End-to-End-Chest-Cancer-Classification-using-Mlflow-DVC/main.py

from cnnClassifier import logger
from cnnClassifier.pipeline.stage_01_data_ingestion import DataIngestionTrainingPipeline
from cnnClassifier.pipeline.stage_02_prepare_base_model import PrepareBaseModelTrainingPipeline
from cnnClassifier.pipeline.stage_03_model_trainer import ModelTrainingPipeline
from cnnClassifier.pipeline.stage_04_model_evaluation import EvaluationPipeline


STAGE_NAME = "Data Ingestion Stage"


try:
    logger.info(f'>>>>>>>> stage {STAGE_NAME}  started <<<<<<<<')
    obj = DataIngestionTrainingPipeline()
    obj.main()
    logger.info(f'>>>>>>>> Stage {STAGE_NAME} completed <<<<<<<<\n\nx=================x')
except Exception as e:
    logger.exception(e)
    raise e


STAGE_NAME = "Prepare Base Model"

try:
    logger.info(f'********************')
    logger.info(f'>>>>>> stage {STAGE_NAME} started <<<<<<')
    obj = PrepareBaseModelTrainingPipeline()
    obj.main()
    logger.info(f'>>>>>> stage {STAGE_NAME} completed <<<<<<\n\nx===================x')
except Exception as e:
    logger.exception(e)
    raise e
        
        
STAGE_NAME = "Training"  

try:
    logger.info(f'****************')
    logger.info(f'>>>>> stage {STAGE_NAME} started <<<<<')
    obj = ModelTrainingPipeline()
    obj.main()
    logger.info(f'>>>>> stage {STAGE_NAME} completed <<<<<\n\nx================x')
except Exception as e:
    logger.exception(e)
    raise e

STAGE_NAME = "Evaluation stage"

try:
    logger.info(f'**********************')
    logger.info(f'>>>>>>>>> stage {STAGE_NAME} started <<<<<<<<<<<')
    obj = EvaluationPipeline()
    obj.main()
    logger.info(f'>>>>>>>>> stage {STAGE_NAME} completed <<<<<<<<<<<\n\nx============x')
except Exception as e:
    logger.exception(e)
    raise e