Tensorboard logger fails to save model OmegaConf hparams

[ananthsub]

🐛 Bug

The Tensorboard logger fails to log module hyperparameters configured with OmegaConf. This happens when updating the logger hparams here:

• The trainer calls the logger's log_hyperparams here:
• Inside log_hyperparams the logger's hparams are updated here. This causes the hparams type to now be dict instead of DictConfig
• As a result, this branch in [save_hparams_to_yaml](https://github.com/PyTorchLightning/pytorch-lightning/blob/master/pytorch_lightning/core/saving.py#L330-L333) is never triggered

This is the stacktrace when logging hyperparams: https://gist.github.com/ananthsub/7acfdb0e0f551ed030f05f7674c37b46

To Reproduce

Code sample

A hacky fix would be something like changing the hparams update to use this inside the tensorboard logger:

if isinstance(params, Container):
   self.hparams = OmegaConf.merge(self.hparams, params)
else:
    self.hparams.update(params)

Expected behavior

Environment

Please copy and paste the output from our
environment collection script
(or fill out the checklist below manually).

You can get the script and run it with:

wget https://raw.githubusercontent.com/PyTorchLightning/pytorch-lightning/master/tests/collect_env_details.py
# For security purposes, please check the contents of collect_env_details.py before running it.
python collect_env_details.py

• PyTorch Version (e.g., 1.0):
• OS (e.g., Linux):
• How you installed PyTorch (conda, pip, source):
• Build command you used (if compiling from source):
• Python version:
• CUDA/cuDNN version:
• GPU models and configuration:
• Any other relevant information:

Additional context