PyTorch Lightning 0.10 compatibility and classification

Added

• Additional checks for TimeSeriesDataSet inputs - now flagging if series are lost due to high min_encoder_length and ensure parameters are integers
• Enable classification - simply change the target in the TimeSeriesDataSet to a non-float variable, use the CrossEntropy metric to optimize and output as many classes as you want to predict

Changed

• Ensured PyTorch Lightning 0.10 compatibility
  • Using LearningRateMonitor instead of LearningRateLogger
  • Use EarlyStopping callback in trainer callbacks instead of early_stopping argument
  • Update metric system update() and compute() methods
  • Use trainer.tuner.lr_find() instead of trainer.lr_find() in tutorials and examples
• Update poetry to 1.1.0