TrainerClass.py

@@ -361,8 +361,7 @@ class eNoseTrainer:
             plt.close()
 
     def fit(self):
-        windows = [128,]
-#        windows = [128, 256, 384]
+        windows = [128, 256, 384]
         total_train_queue = 2*int(1/self.ratio)*(len(self.get_model_train())+len(windows))
         self.logger.info("{:=^60}".format(f'Begin Fit {total_train_queue} Models'))
         self.trained = 0

create_conda.sh

@@ -13,7 +13,7 @@ fi
 
 env_name=$1
 
-conda create -n "$env_name" python scikit-learn==1.3.1 xgboost conda-forge::tensorflow-cpu conda-forge::optuna keras pandas numpy matplotlib openpyxl xlsxwriter conda-forge::enlighten
+conda create -n "$env_name" python scikit-learn==1.3.1 xgboost conda-forge::tensorflow-cpu conda-forge::ray-tune keras pandas numpy matplotlib openpyxl xlsxwriter conda-forge::enlighten
 if [ $? -eq 0 ]; then
   echo "Packages installed successfully in environment '$env_name'"
 else