tf 1.15 在 sess.run 上无限期挂起

Question

我正在尝试完成将张量从1.5MB大小的 tf.record 文件转换为 NumPy 的简单任务。
这是我到目前为止所做的，不幸的是，代码无限期地挂在data_vol.eval()

    decomp_feature = {
            'dsize_dim0': tf.FixedLenFeature([], tf.int64),
            'dsize_dim1': tf.FixedLenFeature([], tf.int64),
            'dsize_dim2': tf.FixedLenFeature([], tf.int64),
            'lsize_dim0': tf.FixedLenFeature([], tf.int64),
            'lsize_dim1': tf.FixedLenFeature([], tf.int64),
            'lsize_dim2': tf.FixedLenFeature([], tf.int64),
            'data_vol': tf.FixedLenFeature([], tf.string),
            'label_vol': tf.FixedLenFeature([], tf.string)}
    raw_size = [256, 256, 3] # original raw input size
    volume_size = [256, 256, 3] # volume size after processing

    reader =  tf.TFRecordReader()
    file_example = "output/tmp/image_01.tfrecords"
    filename_queue = tf.train.string_input_producer(
        [file_example], num_epochs=1)

    fid, serialized_example = reader.read(filename_queue)
    parser = tf.parse_single_example(serialized_example, features = decomp_feature)
    data_vol = tf.decode_raw(parser['data_vol'], tf.float32)

    data_vol = tf.reshape(data_vol, raw_size)
    data_vol = tf.slice(data_vol, [0,0,0], volume_size)
    with tf.Session() as sess:  
        ### Tried without initializing and finalizing the graph, same problem ###
        sess.run(tf.initialize_all_variables())
        sess.graph.finalize()
        ######################

        sess.run(data_vol).eval()
        a = data_vol.eval() < --- stuck