{-j ddlmZmZmZmZmZddlZddlm Z ddl m Z m Z ddl mZddlmZd d lmZeje d Gd d eZdS))AnyDictListOptionalUnionN)pipeline_requires_extra) HPIConfigPaddlePredictorOption) TSClsResult) benchmark) BasePipelinetsceZdZdZdZddddddddedeedeed eeeefd ee d e d ee eeefe fd dffdZ de eeeejeejfd efdZxZS) TSClsPipelinezTSClsPipeline Pipelinets_classificationNFdeviceengine engine_config pp_optionuse_hpip hpi_configconfigrrrrrrreturnc tjd||||||d||dd} || |_dS)aInitializes the time series classification pipeline. Args: config (Dict): Configuration dictionary containing various settings. device (Optional[str], optional): The device to use for prediction. Defaults to `None`. engine (Optional[str], optional): Inference engine. Defaults to `None`. engine_config (Optional[Dict[str, Any]], optional): Engine-specific config. Defaults to `None`. pp_option (Optional[PaddlePredictorOption], optional): Paddle predictor options. Defaults to `None`. use_hpip (bool, optional): Whether to use HPIP. Defaults to `False`. hpi_config (Optional[Union[Dict[str, Any], HPIConfig]], optional): HPIP configuration. Defaults to `None`. r SubModulesTSClassificationN)super__init__ create_modelts_classification_model) selfrrrrrrrkwargsts_classification_model_config __class__s v/var/www/html/banglarbhumi/venv/lib/python3.11/site-packages/paddlex/inference/pipelines/ts_classification/pipeline.pyr#zTSClsPipeline.__init__!sv2  '!      *0 )=>P)Q&'+'8'89W'X'X$$$inputc+@K||Ed{VdS)aPredicts time series classification results for the given input. Args: input (Union[str, list[str], pd.DataFrame, list[pd.DataFrame]]): The input image(s) or path(s) to the images. **kwargs: Additional keyword arguments that can be passed to the function. Returns: TSFcResult: The predicted time series classification results. N)r%)r&r,r's r*predictzTSClsPipeline.predictGs4//66666666666r+)__name__ __module__ __qualname____doc__entitiesrrstrrr boolrr r#rpd DataFramer r. __classcell__)r)s@r*rrs8! "H !% $2659AE$Y$Y$Y$Y $Y  $Y  S#X/ $Y12$Y$YU4S>9#<=>$Y $Y$Y$Y$Y$Y$YL 73S 2<bl9KKL 7  7 7 7 7 7 7 7 7r+r)typingrrrrrpandasr6 utils.depsr modelsr r models.ts_classification.resultr utils.benchmarkrbaser time_methodsrr!r+r*rAs4333333333333322222266666666::::::(((((( 7777777777L7777777777r+