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main.py
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from src.mlProject import logger
from mlProject.pipeline.data_ingestion_pipeline import DataIngestionTrainingPipeline
from mlProject.pipeline.data_validation_pipeline import DataValidationTrainingPipeline
from mlProject.pipeline.data_transformation_pipeline import DataTransformationTrainingPipeline
from mlProject.pipeline.model_trainer_pipeline import ModelTrainingPipeline
from mlProject.pipeline.model_evaluation_pipeline import ModelEvaluationPipeline
logger.info("Welcome to MLOps Project")
STAGE_NAME = "Data Ingestion Stage"
try:
logger.info(f">>>>>> stage {STAGE_NAME} started <<<<<<")
data_ingestion = DataIngestionTrainingPipeline()
data_ingestion.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 <<<<<<")
data_validation = DataValidationTrainingPipeline()
data_validation.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"
try:
logger.info(f">>>>>> stage {STAGE_NAME} started <<<<<<")
data_transformation = DataTransformationTrainingPipeline()
data_transformation.main()
logger.info(f">>>>>> stage {STAGE_NAME} completed <<<<<<\n\nx==========x")
except Exception as e:
logger.exception(e)
raise e
STAGE_NAME = "Model Training Stage"
try:
logger.info(f">>>>>> stage {STAGE_NAME} started <<<<<<")
model_trainer = ModelTrainingPipeline()
model_trainer.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 <<<<<<")
model_evaluation = ModelEvaluationPipeline()
model_evaluation.main()
logger.info(f">>>>>> stage {STAGE_NAME} completed <<<<<<\n\nx==========x")
except Exception as e:
logger.exception(e)
raise e