+ model_for_generation,
+ models_for_validation,
+ min_ave_seq_logproba,
+ n_epoch,
+ result_dir,
+ ):
+ c_quizzes, ave_seq_logproba = self.generate_quizzes(
+ nb, model_for_generation, min_ave_seq_logproba
+ )
+
+ nb_correct = self.comput_correctness(c_quizzes, models_for_validation)
+
+ return c_quizzes, nb_correct, ave_seq_logproba
+
+ ######################################################################
+
+ def gang_create_c_quizzes(
+ self,
+ nb,
+ nb_models_for_generation,
+ models,
+ mode,
+ min_ave_seq_logproba,
+ n_epoch,
+ result_dir,
+ ):
+ model_for_generation = Gang(models, nb_models_for_generation, mode)
+ models_for_validation = models
+ return self.create_c_quizzes(
+ nb,
+ model_for_generation,
+ models_for_validation,
+ min_ave_seq_logproba,
+ n_epoch,
+ result_dir,
+ )