Function evaluate

test/tensorflow/test_quantize_model.py:112–128

(model)

def evaluate(model):
    input_tensor = model.input_tensor
    output_tensor = model.output_tensor if len(model.output_tensor) > 1 else model.output_tensor[0]

    iteration = -1
    calib_dataloader = MyDataloader(dataset=Dataset())
    for idx, (inputs, labels) in enumerate(calib_dataloader):
        # dataloader should keep the order and len of inputs same with input_tensor
        inputs = np.array([inputs])
        feed_dict = dict(zip(input_tensor, inputs))

        start = time.time()
        predictions = model.sess.run(output_tensor, feed_dict)
        end = time.time()

        if idx + 1 == iteration:
            break


class TestQuantizeModel(unittest.TestCase):