change a bunch of stuff, add wip lightning implementation

nets/attention/transformer.py

@@ -86,8 +86,15 @@ class LocalFeatureTransformer(nn.Module):
         """
         assert self.d_model == feat0.size(2), "the feature number of src and transformer must be equal"
 
-        for layer, name in zip(self.layers, self.layer_names):
-
+        # NOTE Workaround for non statically determinable zip
+        # for layer, name in zip(self.layers, self.layer_names):
+        # layer_zip = ((layer, self.layer_names[i]) for i, layer in enumerate(self.layers))
+        # layer_zip = []
+        # for i, layer in enumerate(self.layers):
+            # layer_zip.append((layer, self.layer_names[i]))
+            
+        for i, layer in enumerate(self.layers):
+            name = self.layer_names[i]
             if name == 'self':
                 feat0 = layer(feat0, feat0, mask0, mask0)
                 feat1 = layer(feat1, feat1, mask1, mask1)
@@ -97,4 +104,4 @@ class LocalFeatureTransformer(nn.Module):
             else:
                 raise KeyError
 
-        return feat0, feat1
+        return feat0, feat1