start implementation

configurations/dev_example.yml

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+# Example configuration file for a data processing pipeline
+
+general:
+  logging: "console"  # Options: "console", "file", "both"
+  log_level: "INFO"  # Options: "DEBUG", "INFO", "WARN", "ERROR", "CRITICAL"
+  log_file: "logs/pipeline.log"  # Path to the log file if logging to file
+
+stages:
+  - name: "Load_datasets"
+    output_stream: "input_dataset"
+    module_path: "EEG_preprocessing_modules/data_loader.py"
+    module_params:
+      datasets:
+        - path: "data/dataset1.csv"
+          name: "dataset1"
+        - path: "data/dataset2.csv"
+          name: "dataset2"
+      action: "merge"
+  
+  - name: "Process_data"
+    input_stream: "input_dataset"
+    output_stream: "processed_dataset"
+    module_path: "EEG_preprocessing_modules/preprocessing.py"
+    module_params:
+      select_channels:
+        - "channel1"
+        - "channel2"
+      filter_frequency: 0.5
+      resample_rate: 1000
+
+  - name: "Train_augment_model"
+    type: "train"
+    input_stream: "processed_dataset"
+    module_path: "models_augment/GAN/main.py"
+    module_params: # Model specific parameters, they're passed to the module script as dictionary
+      noise_level: 0.01
+      save_path: "models_augment/GAN/model.pth"
+
+
+  - name: "Augment_data"
+    type: "inference" # Inference is default, but can be specified explicitly
+    input_stream: "processed_dataset"
+    output_stream: "augmented_dataset"
+    module_path: "models_augment/GAN/main.py"
+    module_params: # Model specific parameters, they're passed to the model script as dict
+      noise_level: 0.01
+      model_weights: "models_augment/GAN/model.pth"
+
+  - name: "Save_dataset"
+    input_stream: "augmented_dataset"
+    module_params:
+      output_path: "data/augmented_dataset.mne"