Continuing training resets logger step
🐛 Bug
I am running Pytorch Lightning in a federated learning setting. Therefore I have several models and I need to instantiate a Trainer object for one model multiple times. Every time I do that the associated logger resets the epoch and logs the metrics on top of each other in the plots. Since instantiating a new Trainer object to continue training a model is allowed as far as I know: Do you know if that is expected behaviour and whether there is a workaround?
In this picture is an example of the logging output of three consecutively called trainers with a common logger.

Please reproduce using the BoringModel
The Colab currently does not work with lightning and lightning_bolts.
To Reproduce
Create a TestTubeLogger and instantiate multiple Trainers with a common logger for the same model and fit the trainers consecutively.
Expected behaviour
The x-axis of the logged metrics should not reset between runs.
Environment

CUDA:

GPU:
available:         False
version:           None


Packages:

numpy:             1.20.1
pyTorch_debug:     False
pyTorch_version:   1.8.0+cpu
pytorch-lightning: 1.2.1
tqdm:              4.58.0


System:

OS:                Linux
architecture:

64bit
ELF


processor:         x86_64
python:            3.8.5
version:           #74-Ubuntu SMP Wed Jan 27 22:54:38 UTC 2021