def on_train_begin(self): if (len(self.datasets) > 0 or len(self.testers) > 0) and self.trainer.dev_data is None: raise RuntimeError("Trainer has no dev data, you cannot pass extra data to do evaluation.") if len(self.datasets) > 0: for key, data in self.datasets.items(): tester = Tester(data=data, model=self.model, batch_size=self.batch_size, metrics=self.trainer.metrics, verbose=0) self.testers[key] = tester fitlog.add_progress(total_steps=self.n_steps)
def on_train_begin(self): if len(self.datasets) > 0: for key, data in self.datasets.items(): tester = Tester(data=data, model=self.model, batch_size=self.trainer.kwargs.get('dev_batch_size', self.batch_size), metrics=self.trainer.metrics, verbose=0, use_tqdm=self.trainer.test_use_tqdm) self.testers[key] = tester fitlog.add_progress(total_steps=self.n_steps)
def on_train_begin(self): if (len(self.datasets) > 0 or len(self.testers) > 0) and self.trainer.dev_data is None: raise RuntimeError("Trainer has no dev data, you cannot pass extra data to do evaluation.") if len(self.datasets) > 0: for key, data in self.datasets.items(): tester = Tester(data=data, model=self.model, batch_size=self.trainer.kwargs.get('dev_batch_size', self.trainer.batch_size), metrics=self.trainer.metrics, verbose=0, use_tqdm=self.trainer.kwargs.get('test_use_tqdm', self.trainer.use_tqdm), sampler=self.trainer.kwargs.get('test_sampler', None)) self.testers[key] = tester fitlog.add_progress(total_steps=self.n_steps)