Error while training an NMT Model on Machine
State: closed | Pull request: no

## Issue : 
I'm trying to train a NMT model using Nemo on my machine. I followed the instructions from the [documentation](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/stable/nlp/machine_translation.html) using the example script and the default configuration file. This runs perfectly on colab, but when I'm trying it on my local machine, I get the following error :
( I'm using branch r1.0.0rc1 and have tried using the Nemo docker image and installing from a repository on a PyTorch Image.)

## The error : 

Traceback (most recent call last):
  File "enc_dec_nmt.py", line 105, in main
    cfg = update_model_config(default_cfg, cfg)
  File "/opt/conda/lib/python3.6/site-packages/nemo/utils/config_utils.py", line 79, in update_model_config
    model_cls = _add_subconfig_keys(model_cls, update_cfg, subconfig_key='optim')
  File "/opt/conda/lib/python3.6/site-packages/nemo/utils/config_utils.py", line 169, in _add_subconfig_keys
    subconfig = OmegaConf.merge(update_subconfig, subconfig)
ValueError: Cannot merge with a None config
	full_key: model.optim
	reference_type=Any
	object_type=dict

## Here's the code I'm running :

!python enc_dec_nmt.py \
  -cn aayn_base \
  do_training=true \
  trainer.gpus=1 \
  ~trainer.max_epochs \
  +trainer.max_steps=100000 \
  +trainer.val_check_interval=1000 \
  +exp_manager.exp_dir=/workspace/dirname/exp \
  +exp_manager.create_checkpoint_callback=True \
  +exp_manager.checkpoint_callback_params.monitor=val_sacreBLEU \
  +exp_manager.checkpoint_callback_params.mode=max \
  +exp_manager.checkpoint_callback_params.save_top_k=5 \
  model.preproc_out_dir=/workspace/dirname/preproc \
  model.train_ds.use_tarred_dataset=true \
  model.train_ds.lines_per_dataset_fragment=1000000 \
  model.train_ds.num_batches_per_tarfile=200 \
  model.train_ds.src_file_name=/workspace/dirname/train_in \
  model.train_ds.tgt_file_name=/workspace/dirname/train_out \
  model.validation_ds.src_file_name=/workspace/dirname/splits/val_in \
  model.validation_ds.tgt_file_name=/workspace/dirname/val_out \
  model.encoder_tokenizer.vocab_size=32000 \
  model.decoder_tokenizer.vocab_size=32000 \
  ~model.test_ds 

(I have put the aayn_base.yaml file inside a folder _conf_ in the same directory)

## Here's the full stack trace

Traceback (most recent call last):
  File "enc_dec_nmt.py", line 136, in <module>
    main()
  File "/opt/conda/lib/python3.6/site-packages/nemo/core/config/hydra_runner.py", line 103, in wrapper
    strict=None,
  File "/opt/conda/lib/python3.6/site-packages/hydra/_internal/utils.py", line 347, in _run_hydra
    lambda: hydra.run(
  File "/opt/conda/lib/python3.6/site-packages/hydra/_internal/utils.py", line 201, in run_and_report
    raise ex
  File "/opt/conda/lib/python3.6/site-packages/hydra/_internal/utils.py", line 198, in run_and_report
    return func()
  File "/opt/conda/lib/python3.6/site-packages/hydra/_internal/utils.py", line 350, in <lambda>
    overrides=args.overrides,
  File "/opt/conda/lib/python3.6/site-packages/hydra/_internal/hydra.py", line 112, in run
    configure_logging=with_log_configuration,
  File "/opt/conda/lib/python3.6/site-packages/hydra/core/utils.py", line 127, in run_job
    ret.return_value = task_function(task_cfg)
  File "enc_dec_nmt.py", line 105, in main
    cfg = update_model_config(default_cfg, cfg)
  File "/opt/conda/lib/python3.6/site-packages/nemo/utils/config_utils.py", line 79, in update_model_config
    model_cls = _add_subconfig_keys(model_cls, update_cfg, subconfig_key='optim')
  File "/opt/conda/lib/python3.6/site-packages/nemo/utils/config_utils.py", line 169, in _add_subconfig_keys
    subconfig = OmegaConf.merge(update_subconfig, subconfig)
  File "/opt/conda/lib/python3.6/site-packages/omegaconf/omegaconf.py", line 321, in merge
    target.merge_with(*others[1:])
  File "/opt/conda/lib/python3.6/site-packages/omegaconf/basecontainer.py", line 331, in merge_with
    self._format_and_raise(key=None, value=None, cause=e)
  File "/opt/conda/lib/python3.6/site-packages/omegaconf/base.py", line 101, in _format_and_raise
    type_override=type_override,
  File "/opt/conda/lib/python3.6/site-packages/omegaconf/_utils.py", line 694, in format_and_raise
    _raise(ex, cause)
  File "/opt/conda/lib/python3.6/site-packages/omegaconf/_utils.py", line 610, in _raise
    raise ex  # set end OC_CAUSE=1 for full backtrace
ValueError: Cannot merge with a None config
	full_key: model.optim
	reference_type=Any
	object_type=dict

Any help is greatly appreciated. Thank you!