[Major] Combined future regressor layer arguments into one single integer list `regressors_layers` like `ar_layers`

[kneureither]

:microscope: Background

• fixes issue #1375

:crystal_ball: Key changes

Removed the arguments future_regressors_num_hidden_layers and future_regressors_d_hidden and replaced them with a single argument future_regressors_layers : Optional[List[int]]. (following the practice of ar_layers)

• length holds the number of hidden layers
• values hold the dimension of each layer

:clipboard: Review Checklist

• [x] I have performed a self-review of my own code.
• [x] I have commented my code, added docstrings and data types to function definitions.
• [x] I have added pytests to check whether my feature / fix works.

[ourownstory]

Labelled as Major as it is a breaking change.

[github-actions[bot]]

Model Benchmark

Benchmark	Metric	main	current	diff
AirPassengers	MAE_val	30.8317	30.8317	0.0%	:white_check_mark:
AirPassengers	RMSE_val	31.8177	31.8177	0.0%	:white_check_mark:
AirPassengers	Loss_val	0.01301	0.01301	0.0%	:white_check_mark:
AirPassengers	train_loss	0.00071	0.00071	0.0%	:white_check_mark:
AirPassengers	reg_loss	0	0	0.0%	:white_check_mark:
AirPassengers	MAE	6.88164	6.88164	0.0%	:white_check_mark:
AirPassengers	RMSE	8.92097	8.92097	0.0%	:white_check_mark:
AirPassengers	Loss	0.00076	0.00076	0.0%	:white_check_mark:
AirPassengers	time	17.5903	18.01	2.39%	:white_check_mark:
EnergyPriceDaily	MAE_val	5.64183	5.64183	0.0%	:white_check_mark:
EnergyPriceDaily	RMSE_val	7.19915	7.19915	0.0%	:white_check_mark:
EnergyPriceDaily	Loss_val	0.02893	0.02893	0.0%	:white_check_mark:
EnergyPriceDaily	train_loss	0.02957	0.02957	0.0%	:white_check_mark:
EnergyPriceDaily	reg_loss	0	0	0.0%	:white_check_mark:
EnergyPriceDaily	MAE	6.39657	6.39657	0.0%	:white_check_mark:
EnergyPriceDaily	RMSE	8.56213	8.56213	0.0%	:white_check_mark:
EnergyPriceDaily	Loss	0.02936	0.02936	0.0%	:white_check_mark:
EnergyPriceDaily	time	85.4153	89.36	4.62%	:warning:
YosemiteTemps	MAE_val	0.59751	0.59751	0.0%	:white_check_mark:
YosemiteTemps	RMSE_val	0.88859	0.88859	0.0%	:white_check_mark:
YosemiteTemps	Loss_val	0.00046	0.00046	0.0%	:white_check_mark:
YosemiteTemps	train_loss	0.00126	0.00126	0.0%	:white_check_mark:
YosemiteTemps	reg_loss	0	0	0.0%	:white_check_mark:
YosemiteTemps	MAE	0.97464	0.97464	0.0%	:white_check_mark:
YosemiteTemps	RMSE	1.70813	1.70813	0.0%	:white_check_mark:
YosemiteTemps	Loss	0.00126	0.00126	0.0%	:white_check_mark:
YosemiteTemps	time	334.987	350.09	4.51%	:warning:
PeytonManning	MAE_val	0.35542	0.35542	0.0%	:white_check_mark:
PeytonManning	RMSE_val	0.50403	0.50403	0.0%	:white_check_mark:
PeytonManning	Loss_val	0.01803	0.01803	0.0%	:white_check_mark:
PeytonManning	train_loss	0.01466	0.01466	0.0%	:white_check_mark:
PeytonManning	reg_loss	0	0	0.0%	:white_check_mark:
PeytonManning	MAE	0.34755	0.34755	0.0%	:white_check_mark:
PeytonManning	RMSE	0.49449	0.49449	0.0%	:white_check_mark:
PeytonManning	Loss	0.01465	0.01465	0.0%	:white_check_mark:
PeytonManning	time	100.415	110.75	10.29%	:x:

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Model training plots

\n ## Model Training ### PeytonManning  ### YosemiteTemps  ### AirPassengers  ### EnergyPriceDaily  \n