X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=quizz_machine.py;h=ee7af90b51b0259a99dcfd4fedba375f0d6cf510;hb=c4d4765d75961b8cdfa69ef1c56aeabcf3bdf42a;hp=6e57fb4bebb5ac15a4e9fdce3dcc3f9a0a27b870;hpb=f4d12501685fe9b46a75e3768115f86ea9b75fa6;p=culture.git diff --git a/quizz_machine.py b/quizz_machine.py index 6e57fb4..ee7af90 100755 --- a/quizz_machine.py +++ b/quizz_machine.py @@ -122,12 +122,13 @@ class QuizzMachine: forward_to_backward = torch.cat( [ quizzes[:, 0:1], - quizzes[:, 2 + self.prompt_len :], - quizzes[:, 1 + self.prompt_len : 2 + self.prompt_len], + quizzes[:, 2 + self.prompt_len : 2 + self.prompt_len + self.answer_len], + quizzes[:, 1 + self.prompt_len : 1 + self.prompt_len + 1], quizzes[:, 1 : 1 + self.prompt_len], ], dim=1, ) + forward_to_backward[:, 0] = self.token_backward forward_to_backward[:, 1 + self.answer_len] = self.token_backward @@ -234,14 +235,14 @@ class QuizzMachine: if result_dir is not None: self.save_quizzes( - result_dir, "culture_w_quizzes", self.train_w_quizzes[:72] + result_dir, + "culture_w_quizzes", + self.train_w_quizzes[:72], + prediction=True, ) - # toto = self.reverse_time(self.train_w_quizzes[:72]) - # self.save_quizzes(result_dir, "toto", toto) - # exit(0) - def save_quizzes(self, result_dir, filename_prefix, quizzes, prediction=False): + quizzes = quizzes.clone() forward = quizzes[quizzes[:, 0] == self.token_forward] ib = quizzes[:, 0] == self.token_backward backward = quizzes[ib] @@ -326,6 +327,21 @@ class QuizzMachine: device=self.device, ) + #!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! + self.save_quizzes( + result_dir, + f"DEBUG_input_{n_epoch}_{result.size(0):04d}", + quizzes=input[:72], + prediction=True, + ) + self.save_quizzes( + result_dir, + f"DEBUG_result_{n_epoch}_{result.size(0):04d}", + quizzes=result[:72], + prediction=True, + ) + #!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! + if self.back_accuracy: n_forward = input[:, 0] == self.token_forward nb_total = input[n_forward].size(0) @@ -334,21 +350,33 @@ class QuizzMachine: .long() .min(dim=1) .values.sum() + .item() + ) + + self.logger( + f"back_accuracy {n_epoch=} {model.id=} {nb_correct=} {nb_total=}" ) n_backward = input[:, 0] == self.token_backward back_input = self.reverse_time(result[n_backward]) + if back_input.size(0) > 0: back_input[:, 2 + self.prompt_len :] = input[ - n_backward, 2 + self.prompt_len : + n_backward, 1 : 1 + self.answer_len ] back_nb_total, back_nb_correct = compute_accuracy(back_input) + self.logger( + f"back_accuracy {n_epoch=} {model.id=} {back_nb_correct=} {back_nb_total=}" + ) nb_total += back_nb_total nb_correct += back_nb_correct + else: nb_total = input.size(0) nb_correct = (input == result).long().min(dim=1).values.sum() + exit(0) + return nb_total, nb_correct train_nb_total, train_nb_correct = compute_accuracy(self.train_w_quizzes[:nmax])