src/entity/config_entity.py

from dataclasses import dataclass
from src.constants import *
import os
from datetime import datetime
TIMESTAMP: str = datetime.now().strftime("%m_%d_%Y_%H_%M_%S")

@dataclass
class TrainingPipelineConfig:
    pipeline_name: str = PIPELINE_NAME
    artifact_dir: str = os.path.join(ARTIFACT_DIR, TIMESTAMP)
    timestamp: str = TIMESTAMP


training_pipeline_config:TrainingPipelineConfig=TrainingPipelineConfig()
@dataclass
class DataIngestionConfig:
    data_ingestion_dir: str = os.path.join(training_pipeline_config.artifact_dir, DATA_INGESTION_DIR_NAME)
    feature_store_file_path: str = os.path.join(data_ingestion_dir, DATA_INGESTION_FEATURE_STORE_DIR, FILE_NAME)
    training_file_path: str = os.path.join(data_ingestion_dir, DATA_INGESTION_INGESTED_DIR, TRAIN_FILE_NAME)
    testing_file_path: str = os.path.join(data_ingestion_dir, DATA_INGESTION_INGESTED_DIR, TEST_FILE_NAME)
    train_test_split_ratio: float = DATA_INGESTION_TRAIN_TEST_SPLIT_RATIO
    collection_name:str = DATA_INGESTION_COLLECTION_NAME    


@dataclass
class DataValidationConfig:
    data_validation_dir:str=os.path.join(training_pipeline_config.artifact_dir,DATA_VALIDATION_DIR_NAME)
    validation_report_file_path:str=os.path.join(data_validation_dir,DATA_VALIDATION_REPORT_FILE_NAME)


@dataclass
class DataTransformationConfig:
    data_transformation_dir:str=os.path.join(training_pipeline_config.artifact_dir,DATA_TRANSFORMATION_DIR)
    transformed_train_file_path:str=os.path.join(data_transformation_dir,TRANSFORMED_TRAIN_FILE_PATH)
    transformed_test_file_path:str=os.path.join(data_transformation_dir,TRANSFORMED_TEST_FILE_PATH)
    transformed_object_file_path:str=os.path.join(data_transformation_dir,TRANSFORMED_OBJECT_FILE_PATH)


 
@dataclass
class ModelTrainerConfig:
    model_trainer_dir: str = os.path.join(training_pipeline_config.artifact_dir, MODEL_TRAINER_DIR_NAME)
    trained_model_file_path: str = os.path.join(model_trainer_dir, MODEL_TRAINER_TRAINED_MODEL_DIR, MODEL_FILE_NAME)
    expected_accuracy: float = MODEL_TRAINER_EXPECTED_SCORE
    model_config_file_path: str = MODEL_TRAINER_MODEL_CONFIG_FILE_PATH
    n_estimators = MODEL_TRAINER_N_ESTIMATORS
    min_samples_split = MODEL_TRAINER_MIN_SAMPLES_SPLIT
    min_samples_leaf = MODEL_TRAINER_MIN_SAMPLES_LEAF
    max_depth = MIN_SAMPLES_SPLIT_MAX_DEPTH
    criterion = MIN_SAMPLES_SPLIT_CRITERION
    random_state = MIN_SAMPLES_SPLIT_RANDOM_STATE