h>`SrSSKJrJrJrJrJrJrJr SSK J r SSK r SSK J r SSKJr SSKJrJrJr SS KJrJr \"5SSSSSSS4S \S \\S \\S \\S\\S\\S\\S\\S\\\S\4Sjjr\"5SSSSSS4S \S \\S \\S \\S\\S\\S\\S\\S\4Sjjr\"5SSSS4S \S \\S \\S \\S\\S\\S\4Sjjr\"5SS4S \S \\S \\S \\S\4 Sjjr\"54S \S \\S\4SjjrS\ 4SjrS\"54S\ SSS\S\\S \\S\4 SjjrS\ S\\\\44S jrS+S\ S\\\\4S!\S \\4S"jjr S,S\ S#\S$\S%\S&\\\\4S'\\\4 S(jjr!S\ S\\\\4S)\\/\"44S*jr#g)-z= A logger that logs training activity to Weights and Biases. )DictAnyTupleCallableListIOOptional) ModuleTypeN)Language)SimpleFrozenList) dict_to_dot dot_to_dictmatcher_for_regex_patterns)setup_default_console_loggerLoggerT project_nameremove_config_valuesmodel_log_intervallog_dataset_direntityrun_name log_best_dirlog_latest_dirlog_custom_statsreturnc  ^^^^^^^^^^ [5m [R[R4SSS[S[S[ [ [[[4/S4[ /S444UUUUUUUUUU 4 Sjjjn U $)aCreates a logger that interoperates with the Weights & Biases framework. Args: project_name (str): The name of the project in the Weights & Biases interface. The project will be created automatically if it doesn't exist yet. remove_config_values (List[str]): A list of values to exclude from the config before it is uploaded to W&B. Defaults to []. model_log_interval (Optional[int]): Steps to wait between logging model checkpoints to the W&B dasboard. Defaults to None. log_dataset_dir (Optional[str]): Directory containing the dataset to be logged and versioned as a W&B artifact. Defaults to None. entity (Optional[str]): An entity is a username or team name where you're sending runs. If you don't specify an entity, the run will be sent to your default entity, which is usually your username. Defaults to None. run_name (Optional[str]): The name of the run. If you don't specify a run name, the name will be created by the `wandb` library. Defaults to None. log_best_dir (Optional[str]): Directory containing the best trained model as saved by spaCy, to be logged and versioned as a W&B artifact. Defaults to None. log_latest_dir (Optional[str]): Directory containing the latest trained model as saved by spaCy, to be logged and versioned as a W&B artifact. Defaults to None. log_custom_stats (Optional[List[str]]): A list of regular expressions that will be applied to the info dictionary passed to the logger. Statistics and metrics that match these regexps will be automatically logged. Defaults to None. Returns: LoggerT: Logger instance. nlpr stdoutstderrrNc> ^^[T 5m[TUT TTS9mT(aTTRlT (a [ TT SSS9 S[ [ [[44UU UU4SjjnSUU U4SjjnX44$)NrrdatasetpathnametypeinfocT>[TU5 [TUTT5 [TUT5 gN) _log_scores_log_model_artifact_log_custom_stats)r( match_statrrunwandbs M/home/james-whalen/.local/lib/python3.13/site-packages/spacy_loggers/wandb.pylog_step7wandb_logger_v5..setup_logger..log_stepJs( t $ tS2D E eT: 6cr>T(a [TTSSS9 T(a [TTSSS9 TR5 gN model_bestmodelr$ model_last_log_dir_artifactjoin)rrr0sr1finalize7wandb_logger_v5..setup_logger..finalizeOs>!%% !'%  JJLr4rN) r _setup_wandbr/r&r;r rstrr)rrr r2r=r.r/rrrrrrrrrr0s @@r1 setup_logger%wandb_logger_v5..setup_logger7s00@A    !5   %EIIN  O))  78DcN3 7 7   $!!r4 _import_wandbsysrr rrrrrAr) rrrrrrrrrrBr0s ````````` @r1wandb_logger_v5rGs}H OE'*jjszz*" *"!#*":<*" xc3h($./"d(1CC D*"*"*"X r4c ^^^^^^^^^ [5m [R[R4SSS[S[S[ [ [[[4/S4[ /S444UUUUUUUUU 4 SjjjnU$)aCreates a logger that interoperates with the Weights & Biases framework. Args: project_name (str): The name of the project in the Weights & Biases interface. The project will be created automatically if it doesn't exist yet. remove_config_values (List[str]): A list of values to exclude from the config before it is uploaded to W&B. Defaults to []. model_log_interval (Optional[int]): Steps to wait between logging model checkpoints to the W&B dasboard. Defaults to None. log_dataset_dir (Optional[str]): Directory containing the dataset to be logged and versioned as a W&B artifact. Defaults to None. entity (Optional[str]): An entity is a username or team name where you're sending runs. If you don't specify an entity, the run will be sent to your default entity, which is usually your username. Defaults to None. run_name (Optional[str]): The name of the run. If you don't specify a run name, the name will be created by the `wandb` library. Defaults to None. log_best_dir (Optional[str]): Directory containing the best trained model as saved by spaCy, to be logged and versioned as a W&B artifact. Defaults to None. log_latest_dir (Optional[str]): Directory containing the latest trained model as saved by spaCy, to be logged and versioned as a W&B artifact. Defaults to None. Returns: LoggerT: Logger instance. rr rr rNc> ^^^[XU5umm[TUT TTS9mT(aTTRlT (a [ TT SSS9 S[ [ [[44UU UU4SjjnSUU U U4SjjnX44$)Nr"r#r$r(cJ>T"U5 [TU5 [TUTT5 gr*r+r,r(console_log_steprr/r0s r1r27wandb_logger_v4..setup_logger..log_step$ T " t $ tS2D Er4c>T(a [TTSSS9 T(a [TTSSS9 T"5 TR5 gr6r:)console_finalizerrr0sr1r=7wandb_logger_v4..setup_logger..finalizesD!%% !'%    JJLr4r? rr@r/r&r;r rrAr)rrr r2r=rQrMr/rrrrrrrrr0s @@@r1rB%wandb_logger_v4..setup_loggers.J . **   !5   %EIIN  O))  F8DcN3 F F   &!!r4rD) rrrrrrrrrBr0s ```````` @r1wandb_logger_v4rUgs}B OE'*jjszz-" -"!#-":<-" xc3h($./"d(1CC D-"-"-"^ r4c ^^^^^^^[5m[R[R4SSS[S[S[ [ [[[4/S4[ /S444UUUUUUU4SjjjnU$)a5Creates a logger that interoperates with the Weights & Biases framework. Args: project_name (str): The name of the project in the Weights & Biases interface. The project will be created automatically if it doesn't exist yet. remove_config_values (List[str]): A list of values to exclude from the config before it is uploaded to W&B. Defaults to []. model_log_interval (Optional[int]): Steps to wait between logging model checkpoints to the W&B dasboard. Defaults to None. log_dataset_dir (Optional[str]): Directory containing the dataset to be logged and versioned as a W&B artifact. Defaults to None. entity (Optional[str]): An entity is a username or team name where you're sending runs. If you don't specify an entity, the run will be sent to your default entity, which is usually your username. Defaults to None. run_name (Optional[str]): The name of the run. If you don't specify a run name, the name will be created by the `wandb` library. Defaults to None. Returns: LoggerT: Logger instance. rr rr rNc>^^^[XU5umm[TUT T TS9mT (aT TRlT (a [ TT SSS9 S[ [ [[44UU UU4SjjnSUU4SjjnX44$)Nr"r#r$r(cJ>T"U5 [TU5 [TUTT5 gr*rKrLs r1r27wandb_logger_v3..setup_logger..log_steprOr4c4>T"5 TR5 gr*r<rQr0sr1r=7wandb_logger_v3..setup_logger..finalize   JJLr4r?rS)rrr r2r=rQrMr/rrrrrrr0s @@@r1rB%wandb_logger_v3..setup_loggers.J . **   !5   %EIIN  O))  F8DcN3 F F   !!r4rD)rrrrrrrBr0s`````` @r1wandb_logger_v3r`sv6 OE'*jjszz" "!#":<" xc3h($./"d(1CC D""@ r4c ^^^^^[5m[R[R4SSS[S[S[ [ [[[4/S4[ /S444UUUUU4SjjjnU$)aCreates a logger that interoperates with the Weights & Biases framework. Args: project_name (str): The name of the project in the Weights & Biases interface. The project will be created automatically if it doesn't exist yet. remove_config_values (List[str]): A list of values to exclude from the config before it is uploaded to W&B. Defaults to []. model_log_interval (Optional[int]): Steps to wait between logging model checkpoints to the W&B dasboard. Defaults to None. log_dataset_dir (Optional[str]): Directory containing the dataset to be logged and versioned as a W&B artifact. Defaults to None. Returns: LoggerT: Logger instance. rr rr rNc>^^^[XU5umm[T UT T S9mT(a [T TSSS9 S[[[ [ 44UU UU 4SjjnSUU 4SjjnX44$)Nrr#r$r(cJ>T"U5 [TU5 [TUTT5 gr*rKrLs r1r27wandb_logger_v2..setup_logger..log_step$rOr4c4>T"5 TR5 gr*r[r\sr1r=7wandb_logger_v2..setup_logger..finalize)r^r4r?)rr@r;r rrAr) rrr r2r=rQrMr/rrrrr0s @@@r1rB%wandb_logger_v2..setup_loggers~.J . ** 3 ;O   O))  F8DcN3 F F   !!r4rD)rrrrrBr0s```` @r1wandb_logger_v2risu* OE'*jjszz" "!#":<" xc3h($./"d(1CC D""4 r4c ^^^[5m[R[R4SSS[S[S[ [ [[[4/S4[ /S444UUU4SjjjnU$)aCreates a logger that interoperates with the Weights & Biases framework. Args: project_name (str): The name of the project in the Weights & Biases interface. The project will be created automatically if it doesn't exist yet. remove_config_values (List[str]): A list of values to exclude from the config before it is uploaded to W&B. Defaults to []. Returns: LoggerT: Logger instance. rr rr rNc>^^[XU5umm[T UTTS9 S[[[[ 44UU 4SjjnSUU 4SjjnX44$)Nrcr(c.>T"U5 [TU5 gr*)r+)r(rMr0s r1r27wandb_logger_v1..setup_logger..log_stepMs T " t $r4c4>T"5 TR5 gr*r[r\sr1r=7wandb_logger_v1..setup_logger..finalizeQr^r4r?)rr@r rrAr) rrr r2r=rQrMrrr0s @@r1rB%wandb_logger_v1..setup_loggerCsc.J . **  3 ;O  %8DcN3 % %  !!r4rD)rrrBr0s`` @r1wandb_logger_v1rq3su OE'*jjszz" "!#":<" xc3h($./"d(1CC D""( r4cVSSKnSSKJnJnJn U$![a [ S5ef=f)Nr)initlogr<zThe 'wandb' library could not be found - did you install it? Alternatively, specify the 'ConsoleLogger' in the 'training.logger' config section, instead of the 'WandbLogger'.)r0rsrtr< ImportError)r0rsrtr<s r1rErEZs9   *)   N   s(r0rr projectcURR5n[U5nUHnXg M [U5nUR X%USS9nU$)NT)rvconfigrreinit)rx interpolaterrrs) r0rrvrrrx config_dotfieldr/s r1r@r@jsSZZ # # %FV$J%  &  $F **WF4* PC Jr4r(c(UbUSnUSnUSnURSU05 U(a8URUR5VVs0sH upVSU3U_M snn5 [U[5(aURU5 gggs snnf)Nscore other_scoreslossesloss_)rtitems isinstancedict)r0r(r~rrkvs r1r+r+zs W N+ h 7E"#  II&,,.A.$!qc{A~.A B lD ) ) IIl # * Bs B r/cUb~U(avURS5(a_USU-S:XaRUSS:waH[UUSSUR-SUSUSSUS3S US [US 5S:XaS OS /S9 gggggg)N output_pathstepr pipeline_ checkpointzepoch epochz step latestr~ checkpointsbest)r%r&r'metadataaliases)getr;idmax)r0r(r/rs r1r,r,s   $((="9"9F|00A5$v,!:K!m,$svv-%! gvd6l^D "&w-3tM7J3KA3N"NTV ;L5#: r4r%r&r'rrc`URX#US9nURXS9 URXeS9 g)N)r'r)r&)r)Artifactadd_dir log_artifact)r0r%r&r'rrdataset_artifacts r1r;r;s:~~d~IT- '9r4matchercUb;UR5H&up4U"U5(dMURX405 M( ggr*)rrt)r0r(rrrs r1r-r-s8 JJLDAqzz 1&!!r4r*)NN)$__doc__typingrrrrrrr typesr rFspacyr spacy.utilr utilrrrrrrAintrGrUr`rirqrEr@r+r,r;boolr-r4r1rsBAA 'FF7 '7&8(,%) ""&$(,0RRs)R! Rc] R SM R sm R3-RSMRtCy)R Rp'7&8(,%) ""&$(RRs)R! Rc] R SM R sm R3-RSMR Rp'7&8(,%) " ==s)=! =c] = SM = sm = =F'7&8(,%) 11s)1! 1c] 1  1l:J9K$$-1#Y$ $N  z  (!&6&8       SM  s)    $z $$sCx.)A $ )-   4S> " ! 8*.#' :  :  :  :  : tCH~& : d3i :" "%d38n5"@H#PT@U"r4