Create config_entity.py

src/entity/config_entity.py

@@ -0,0 +1,75 @@
+
+from datetime import datetime
+import os 
+from src.constants import training_pipeline
+
+print(training_pipeline.PIPELINE_NAME)
+print(training_pipeline.ARTIFACT_DIR)
+
+
+class TrainingPipelineConfig:
+    def __init__(self, timestamp=datetime.now()):
+        timestamp=timestamp.strftime("%m_%d_%Y_%H_%M_%S")
+        self.pipeline_name = training_pipeline.PIPELINE_NAME
+        self.artifact_name = training_pipeline.ARTIFACT_DIR
+        self.artifact_dir = os.path.join(self.artifact_name, timestamp)
+        self.model_dir = os.path.join("final_model")
+        self.timestamp:str=timestamp
+
+
+class DataIngestionConfig:
+    def __init__(self, training_pipeline_config:TrainingPipelineConfig):
+        self.data_ingestion_dir:str = os.path.join(
+            training_pipeline_config.artifact_dir, training_pipeline.DATA_INGESTION_DIR_NAME
+        )
+        self.feature_store_file_path:str = os.path.join(
+            self.data_ingestion_dir, training_pipeline.DATA_INGESTION_FEATURE_STORE_DIR, training_pipeline.FILE_NAME
+        )
+        self.training_file_path:str = os.path.join(
+            self.data_ingestion_dir, training_pipeline.DATA_INGESTION_INGESTED_DIR, training_pipeline.TRAIN_FILE_NAME
+        )
+        self.testing_file_path:str = os.path.join(
+            self.data_ingestion_dir, training_pipeline.DATA_INGESTION_INGESTED_DIR, training_pipeline.TEST_FILE_NAME
+        )
+        self.train_test_split_ratio:float = training_pipeline.DATA_INGESTION_TRAIN_TEST_SPLIT_RATION
+        self.collection_name:str = training_pipeline.DATA_INGESTION_COLLECTION_NAME
+        self.database_name:str = training_pipeline.DATA_INGESTION_DATABASE_NAME
+
+
+class DataValidationConfig:
+    def __init__(self, training_pipeline_config:TrainingPipelineConfig):
+        self.data_validation_dir:str = os.path.join(training_pipeline_config.artifact_dir, training_pipeline.DATA_VALIDATION_DIR_NAME)
+        self.valid_data_dir:str = os.path.join(self.data_validation_dir, training_pipeline.DATA_VALIDATION_VALID_DIR)
+        self.invalid_data_dir:str = os.path.join(self.data_validation_dir, training_pipeline.DATA_VALIDATION_INVALID_DIR)
+        self.valid_train_file_path:str = os.path.join(self.valid_data_dir, training_pipeline.TRAIN_FILE_NAME)
+        self.valid_test_file_path:str = os.path.join(self.valid_data_dir, training_pipeline.TEST_FILE_NAME)
+        self.invalid_train_file_path:str = os.path.join(self.invalid_data_dir, training_pipeline.TRAIN_FILE_NAME)
+        self.invalid_test_file_path:str = os.path.join(self.invalid_data_dir, training_pipeline.TEST_FILE_NAME)
+        self.drift_report_file_path:str = os.path.join(
+            self.data_validation_dir,
+            training_pipeline.DATA_VALIDATION_DRIFT_REPORT_DIR,
+            training_pipeline.DATA_VALIDATION_DRIFT_REPORT_FILE_NAME
+        )
+
+class DataTransformationConfig:
+    def __init__(self, training_pipeline_config:TrainingPipelineConfig):
+        self.data_transformation_dir:str = os.path.join(training_pipeline_config.artifact_dir, training_pipeline.DATA_TRANSFORMATION_DIR_NAME)
+        self.transformed_train_file_path: str=os.path.join(self.data_transformation_dir, training_pipeline.DATA_TRANSFORMATION_TRANSFORMED_DATA_DIR,
+                                                           training_pipeline.TRAIN_FILE_NAME.replace("csv", "npy"))
+        self.transformed_test_file_path: str = os.path.join(self.data_transformation_dir, training_pipeline.DATA_TRANSFORMATION_TRANSFORMED_DATA_DIR,
+                                                            training_pipeline.TEST_FILE_NAME.replace("csv", "npy"))
+        self.transformed_object_file_path:str=os.path.join(self.data_transformation_dir, training_pipeline.DATA_TRANSFORMATION_TRANSFORMED_OBJECT_DIR,
+                                                           training_pipeline.PREPROCESSING_OBJECT_FILE_NAME)
+        
+
+class ModelTrainerConfig:
+    def __init__(self, training_pipeline_config:TrainingPipelineConfig):
+        self.model_trainer_dir:str = os.path.join(
+            training_pipeline_config.artifact_dir, training_pipeline.MODEL_TRAINER_DIR_NAME
+        )
+        self.trained_model_file_path:str = os.path.join(
+            self.model_trainer_dir, training_pipeline.MODEL_TRAINER_TRAINED_MODEL_DIR,
+            training_pipeline.MODEL_FILE_NAME
+        )
+        self.expected_accuracy:float =  training_pipeline.MODEL_TRAINER_EXPECTED_SCORE
+        self.overfitting_underfitting_threshold=training_pipeline.MODEL_TRAINER_OVER_FIITING_UNDER_FITTING_THRESHOLD