20675f9f01e8c365999fee3ff1e4ec55ec5f8b57,tests/onnx/test_onnx_model_export.py,,predicted,#Any#Any#,80

Before Change

@pytest.fixture(scope="module")
def predicted(model, data):
    return model.predict(data[0])


@pytest.fixture(scope="module")
def tf_model_multiple_inputs_float64():

After Change

@pytest.fixture(scope="module")
def predicted(model, dataset):
    batch_size = 16
    num_workers = 4
    dataloader = DataLoader(
        dataset, batch_size=batch_size, num_workers=num_workers, shuffle=False, drop_last=False
    )
    predictions = np.zeros((len(dataloader.sampler),))
    model.eval()
    with torch.no_grad():
        for i, batch in enumerate(dataloader):
            y_preds = model(batch[0]).squeeze(dim=1).numpy()
            predictions[i * batch_size : (i + 1) * batch_size] = y_preds
    return predictions


@pytest.fixture(scope="module")

Instances