nnunetv2系列：查看命令对应的函数
在nnUNet\pyproject.toml文件中定义了入口函数。
nnUNetv2_plan_and_preprocess = "nnunetv2.experiment_planning.plan_and_preprocess_entrypoints:plan_and_preprocess_entry"
nnUNetv2_extract_fingerprint = "nnunetv2.experiment_planning.plan_and_preprocess_entrypoints:extract_fingerprint_entry"
nnUNetv2_plan_experiment = "nnunetv2.experiment_planning.plan_and_preprocess_entrypoints:plan_experiment_entry"
nnUNetv2_preprocess = "nnunetv2.experiment_planning.plan_and_preprocess_entrypoints:preprocess_entry"
nnUNetv2_train = "nnunetv2.run.run_training:run_training_entry"
nnUNetv2_predict_from_modelfolder = "nnunetv2.inference.predict_from_raw_data:predict_entry_point_modelfolder"
nnUNetv2_predict = "nnunetv2.inference.predict_from_raw_data:predict_entry_point"
nnUNetv2_convert_old_nnUNet_dataset = "nnunetv2.dataset_conversion.convert_raw_dataset_from_old_nnunet_format:convert_entry_point"
nnUNetv2_find_best_configuration = "nnunetv2.evaluation.find_best_configuration:find_best_configuration_entry_point"
nnUNetv2_determine_postprocessing = "nnunetv2.postprocessing.remove_connected_components:entry_point_determine_postprocessing_folder"
nnUNetv2_apply_postprocessing = "nnunetv2.postprocessing.remove_connected_components:entry_point_apply_postprocessing"
nnUNetv2_ensemble = "nnunetv2.ensembling.ensemble:entry_point_ensemble_folders"
nnUNetv2_accumulate_crossval_results = "nnunetv2.evaluation.find_best_configuration:accumulate_crossval_results_entry_point"
nnUNetv2_plot_overlay_pngs = "nnunetv2.utilities.overlay_plots:entry_point_generate_overlay"
nnUNetv2_download_pretrained_model_by_url = "nnunetv2.model_sharing.entry_points:download_by_url"
nnUNetv2_install_pretrained_model_from_zip = "nnunetv2.model_sharing.entry_points:install_from_zip_entry_point"
nnUNetv2_export_model_to_zip = "nnunetv2.model_sharing.entry_points:export_pretrained_model_entry"
nnUNetv2_move_plans_between_datasets = "nnunetv2.experiment_planning.plans_for_pretraining.move_plans_between_datasets:entry_point_move_plans_between_datasets"
nnUNetv2_evaluate_folder = "nnunetv2.evaluation.evaluate_predictions:evaluate_folder_entry_point"
nnUNetv2_evaluate_simple = "nnunetv2.evaluation.evaluate_predictions:evaluate_simple_entry_point"
nnUNetv2_convert_MSD_dataset = "nnunetv2.dataset_conversion.convert_MSD_dataset:entry_point"
