def test_05_load_model(self): path = ROOT_PATH manager = InstanceManager(path) model = DummyModel input_shape = (32, 32, 3) manager.build_instance(model) visualizer_1 = DummyVisualizer_1 visualizer_2 = DummyVisualizer_2 visualizers = [visualizer_1, visualizer_2] manager.load_visualizer(visualizers) dataset = DummyDataset() epoch_time = 10 check_point_interval = 2 manager.train_instance(dataset, epoch_time, check_point_interval) # manager = InstanceManager(path) manager.load_instance(input_shape) visualizer_1 = DummyVisualizer_1 visualizer_2 = DummyVisualizer_2 visualizers = [visualizer_1, visualizer_2] manager.load_visualizer(visualizers) dataset = DummyDataset() epoch_time = 10 check_point_interval = 2 manager.train_instance(dataset, epoch_time, check_point_interval)
def test_03_train_model(self): path = ROOT_PATH manager = InstanceManager(path) model = DummyModel manager.build_instance(model) visualizer_1 = DummyVisualizer_1 visualizer_2 = DummyVisualizer_2 visualizers = [visualizer_1, visualizer_2] manager.load_visualizer(visualizers) dataset = DummyDataset() epoch_time = 10 manager.train_instance(dataset, epoch_time)
def test_03_train_model(self): path = ROOT_PATH manager = InstanceManager(path) model = DummyModel input_shape = (32, 32, 3) manager.gen_instance(model, input_shape) visualizer_1 = DummyVisualizer_1 visualizer_2 = DummyVisualizer_2 visualizers = [visualizer_1, visualizer_2] manager.load_visualizer(visualizers) dataset = DummyDataset() epoch_time = 10 manager.train_model(dataset, epoch_time)
def f(): path = ROOT_PATH manager = InstanceManager(path) model = DummyModel input_shape = (32, 32, 3) manager.gen_instance(model, input_shape) visualizers = [ (dummy_log, 10), ] manager.load_visualizer(visualizers) dataset = DummyDataset() epoch_time = 1 check_point_interval = 500 manager.train_model(dataset, epoch_time, check_point_interval)
visualizer_1 = DummyVisualizer_1 visualizer_2 = DummyVisualizer_2 visualizers = [visualizer_1, visualizer_2] manager.load_visualizer(visualizers) dataset = DummyDataset() epoch_time = 10 check_point_interval = 2 manager.train_instance(dataset, epoch_time, check_point_interval) if __name__ == '__main__': path = ROOT_PATH manager = InstanceManager(path) model = DummyModel input_shape = (32, 32, 3) manager.build_instance(model) visualizers = [ (dummy_log, 10), ] manager.load_visualizer(visualizers) dataset = DummyDataset() epoch_time = 1 check_point_interval = 500 manager.train_instance(dataset, epoch_time, check_point_interval)