Regarding the runtime error

[applelalala]

After running the code, the following error occurred:
Traceback (most recent call last):
File "D:\Users\admin\anaconda3\envs\refdnn\lib\contextlib.py", line 99, in exit
self.gen.throw(type, value, traceback)
File "D:\Users\admin\anaconda3\envs\refdnn\lib\site-packages\tensorflow\python\eager\context.py", line 843, in _mode
yield
File "D:\Users\admin\anaconda3\envs\refdnn\lib\site-packages\tensorflow_estimator\python\estimator\estimator.py", line 350, in train
loss = self._train_model(input_fn, hooks, saving_listeners)
File "D:\Users\admin\anaconda3\envs\refdnn\lib\site-packages\tensorflow_estimator\python\estimator\estimator.py", line 1176, in _train_model
return self._train_model_default(input_fn, hooks, saving_listeners)
File "D:\Users\admin\anaconda3\envs\refdnn\lib\site-packages\tensorflow_estimator\python\estimator\estimator.py", line 1209, in _train_model_default
saving_listeners)
File "D:\Users\admin\anaconda3\envs\refdnn\lib\site-packages\tensorflow_estimator\python\estimator\estimator.py", line 1515, in _train_with_estimator_spec
save_graph_def=self._config.checkpoint_save_graph_def) as mon_sess:
File "D:\Users\admin\anaconda3\envs\refdnn\lib\site-packages\tensorflow\python\training\monitored_session.py", line 605, in MonitoredTrainingSession
stop_grace_period_secs=stop_grace_period_secs)
File "D:\Users\admin\anaconda3\envs\refdnn\lib\site-packages\tensorflow\python\training\monitored_session.py", line 1039, in init
stop_grace_period_secs=stop_grace_period_secs)
File "D:\Users\admin\anaconda3\envs\refdnn\lib\site-packages\tensorflow\python\training\monitored_session.py", line 750, in init
self._sess = _RecoverableSession(self._coordinated_creator)
File "D:\Users\admin\anaconda3\envs\refdnn\lib\site-packages\tensorflow\python\training\monitored_session.py", line 1232, in init
_WrappedSession.init(self, self._create_session())
File "D:\Users\admin\anaconda3\envs\refdnn\lib\site-packages\tensorflow\python\training\monitored_session.py", line 1237, in _create_session
return self._sess_creator.create_session()
File "D:\Users\admin\anaconda3\envs\refdnn\lib\site-packages\tensorflow\python\training\monitored_session.py", line 910, in create_session
hook.after_create_session(self.tf_sess, self.coord)
File "D:\Users\admin\anaconda3\envs\refdnn\lib\site-packages\tensorflow\python\training\basic_session_run_hooks.py", line 587, in after_create_session
self._save(session, global_step)
File "D:\Users\admin\anaconda3\envs\refdnn\lib\site-packages\tensorflow\python\training\basic_session_run_hooks.py", line 620, in _save
write_meta_graph=self._save_graph_def)
File "D:\Users\admin\anaconda3\envs\refdnn\lib\site-packages\tensorflow\python\training\saver.py", line 1190, in save
{self.saver_def.filename_tensor_name: checkpoint_file})
File "D:\Users\admin\anaconda3\envs\refdnn\lib\site-packages\tensorflow\python\client\session.py", line 968, in run
run_metadata_ptr)
File "D:\Users\admin\anaconda3\envs\refdnn\lib\site-packages\tensorflow\python\client\session.py", line 1191, in _run
feed_dict_tensor, options, run_metadata)
File "D:\Users\admin\anaconda3\envs\refdnn\lib\site-packages\tensorflow\python\client\session.py", line 1369, in _do_run
run_metadata)
File "D:\Users\admin\anaconda3\envs\refdnn\lib\site-packages\tensorflow\python\client\session.py", line 1375, in _do_call
return fn(*args)
File "D:\Users\admin\anaconda3\envs\refdnn\lib\site-packages\tensorflow\python\client\session.py", line 1360, in _run_fn
target_list, run_metadata)
File "D:\Users\admin\anaconda3\envs\refdnn\lib\site-packages\tensorflow\python\client\session.py", line 1453, in _call_tf_sessionrun
run_metadata)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xd5 in position 192: invalid continuation byte

I suspect there might be an issue with the TFRecord file, but the data is provided within the code. I'm not sure how to resolve this problem. Can you help me?

[prassepaul]

This looks like an internal error of your installed environment. I added a *.yml file, from which you can create an environment that should be able to run the code. The TFRecord files are created on the fly using the CSV-files with the data.