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main.py
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main.py
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from src.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_mlflow import ModelEvaluationPipeline
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} ended <<<<\n\nx==========x")
except Exception as e:
logger.exception(e)
raise e
stage_name = 'Prepare base model stage'
try:
logger.info(f"*"*19)
logger.info(f">>>> stage: {stage_name} started <<<<")
prepare_base_model = PrepareBaseModelTrainingPipeline()
prepare_base_model.main()
logger.info(f">>>> stage: {stage_name} ended <<<<\n\nx==========x")
except Exception as e:
logger.exception(e)
raise e
stage_name = 'Training'
try:
logger.info(f"*"*19)
logger.info(f">>>> stage: {stage_name} started <<<<")
model_trainer = ModelTrainingPipeline()
model_trainer.main()
logger.info(f">>>> stage: {stage_name} ended <<<<\n\nx==========x")
except Exception as e:
logger.exception(e)
raise e
stage_name = 'Evaluation'
try:
logger.info(f"*"*19)
logger.info(f">>>> stage: {stage_name} started <<<<")
model_evaluation = ModelEvaluationPipeline()
model_evaluation.main()
logger.info(f">>>> stage: {stage_name} ended <<<<\n\nx==========x")
except Exception as e:
logger.exception(e)
raise e