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main.py
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from mlProject import logger
from mlProject.pipeline.stage_01_data_ingestion import DataIngestionTrainingPipeline
from mlProject.pipeline.stage_02_data_validation import DataValidationTrainingPipeline
from mlProject.pipeline.stage_03_data_transformation import DataTransformationTrainingPipeline
from mlProject.pipeline.stage_04_model_trainer import ModelTrainerTrainingPipeline
from mlProject.pipeline.stage_05_model_evaluation import ModelEvaluationTrainingPipeline
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 = 'Data validation stage'
try:
logger.info(f">>>>>>>> Stage : {STAGE_NAME} started <<<<<<<<<")
obj = DataValidationTrainingPipeline()
obj.main()
logger.info(f">>>>>>>> Stage : {STAGE_NAME} completed <<<<<<<<<\n\nx===============x")
except Exception as e:
logger.exception(e)
raise e
STAGE_NAME = 'Data transformation stage'
if __name__ == '__main__':
try:
logger.info(f">>>>>>>> Stage {STAGE_NAME} started <<<<<<<<<")
obj = DataTransformationTrainingPipeline()
obj.main()
logger.info(f">>>>>>>> Stage {STAGE_NAME} completed <<<<<<<<<\n\nx===============x")
except Exception as e:
logger.exception(e)
raise e
STAGE_NAME = "Model Trainer stage"
try:
logger.info(f">>>>>> stage {STAGE_NAME} started <<<<<<")
data_ingestion = ModelTrainerTrainingPipeline()
data_ingestion.main()
logger.info(f">>>>>> stage {STAGE_NAME} completed <<<<<<\n\nx==========x")
except Exception as e:
logger.exception(e)
raise e
STAGE_NAME = "Model evaluation stage"
try:
logger.info(f">>>>>> stage {STAGE_NAME} started <<<<<<")
data_ingestion = ModelEvaluationTrainingPipeline()
data_ingestion.main()
logger.info(f">>>>>> stage {STAGE_NAME} completed <<<<<<\n\nx==========x")
except Exception as e:
logger.exception(e)
raise e