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How to use test_model_validation method in pandera

Best Python code snippet using pandera_python

test_training.py

Source:test_training.py

...73lr_scheduler = torch.optim.lr_scheduler.StepLR(optimizer, step_size=3, gamma=0.1)74class TestClass:    75    76    @pytest.fixture()    77    def test_model_validation(self):78        ## load the model specified in the path79        metric_collector = []80        validation_accuracy_old = 081        validation_AP_accuracy = 082        for epoch in tqdm.tqdm(range(num_epochs)):83            validation_accuracy_old = validation_AP_accuracy84            # train for one epoch, printing every 5 iterations85            metric_logger = train_one_epoch(86                model, optimizer, train_loader, device, epoch, print_freq=587            )88            metric_collector.append(metric_logger)89            # update the learning rate90            lr_scheduler.step()91            # Evaluate with validation dataset...

__init__.py

Source:__init__.py

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