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51f7cb3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 | from src.entity.artifact_entity import RunTrainingArtifact
from src.constants import FINAL_MODEL_FILE_PATH,FINAL_MODEL_PERFORMANCE_PATH,RUN_TRAINING_DIR_NAME,TRANSFORMED_OBJECT_FILE_PATH
from src.utils.main_utils import load_object,save_object,read_yaml_file,write_yaml_file
import logging
from src.exception import MyException
import sys
import os
class ModelEvaluation:
def __init__(self):
pass
async def init_config(self,run_train_artifact:RunTrainingArtifact):
self.run_train_artifact=run_train_artifact
async def check_validation(self,per_yaml,to_yaml)->bool:
if per_yaml['model_trained_artifact']['metric_artifact']['r2_score']>=to_yaml.model_trained_artifact.metric_artifact.r2_score:
return False
return True
async def save_model(self):
try:
model=await load_object(file_path=self.run_train_artifact.model_trained_artifact.trained_model_file_path)
# Check if existing model exists before loading
if not os.path.exists(FINAL_MODEL_FILE_PATH):
logging.info(f"Existing model not found at {FINAL_MODEL_FILE_PATH}. Saving first model.")
await save_object(file_path=FINAL_MODEL_FILE_PATH,obj=model)
obj=await load_object(file_path=self.run_train_artifact.data_transformed_artifact.transformed_object_file_path)
await save_object(file_path=os.path.join(RUN_TRAINING_DIR_NAME,TRANSFORMED_OBJECT_FILE_PATH),obj=obj)
# Also save the performance yaml for first run
await write_yaml_file(file_path=FINAL_MODEL_PERFORMANCE_PATH,content=self.run_train_artifact)
return
saved_model=await load_object(file_path=FINAL_MODEL_FILE_PATH)
if not saved_model:
await save_object(file_path=FINAL_MODEL_FILE_PATH,obj=model)
obj=await load_object(file_path=self.run_train_artifact.data_transformed_artifact.transformed_object_file_path)
await save_object(file_path=os.path.join(RUN_TRAINING_DIR_NAME,TRANSFORMED_OBJECT_FILE_PATH),obj=obj)
else:
per_yaml=await read_yaml_file(file_path=FINAL_MODEL_PERFORMANCE_PATH)
is_ok=await self.check_validation(per_yaml=per_yaml,to_yaml=self.run_train_artifact)
if is_ok:
# saving new model
await write_yaml_file(file_path=FINAL_MODEL_PERFORMANCE_PATH,content=self.run_train_artifact)
await save_object(file_path=FINAL_MODEL_FILE_PATH,obj=model)
obj=await load_object(file_path=self.run_train_artifact.data_transformed_artifact.transformed_object_file_path)
await save_object(file_path=os.path.join(RUN_TRAINING_DIR_NAME,TRANSFORMED_OBJECT_FILE_PATH),obj=obj)
except Exception as e:
raise MyException(e,sys)
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