add baseline fredformer

baselines/Fredformer/ETTm1.py

@@ -0,0 +1,155 @@
+import os
+import sys
+from easydict import EasyDict
+sys.path.append(os.path.abspath(__file__ + '/../../..'))
+
+from basicts.metrics import masked_mae, masked_mse
+from basicts.data import TimeSeriesForecastingDataset
+from basicts.runners import SimpleTimeSeriesForecastingRunner
+from basicts.scaler import ZScoreScaler
+from basicts.utils import get_regular_settings
+
+from .arch import Fredformer
+
+############################## Hot Parameters ##############################
+# Dataset & Metrics configuration
+DATA_NAME = 'ETTm1'  # Dataset name
+regular_settings = get_regular_settings(DATA_NAME)
+# INPUT_LEN = regular_settings['INPUT_LEN']  # Length of input sequence
+# OUTPUT_LEN = regular_settings['OUTPUT_LEN']  # Length of output sequence
+INPUT_LEN = 96
+OUTPUT_LEN = 96
+TRAIN_VAL_TEST_RATIO = regular_settings['TRAIN_VAL_TEST_RATIO']  # Train/Validation/Test split ratios
+NORM_EACH_CHANNEL = regular_settings['NORM_EACH_CHANNEL'] # Whether to normalize each channel of the data
+RESCALE = regular_settings['RESCALE'] # Whether to rescale the data
+NULL_VAL = regular_settings['NULL_VAL'] # Null value in the data
+# Model architecture and parameters
+MODEL_ARCH = Fredformer
+NUM_NODES = 7
+MODEL_PARAM = {
+    "c_in": NUM_NODES,                              # num nodes
+    "context_window": INPUT_LEN,           # input sequence length
+    "target_window": OUTPUT_LEN,         # prediction sequence length\
+    "patch_len": 4,
+    "stride": 4,
+    "d_model": 24,
+    "n_heads": 16,
+    "e_layers": 3,                              # num of encoder layers
+    "d_ff": 128,
+    "dropout": 0.2,
+    "fc_dropout": 0.2,
+    "cf_drop": 0.2,
+    "head_dropout": 0,
+    "cf_dim": 128,
+    "cf_depth": 2,
+    "cf_heads": 8,
+    "cf_mlp": 96,
+    "cf_head_dim": 32,
+    "use_nys": 0,
+    "individual": False, 
+    "ablation": 0,
+    "mlp_drop": 0.3, 
+    "mlp_hidden": 64,
+    "padding_patch": "end",
+    "revin": True,
+    "affine": True,
+    "subtract_last": False,
+    "output": 0, # 感觉可能没用
+
+    }
+NUM_EPOCHS = 100
+
+############################## General Configuration ##############################
+CFG = EasyDict()
+# General settings
+CFG.DESCRIPTION = 'An Example Config'
+CFG.GPU_NUM = 1 # Number of GPUs to use (0 for CPU mode)
+# Runner
+CFG.RUNNER = SimpleTimeSeriesForecastingRunner
+
+############################## Dataset Configuration ##############################
+CFG.DATASET = EasyDict()
+# Dataset settings
+CFG.DATASET.NAME = DATA_NAME
+CFG.DATASET.TYPE = TimeSeriesForecastingDataset
+CFG.DATASET.PARAM = EasyDict({
+    'dataset_name': DATA_NAME,
+    'train_val_test_ratio': TRAIN_VAL_TEST_RATIO,
+    'input_len': INPUT_LEN,
+    'output_len': OUTPUT_LEN,
+    # 'mode' is automatically set by the runner
+})
+
+############################## Scaler Configuration ##############################
+CFG.SCALER = EasyDict()
+# Scaler settings
+CFG.SCALER.TYPE = ZScoreScaler # Scaler class
+CFG.SCALER.PARAM = EasyDict({
+    'dataset_name': DATA_NAME,
+    'train_ratio': TRAIN_VAL_TEST_RATIO[0],
+    'norm_each_channel': NORM_EACH_CHANNEL,
+    'rescale': RESCALE,
+})
+
+############################## Model Configuration ##############################
+CFG.MODEL = EasyDict()
+# Model settings
+CFG.MODEL.NAME = MODEL_ARCH.__name__
+CFG.MODEL.ARCH = MODEL_ARCH
+CFG.MODEL.PARAM = MODEL_PARAM
+CFG.MODEL.FORWARD_FEATURES = [0]
+CFG.MODEL.TARGET_FEATURES = [0]
+
+############################## Metrics Configuration ##############################
+
+CFG.METRICS = EasyDict()
+# Metrics settings
+CFG.METRICS.FUNCS = EasyDict({
+                                'MAE': masked_mae,
+                                'MSE': masked_mse
+                            })
+CFG.METRICS.TARGET = 'MAE'
+CFG.METRICS.NULL_VAL = NULL_VAL
+
+############################## Training Configuration ##############################
+CFG.TRAIN = EasyDict()
+CFG.TRAIN.NUM_EPOCHS = NUM_EPOCHS
+CFG.TRAIN.CKPT_SAVE_DIR = os.path.join(
+    'checkpoints',
+    MODEL_ARCH.__name__,
+    '_'.join([DATA_NAME, str(CFG.TRAIN.NUM_EPOCHS), str(INPUT_LEN), str(OUTPUT_LEN)])
+)
+CFG.TRAIN.LOSS = masked_mae
+# Optimizer settings
+CFG.TRAIN.OPTIM = EasyDict()
+CFG.TRAIN.OPTIM.TYPE = "Adam"
+CFG.TRAIN.OPTIM.PARAM = {
+    "lr": 0.001
+}
+CFG.TRAIN.CLIP_GRAD_PARAM = {
+    'max_norm': 5.0
+}
+# Train data loader settings
+CFG.TRAIN.DATA = EasyDict()
+CFG.TRAIN.DATA.BATCH_SIZE = 64
+CFG.TRAIN.DATA.SHUFFLE = True
+
+############################## Validation Configuration ##############################
+CFG.VAL = EasyDict()
+CFG.VAL.INTERVAL = 1
+CFG.VAL.DATA = EasyDict()
+CFG.VAL.DATA.BATCH_SIZE = 64
+
+############################## Test Configuration ##############################
+CFG.TEST = EasyDict()
+CFG.TEST.INTERVAL = 1
+CFG.TEST.DATA = EasyDict()
+CFG.TEST.DATA.BATCH_SIZE = 64
+
+############################## Evaluation Configuration ##############################
+
+CFG.EVAL = EasyDict()
+
+# Evaluation parameters
+CFG.EVAL.HORIZONS = [12, 24, 48, 96]
+CFG.EVAL.USE_GPU = True # Whether to use GPU for evaluation. Default: True

baselines/Fredformer/Weather.py

@@ -0,0 +1,155 @@
+import os
+import sys
+from easydict import EasyDict
+sys.path.append(os.path.abspath(__file__ + '/../../..'))
+
+from basicts.metrics import masked_mae, masked_mse
+from basicts.data import TimeSeriesForecastingDataset
+from basicts.runners import SimpleTimeSeriesForecastingRunner
+from basicts.scaler import ZScoreScaler
+from basicts.utils import get_regular_settings
+
+from .arch import Fredformer
+
+############################## Hot Parameters ##############################
+# Dataset & Metrics configuration
+DATA_NAME = 'Weather'  # Dataset name
+regular_settings = get_regular_settings(DATA_NAME)
+# INPUT_LEN = regular_settings['INPUT_LEN']  # Length of input sequence
+# OUTPUT_LEN = regular_settings['OUTPUT_LEN']  # Length of output sequence
+INPUT_LEN = 96
+OUTPUT_LEN = 192
+TRAIN_VAL_TEST_RATIO = regular_settings['TRAIN_VAL_TEST_RATIO']  # Train/Validation/Test split ratios
+NORM_EACH_CHANNEL = regular_settings['NORM_EACH_CHANNEL'] # Whether to normalize each channel of the data
+RESCALE = regular_settings['RESCALE'] # Whether to rescale the data
+NULL_VAL = regular_settings['NULL_VAL'] # Null value in the data
+# Model architecture and parameters
+MODEL_ARCH = Fredformer
+NUM_NODES = 21
+MODEL_PARAM = {
+    "c_in": NUM_NODES,                              # num nodes
+    "context_window": INPUT_LEN,           # input sequence length
+    "target_window": OUTPUT_LEN,         # prediction sequence length\
+    "patch_len": 16,
+    "stride": 16,
+    "d_model": 8,
+    "n_heads": 16,
+    "e_layers": 3,                              # num of encoder layers
+    "d_ff": 256,
+    "dropout": 0.2,
+    "fc_dropout": 0.2,
+    "cf_drop": 0.2,
+    "head_dropout": 0,
+    "cf_dim": 32,
+    "cf_depth": 3,
+    "cf_heads": 8,
+    "cf_mlp": 32,
+    "cf_head_dim": 8,
+    "use_nys": 0,
+    "individual": False, 
+    "ablation": 0,
+    "mlp_drop": 0.3, 
+    "mlp_hidden": 64,
+    "padding_patch": "end",
+    "revin": True,
+    "affine": True,
+    "subtract_last": False,
+    "output": 0, # 感觉可能没用
+
+    }
+NUM_EPOCHS = 100
+
+############################## General Configuration ##############################
+CFG = EasyDict()
+# General settings
+CFG.DESCRIPTION = 'An Example Config'
+CFG.GPU_NUM = 1 # Number of GPUs to use (0 for CPU mode)
+# Runner
+CFG.RUNNER = SimpleTimeSeriesForecastingRunner
+
+############################## Dataset Configuration ##############################
+CFG.DATASET = EasyDict()
+# Dataset settings
+CFG.DATASET.NAME = DATA_NAME
+CFG.DATASET.TYPE = TimeSeriesForecastingDataset
+CFG.DATASET.PARAM = EasyDict({
+    'dataset_name': DATA_NAME,
+    'train_val_test_ratio': TRAIN_VAL_TEST_RATIO,
+    'input_len': INPUT_LEN,
+    'output_len': OUTPUT_LEN,
+    # 'mode' is automatically set by the runner
+})
+
+############################## Scaler Configuration ##############################
+CFG.SCALER = EasyDict()
+# Scaler settings
+CFG.SCALER.TYPE = ZScoreScaler # Scaler class
+CFG.SCALER.PARAM = EasyDict({
+    'dataset_name': DATA_NAME,
+    'train_ratio': TRAIN_VAL_TEST_RATIO[0],
+    'norm_each_channel': NORM_EACH_CHANNEL,
+    'rescale': RESCALE,
+})
+
+############################## Model Configuration ##############################
+CFG.MODEL = EasyDict()
+# Model settings
+CFG.MODEL.NAME = MODEL_ARCH.__name__
+CFG.MODEL.ARCH = MODEL_ARCH
+CFG.MODEL.PARAM = MODEL_PARAM
+CFG.MODEL.FORWARD_FEATURES = [0]
+CFG.MODEL.TARGET_FEATURES = [0]
+
+############################## Metrics Configuration ##############################
+
+CFG.METRICS = EasyDict()
+# Metrics settings
+CFG.METRICS.FUNCS = EasyDict({
+                                'MAE': masked_mae,
+                                'MSE': masked_mse
+                            })
+CFG.METRICS.TARGET = 'MAE'
+CFG.METRICS.NULL_VAL = NULL_VAL
+
+############################## Training Configuration ##############################
+CFG.TRAIN = EasyDict()
+CFG.TRAIN.NUM_EPOCHS = NUM_EPOCHS
+CFG.TRAIN.CKPT_SAVE_DIR = os.path.join(
+    'checkpoints',
+    MODEL_ARCH.__name__,
+    '_'.join([DATA_NAME, str(CFG.TRAIN.NUM_EPOCHS), str(INPUT_LEN), str(OUTPUT_LEN)])
+)
+CFG.TRAIN.LOSS = masked_mae
+# Optimizer settings
+CFG.TRAIN.OPTIM = EasyDict()
+CFG.TRAIN.OPTIM.TYPE = "Adam"
+CFG.TRAIN.OPTIM.PARAM = {
+    "lr": 0.001
+}
+CFG.TRAIN.CLIP_GRAD_PARAM = {
+    'max_norm': 5.0
+}
+# Train data loader settings
+CFG.TRAIN.DATA = EasyDict()
+CFG.TRAIN.DATA.BATCH_SIZE = 64
+CFG.TRAIN.DATA.SHUFFLE = True
+
+############################## Validation Configuration ##############################
+CFG.VAL = EasyDict()
+CFG.VAL.INTERVAL = 1
+CFG.VAL.DATA = EasyDict()
+CFG.VAL.DATA.BATCH_SIZE = 64
+
+############################## Test Configuration ##############################
+CFG.TEST = EasyDict()
+CFG.TEST.INTERVAL = 1
+CFG.TEST.DATA = EasyDict()
+CFG.TEST.DATA.BATCH_SIZE = 64
+
+############################## Evaluation Configuration ##############################
+
+CFG.EVAL = EasyDict()
+
+# Evaluation parameters
+CFG.EVAL.HORIZONS = [12, 24, 48, 96]
+CFG.EVAL.USE_GPU = True # Whether to use GPU for evaluation. Default: True