Replace nats_bench by soft link

lib/layers/super_mlp.py

@@ -0,0 +1,24 @@
+import torch.nn as nn
+from typing import Optional
+
+class MLP(nn.Module):
+  # MLP: FC -> Activation -> Drop -> FC -> Drop
+  def __init__(self, in_features, hidden_features: Optional[int] = None,
+               out_features: Optional[int] = None,
+               act_layer=nn.GELU,
+               drop: Optional[float] = None):
+    super(MLP, self).__init__()
+    out_features = out_features or in_features
+    hidden_features = hidden_features or in_features
+    self.fc1 = nn.Linear(in_features, hidden_features)
+    self.act = act_layer()
+    self.fc2 = nn.Linear(hidden_features, out_features)
+    self.drop = nn.Dropout(drop or 0)
+
+  def forward(self, x):
+    x = self.fc1(x)
+    x = self.act(x)
+    x = self.drop(x)
+    x = self.fc2(x)
+    x = self.drop(x)
+    return x

lib/layers/super_module.py

@@ -0,0 +1,7 @@
+import torch.nn as nn
+
+class SuperModule(nn.Module):
+  def __init__(self):
+    super(SuperModule, self).__init__()
+
+