# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os from ....utils.misc import abspath from ..ts_base.config import BaseTSConfig class TSClassifyConfig(BaseTSConfig): """TS Classify Config""" def update_dataset(self, dataset_dir: str, dataset_type: str = None): """ update the dataset Args: dataset_dir (str): dataset root path dataset_type (str, optional): type to set for dataset. Default='TSDataset' """ if dataset_type is None: dataset_type = "TSCLSDataset" dataset_dir = abspath(dataset_dir) ds_cfg = self._make_custom_dataset_config(dataset_dir) self.update(ds_cfg) def update_basic_info(self, info_params: dict): """ update basic info including time_col, freq, target_cols. Args: info_params (dict): update basic info Raises: TypeError: if info_params is not dict, raising TypeError """ if isinstance(info_params, dict): self.update({"info_params": info_params}) else: raise TypeError("`info_params` must be a dict.") def _make_custom_dataset_config(self, dataset_root_path: str): """construct the dataset config that meets the format requirements Args: dataset_root_path (str): the root directory of dataset. Returns: dict: the dataset config. """ ds_cfg = { "dataset": { "name": "TSCLSDataset", "dataset_root": dataset_root_path, "train_path": os.path.join(dataset_root_path, "train.csv"), "val_path": os.path.join(dataset_root_path, "val.csv"), }, } return ds_cfg