How to solve tensor_util.py 'TypeError: Incompatible types: <dtype: 'string'> vs. object.'?

I'm using object detection raccoon by datitran(https://github.com/datitran/raccoon_dataset) to train my own dataset and met an issue.

Environment Info.:

OS:Windows 10 64bit

CUDA and CUDNN: CUDA 10/CUDNN 7.5.0

Tensorflow version:1.13.1(GPU)

Python version:3.7.0 64 bit (Anaconda, Inc. on win32)

Model:ssd_mobilenet_v1_coco

Issue:

start trainning by

python model_main.py 
--pipeline_config_path=Z:/Train/ssd_mobilenet_v1_coco_ship.config 
--model_dir=Z:/Train/train 
--alsologtostderr

and

WARNING: The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:
  * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
  * https://github.com/tensorflow/addons
If you depend on functionality not listed there, please file an issue.

WARNING:tensorflow:Forced number of epochs for all eval validations to be 1.
WARNING:tensorflow:Expected number of evaluation epochs is 1, but instead encountered `eval_on_train_input_config.num_epochs` = 0. Overwriting `num_epochs` to 1.
WARNING:tensorflow:Estimator's model_fn (<function create_model_fn.<locals>.model_fn at 0x000001DB9EADB8C8>) includes params argument, but params are not passed to Estimator.
WARNING:tensorflow:From D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.
Instructions for updating:
Colocations handled automatically by placer.
WARNING:tensorflow:num_readers has been reduced to 1 to match input file shards.
WARNING:tensorflow:From D:\Anaconda\envs\tensorflow\Lib\models\research\object_detection\builders\dataset_builder.py:80: parallel_interleave (from tensorflow.contrib.data.python.ops.interleave_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.data.experimental.parallel_interleave(...)`.
Traceback (most recent call last):
  File "model_main.py", line 109, in <module>
    tf.app.run()
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\platform\app.py", line 125, in run
    _sys.exit(main(argv))
  File "model_main.py", line 105, in main
    tf.estimator.train_and_evaluate(estimator, train_spec, eval_specs[0])
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow_estimator\python\estimator\training.py", line 471, in train_and_evaluate
    return executor.run()
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow_estimator\python\estimator\training.py", line 611, in run
    return self.run_local()
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow_estimator\python\estimator\training.py", line 712, in run_local
    saving_listeners=saving_listeners)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow_estimator\python\estimator\estimator.py", line 358, in train
    loss = self._train_model(input_fn, hooks, saving_listeners)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow_estimator\python\estimator\estimator.py", line 1124, in _train_model
    return self._train_model_default(input_fn, hooks, saving_listeners)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow_estimator\python\estimator\estimator.py", line 1151, in _train_model_default
    input_fn, model_fn_lib.ModeKeys.TRAIN))
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow_estimator\python\estimator\estimator.py", line 992, in _get_features_and_labels_from_input_fn
    self._call_input_fn(input_fn, mode))
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow_estimator\python\estimator\estimator.py", line 1079, in _call_input_fn
    return input_fn(**kwargs)
  File "D:\Anaconda\envs\tensorflow\Lib\models\research\object_detection\inputs.py", line 488, in _train_input_fn
    batch_size=params['batch_size'] if params else train_config.batch_size)
  File "D:\Anaconda\envs\tensorflow\Lib\models\research\object_detection\builders\dataset_builder.py", line 134, in build
    config.input_path[:], input_reader_config)
  File "D:\Anaconda\envs\tensorflow\Lib\models\research\object_detection\builders\dataset_builder.py", line 80, in read_dataset
    sloppy=config.shuffle))
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\data\ops\dataset_ops.py", line 1605, in apply
    return DatasetV1Adapter(super(DatasetV1, self).apply(transformation_func))
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\data\ops\dataset_ops.py", line 1127, in apply
    dataset = transformation_func(self)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\data\experimental\ops\interleave_ops.py", line 88, in _apply_fn
    buffer_output_elements, prefetch_input_elements)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\data\ops\readers.py", line 133, in __init__
    cycle_length, block_length)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\data\ops\dataset_ops.py", line 2827, in __init__
    super(InterleaveDataset, self).__init__(input_dataset, map_func)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\data\ops\dataset_ops.py", line 2798, in __init__
    map_func, self._transformation_name(), dataset=input_dataset)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\data\ops\dataset_ops.py", line 2124, in __init__
    self._function.add_to_graph(ops.get_default_graph())
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\function.py", line 490, in add_to_graph
    self._create_definition_if_needed()
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\function.py", line 341, in _create_definition_if_needed
    self._create_definition_if_needed_impl()
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\function.py", line 355, in _create_definition_if_needed_impl
    whitelisted_stateful_ops=self._whitelisted_stateful_ops)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\function.py", line 883, in func_graph_from_py_func
    outputs = func(*func_graph.inputs)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\data\ops\dataset_ops.py", line 2099, in tf_data_structured_function_wrapper
    ret = func(*nested_args)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\data\ops\readers.py", line 247, in __init__
    filenames, compression_type, buffer_size, num_parallel_reads)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\data\ops\readers.py", line 212, in __init__
    self._impl = filenames.flat_map(read_one_file)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\data\ops\dataset_ops.py", line 1005, in flat_map
    return FlatMapDataset(self, map_func)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\data\ops\dataset_ops.py", line 2798, in __init__
    map_func, self._transformation_name(), dataset=input_dataset)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\data\ops\dataset_ops.py", line 2124, in __init__
    self._function.add_to_graph(ops.get_default_graph())
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\function.py", line 490, in add_to_graph
    self._create_definition_if_needed()
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\function.py", line 341, in _create_definition_if_needed
    self._create_definition_if_needed_impl()
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\function.py", line 355, in _create_definition_if_needed_impl
    whitelisted_stateful_ops=self._whitelisted_stateful_ops)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\function.py", line 883, in func_graph_from_py_func
    outputs = func(*func_graph.inputs)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\data\ops\dataset_ops.py", line 2099, in tf_data_structured_function_wrapper
    ret = func(*nested_args)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\data\ops\readers.py", line 209, in read_one_file
    return _TFRecordDataset(filename, compression_type, buffer_size)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\data\ops\readers.py", line 111, in __init__
    argument_dtype=dtypes.string)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\data\util\convert.py", line 35, in optional_param_to_tensor
    argument_default, dtype=argument_dtype, name=argument_name)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\constant_op.py", line 245, in constant
    allow_broadcast=True)
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\constant_op.py", line 283, in _constant_impl
    allow_broadcast=allow_broadcast))
  File "D:\Anaconda\envs\tensorflow\lib\site-packages\tensorflow\python\framework\tensor_util.py", line 501, in make_tensor_proto
    (dtype, nparray.dtype, values))
TypeError: Incompatible types: <dtype: 'string'> vs. object. Value is

how to handle with this?

EDIT:I have uninstalled the latest version TensorFlow, the previous version works well. Therefore I can not offer more error Info. @rachelim