Provide better error message on irregular configuration file formats failures

[scarlett2018]

Short summary about the issue/question:
When the configuration schema is not correct, current the Error message is not informational enough for user to fix the issues by themself.

How to reproduce it:
Error got:
ERROR: Your config file is not correct, please check your config file content!
Key 'tuner' error:
Or({'builtinTunerName': Or('TPE', 'Random', 'Anneal', 'SMAC', 'Evolution'), Optional('classArgs'): {'optimize_mode': Or('maximize', 'minimize')}, Optional('gpuNum'): And(<class 'int'>, <function at 0x7f6a5a2e2620>)}, {'builtinTunerName': Or('BatchTuner', 'GridSearch'), Optional('gpuNum'): And(<class 'int'>, <function at 0x7f6a5a2e26a8>)}, {'builtinTunerName': 'NetworkMorphism', 'classArgs': {Optional('optimize_mode'): Or('maximize', 'minimize'), Optional('task'): And(<class 'str'>, <function at 0x7f6a5a2e2730>), Optional('input_width'): <class 'int'>, Optional('input_channel'): <class 'int'>, Optional('n_output_node'): <class 'int'>}, Optional('gpuNum'): And(<class 'int'>, <function at 0x7f6a5a2e27b8>)}, {'builtinTunerName': 'MetisTuner', 'classArgs': {Optional('optimize_mode'): Or('maximize', 'minimize'), Optional('no_resampling'): <class 'bool'>, Optional('no_candidates'): <class 'bool'>, Optional('selection_num_starting_points'): <class 'int'>, Optional('cold_start_num'): <class 'int'>}, Optional('gpuNum'): And(<class 'int'>, <function at 0x7f6a5a2e2840>)}, {'codeDir': <function exists at 0x7f6a6967fa60>, 'classFileName': <class 'str'>, 'className': <class 'str'>, Optional('classArgs'): <class 'dict'>, Optional('gpuNum'): And(<class 'int'>, <function at 0x7f6a5a2e28c8>)}) did not validate {'builtinTunerName': 'Hyperband', 'classArgs': {'optimize_mode': 'maximize'}}
Missing keys: 'classFileName', 'className', 'codeDir'

The config file user have is this:

authorName: default
experimentName: surprise_svd
maxExecDuration: 1h
maxTrialNum: 100
searchSpacePath: search_space_svd.json
trainingServicePlatform: local
trial:
codeDir: .
command: python3 svd_training.py --datastore /data/home/anargyri/notebooks/Recommenders/notebooks/04_model_select_and_optimize/aml_data
--train-datapath movielens_100k_train.pkl --validation-datapath movielens_100k_val.pkl
--surprise-reader ml-100k --rating-metrics rmse --ranking-metrics precision_at_k
ndcg_at_k --usercol userID --itemcol itemID --k 10 --random-state 0 --epochs 30
--primary-metric precision_at_k --biased --verbose
gpuNum: 0
trialConcurrency: 8
tuner:
builtinTunerName: Hyperband
classArgs:
optimize_mode: maximize
useAnnotation: false