first push

cirtorch/layers/normalization.py

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+import torch
+import torch.nn as nn
+
+import cirtorch.layers.functional as LF
+
+# --------------------------------------
+# Normalization layers
+# --------------------------------------
+
+class L2N(nn.Module):
+
+    def __init__(self, eps=1e-6):
+        super(L2N,self).__init__()
+        self.eps = eps
+
+    def forward(self, x):
+        return LF.l2n(x, eps=self.eps)
+        
+    def __repr__(self):
+        return self.__class__.__name__ + '(' + 'eps=' + str(self.eps) + ')'
+
+
+class PowerLaw(nn.Module):
+
+    def __init__(self, eps=1e-6):
+        super(PowerLaw, self).__init__()
+        self.eps = eps
+
+    def forward(self, x):
+        return LF.powerlaw(x, eps=self.eps)
+        
+    def __repr__(self):
+        return self.__class__.__name__ + '(' + 'eps=' + str(self.eps) + ')'