MLOPS-Network-Security-System/main.py at main · Phantom-VK/MLOPS-Network-Security-System · GitHub

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import logging
import sys

from networksecurity.components.data_ingestion import DataIngestion
from networksecurity.components.data_transformation import DataTransformation
from networksecurity.components.data_validation import DataValidation
from networksecurity.components.model_trainer import ModelTrainer
from networksecurity.exception.exception import NetworkSecurityException
from networksecurity.entity.config_entity import DataIngestionConfig, TrainingPipelineConfig, DataValidationConfig, \
    DataTransformationConfig, ModelTrainerConfig
from networksecurity.pipeline.training_pipeline import TrainingPipeline

if __name__ == "__main__":
    try:
        # training_pipeline_config = TrainingPipelineConfig()
        # di_config = DataIngestionConfig(training_pipeline_config)
        # di = DataIngestion(di_config)
        # logging.info("Initiating the data ingestion")
        # di_artifact = di.initiate_data_ingestion()
        #
        # dv_config = DataValidationConfig(training_pipeline_config)
        # dv = DataValidation(data_ingestion_artifact=di_artifact, data_validation_config=dv_config)
        # logging.info("Initiating the data validation")
        # dv_artifact = dv.initiate_data_validation()
        # print(dv_artifact)
        #
        # dt_config = DataTransformationConfig(training_pipeline_config)
        # dt = DataTransformation(data_transformation_config=dt_config, data_validation_artifact=dv_artifact)
        # logging.info("Initiated data transformation")
        # dt_artifact = dt.initiate_data_transformation()
        # print(dt_artifact)
        #
        # mt_config = ModelTrainerConfig(training_pipeline_config)
        # mt = ModelTrainer(model_trainer_config=mt_config, data_transformation_artifact=dt_artifact)
        # logging.info("Initiated model training")
        # mt_artifact = mt.initiate_model_trainer()
        # print(mt_artifact)

        training_pipeline = TrainingPipeline()
        training_pipeline.run_pipeline()
    except Exception as e:
        raise NetworkSecurityException(e, sys)