feat: add TimesNet_Q and xPatch models with Q matrix transformations

layers/decomp.py

@@ -0,0 +1,21 @@
+import torch
+from torch import nn
+
+from layers.ema import EMA
+from layers.dema import DEMA
+
+class DECOMP(nn.Module):
+    """
+    Series decomposition block
+    """
+    def __init__(self, ma_type, alpha, beta):
+        super(DECOMP, self).__init__()
+        if ma_type == 'ema':
+            self.ma = EMA(alpha)
+        elif ma_type == 'dema':
+            self.ma = DEMA(alpha, beta)
+
+    def forward(self, x):
+        moving_average = self.ma(x)
+        res = x - moving_average
+        return res, moving_average