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main.py
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main.py
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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_training import ModelTrainingPipeline
from cnnClassifier.pipeline.stage_04_model_evaluation import EvaluationPipeline
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 = "Prepare base model"
try:
logger.info(f"*******************")
logger.info(f">>>>>> stage {STAGE_NAME} started <<<<<<")
prepare_base_model = PrepareBaseModelTrainingPipeline()
prepare_base_model.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 <<<<<<")
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 = "Evaluation stage"
try:
logger.info(f"*******************")
logger.info(f">>>>>> stage {STAGE_NAME} started <<<<<<")
model_evalution = EvaluationPipeline()
model_evalution.main()
logger.info(f">>>>>> stage {STAGE_NAME} completed <<<<<<\n\nx==========x")
except Exception as e:
logger.exception(e)
raise e