LCjQdZddlZddlZddlmZmZddlmZddlmZejejdde d ejfd Z d ed e d ee efdee deded dfdZdded e ded dfdZy)u Shared training utilities. Common helpers used across all training scripts in this directory — kept here once rather than copy-pasted six times, so a fix (e.g. to how model metadata is saved) only needs to happen in one place. N)datetimetimezone)Path)Anyz%%(asctime)s %(levelname)s %(message)s)levelformatnamereturnc,tj|S)N)logging getLogger)r s PC:\Crop_Prediction\Backend\crop-ai-system\ml_pipeline\training\training_utils.py get_loggerrs   T "" output_dir model_namemetrics feature_colsn_trainn_testc|tjtjj ||||d}||dz }t |dd5}t j||dtdddy#1swYyxYw) u Writes a metadata JSON alongside every .pkl artifact — this is what lets you (or the client) audit exactly when a model was trained, on how much data, and what its validation metrics were, without having to re-run training or dig through terminal scrollback. )rtrained_at_utcn_train_samplesn_test_samplesfeature_columnsrz_metadata.jsonwzutf-8)encoding)indentdefaultN) rnowrutc isoformatopenjsondumpstr) rrrrrrmetadata metadata_pathfs rsave_training_metadatar+s{!",,x||4>>@" ' HJ<~!>>M mS7 36q (Aa5666s A66A?df_lenminimumc 8||krtd|d|d|dy)NzOnly z! samples available for training 'z', minimum required is u. Training on fewer samples than this produces unreliable models — collect more data or lower this threshold deliberately (not silently).) ValueError)r,rr-s rcheck_minimum_samplesr01s? F8r<s '',,/VW#S#W^^#666#s(^6s) 6  6  6 66 # 3  t r