main.py

from speechRecognition import logger
from speechRecognition.pipeline.stage_01_data_ingestion import DataIngestionTrainingPipeline
from speechRecognition.pipeline.stage_02_prepare_base_model import PrepareBaseModelTrainingPipeline
from speechRecognition.pipeline.stage_03_model_trainer import ModelTrainingPipeline


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