# copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve. # # 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 import os.path as osp from ...base.register import register_model_info, register_suite_info from ..ts_base.model import TSModel from ..ts_base.runner import TSRunner from .config import LongForecastConfig REPO_ROOT_PATH = os.environ.get("PADDLE_PDX_PADDLETS_PATH") PDX_CONFIG_DIR = osp.abspath(osp.join(osp.dirname(__file__), "..", "configs")) register_suite_info( { "suite_name": "LongForecast", "model": TSModel, "runner": TSRunner, "config": LongForecastConfig, "runner_root_path": REPO_ROOT_PATH, } ) ################ Models Using Universal Config ################ # DLinear DLinear_CFG_PATH = osp.join(PDX_CONFIG_DIR, "DLinear.yaml") register_model_info( { "model_name": "DLinear", "suite": "LongForecast", "config_path": DLinear_CFG_PATH, "supported_apis": ["train", "evaluate", "predict", "export"], "supported_train_opts": { "device": ["cpu", "gpu_n1cx", "xpu", "npu", "mlu"], "dy2st": False, "amp": [], }, "supported_evaluate_opts": { "device": ["cpu", "gpu_n1cx", "xpu", "npu", "mlu"], "amp": [], }, "supported_predict_opts": {"device": ["cpu", "gpu", "xpu", "npu", "mlu"]}, "supported_infer_opts": {"device": ["cpu", "gpu"]}, } ) DLinear_CFG_PATH = osp.join(PDX_CONFIG_DIR, "RLinear.yaml") register_model_info( { "model_name": "RLinear", "suite": "LongForecast", "config_path": DLinear_CFG_PATH, "supported_apis": ["train", "evaluate", "predict", "export"], "supported_train_opts": { "device": ["cpu", "gpu_n1cx", "xpu", "npu", "mlu"], "dy2st": False, "amp": [], }, "supported_evaluate_opts": { "device": ["cpu", "gpu_n1cx", "xpu", "npu", "mlu"], "amp": [], }, "supported_predict_opts": {"device": ["cpu", "gpu", "xpu", "npu", "mlu"]}, "supported_infer_opts": {"device": ["cpu", "gpu", "xpu", "npu", "mlu"]}, } ) DLinear_CFG_PATH = osp.join(PDX_CONFIG_DIR, "NLinear.yaml") register_model_info( { "model_name": "NLinear", "suite": "LongForecast", "config_path": DLinear_CFG_PATH, "supported_apis": ["train", "evaluate", "predict", "export"], "supported_train_opts": { "device": ["cpu", "gpu_n1cx", "xpu", "npu", "mlu"], "dy2st": False, "amp": [], }, "supported_evaluate_opts": { "device": ["cpu", "gpu_n1cx", "xpu", "npu", "mlu"], "amp": [], }, "supported_predict_opts": {"device": ["cpu", "gpu", "xpu", "npu", "mlu"]}, "supported_infer_opts": {"device": ["cpu", "gpu", "xpu", "npu", "mlu"]}, } ) # TiDE TiDE_CFG_PATH = osp.join(PDX_CONFIG_DIR, "TiDE.yaml") register_model_info( { "model_name": "TiDE", "suite": "LongForecast", "config_path": TiDE_CFG_PATH, "supported_apis": ["train", "evaluate", "predict", "export"], "supported_train_opts": { "device": ["cpu", "gpu_n1cx", "xpu", "npu", "mlu"], "dy2st": False, "amp": [], }, "supported_evaluate_opts": { "device": ["cpu", "gpu_n1cx", "xpu", "npu", "mlu"], "amp": [], }, "supported_predict_opts": {"device": ["cpu", "gpu", "xpu", "npu", "mlu"]}, "supported_infer_opts": {"device": ["cpu", "gpu", "xpu", "npu", "mlu"]}, } ) # PatchTST PatchTST_CFG_PATH = osp.join(PDX_CONFIG_DIR, "PatchTST.yaml") register_model_info( { "model_name": "PatchTST", "suite": "LongForecast", "config_path": PatchTST_CFG_PATH, "supported_apis": ["train", "evaluate", "predict", "export"], "supported_train_opts": { "device": ["cpu", "gpu_n1cx", "xpu", "npu", "mlu"], "dy2st": False, "amp": [], }, "supported_evaluate_opts": {"device": ["cpu", "gpu_n1cx"], "amp": []}, "supported_predict_opts": {"device": ["cpu", "gpu"]}, "supported_infer_opts": {"device": ["cpu", "gpu"]}, } ) # Non-stationary Nonstationary_CFG_PATH = osp.join(PDX_CONFIG_DIR, "Nonstationary.yaml") register_model_info( { "model_name": "Nonstationary", "suite": "LongForecast", "config_path": Nonstationary_CFG_PATH, "supported_apis": ["train", "evaluate", "predict", "export"], "supported_train_opts": { "device": ["cpu", "gpu_n1cx", "xpu", "npu", "mlu"], "dy2st": False, "amp": [], }, "supported_evaluate_opts": { "device": ["cpu", "gpu_n1cx", "xpu", "npu", "mlu"], "amp": [], }, "supported_predict_opts": {"device": ["cpu", "gpu", "xpu", "npu", "mlu"]}, "supported_infer_opts": {"device": ["cpu", "gpu", "xpu", "npu", "mlu"]}, } ) # timesnet TimesNet_CFG_PATH = osp.join(PDX_CONFIG_DIR, "TimesNet.yaml") register_model_info( { "model_name": "TimesNet", "suite": "LongForecast", "config_path": TimesNet_CFG_PATH, "supported_apis": ["train", "evaluate", "predict", "export"], "supported_train_opts": { "device": ["cpu", "gpu_n1cx", "xpu", "npu", "mlu"], "dy2st": False, "amp": [], }, "supported_evaluate_opts": { "device": ["cpu", "gpu_n1cx", "xpu", "npu", "mlu"], "amp": [], }, "supported_predict_opts": {"device": ["cpu", "gpu", "xpu", "npu", "mlu"]}, "supported_infer_opts": {"device": ["cpu", "gpu", "xpu", "npu", "mlu"]}, } )