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update baselines
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@zezhishao
zezhishao committed Jan 2, 2024
1 parent f5c1e24 commit daedbfb
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103 changes: 103 additions & 0 deletions baselines/DeepAR/ETTh1.py
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import os
import sys

# TODO: remove it when basicts can be installed by pip
sys.path.append(os.path.abspath(__file__ + "/../../.."))
from easydict import EasyDict
from basicts.data import TimeSeriesForecastingDataset

from .arch import DeepAR
from .runner import DeepARRunner
from .loss import gaussian_loss

CFG = EasyDict()

# ================= general ================= #
CFG.DESCRIPTION = "DeepAR model configuration"
CFG.RUNNER = DeepARRunner
CFG.DATASET_CLS = TimeSeriesForecastingDataset
CFG.DATASET_NAME = "ETTh1"
CFG.DATASET_TYPE = "Traffic flow"
CFG.DATASET_INPUT_LEN = 96
CFG.DATASET_OUTPUT_LEN = 336
CFG.GPU_NUM = 1

# ================= environment ================= #
CFG.ENV = EasyDict()
CFG.ENV.SEED = 1
CFG.ENV.CUDNN = EasyDict()
CFG.ENV.CUDNN.ENABLED = True

# ================= model ================= #
CFG.MODEL = EasyDict()
CFG.MODEL.NAME = "DeepAR"
CFG.MODEL.ARCH = DeepAR
CFG.MODEL.PARAM = {
"cov_feat_size" : 2,
"embedding_size" : 32,
"hidden_size" : 64,
"num_layers": 3,
"use_ts_id" : True,
"id_feat_size": 32,
"num_nodes": 7
}
CFG.MODEL.FORWARD_FEATURES = [0, 1, 2]
CFG.MODEL.TARGET_FEATURES = [0]

# ================= optim ================= #
CFG.TRAIN = EasyDict()
CFG.TRAIN.LOSS = gaussian_loss
CFG.TRAIN.OPTIM = EasyDict()
CFG.TRAIN.OPTIM.TYPE = "Adam"
CFG.TRAIN.OPTIM.PARAM= {
"lr":0.003,
}

# ================= train ================= #
CFG.TRAIN.NUM_EPOCHS = 50
CFG.TRAIN.CKPT_SAVE_DIR = os.path.join(
"checkpoints",
"_".join([CFG.MODEL.NAME, str(CFG.TRAIN.NUM_EPOCHS)])
)
# train data
CFG.TRAIN.DATA = EasyDict()
# read data
CFG.TRAIN.DATA.DIR = "datasets/" + CFG.DATASET_NAME
# dataloader args, optional
CFG.TRAIN.DATA.BATCH_SIZE = 64
CFG.TRAIN.DATA.PREFETCH = False
CFG.TRAIN.DATA.SHUFFLE = True
CFG.TRAIN.DATA.NUM_WORKERS = 2
CFG.TRAIN.DATA.PIN_MEMORY = False

# ================= validate ================= #
CFG.VAL = EasyDict()
CFG.VAL.INTERVAL = 1
# validating data
CFG.VAL.DATA = EasyDict()
# read data
CFG.VAL.DATA.DIR = "datasets/" + CFG.DATASET_NAME
# dataloader args, optional
CFG.VAL.DATA.BATCH_SIZE = 64
CFG.VAL.DATA.PREFETCH = False
CFG.VAL.DATA.SHUFFLE = False
CFG.VAL.DATA.NUM_WORKERS = 2
CFG.VAL.DATA.PIN_MEMORY = False

# ================= test ================= #
CFG.TEST = EasyDict()
CFG.TEST.INTERVAL = 1
# test data
CFG.TEST.DATA = EasyDict()
# read data
CFG.TEST.DATA.DIR = "datasets/" + CFG.DATASET_NAME
# dataloader args, optional
CFG.TEST.DATA.BATCH_SIZE = 64
CFG.TEST.DATA.PREFETCH = False
CFG.TEST.DATA.SHUFFLE = False
CFG.TEST.DATA.NUM_WORKERS = 2
CFG.TEST.DATA.PIN_MEMORY = False

# ================= evaluate ================= #
CFG.EVAL = EasyDict()
CFG.EVAL.HORIZONS = [3, 6, 12]
103 changes: 103 additions & 0 deletions baselines/DeepAR/ETTm1.py
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import os
import sys

# TODO: remove it when basicts can be installed by pip
sys.path.append(os.path.abspath(__file__ + "/../../.."))
from easydict import EasyDict
from basicts.data import TimeSeriesForecastingDataset

from .arch import DeepAR
from .runner import DeepARRunner
from .loss import gaussian_loss

CFG = EasyDict()

# ================= general ================= #
CFG.DESCRIPTION = "DeepAR model configuration"
CFG.RUNNER = DeepARRunner
CFG.DATASET_CLS = TimeSeriesForecastingDataset
CFG.DATASET_NAME = "ETTm1"
CFG.DATASET_TYPE = "Traffic flow"
CFG.DATASET_INPUT_LEN = 96
CFG.DATASET_OUTPUT_LEN = 336
CFG.GPU_NUM = 1

# ================= environment ================= #
CFG.ENV = EasyDict()
CFG.ENV.SEED = 1
CFG.ENV.CUDNN = EasyDict()
CFG.ENV.CUDNN.ENABLED = True

# ================= model ================= #
CFG.MODEL = EasyDict()
CFG.MODEL.NAME = "DeepAR"
CFG.MODEL.ARCH = DeepAR
CFG.MODEL.PARAM = {
"cov_feat_size" : 2,
"embedding_size" : 32,
"hidden_size" : 64,
"num_layers": 3,
"use_ts_id" : True,
"id_feat_size": 32,
"num_nodes": 7
}
CFG.MODEL.FORWARD_FEATURES = [0, 1, 2]
CFG.MODEL.TARGET_FEATURES = [0]

# ================= optim ================= #
CFG.TRAIN = EasyDict()
CFG.TRAIN.LOSS = gaussian_loss
CFG.TRAIN.OPTIM = EasyDict()
CFG.TRAIN.OPTIM.TYPE = "Adam"
CFG.TRAIN.OPTIM.PARAM= {
"lr":0.003,
}

# ================= train ================= #
CFG.TRAIN.NUM_EPOCHS = 50
CFG.TRAIN.CKPT_SAVE_DIR = os.path.join(
"checkpoints",
"_".join([CFG.MODEL.NAME, str(CFG.TRAIN.NUM_EPOCHS)])
)
# train data
CFG.TRAIN.DATA = EasyDict()
# read data
CFG.TRAIN.DATA.DIR = "datasets/" + CFG.DATASET_NAME
# dataloader args, optional
CFG.TRAIN.DATA.BATCH_SIZE = 64
CFG.TRAIN.DATA.PREFETCH = False
CFG.TRAIN.DATA.SHUFFLE = True
CFG.TRAIN.DATA.NUM_WORKERS = 2
CFG.TRAIN.DATA.PIN_MEMORY = False

# ================= validate ================= #
CFG.VAL = EasyDict()
CFG.VAL.INTERVAL = 1
# validating data
CFG.VAL.DATA = EasyDict()
# read data
CFG.VAL.DATA.DIR = "datasets/" + CFG.DATASET_NAME
# dataloader args, optional
CFG.VAL.DATA.BATCH_SIZE = 64
CFG.VAL.DATA.PREFETCH = False
CFG.VAL.DATA.SHUFFLE = False
CFG.VAL.DATA.NUM_WORKERS = 2
CFG.VAL.DATA.PIN_MEMORY = False

# ================= test ================= #
CFG.TEST = EasyDict()
CFG.TEST.INTERVAL = 1
# test data
CFG.TEST.DATA = EasyDict()
# read data
CFG.TEST.DATA.DIR = "datasets/" + CFG.DATASET_NAME
# dataloader args, optional
CFG.TEST.DATA.BATCH_SIZE = 64
CFG.TEST.DATA.PREFETCH = False
CFG.TEST.DATA.SHUFFLE = False
CFG.TEST.DATA.NUM_WORKERS = 2
CFG.TEST.DATA.PIN_MEMORY = False

# ================= evaluate ================= #
CFG.EVAL = EasyDict()
CFG.EVAL.HORIZONS = [3, 6, 12]
103 changes: 103 additions & 0 deletions baselines/DeepAR/Electricity.py
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import os
import sys

# TODO: remove it when basicts can be installed by pip
sys.path.append(os.path.abspath(__file__ + "/../../.."))
from easydict import EasyDict
from basicts.data import TimeSeriesForecastingDataset

from .arch import DeepAR
from .runner import DeepARRunner
from .loss import gaussian_loss

CFG = EasyDict()

# ================= general ================= #
CFG.DESCRIPTION = "DeepAR model configuration"
CFG.RUNNER = DeepARRunner
CFG.DATASET_CLS = TimeSeriesForecastingDataset
CFG.DATASET_NAME = "Electricity"
CFG.DATASET_TYPE = "Traffic flow"
CFG.DATASET_INPUT_LEN = 96
CFG.DATASET_OUTPUT_LEN = 336
CFG.GPU_NUM = 1

# ================= environment ================= #
CFG.ENV = EasyDict()
CFG.ENV.SEED = 1
CFG.ENV.CUDNN = EasyDict()
CFG.ENV.CUDNN.ENABLED = True

# ================= model ================= #
CFG.MODEL = EasyDict()
CFG.MODEL.NAME = "DeepAR"
CFG.MODEL.ARCH = DeepAR
CFG.MODEL.PARAM = {
"cov_feat_size" : 2,
"embedding_size" : 32,
"hidden_size" : 64,
"num_layers": 3,
"use_ts_id" : True,
"id_feat_size": 32,
"num_nodes": 321
}
CFG.MODEL.FORWARD_FEATURES = [0, 1, 2]
CFG.MODEL.TARGET_FEATURES = [0]

# ================= optim ================= #
CFG.TRAIN = EasyDict()
CFG.TRAIN.LOSS = gaussian_loss
CFG.TRAIN.OPTIM = EasyDict()
CFG.TRAIN.OPTIM.TYPE = "Adam"
CFG.TRAIN.OPTIM.PARAM= {
"lr":0.003,
}

# ================= train ================= #
CFG.TRAIN.NUM_EPOCHS = 15
CFG.TRAIN.CKPT_SAVE_DIR = os.path.join(
"checkpoints",
"_".join([CFG.MODEL.NAME, str(CFG.TRAIN.NUM_EPOCHS)])
)
# train data
CFG.TRAIN.DATA = EasyDict()
# read data
CFG.TRAIN.DATA.DIR = "datasets/" + CFG.DATASET_NAME
# dataloader args, optional
CFG.TRAIN.DATA.BATCH_SIZE = 16
CFG.TRAIN.DATA.PREFETCH = False
CFG.TRAIN.DATA.SHUFFLE = True
CFG.TRAIN.DATA.NUM_WORKERS = 2
CFG.TRAIN.DATA.PIN_MEMORY = False

# ================= validate ================= #
CFG.VAL = EasyDict()
CFG.VAL.INTERVAL = 1
# validating data
CFG.VAL.DATA = EasyDict()
# read data
CFG.VAL.DATA.DIR = "datasets/" + CFG.DATASET_NAME
# dataloader args, optional
CFG.VAL.DATA.BATCH_SIZE = 64
CFG.VAL.DATA.PREFETCH = False
CFG.VAL.DATA.SHUFFLE = False
CFG.VAL.DATA.NUM_WORKERS = 2
CFG.VAL.DATA.PIN_MEMORY = False

# ================= test ================= #
CFG.TEST = EasyDict()
CFG.TEST.INTERVAL = 1
# test data
CFG.TEST.DATA = EasyDict()
# read data
CFG.TEST.DATA.DIR = "datasets/" + CFG.DATASET_NAME
# dataloader args, optional
CFG.TEST.DATA.BATCH_SIZE = 64
CFG.TEST.DATA.PREFETCH = False
CFG.TEST.DATA.SHUFFLE = False
CFG.TEST.DATA.NUM_WORKERS = 2
CFG.TEST.DATA.PIN_MEMORY = False

# ================= evaluate ================= #
CFG.EVAL = EasyDict()
CFG.EVAL.USE_GPU = False
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