如何在Tensorflow中将字符串张量转换为Python字符串？

以下代码是批量数据提供程序.mat文件，但运行时出现以下问题：

    TypeError: expected str, bytes or os.PathLike object, not FIFOQueue

代码是：

    import numpy as np
    import tensorflow as tf
    from tensorflow.python.framework import ops
    from tensorflow.python.framework import dtypes
    import h5py

    def Reader(filename):
        with h5py.File(filename, 'r') as f:
            image = np.transpose(np.array(f.get('patch_x'), dtype=np.float32))
            label = np.transpose(np.array(f.get('patch_y'), dtype=np.float32))
        image = ops.convert_to_tensor(image, dtype=dtypes.float32)
        label = ops.convert_to_tensor(label, dtype=dtypes.float32)

        return image, label

    def Inputs(filenames, batch_size, shuffle=True):
        filenames = ops.convert_to_tensor(filenames, dtype=dtypes.string)
        filename_queue = tf.train.string_input_producer(filenames, shuffle=shuffle)
        image, label = Reader(filename_queue)
        image = tf.cast(image, tf.float32)
        label = tf.cast(label, tf.float32)

        num_preprocess_threads = 4
        if shuffle:
            image_batch, label_batch = tf.train.shuffle_batch([image, label], batch_size=batch_size, num_threads=num_preprocess_threads, capacity=5*batch_size, min_after_dequeue=2*batch_size)
        else:
            image_batch, label_batch = tf.train.batch([image, label], batch_size=batch_size, num_threads=num_preprocess_threads, capacity=5*batch_size, min_after_dequeue=2*batch_size)
        return image_batch, label_batch

有谁知道如何转换string张量到Pythonstring容易地？谢谢。

更新1: 当使用filename.dequeue()，错误信息为：

    TypeError: expected str, bytes or os.PathLike object, not Tensor

要将字符串 TensorFlow 张量转换为 Python 字符串， 跑步bytes.decode(string_tensor.numpy()).