diff --git a/src/pytorch-metadata.json b/src/pytorch-metadata.json
index 4e025df53a..553bc1fd02 100755
--- a/src/pytorch-metadata.json
+++ b/src/pytorch-metadata.json
@@ -156,13 +156,6 @@
       "package": "torch.nn.modules.activation"
     }
   },
-  {
-    "name": "Threshold",
-    "schema": {
-      "category": "Activation",
-      "package": "torch.nn.modules.activation"
-    }
-  },
   {
     "name": "ReLU",
     "schema": {
@@ -529,6 +522,12 @@
       "package": "torch.nn.modules.padding"
     }
   },
+  {
+    "name": "PixelShuffle",
+    "schema": {
+      "package": "torch.nn.modules.pixelshuffle"
+    }
+  },
   {
     "name": "InstanceNorm1d",
     "schema": {
diff --git a/src/pytorch.js b/src/pytorch.js
index 32d5b75e36..4e020f9169 100755
--- a/src/pytorch.js
+++ b/src/pytorch.js
@@ -120,6 +120,7 @@ pytorch.ModelFactory = class {
             constructorTable['torch.nn.modules.padding.ConstantPad1d'] = function () {};
             constructorTable['torch.nn.modules.padding.ConstantPad2d'] = function () {};
             constructorTable['torch.nn.modules.padding.ConstantPad3d'] = function () {};
+            constructorTable['torch.nn.modules.pixelshuffle.PixelShuffle'] = function () {};
             constructorTable['torch.nn.modules.pooling.AvgPool1d'] = function () {};
             constructorTable['torch.nn.modules.pooling.AvgPool2d'] = function () {};
             constructorTable['torch.nn.modules.pooling.AvgPool3d'] = function () {};
@@ -138,6 +139,7 @@ pytorch.ModelFactory = class {
             constructorTable['torch.nn.modules.upsampling.Upsample'] = function() {};
             constructorTable['torch.nn.parallel.data_parallel.DataParallel'] = function() {}; 
             constructorTable['torch.nn.parameter.Parameter'] = function(data, requires_grad) { this.data = data; this.requires_grad = requires_grad; };
+            constructorTable['torch.nn.utils.spectral_norm.SpectralNorm'] = function () {};
             constructorTable['torch.nn.utils.weight_norm.WeightNorm'] = function () {};
             constructorTable['torchvision.models.alexnet.AlexNet'] = function () {};
             constructorTable['torchvision.models.densenet.DenseNet'] = function () {};