hFSrSSKJrJrJrJrJrJrJr SSK J r SSK r SSK r SSK JrJr SSKJr SSKJrJrJr SS KJrJr SSSS S\"5S4S \\S \\S \\S\S\\\\4S\\S\\\S\4SjjrSSSS S\"54S \\S \\S \\S\S\\\\4S\\S\4SjjrS\ 4SjrSSSS S\"54S\ S\S \\S \\S \\S\S\\\\4S\\4SjjrS\ S\\\\44SjrS\ 4SjrS\ S\\\\4S\\/\44Sjr g)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  ^^^^^^^^[5m[R[R4S[S[ S[ S[ [[[[4/S4[/S444UUUUUUUU4SjjjnU$)aUCreates a logger that interoperates with the MLflow framework. Args: run_id (Optional[str]): Unique ID of an existing MLflow run to which parameters and metrics are logged. Can be omitted if `experiment_id` and `run_id` are provided. Defaults to None. experiment_id (Optional[str]): ID of an existing experiment under which to create the current run. Only applicable when `run_id` is `None`. Defaults to None. run_name (Optional[str]): Name of new run. Only applicable when `run_id` is `None`. Defaults to None. nested (bool): Controls whether run is nested in parent run. `True` creates a nested run. Defaults to False. tags (Optional[Dict[str, Any]]): A dictionary of string keys and values to set as tags on the run. If a run is being resumed, these tags are set on the resumed run. If a new run is being created, these tags are set on the new run. Defaults to None. remove_config_values (List[str]): A list of values to exclude from the config before it is uploaded to MLflow. Defaults to an empty list. log_custom_stats (Optional[List[str]]): A list of regular expressions that will be applied to the info dictionary passed to the logger. Statistics and metrics that match these regexps will be automatically logged. Defaults to None. Returns: LoggerT: Logger instance. nlpstdoutstderrrNc >^[T5m[TUT TT T T T 5 S[[[[ 44UU4SjjnSU4SjjnX44$)Ninfoc8>[TU5 [TUT5 gN)_log_step_mlflow_log_custom_stats)r! match_statmlflows N/home/james-whalen/.local/lib/python3.13/site-packages/spacy_loggers/mlflow.pylog_step8mlflow_logger_v2..setup_logger..log_step@s VT * fdJ 7c>[T5 gr#_finalize_mlflowr'sr(finalize8mlflow_logger_v2..setup_logger..finalizeDs V $r+rN)r _setup_mlflowrrstrr)rrrr)r0r&rrr'rrrrrs @r( setup_logger&mlflow_logger_v2..setup_logger1s^00@A           88DcN3 8 8 %!!r+ _import_mlflowsysrrr r rrrr4r) rrrrrrrr5r's ``````` @r(mlflow_logger_v2r:sv< F%(JJSZZ" "!"8:" xc3h($./"d(1CC D""0 r+c ^^^^^^^[5m[R[R4S[S[ S[ S[ [[[[4/S4[/S444UUUUUUU4SjjjnU$)aaCreates a logger that interoperates with the MLflow framework. Args: run_id (Optional[str]): Unique ID of an existing MLflow run to which parameters and metrics are logged. Can be omitted if `experiment_id` and `run_id` are provided. Defaults to None. experiment_id (Optional[str]): ID of an existing experiment under which to create the current run. Only applicable when `run_id` is `None`. Defaults to None. run_name (Optional[str]): Name of new run. Only applicable when `run_id` is `None`. Defaults to None. nested (bool): Controls whether run is nested in parent run. `True` creates a nested run. Defaults to False. tags (Optional[Dict[str, Any]]): A dictionary of string keys and values to set as tags on the run. If a run is being resumed, these tags are set on the resumed run. If a new run is being created, these tags are set on the new run. Defaults to None. remove_config_values (List[str]): A list of values to exclude from the config before it is uploaded to MLflow. Defaults to an empty list. Returns: LoggerT: Logger instance. rrrrNc >^^[XU5umm[TUT TT T T T 5 S[[[[ 44UU4SjjnSUU4SjjnX44$)Nr!c.>T"U5 [TU5 gr#)r$)r!console_log_stepr's r(r)8mlflow_logger_v1..setup_logger..log_step{s T " VT *r+c*>T"5 [T5 gr#r-)console_finalizer'sr(r08mlflow_logger_v1..setup_logger..finalizes   V $r+r2)rr3rrr4r)rrrr)r0rAr>rr'rrrrrs @@r(r5&mlflow_logger_v1..setup_loggerjsq.J . **           +8DcN3 + + % %!!r+r7)rrrrrrr5r's`````` @r(mlflow_logger_v1rDMsv6 F%(JJSZZ" "!"8:" xc3h($./"d(1CC D""6 r+c^SSKnSSKJnJnJnJnJn U$![ a [ S5ef=f)Nr) start_run log_metric log_metrics log_artifactend_runzThe 'mlflow' library could not be found - did you install it? Alternatively, specify the 'ConsoleLogger' in the 'training.logger' config section, instead of the 'MLflowLogger'.)r'rFrGrHrIrJ ImportError)r'rFrGrHrIrJs r(r8r8s?    M   O   s,r'rc URR5n[U5n UHn X M [U 5nUR UUUUUS9 [ U R 55n [S[U 5S5V s/sH oXS-PM n n U H;nURUVVs0sHunnURSS5U_M snn5 M= gs sn fs snnf)N)rrrrrrd@) config interpolaterrrFlistitemsrangelen log_paramsreplace)r'rrrrrrrrP config_dotfieldconfig_dot_itemsiconfig_dot_batchesbatchkvs r(r3r3sZZ # # %FV$J%  &  $F #  J,,.//4QU[US5S:Xa([U5nURRUS5 gggs snnfs snnf) Nscore other_scoreslosses output_pathloss_ checkpointsrbest) getrGrHrS isinstancedictrfloatintmaxr spacy log_model) r'r!rarbrcrdr^r_rs r(r$r$s- | ME'L (^F((=$/K '5) v||~F~tqeA3KN~FG,%%( 5;;= =DAa'':a+==  uD$7 8 ;;; sF+<{G s D> 60E *E c$UR5 gr#)rJr/s r(r.r.s NNr+matchercUbVUR5VVs0sHup4U"U5(dMX4_M nnn[U5(aURU5 gggs snnfr#)rSrUrH)r'r!rqr^r_matcheds r(r%r%sT $(JJL?LDAGAJ414L? w<<   w ' ?s AA)!__doc__typingrrrrrrr typesr osr9rnr r spacy.utilr utilrrrrrr4boolr:rDr8r3r$r.r%r+r(r|s<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+