X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=tasks.py;h=7a4abbeea23d9494d835cf6a040a36ab2eb53cc2;hb=6e09c88d26d0bfd675af9afd9cdc32aa3485d1b7;hp=44599f7db31bd7abe2b971afeb6ff5b795875682;hpb=4aa7e109b4c712643cdddc2480b66d8799f71d3f;p=picoclvr.git diff --git a/tasks.py b/tasks.py index 44599f7..7a4abbe 100755 --- a/tasks.py +++ b/tasks.py @@ -111,13 +111,19 @@ class SandBox(Task): self.nb_codes = max(self.train_input.max(), self.test_input.max()) + 1 # A bit of paranoia never hurts - assert ( - self.nb_codes <= max_nb_codes - and self.train_input.min() >= 0 - and self.test_input.min() >= 0 - and tuple(self.train_ar_mask.unique()) == (0, 1) - and tuple(self.test_ar_mask.unique()) == (0, 1) - ) + assert self.nb_codes <= max_nb_codes + assert self.train_input.min() >= 0 + assert self.test_input.min() >= 0 + assert tuple(x.item() for x in self.train_ar_mask.unique()) in { + (0,), + (1,), + (0, 1), + } + assert tuple(x.item() for x in self.test_ar_mask.unique()) in { + (0,), + (1,), + (0, 1), + } def batches(self, split="train", nb_to_use=-1, desc=None): assert split in {"train", "test"} @@ -151,17 +157,24 @@ class SandBox(Task): device=self.device, ) + log_ground_truth = ar_mask.min() == 0 + if logger is not None: for sp, st in zip(result[:10], input[:10]): logger( f"test_sequences {n_epoch} prediction {self.problem.seq2str(sp)}" ) - logger( - f" {n_epoch} ground truth {self.problem.seq2str(st)}" - ) + if log_ground_truth: + logger( + f" {n_epoch} ground truth {self.problem.seq2str(st)}" + ) - nb_total = ar_mask.sum().item() - nb_correct = ((result == input).long() * ar_mask).sum().item() + nb_total, nb_correct = self.problem.compute_nb_correct( + input, ar_mask, result + ) + + # nb_total = ar_mask.sum().item() + # nb_correct = ((result == input).long() * ar_mask).sum().item() return nb_total, nb_correct @@ -1588,13 +1601,19 @@ class QMLP(Task): self.train_input = seq[:nb_train_samples] self.train_q_test_set = q_test_set[:nb_train_samples] + self.train_ref_test_errors = test_error[:nb_train_samples] self.test_input = seq[nb_train_samples:] self.test_q_test_set = q_test_set[nb_train_samples:] - self.ref_test_errors = test_error + self.test_ref_test_errors = test_error[nb_train_samples:] + + filename = os.path.join(result_dir, f"train_errors_ref.dat") + with open(filename, "w") as f: + for e in self.train_ref_test_errors: + f.write(f"{e}\n") filename = os.path.join(result_dir, f"test_errors_ref.dat") with open(filename, "w") as f: - for e in self.ref_test_errors: + for e in self.test_ref_test_errors: f.write(f"{e}\n") self.nb_codes = max(self.train_input.max(), self.test_input.max()) + 1