hparams.yaml saved twice when using TensorBoardLogger
🐛 Bug
When using TensorBoardLogger(...default_hp_metric=False...) and calling self.save_hyperparameters() from LightningModule instance, two hparams.yaml files are created (unexpected one in the logger's save_dir and second under proper experiment version dir).
Please reproduce using the BoringModel
See BoringModel.
To Reproduce

Create LightningModule with self.save_hyperparameters() call in __init__
Create TensorBoardLogger with default_hp_metric=False
Start training

Expected behavior
Only one hparams.yaml in save_dir/name/version should be created (like it happens when using tb logger with default_hp_metric=True).
Environment
From Collab Notebook:

CUDA:

GPU:

Tesla T4


available:         True
version:           10.1


Packages:

numpy:             1.19.5
pyTorch_debug:     True
pyTorch_version:   1.7.0+cu101
pytorch-lightning: 1.1.4
tqdm:              4.41.1


System:

OS:                Linux
architecture:

64bit



processor:         x86_64
python:            3.6.9
version:           1 SMP Thu Jul 23 08:00:38 PDT 2020