def download_training_and_eval_data()

in tensorflow_script_mode_local_gpu_training_resnet50/tensorflow_script_mode_local_training_resnet50.py [0:0]

• 18 lines of code
• 5 McCabe index (conditional complexity)

def download_training_and_eval_data():
    if os.path.isfile('./data/training/train_data.npy') and \
            os.path.isfile('./data/training/train_labels.npy') and \
            os.path.isfile('./data/validation/validation_data.npy') and \
            os.path.isfile('./data/validation/validation_labels.npy'):
        print('Training and evaluation datasets exist. Skipping Download')
    else:
        print('Downloading training and evaluation dataset')
        (X_train, y_train), (X_valid, y_valid) = cifar10.load_data()

        with open('./data/training/train_data.npy', 'wb') as f:
            np.save(f, X_train)

        with open('./data/training/train_labels.npy', 'wb') as f:
            np.save(f, y_train)

        with open('./data/validation/validation_data.npy', 'wb') as f:
            np.save(f, X_valid)

        with open('./data/validation/validation_labels.npy', 'wb') as f:
            np.save(f, y_valid)

        print('Downloading completed')