Conflict between Tensorboard and Tensorflow Training (accessing Checkpoints)

When I run the Tensorflow Object Detection API, start a training, interrupt the training and continue the training later while the Tensorboard is running, training failes, because it tries to rename some checkpoint files, which are apparently locked by the Tensorboard:

2018-01-19 15:54:45.633575: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\
core\framework\op_kernel.cc:1192] Unknown: Failed to rename: C:/Users/Alex/Repositories/MusicObjec
tDetector-TF/MusicObjectDetector/data/checkpoints-faster_rcnn_inception_resnet_v2_atrous_muscima_p
retrained_with_stafflines_dimension_clustering2-train\model.ckpt-92013.index.tempstate676747125244
4121708 to: C:/Users/Alex/Repositories/MusicObjectDetector-TF/MusicObjectDetector/data/checkpoints
-faster_rcnn_inception_resnet_v2_atrous_muscima_pretrained_with_stafflines_dimension_clustering2-t
rain\model.ckpt-92013.index : Access is denied.
; Input/output error
INFO:tensorflow:Error reported to Coordinator: <class tensorflow.python.framework.errors_impl.Unkn
ownError'>, Failed to rename: C:/Users/Alex/Repositories/MusicObjectDetector-TF/MusicObjectDetecto
r/data/checkpoints-faster_rcnn_inception_resnet_v2_atrous_muscima_pretrained_with_stafflines_dimen
sion_clustering2-train\model.ckpt-92013.index.tempstate6767471252444121708 to: C:/Users/Alex/Repos
itories/MusicObjectDetector-TF/MusicObjectDetector/data/checkpoints-faster_rcnn_inception_resnet_v
2_atrous_muscima_pretrained_with_stafflines_dimension_clustering2-train\model.ckpt-92013.index : 
Access is denied.

I was wondering, if it would be possible to make sure that the Tensorboard does not lock out any other processes? Or is this entirely impossible to read a file, without locking? I don't know what the TensorBoard actually reads from the *.index file that takes longer than a split-second, releasing the file immediately afterwards. I understand, that loading the events from the events.out.tfevents.*.* takes a while to process, but there is apparently works.

Start by reproducing the Windows failure with TensorBoard running while TensorFlow training resumes from a checkpoint, focusing on the reported .index and events.out.tfevents. files. Trace which TensorBoard operation keeps the checkpoint open; done means training can rename and continue using the checkpoint while TensorBoard remains active.