Unified API : `model.params` attribute

Hello! Firstly, I wanted to thank you for this wonderful library.

Unified API to get model's params might make darts more convenient. For example, to get params of Exponential Smoothing model, We have to code like this:

model = ExponentialSmoothing()
model.fit(train)

print(model.model.model.params) # {'smoothing_level': 0.5789473661331209, 'smoothing_slope': ...

So, I want to implement model.get_params() method like sklearn. model.params attribute with property like statsmodels and fbprophet.

I would like to get your opinion before send PR. Thanks!

• Models
  • abstract params() function in the ForecastingModel superclass
  • ARIMA
  • AutoARIMA
  • Baseline Models
    • NaiveDrift
    • NaiveMean
    • NaiveSeasonal
  • ExponentialSmoothing
  • FFT
  • Prophet
  • StandardRegressionModel
  • TCNModel
  • Theta
  • TorchForecastingModel (RNNModel)
• Preprocessing
  • Scaler wrapper