logicsame
new file: dvc.yaml
82c8d9a
raw
history blame
1.69 kB
from benglasummarization.logging import logger
from benglasummarization.pipeline.stage01_data_ingestion import DataIngestionPipeline
from benglasummarization.pipeline.stage_02_prepare_ben_tok import BenTokenizationPreparePipeLine
from benglasummarization.pipeline.stage_03_train_ban_token import TrainTokenizePipeLine
from benglasummarization.pipeline.stage_04_model_Training import ModelTrainingPipeline
STAGE_NAME = 'Data Ingestion Stage'
try:
logger.info(f">>>>>> stage {STAGE_NAME} started <<<<<<")
data_ingestion = DataIngestionPipeline()
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 Ban Tokeniation Stage'
try:
logger.info(f">>>>>> stage {STAGE_NAME} started <<<<<<")
Ban_Token = BenTokenizationPreparePipeLine()
Ban_Token.main()
logger.info(f">>>>>> stage {STAGE_NAME} completed <<<<<<\n\nx==========x")
except Exception as e:
logger.exception(e)
raise e
STAGE_NAME = 'Training Bengla Tokenization Stage'
try:
logger.info(f">>>>>> stage {STAGE_NAME} started <<<<<<")
Train_Ban_Token = TrainTokenizePipeLine()
Train_Ban_Token.main()
logger.info(f">>>>>> stage {STAGE_NAME} completed <<<<<<\n\nx==========x")
except Exception as e:
logger.exception(e)
raise e
STAGE_NAME = 'Model Training PipeLine Stage'
try:
logger.info(f">>>>>> stage {STAGE_NAME} started <<<<<<")
train_model = ModelTrainingPipeline()
train_model.main()
logger.info(f">>>>>> stage {STAGE_NAME} completed <<<<<<\n\nx==========x")
except Exception as e:
logger.exception(e)
raise e