j2dZddlmZmZmZmZmZmZmZddl m Z ddl Z ddl Z ddl mZmZddlmZddlmZmZmZdd lmZmZdddd dedfd eed eed eededeeeefdeedeeedefdZdddd defd eed eed eededeeeefdeedefdZde fdZdddd defde ded eed eed eededeeeefdeefdZde deeeeffdZde fdZde deeeefdeegeffdZ y)z1 A logger that logs training activity to MLflow. )DictAnyTupleCallableListOptionalIO) ModuleTypeN)Languageload)SimpleFrozenList) dict_to_dot dot_to_dictmatcher_for_regex_patterns)setup_default_console_loggerLoggerTFrun_id experiment_idrun_namenestedtagsremove_config_valueslog_custom_statsreturnc ttjtjfdtdt dt dt ttttfgdftgdffffd }|S)aCreates a logger that interoperates with the MLflow framework. Args: run_id (Optional[str]): Unique ID of an existing MLflow run to which parameters and metrics are logged. Can be omitted if `experiment_id` and `run_id` are provided. Defaults to None. experiment_id (Optional[str]): ID of an existing experiment under which to create the current run. Only applicable when `run_id` is `None`. Defaults to None. run_name (Optional[str]): Name of new run. Only applicable when `run_id` is `None`. Defaults to None. nested (bool): Controls whether run is nested in parent run. `True` creates a nested run. Defaults to False. tags (Optional[Dict[str, Any]]): A dictionary of string keys and values to set as tags on the run. If a run is being resumed, these tags are set on the resumed run. If a new run is being created, these tags are set on the new run. Defaults to None. remove_config_values (List[str]): A list of values to exclude from the config before it is uploaded to MLflow. Defaults to an empty list. log_custom_stats (Optional[List[str]]): A list of regular expressions that will be applied to the info dictionary passed to the logger. Statistics and metrics that match these regexps will be automatically logged. Defaults to None. Returns: LoggerT: Logger instance. nlpstdoutstderrrNc tt|  dtttt fffd }dfd }||fS)Ninfoc8t|t|yN)_log_step_mlflow_log_custom_stats)r! match_statmlflows ^/home/spazio/kingdom_calls/work5/transenv/lib/python3.12/site-packages/spacy_loggers/mlflow.pylog_stepz8mlflow_logger_v2..setup_logger..log_step@s VT * fdJ 7ctyr#_finalize_mlflowr'sr(finalizez8mlflow_logger_v2..setup_logger..finalizeDs V $r*rN)r _setup_mlflowrrstrr)rrrr)r/r&rrr'rrrrrs @r( setup_loggerz&mlflow_logger_v2..setup_logger1s[00@A           88DcN3 8 %!!r* _import_mlflowsysrrr r rrrr2r) rrrrrrrr3r's ``````` @r(mlflow_logger_v2r7sv< F%(JJSZZ" "!"8:" xc3h($./"d(1CC D""0 r*c ttjtjfdtdt dt dt ttttfgdftgdffffd }|S)aCreates a logger that interoperates with the MLflow framework. Args: run_id (Optional[str]): Unique ID of an existing MLflow run to which parameters and metrics are logged. Can be omitted if `experiment_id` and `run_id` are provided. Defaults to None. experiment_id (Optional[str]): ID of an existing experiment under which to create the current run. Only applicable when `run_id` is `None`. Defaults to None. run_name (Optional[str]): Name of new run. Only applicable when `run_id` is `None`. Defaults to None. nested (bool): Controls whether run is nested in parent run. `True` creates a nested run. Defaults to False. tags (Optional[Dict[str, Any]]): A dictionary of string keys and values to set as tags on the run. If a run is being resumed, these tags are set on the resumed run. If a new run is being created, these tags are set on the new run. Defaults to None. remove_config_values (List[str]): A list of values to exclude from the config before it is uploaded to MLflow. Defaults to an empty list. Returns: LoggerT: Logger instance. rrrrNc t|||\t|  dtttt fffd }dfd }||fS)Nr!c.|t|yr#)r$)r!console_log_stepr's r(r)z8mlflow_logger_v1..setup_logger..log_step{s T " VT *r*c*tyr#r,)console_finalizer'sr(r/z8mlflow_logger_v1..setup_logger..finalizes   V $r*r0)rr1rrr2r)rrrr)r/r=r;rr'rrrrrs @@r(r3z&mlflow_logger_v1..setup_loggerjsk.J . **           +8DcN3 + %!!r*r4)rrrrrrr3r's`````` @r(mlflow_logger_v1r>Msv6 F%(JJSZZ" "!"8:" xc3h($./"d(1CC D""6 r*c\ ddl}ddlm}m}m}m}m}|S#t $r t dwxYw)Nr) start_run log_metric log_metrics log_artifactend_runzThe 'mlflow' library could not be found - did you install it? Alternatively, specify the 'ConsoleLogger' in the 'training.logger' config section, instead of the 'MLflowLogger'.)r'r@rArBrCrD ImportError)r'r@rArBrCrDs r(r5r5s?    M   O   s+r'rc |jj}t|} |D]} | | =t| }|j |||||t | j } tdt| dD cgc] } | | | dz } } | D]7}|j|Dcic]\}}|jdd|c}}9ycc} wcc}}w)N)rrrrrrd@) config interpolaterrr@listitemsrangelen log_paramsreplace)r'rrrrrrrrJ config_dotfieldconfig_dot_itemsiconfig_dot_batchesbatchkvs r(r1r1sZZ # # %FV$J% u   $F #  J,,.//4Qr5r1r$r-r%r*r(rvs<BAA 'FF7 !#'"%)&6&8,08 SM8C=8sm8  8 4S> " 8 s) 8tCy)8 8z!#'"%)&6&8 8 SM8C=8sm8  8 4S> " 8 s) 8 8v 0!#'"%)&6&8E E E SMEC= E sm E  E 4S> "Es)E@, , 4S> ",8  ( (&tCH~6(AI3%QU+AV(r*