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from src.logger import logging |
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from src.exception import CropException |
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from src.utils import get_collection_as_dataframe |
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from src.entity import config_entity |
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from src.entity import artifact_entity |
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import sys |
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from src.components.data_ingestion import DataIngestion |
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from src.components.data_validation import DataValidation |
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from src.components.data_trasformation import DataTransformation |
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from src.components.model_trainer import ModelTrainer |
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from src.components.model_evaluation import ModelEvaluation |
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from src.components.model_pusher import ModelPusher |
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def start_training_pipeline(): |
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try: |
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training_pipeline_config = config_entity.TrainingPipelineConfig() |
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data_ingestion_config = config_entity.DataIngestionConfig( |
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training_pipeline_config=training_pipeline_config |
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) |
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data_ingestion_config.to_dict() |
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data_ingestion = DataIngestion(data_ingestion_config=data_ingestion_config) |
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data_ingestion_artifact = data_ingestion.initiate_data_ingestion() |
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print(f"Data Ingestion complete") |
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data_validation_config = config_entity.DataValidationConfig( |
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training_pipeline_config=training_pipeline_config |
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) |
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data_validation = DataValidation( |
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data_validation_config=data_validation_config, |
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data_ingestion_artifact=data_ingestion_artifact, |
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) |
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data_validation.initiate_data_validation() |
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print(f"Data Validation Complete") |
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data_transformation_config = config_entity.DataTransformationConfig( |
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training_pipeline_config=training_pipeline_config |
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) |
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data_transformation = DataTransformation( |
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data_transformation_config=data_transformation_config, |
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data_ingestion_artifact=data_ingestion_artifact, |
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) |
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data_transformation_artifact = ( |
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data_transformation.initiate_data_transformation() |
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) |
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print(f"Data Transformation Complete") |
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model_trainer_config = config_entity.ModelTrainerConfig( |
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training_pipeline_config=training_pipeline_config |
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) |
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model_trainer = ModelTrainer( |
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model_trainer_config=model_trainer_config, |
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data_transformation_artifact=data_transformation_artifact, |
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) |
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model_trainer_artifact = model_trainer.initiate_model_trainer() |
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print(f"Model Training Complete") |
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model_eval_config = config_entity.ModelEvaluationConfig( |
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training_pipeline_config=training_pipeline_config |
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) |
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model_eval = ModelEvaluation( |
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model_eval_config=model_eval_config, |
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data_ingesiton_artifact=data_ingestion_artifact, |
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data_transformation_artifact=data_transformation_artifact, |
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model_trainer_artifact=model_trainer_artifact, |
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) |
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model_eval_artifact = model_eval.initiate_model_evaluation() |
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print(f"Model Evaluation Complete") |
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model_pusher_config = config_entity.ModelPusherConfig(training_pipeline_config=training_pipeline_config) |
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model_pusher = ModelPusher(model_pusher_config=model_pusher_config, |
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data_transformation_artifact=data_transformation_config, |
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model_trainer_artifact=model_trainer_artifact) |
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model_pusher_artifact = model_pusher.initiate_model_pusher() |
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print(f"Model Pusher Complete") |
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except Exception as e: |
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print(e) |
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