OutOfRangeError: RandomShuffleQueue '_1_shuffle_batch/random_shuffle_queue' is closed and has insufficient elements (requested 32, current size 0) about h-net HOT 4 OPEN

def createDataRecord_individual(out_folder, addrs):
    for i in range(len(addrs)):
        # open the TFRecords file
        fname = out_folder+str(i)+".tfrecords"
        writer = tf.io.TFRecordWriter(fname)
        
        # Load the image
        rgbIm, renIm, label = load_sample(addrs[i])

        # Create a feature
        feature = {
            "uds": _bytes_feature(renIm.tostring()),
            "label": _int64_feature(label),
            "photo": _bytes_feature(rgbIm.tostring())
        }
        # Create an example protocol buffer
        example = tf.train.Example(features=tf.train.Features(feature=feature))

        # Serialize to string and write on the file
        writer.write(example.SerializeToString())
        print("writing sample: ", fname)
        writer.close()
        sys.stdout.flush()


base_images_folder = "CrossDomainImage_processed/*.pickle"
# read addresses and labels from the 'train' folder
addrs = glob.glob(base_images_folder)
labels = [1 if "Match" in addr else -1 for addr in addrs]  # 0 = Cat, 1 = Dog

# to shuffle data
c = list(zip(addrs, labels))
shuffle(c)
addrs, labels = zip(*c)

# Divide the data into 60% train, 20% validation, and 20% test
train_addrs = addrs[0 : int(0.6 * len(addrs))]
val_addrs = addrs[int(0.6 * len(addrs)) : int(0.8 * len(addrs))]
test_addrs = addrs[int(0.8 * len(addrs)) :]

createDataRecord_individual("./baseTrainExample2/train/HNET_TRAIN_",train_addrs)
createDataRecord_individual("./baseTrainExample2/val/HNET_VAL_",val_addrs)
createDataRecord_individual("./baseTrainExample2/test/HNET_TEST_",test_addrs)