o 1jO@s@ddlmZddlZddlmZddlmZGdddeZdS) )UnionN)abspath) BaseConfigc@seZdZdZdefddZdefddZdefdd Z dd d d ed edefddZ dde defddZ de fddZ de fddZdefddZde fd d!Zd"e fd#d$Zd%e fd&d'Zd(efd)d*Zd+ed effd,d-Zd.e fd/d0Zd1efd2d3Zd4efd5d6Zd7efd8d9Zd:e fd;d<Zd=efd>d?Zd@efdAdBZdCefdDdEZdFefdGdHZdIe fdJdKZ dLed effdMdNZ!dOefdPdQZ"dRe fdSdTZ#dUe fdVdWZ$dXe fdYdZZ%d[d\Z&d]efd^d_Z'dd`edaefdbdcZ(ddefdedfZ)dgefdhdiZ*d`efdjdkZ+d=efdldmZ,dnefdodpZ-dqefdrdsZ.dOefdtduZ/dvdwZ0dxdyZ1dzd{Z2d|e fd}d~Z3d|e fddZ4d|e fddZ5d|e fddZ6d|e fddZ7d|e fddZ8d|efddZ9dd|e fddZ:d|e fddZ;d|e fddZd|efddZ?d S) ClsConfigz Image Classification Task Config list_like_objcCs&ddlm}||j|}||dS)zupdate self Args: list_like_obj (list): list of pairs(key0.key1.idx.key2=value), such as: [ 'topk=2', 'VALID.transforms.1.ResizeImage.resize_short=300' ] r)override_configN)Zpaddleclas.ppcls.utils.configr dictreset_from_dict)selfrr dict_rl/var/www/html/Deteccion_Ine/venv/lib/python3.10/site-packages/paddlex/repo_apis/PaddleClas_api/cls/config.pyupdates zClsConfig.updateconfig_file_pathcCs2tjt|dtjd}t|tst||dS)zload config from yaml file Args: config_file_path (str): the path of yaml file. 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N ClsDatasetz /train.txt)r"Z MLClsDatasetzDataLoader.Train.dataset.name=z$DataLoader.Train.dataset.image_root=z(DataLoader.Train.dataset.cls_label_path=zDataLoader.Eval.dataset.name=z#DataLoader.Eval.dataset.image_root=z'DataLoader.Eval.dataset.cls_label_path=z/val.txtz$Infer.PostProcess.class_id_map_file=z /label.txtz is not supported.)r ValueErrorreprr)r r r!rZds_cfgrrrupdate_dataset@s"    zClsConfig.update_datasettrain batch_sizemodecCs|dkr |jddddrd|g}n$d|g}dg}n|d kr+d |g}n|d kr6d |g}ntd ||dS)a7update batch size setting Args: batch_size (int): the batch size number to set. mode (str, optional): the mode that to be set batch size, must be one of 'train', 'eval', 'test'. Defaults to 'train'. Raises: ValueError: `mode` error. r&Trainsamplerr'Fz$DataLoader.Train.sampler.batch_size=z"DataLoader.Train.sampler.first_bs=z/DataLoader.Train.dataset.name=MultiScaleDatasetevalz#DataLoader.Eval.sampler.batch_size=testzDataLoader.Infer.batch_size=z/The input `mode` should be train, eval or test.N) DataLoadergetr#r)r r'r(_cfgrrrupdate_batch_sizegs  zClsConfig.update_batch_size learning_ratecCsf|jdddddurd|g}n|jdddddur(d|g}ntd||dS) zoupdate learning rate Args: learning_rate (float): the learning rate value to set. 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NzThe 'pretrained_model' should be a string, indicating the path to the '*.pdparams' file, or 'None', indicating that no pretrained model to be used.zGlobal.pretrained_model=NonezArch.pretrained=FalsedefaultzArch.pretrained=True)zhttp://zhttps:// .pdparamszGlobal.pretrained_model=)rstrtyperlower startswithrreplace)r r;rrrupdate_pretrained_weightss       z#ClsConfig.update_pretrained_weights num_classescCspd|g}|dkr|d||d||jdd}|dur1||||||dS)zmupdate classes number Args: num_classes (int): the classes number value to set. zArch.class_num=ZDistillationModelz Arch.models.0.Teacher.class_num=z Arch.models.1.Student.class_num= MLDecoderN)_get_arch_nameappendr r.update_ml_query_numupdate_ml_class_numr)r rEZupdate_str_listZ ml_decoderrrrupdate_num_classess    zClsConfig.update_num_classes query_numcC<|jdidd}|durd|g}||dSdS)zupdate MLDecoder query number Args: query_num (int): the query number value to set,qury_num should be less than or equal to num_classes. rFrLNzMLDecoder.query_num=r r.r)r rLZbase_query_numr/rrrrI  zClsConfig.update_ml_query_num class_numcCrM)ztupdate MLDecoder query number Args: num_classes (int): the classes number value to set. rFrPNzMLDecoder.class_num=rN)r rPZbase_class_numr/rrrrJrOzClsConfig.update_ml_class_numslim_config_pathcCs0tjt|dtjdd}|d|gdS)zsupdate slim settings Args: slim_config_path (str): the path to slim config yaml file. rrSlimzSlim=N)rrrrr)r rQZ slim_configrrr_update_slim_configszClsConfig._update_slim_configampcCs\|dus|dkrd|jvr|jddSdSd|jvr tddd|g}||dS)zupdate AMP settings Args: amp (None | str): the AMP settings. 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NZOFFAMPz!Config must have AMP information.zAMP.use_amp=Truez AMP.level=)r r4popr#r)r rTr/rrr _update_amps  zClsConfig._update_amp num_workerscCs"d|d|g}||dS)zupdate workers number of train and eval dataloader Args: num_workers (int): the value of train and eval dataloader workers number to set. z$DataLoader.Train.loader.num_workers=z#DataLoader.Eval.loader.num_workers=Nr8)r rXr/rrrupdate_num_workersszClsConfig.update_num_workersshared_memeorycC4t|ts Jdd|d|g}||dS)zupdate shared memory setting of train and eval dataloader Args: shared_memeory (bool): whether or not to use shared memory zshared_memeory should be a boolz*DataLoader.Train.loader.use_shared_memory=z)DataLoader.Eval.loader.use_shared_memory=Nrboolr)r rZr/rrrupdate_shared_memory zClsConfig.update_shared_memoryshufflecCr[)zupdate shuffle setting of train and eval dataloader Args: shuffle (bool): whether or not to shuffle the data zshuffle should be a boolz DataLoader.Train.loader.shuffle=zDataLoader.Eval.loader.shuffle=Nr\)r r`r/rrrupdate_shuffle r_zClsConfig.update_shuffledalicCs4t|ts Jdd|d|g}||dS)z|enable DALI setting of train and eval dataloader Args: dali (bool): whether or not to use DALI zdali should be a boolzGlobal.use_dali=Nr\)r rbr/rrr update_dalir_zClsConfig.update_daliseedcCr7)zXupdate seed Args: seed (int): the random seed value to set z Global.seed=Nr8)r rdr/rrr update_seed$r:zClsConfig.update_seeddevicecCs(|dd}d|g}||dS)zaupdate device setting Args: device (str): the running device to set :rzGlobal.device=Nsplitr)r rfr/rrr update_device-s zClsConfig.update_device dict_pathcCsdt|g}||dS)zsupdate label dict file path Args: dict_path (str): the path of label dict file to set z#PostProcess.Topk.class_id_map_file=N)rr)r rkr/rrrupdate_label_dict_path7s z ClsConfig.update_label_dict_pathdy2stcC|d|gdS)zupdate config to set dynamic to static mode Args: dy2st (bool): whether or not to use the dynamic to static mode. zGlobal.to_static=Nr8)r rmrrr_update_to_staticBzClsConfig._update_to_staticuse_vdlcCrn)zqupdate config to set VisualDL Args: use_vdl (bool): whether or not to use VisualDL. zGlobal.use_visualdl=Nr8)r rqrrr_update_use_vdlJrpzClsConfig._update_use_vdlepochscCrn)zfupdate epochs setting Args: epochs (int): the epochs number value to set zGlobal.epochs=Nr8)r rsrrr_update_epochsRrpzClsConfig._update_epochs resume_pathcCs*|dur |dd}|d|gdS)zupdate checkpoint setting Args: resume_path (None | str): the resume training setting. if is `None`, train from scratch, otherwise, train from checkpoint file that path is `.pdparams` file. Nr=r>zGlobal.checkpoints=)rCr)r rurrr_update_checkpointsZs zClsConfig._update_checkpointssave_dircC|dt|gdS)zeupdate output directory Args: save_dir (str): the path to save outputs. zGlobal.output_dir=Nrrr rwrrr_update_output_direzClsConfig._update_output_dir log_intervalcCrn)zqupdate log interval(steps) Args: log_interval (int): the log interval value to set. zGlobal.print_batch_step=Nr8)r r}rrrupdate_log_intervalmrpzClsConfig.update_log_interval eval_intervalcCrn)zuupdate eval interval(epochs) Args: eval_interval (int): the eval interval value to set. zGlobal.eval_interval=Nr8)r rrrrupdate_eval_intervalurpzClsConfig.update_eval_interval save_intervalcCrn)zuupdate eval interval(epochs) Args: save_interval (int): the save interval value to set. zGlobal.save_interval=Nr8)r rrrrupdate_save_interval}rpzClsConfig.update_save_intervalcCs&|dd}|d|dgdS)z\update log ranks Args: device (str): the running device to set rgzGlobal.log_ranks=""Nrh)r rfZ log_ranksrrrupdate_log_ranksszClsConfig.update_log_ranksprint_mem_infocCs(t|ts Jd|d|gdS)zsetting print memory infozprint_mem_info should be a boolzGlobal.print_mem_info=Nr\)r rrrrupdate_print_mem_infoszClsConfig.update_print_mem_info infer_img infer_listcCs,|r |d|g|d|gdS)zupdate image to be predicted Args: infer_img (str): the path to image that to be predicted. infer_list (str, optional): the path to file that images. Defaults to None. zInfer.infer_list=zInfer.infer_imgs=Nr8)r rrrrr_update_predict_imgszClsConfig._update_predict_imgsave_inference_dircCrx)zupdate directory path to save inference model files Args: save_inference_dir (str): the directory path to set. zGlobal.save_inference_dir=Nry)r rrrr_update_save_inference_dirr|z$ClsConfig._update_save_inference_dir model_dircCrx)zupdate inference model directory Args: model_dir (str): the directory path of inference model fils that used to predict. zGlobal.inference_model_dir=Nry)r rrrr_update_inference_model_dirr|z%ClsConfig._update_inference_model_dircCrn)zoupdate path of image that would be predict Args: infer_img (str): the image path. zGlobal.infer_imgs=Nr8)r rrrr_update_infer_imgrpzClsConfig._update_infer_imgcCs$|d|dddkgdS)zqupdate the device used in predicting Args: device (str): the running device setting zGlobal.use_gpu=rgrZgpuN)rri)r rfrrr_update_infer_devices$zClsConfig._update_infer_device enable_mkldnncCrn)zupdate whether to enable MKLDNN Args: enable_mkldnn (bool): `True` is enable, otherwise is disable. zGlobal.enable_mkldnn=Nr8)r rrrr_update_enable_mkldnnrpzClsConfig._update_enable_mkldnn img_shapecCrn)zupdate image cropping shape in the preprocessing Args: img_shape (str): the shape of cropping in the preprocessing, i.e. `PreProcess.transform_ops.1.CropImage.size`. z*PreProcess.transform_ops.1.CropImage.size=Nr8)r rrrr_update_infer_img_shapesz!ClsConfig._update_infer_img_shapecCrn)zupdate directory that save predicting output Args: save_dir (str): the directory path that save predicting output. zInfer.save_dir=Nr8rzrrr_update_save_predict_resultrpz%ClsConfig._update_save_predict_resultcK.|D]}||}|d|d|gqdS)zupdate model settingszArch.=Nr8r kwargskvrrr update_modelzClsConfig.update_modelcKr)zupdate teacher model settingszArch.models.0.Teacher.rNr8rrrrupdate_teacher_modelrzClsConfig.update_teacher_modelcKr)zupdate student model settingszArch.models.1.Student.rNr8rrrrupdate_student_modelrzClsConfig.update_student_modelreturncC|jddS)ziget epochs Returns: int: the epochs value, i.e., `Global.epochs` in config. Globalrsr r rrrget_epochs_iterszClsConfig.get_epochs_iterscCr)zget log interval(steps) Returns: int: the log interval value, i.e., `Global.print_batch_step` in config. rZprint_batch_steprrrrrget_log_intervalrzClsConfig.get_log_intervalcCr)zget eval interval(epochs) Returns: int: the eval interval value, i.e., `Global.eval_interval` in config. rrrrrrrget_eval_intervalrzClsConfig.get_eval_intervalcCr)zget save interval(epochs) Returns: int: the save interval value, i.e., `Global.save_interval` in config. rrrrrrrget_save_intervalrzClsConfig.get_save_intervalcC|jdddS)zget learning rate Returns: float: the learning rate value, i.e., `Optimizer.lr.learning_rate` in config. r2r3r1rrrrrget_learning_rate zClsConfig.get_learning_ratecCr)zget warmup epochs Returns: int: the warmup epochs value, i.e., `Optimizer.lr.warmup_epochs` in config. r2r3Z warmup_epochrrrrrget_warmup_epochsrzClsConfig.get_warmup_epochscCr)zget label dict file path Returns: str: the label dict file path, i.e., `PostProcess.Topk.class_id_map_file` in config. Z PostProcessZTopkZclass_id_map_filerrrrrget_label_dict_pathrzClsConfig.get_label_dict_pathcC|jddddS)a:get batch size Args: mode (str, optional): the mode that to be get batch size value, must be one of 'train', 'eval', 'test'. Defaults to 'train'. Returns: int: the batch size value of `mode`, i.e., `DataLoader.{mode}.sampler.batch_size` in config. r-r)r*r'r)r r(rrrget_batch_size!s zClsConfig.get_batch_sizecC|S)zLget qat epochs Returns: int: the epochs value. )rrrrrget_qat_epochs_iters-zClsConfig.get_qat_epochs_iterscCr)z\get qat learning rate Returns: float: the learning rate value. )rrrrrget_qat_learning_rate5rzClsConfig.get_qat_learning_ratecCr)z|get architecture name of model Returns: str: the model arch name, i.e., `Arch.name` in config. 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