TensorBoardLogger log_hyperparameters fails when explicitly specified.
🐛 Bug
TensorBoardLogger log_hyperparameters fails with TypeError: log_hyperparams() missing 1 required positional argument: 'params'  when explicitly specified. It behaves correctly when not specified (even though its the default logger).
To Reproduce
See code snippet:
import pytorch_lightning as pl
from pytorch_lightning import Trainer

# This is fine, even though TensorBoardLogger is the default logger.
trainer = Trainer()

# This breaks when `fit` is called, see stacktrace
trainer = Trainer(logger=pl.loggers.tensorboard.TensorBoardLogger)

trainer.fit(model, train_loader, val_loader)

Stacktrace (I removed some Hydra calls from the top of the trace that don't contribute anything). This doesn't happen when logger is not explicitly specified in the Trainer constructor.
Traceback (most recent call last):
  File "train.py", line 65, in train
    trainer.fit(model, train_loader, val_loader)
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 301, in fit
    results = self.accelerator_backend.train()
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/accelerators/gpu_backend.py", line 50, in train
    self.trainer.train_loop.setup_training(model)
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/trainer/training_loop.py", line 124, in setup_training
    self.trainer.logger.log_hyperparams(ref_model.hparams)
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/utilities/distributed.py", line 27, in wrapped_fn
    return fn(*args, **kwargs)
TypeError: log_hyperparams() missing 1 required positional argument: 'params'

Environment
Ran into issue on release 0.9.0 as well as current master ba01ec9

CUDA:
- GPU:
- GeForce GTX 1070
- available:         True
- version:           10.1
Packages:
- numpy:             1.18.5
- pyTorch_debug:     False
- pyTorch_version:   1.6.0
- pytorch-lightning: 0.9.1rc3
- tqdm:              4.46.0
System:
- OS:                Linux
- architecture:
- 64bit
-
- processor:         x86_64
- python:            3.7.7
- version:           #1 SMP Sun Mar 8 14:34:03 CDT 2020

Additional context
I'm explicitly specifying this because I have my own subclass of tensorboard's SummaryWriter that I would like TensorBoardLogger to use. I'm doing this by subclassing TensorBoardLogger and copying the experiment method, replacing the SummaryWriter with my own.