Restoring official Tensorflow Resnet-50 Checkpoint gives 'ExperimentalFunctionBufferingResource' Error - tensorflow

Question

When trying to reload the official tensorflow models for ResNet-50 checkpoint here:
http://download.tensorflow.org/models/official/20181001_resnet/checkpoints/resnet_imagenet_v1_fp32_20181001.tar.gz
...using this code:
import os
import tensorflow as tf
print(tf.__version__)
saver = tf.train.import_meta_graph(os.path.join(
'resnet_imagenet_v1_fp32_20181001',
'model.ckpt-225207.meta'))
I get this error:
1.13.1
Traceback (most recent call last):
File "chehckpoint_to_savedmodel.py", line 11, in <module>
'model.ckpt-225207.meta'))
File "/Users/*user*/Library/Python/3.7/lib/python/site-packages/tensorflow/python/training/saver.py", line 1435, in import_meta_graph
meta_graph_or_file, clear_devices, import_scope, **kwargs)[0]
File "/Users/*user*/Library/Python/3.7/lib/python/site-packages/tensorflow/python/training/saver.py", line 1457, in _import_meta_graph_with_return_elements
**kwargs))
File "/Users/*user*/Library/Python/3.7/lib/python/site-packages/tensorflow/python/framework/meta_graph.py", line 806, in import_scoped_meta_graph_with_return_elements
return_elements=return_elements)
File "/Users/*user*/Library/Python/3.7/lib/python/site-packages/tensorflow/python/util/deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "/Users/*user*/Library/Python/3.7/lib/python/site-packages/tensorflow/python/framework/importer.py", line 399, in import_graph_def
_RemoveDefaultAttrs(op_dict, producer_op_list, graph_def)
File "/Users/*user*/Library/Python/3.7/lib/python/site-packages/tensorflow/python/framework/importer.py", line 159, in _RemoveDefaultAttrs
op_def = op_dict[node.op]
KeyError: 'ExperimentalFunctionBufferingResource'
Funny that googling "KeyError: 'ExperimentalFunctionBufferingResource'" returns zero hits. That's a first.
Ideas?
Not sure how else to reload this model. I also tried this:
path = os.path.join(
'resnet_imagenet_v1_fp32_20181001',
'model.ckpt-225207')
checkpoint = tf.train.Checkpoint()
status = checkpoint.restore(path)
print(status)
status.assert_consumed()
But it fails the assertion with no other information.
Thanks in advance.
P

Answer 1

This seems to be a issue with TF >= 1.13 versions. Try downgrading to 1.12 and give it a try. It should work.
Issues to track would be these : #29751