Update modeling_motif.py

modeling_motif.py

@@ -51,27 +51,8 @@ class PolyNorm(torch.nn.Module):
         return self.weight[0] * self._norm(x ** 3) + self.weight[1] * self._norm(
             x ** 2) + self.weight[2] * self._norm(x) + self.bias
 
-class PolyNorm_Test(torch.nn.Module):
-    """ 
-    A trainable activation function introduced in https://arxiv.org/html/2411.03884v1.
-    The code is copied from https://github.com/BryceZhuo/PolyCom?tab=readme-ov-file/README.md,
-    with the change `* torch.rsqrt` => `/ torch.sqrt` for potential MAF incompatibility. 
-    """
-
-    def __init__(self, eps=1e-6):
-        super(PolyNorm_Test, self).__init__()
-        self.weight = torch.nn.Parameter(torch.ones(3) / 3)
-        self.bias = torch.nn.Parameter(torch.zeros(1))
-        self.eps = eps
-
-    def forward(self, x):
-        
-        #return torch.nn.SiLU(x)
-        return moreh_ops.poly_norm(x, self.weight, self.bias)
-
-
-CUSTOM_ACT2CLS = {"poly_norm": PolyNorm, "poly_norm_test": PolyNorm_Test}
 
+CUSTOM_ACT2CLS = {"poly_norm": PolyNorm}
 ACT2CLS = {**_ACT2CLS, **CUSTOM_ACT2CLS}
 ACT2FN = ClassInstantier(ACT2CLS)