Updated thesis and added quantile performance plots to non autoregressive quantiles

src/training_scripts/non_autoregressive_quantiles.py

@@ -51,7 +51,7 @@ data_processor.set_full_day_skip(True)
 #### Hyperparameters ####
 data_processor.set_output_size(96)
 inputDim = data_processor.get_input_size()
-epochs = 300
+epochs = 2
 
 # add parameters to clearml
 quantiles = task.get_parameter("general/quantiles", cast=True)
@@ -117,7 +117,7 @@ trainer.add_metrics_to_track(
     [PinballLoss(quantiles), MSELoss(), L1Loss(), CRPSLoss(quantiles)]
 )
 trainer.early_stopping(patience=5)
-trainer.plot_every(20)
+trainer.plot_every(1)
 trainer.train(task=task, epochs=epochs, remotely=True)
 
 ### Policy Evaluation ###