Fix SiluActivation (#15718)

src/transformers/activations.py

@@ -30,9 +30,6 @@ class NewGELUActivation(nn.Module):
     the Gaussian Error Linear Units paper: https://arxiv.org/abs/1606.08415
     """
 
-    def __init__(self):
-        super().__init__()
-
     def forward(self, input: Tensor) -> Tensor:
         return 0.5 * input * (1.0 + torch.tanh(math.sqrt(2.0 / math.pi) * (input + 0.044715 * torch.pow(input, 3.0))))
 
@@ -64,9 +61,6 @@ class FastGELUActivation(nn.Module):
     Applies GELU approximation that is slower than QuickGELU but more accurate. See: https://github.com/hendrycks/GELUs
     """
 
-    def __init__(self):
-        super().__init__()
-
     def forward(self, input: Tensor) -> Tensor:
         return 0.5 * input * (1.0 + torch.tanh(input * 0.7978845608 * (1.0 + 0.044715 * input * input)))
 
@@ -76,9 +70,6 @@ class QuickGELUActivation(nn.Module):
     Applies GELU approximation that is fast but somewhat inaccurate. See: https://github.com/hendrycks/GELUs
     """
 
-    def __init__(self):
-        super().__init__()
-
     def forward(self, input: Tensor) -> Tensor:
         return input * torch.sigmoid(1.702 * input)
 
@@ -93,6 +84,7 @@ class SiLUActivation(nn.Module):
     """
 
     def __init__(self):
+        super().__init__()
         if version.parse(torch.__version__) < version.parse("1.7"):
             self.act = self._silu_python
         else:
@@ -130,9 +122,6 @@ class LinearActivation(nn.Module):
     Applies the linear activation function, i.e. forwarding input directly to output.
     """
 
-    def __init__(self):
-        super().__init__()
-
     def forward(self, input: Tensor) -> Tensor:
         return input