from src.components.data_ingestion import DataIngestion from src.components.data_validation import DataValidation from src.components.data_transformation import DataTransformation from src.components.model_trainer import ModelTrainer from src.exception.exception import CustomException from src.logging.logger import logging from src.entity.config_entity import DataIngestionConfig , DataValidationConfig , DataTransformationConfig ,ModelTrainerConfig from src.entity.config_entity import TrainingPipelineConfig import sys if __name__=='__main__': try: trainingpipelineconfig=TrainingPipelineConfig() dataingestionconfig=DataIngestionConfig(trainingpipelineconfig) data_ingestion=DataIngestion(dataingestionconfig) logging.info("Initiate the data ingestion") dataingestionartifact=data_ingestion.initiate_data_ingestion() logging.info("Data Initiation Completed") print(dataingestionartifact) data_validation_config=DataValidationConfig(trainingpipelineconfig) data_validation=DataValidation(dataingestionartifact,data_validation_config) logging.info("Initiate the data Validation") data_validation_artifact=data_validation.initiate_data_validation() logging.info("data Validation Completed") print(data_validation_artifact) data_transformation_config=DataTransformationConfig(trainingpipelineconfig) logging.info("data Transformation started") data_transformation=DataTransformation(data_validation_artifact,data_transformation_config) data_transformation_artifact=data_transformation.initiate_data_transformation() print(data_transformation_artifact) logging.info("data Transformation completed") logging.info("Model Training sstared") model_trainer_config=ModelTrainerConfig(trainingpipelineconfig) model_trainer=ModelTrainer(model_trainer_config=model_trainer_config,data_transformation_artifact=data_transformation_artifact) model_trainer_artifact=model_trainer.initiate_model_trainer() # logging.info("Model Training artifact created") except Exception as e: raise CustomException(e,sys)