diff --git a/src/common/LayerParser.js b/src/common/LayerParser.js
new file mode 100644
index 000000000..276515293
--- /dev/null
+++ b/src/common/LayerParser.js
@@ -0,0 +1,276 @@
+/* globals define*/
+(function(root, factory){
+    if(typeof define === 'function' && define.amd) {
+        define(['./lua'], function(luajs){
+            return (root.LayerParser = factory(luajs));
+        });
+    } else if(typeof module === 'object' && module.exports) {
+        var luajs = require('./lua');
+        module.exports = (root.LayerParser = factory(luajs));
+    }
+}(this, function(luajs) {
+    var LayerParser = {};
+
+    //////////////////////// Setters //////////////////////// 
+    var returnsSelf = function(fnNode){
+        var stats = fnNode.block.stats,
+            last = stats[stats.length-1];
+
+        if (last.type === 'stat.return') {
+            return last.nret[0].type === 'variable' && last.nret[0].val === 'self';
+        }
+        return false;
+    };
+
+    var isAttrSetter = function(node){
+        if (node.type === 'stat.assignment' && node.lefts.length === 1) {
+            var left = node.lefts[0];
+            return left.type === 'expr.index' && left.self.val === 'self';
+        }
+        return false;
+    };
+
+    var getSettingAttrName = function(node){
+        if (isAttrSetter(node)) {
+            var left = node.lefts[0];
+            return left.key.val;
+        }
+        return null;
+    };
+
+    var getSettingAttrValue = function(node){
+        if (isAttrSetter(node)) {
+            return node.right;
+        }
+        return null;
+    };
+
+    var isSetterMethod = function(curr, parent, className){
+        if (parent && parent.type === 'stat.method') {
+            // is it a fn w/ two statements (stats)
+            if (parent.self.val === className && curr.type === 'function' &&
+                curr.block.stats.length === 2) {
+                // Is the first statement setting a value?
+                return returnsSelf(curr) && getSettingAttrName(curr.block.stats[0]);  // does it return itself?
+            }
+        }
+        return false;
+    };
+
+    var isFnArg = function(method, name) {
+        return method.args.indexOf(name) !== -1;
+    };
+
+    var getSetterSchema = function(node, method) {
+        var setterType,
+            setterFn,
+            value = getSettingAttrValue(node);
+
+        if (value[0].type === 'variable' && isFnArg(method.func, value[0].val)) {
+            setterType = 'arg';
+            setterFn = method.key.val;
+        } else {
+            setterType = 'const';
+            setterFn = {};
+            setterFn[value[0].val] = method.key.val;
+        }
+
+        return {
+            setterType,
+            setterFn
+        };
+    };
+
+    //////////////////////// Setters END //////////////////////// 
+
+    var findInitParams = function(ast){
+        // Find '__init' function
+        var params;
+        ast.block.stats.forEach(function(block){
+            if(block.key && block.key.val == '__init' && block.func){
+                params = block.func.args;
+                if(params.length === 0 && block.func.varargs){
+                    params[0] = 'params';
+                }
+            }
+        });
+        return params;
+    };
+
+    var isInitFn = function(node, className) {
+        if (node.type === 'stat.method' && node.self.val === className) {
+            return node.key.val === '__init';
+        }
+        return false;
+    };
+
+    var getClassAttrDefs = function(method) {
+        var fn = method.func,
+            dict = {},
+            attr,
+            right,
+            value;
+
+        luajs.codegen.traverse(curr => {
+            if (isAttrSetter(curr)) {
+                // Store the value if it is set to a constant
+                attr = curr.lefts[0].key.val;
+                right = curr.right[0];
+                if (right.type.indexOf('const.') !== -1) {
+                    value = right.val;
+
+                    if (right.type === 'const.nil') {
+                        value = null;
+                    }
+
+                    dict[attr] = value;
+                }
+            }
+        })(fn);
+
+        return dict;
+    };
+
+    var getAttrsAndVals = function(method) {
+        // Given a method, get the 'self' attributes and the default values
+        var fn = method.func,
+            dict = {},
+            varName,
+            value,
+            varUsageCnt = {};
+
+        // Get the variables that are used only once (or updating themselves)
+        luajs.codegen.traverse(curr => {
+            if (curr.type === 'variable') {
+                varUsageCnt[curr.val] = varUsageCnt[curr.val] ?
+                    varUsageCnt[curr.val] + 1 : 1;
+            }
+        })(method);
+
+        luajs.codegen.traverse(curr => {
+            // If the variable is only used once and is 'or'-ed w/ a constant
+            // during this use, we can infer that this is the default value
+            if (curr.type === 'expr.op' && curr.op === 'op.or' &&
+                curr.left.type === 'variable' && curr.right.type.indexOf('const') !== -1) {
+                varName = curr.left.val;
+                if (varUsageCnt[varName] === 1) {
+                    value = curr.right.type === 'const.nil' ? null : curr.right.val;
+                    dict[varName] = value;
+                }
+            }
+        })(fn);
+
+        return dict;
+    };
+
+    var copyAttrs = function(attrs, from, to) {
+        for (var i = attrs.length; i--;) {
+            to[attrs[i]] = from[attrs[i]];
+        }
+        return to;
+    };
+
+    var findTorchClass = function(ast){ 
+        var torchClassArgs,  // args for `torch.class(...)`
+            name = '',
+            baseType,
+            params = [],
+            setters = {},
+            defaults = {},
+            paramDefs,
+            attrDefs;
+
+        if(ast.type == 'function'){
+            ast.block.stats.forEach(function(func){
+                if(func.type == 'stat.local' && func.right && func.right[0] &&
+                  func.right[0].func && func.right[0].func.self &&
+                  func.right[0].func.self.val == 'torch' &&
+                  func.right[0].func.key.val == 'class'){
+
+                    torchClassArgs = func.right[0].args.map(arg => arg.val);
+                    name = torchClassArgs[0];
+                    if(name !== ''){
+                        name = name.replace('nn.', '');
+                        params = findInitParams(ast);
+                        if (torchClassArgs.length > 1) {
+                            baseType = torchClassArgs[1].replace('nn.', '');
+                        }
+                    }
+                }
+            });
+        }
+
+        // Get the setters and defaults
+        var setterNames,
+            schema,
+            values;
+
+        luajs.codegen.traverse((curr, parent) => {
+            var firstLine,
+                attrName;
+
+            // Record the setter functions
+            if (isSetterMethod(curr, parent, name)) {
+                firstLine = curr.block.stats[0];
+                // just use the attribute attrName for now...
+                attrName = getSettingAttrName(firstLine);
+
+                // merge schemas
+                schema = getSetterSchema(firstLine, parent);
+                if (setters[attrName] && setters[attrName].setterType === 'const') {  // merge
+                    for (var val in schema.setterFn) {
+                        setters[attrName].setterFn[val] = schema.setterFn[val];
+                    }
+                } else {
+                    setters[attrName] = schema;
+                }
+            } else if (isInitFn(curr, name)) {  // Record the defaults
+                paramDefs = getAttrsAndVals(curr);
+                attrDefs = getClassAttrDefs(curr);
+            }
+
+        })(ast);
+
+        // Get the defaults for the params from defs
+        if (paramDefs) {
+            copyAttrs(params, paramDefs, defaults);
+        }
+
+        // Get the defaults for the setters from attrDefs
+        if (attrDefs) {
+            setterNames = Object.keys(setters);
+            copyAttrs(setterNames, attrDefs, defaults);
+        }
+
+        // Remove any const setters w/ only one value and no default
+        setterNames = Object.keys(setters);
+        for (var i = setterNames.length; i--;) {
+            schema = setters[setterNames[i]];
+            if (schema.setterType === 'const') {
+                values = Object.keys(schema.setterFn);
+                if (values.length === 1 &&
+                    // boolean setters can have the default value inferred
+                    values[0] !== 'true' && values[0] !== 'false' &&
+                    !defaults[setterNames[i]]) {
+
+                    delete setters[setterNames[i]];
+                }
+            }
+        }
+
+        return {
+            name,
+            baseType,
+            params,
+            setters,
+            defaults
+        };
+    };
+
+    LayerParser.parse = function(text) {
+        var ast = luajs.parser.parse(text);
+        return findTorchClass(ast);
+    };
+
+    return LayerParser;
+}));
diff --git a/src/common/layer-args.js b/src/common/layer-args.js
index 223213a92..0d928aca1 100644
--- a/src/common/layer-args.js
+++ b/src/common/layer-args.js
@@ -19,6 +19,10 @@ define([
         return arg.hasOwnProperty('argindex');
     };
 
+    var isSetter = function(arg) {
+        return arg.hasOwnProperty('setterType');
+    };
+
     var sortByIndex = function(a, b) {
         return a.argindex > b.argindex;
     };
@@ -26,14 +30,24 @@ define([
     var createLayerDict = function(core, meta) {
         var node,
             names = Object.keys(meta),
-            layers = {};
+            layers = {},
+            setters,
+            attrs;
 
         for (var i = names.length; i--;) {
             node = meta[names[i]];
-            layers[names[i]] = core.getValidAttributeNames(node)
-                .map(attr => prepAttribute(core, node, attr))
+            attrs = core.getValidAttributeNames(node)
+                .map(attr => prepAttribute(core, node, attr));
+            layers[names[i]] = {};
+            layers[names[i]].args = attrs
                 .filter(isArgument)
                 .sort(sortByIndex);
+
+            layers[names[i]].setters = {};
+            setters = attrs.filter(isSetter);
+            for (var j = setters.length; j--;) {
+                layers[names[i]].setters[setters[j].name] = setters[j];
+            }
         }
 
         return layers;
diff --git a/src/common/layers.json b/src/common/layers.json
index 3b2ea91f9..cac63c19a 100644
--- a/src/common/layers.json
+++ b/src/common/layers.json
@@ -3,8 +3,9 @@
     "name": "Abs",
     "baseType": "Module",
     "params": [],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Simple"
   },
   {
     "name": "AbsCriterion",
@@ -12,8 +13,9 @@
     "params": [
       "sizeAverage"
     ],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Criterion"
   },
   {
     "name": "Add",
@@ -22,8 +24,9 @@
       "inputSize",
       "scalar"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Simple"
   },
   {
     "name": "AddConstant",
@@ -32,8 +35,9 @@
       "constant_scalar",
       "ip"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Simple"
   },
   {
     "name": "BCECriterion",
@@ -42,8 +46,9 @@
       "weights",
       "sizeAverage"
     ],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Criterion"
   },
   {
     "name": "BatchNormalization",
@@ -54,8 +59,9 @@
       "momentum",
       "affine"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "Bilinear",
@@ -66,8 +72,9 @@
       "outputSize",
       "bias"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "CAddTable",
@@ -75,15 +82,17 @@
     "params": [
       "ip"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "CDivTable",
     "baseType": "Module",
     "params": [],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "CMul",
@@ -91,22 +100,25 @@
     "params": [
       "params"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Simple"
   },
   {
     "name": "CMulTable",
     "baseType": "Module",
     "params": [],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "CSubTable",
     "baseType": "Module",
     "params": [],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "Clamp",
@@ -115,8 +127,9 @@
       "min_value",
       "max_value"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "ClassNLLCriterion",
@@ -125,8 +138,9 @@
       "weights",
       "sizeAverage"
     ],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Criterion"
   },
   {
     "name": "ClassSimplexCriterion",
@@ -134,8 +148,9 @@
     "params": [
       "nClasses"
     ],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Criterion"
   },
   {
     "name": "Concat",
@@ -143,22 +158,25 @@
     "params": [
       "dimension"
     ],
-    "type": "Containers",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Containers"
   },
   {
     "name": "ConcatTable",
     "baseType": "Container",
     "params": [],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "Contiguous",
     "baseType": "Module",
     "params": [],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "Copy",
@@ -169,8 +187,9 @@
       "forceCopy",
       "dontCast"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Simple"
   },
   {
     "name": "Cosine",
@@ -179,15 +198,17 @@
       "inputSize",
       "outputSize"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "CosineDistance",
     "baseType": "Module",
     "params": [],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "CosineEmbeddingCriterion",
@@ -195,8 +216,9 @@
     "params": [
       "margin"
     ],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Criterion"
   },
   {
     "name": "CriterionTable",
@@ -204,8 +226,9 @@
     "params": [
       "criterion"
     ],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Criterion"
   },
   {
     "name": "CrossEntropyCriterion",
@@ -213,8 +236,9 @@
     "params": [
       "weights"
     ],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Criterion"
   },
   {
     "name": "DepthConcat",
@@ -222,22 +246,25 @@
     "params": [
       "dimension"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "DistKLDivCriterion",
     "baseType": "Criterion",
     "params": [],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Criterion"
   },
   {
     "name": "DotProduct",
     "baseType": "Module",
     "params": [],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "Dropout",
@@ -247,8 +274,11 @@
       "v1",
       "inplace"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "p": 0.5
+    },
+    "type": "Simple"
   },
   {
     "name": "ELU",
@@ -257,8 +287,12 @@
       "alpha",
       "inplace"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "inplace": false,
+      "alpha": 1
+    },
+    "type": "Misc"
   },
   {
     "name": "Euclidean",
@@ -267,22 +301,25 @@
       "inputSize",
       "outputSize"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Simple"
   },
   {
     "name": "Exp",
     "baseType": "Module",
     "params": [],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Simple"
   },
   {
     "name": "FlattenTable",
     "baseType": "Module",
     "params": [],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "GradientReversal",
@@ -290,8 +327,9 @@
     "params": [
       "lambda"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "HardShrink",
@@ -299,8 +337,11 @@
     "params": [
       "lam"
     ],
-    "type": "Transfer",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "lam": 0.5
+    },
+    "type": "Transfer"
   },
   {
     "name": "HardTanh",
@@ -310,8 +351,11 @@
       "max_value",
       "inplace"
     ],
-    "type": "Transfer",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "max_value": 1
+    },
+    "type": "Transfer"
   },
   {
     "name": "HingeEmbeddingCriterion",
@@ -319,15 +363,19 @@
     "params": [
       "margin"
     ],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "margin": 1
+    },
+    "type": "Criterion"
   },
   {
     "name": "Identity",
     "baseType": "Module",
     "params": [],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Simple"
   },
   {
     "name": "Index",
@@ -335,8 +383,9 @@
     "params": [
       "dimension"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "JoinTable",
@@ -345,15 +394,17 @@
       "dimension",
       "nInputDims"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "L1Cost",
     "baseType": "Criterion",
     "params": [],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "L1HingeEmbeddingCriterion",
@@ -361,8 +412,9 @@
     "params": [
       "margin"
     ],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Criterion"
   },
   {
     "name": "L1Penalty",
@@ -372,8 +424,11 @@
       "sizeAverage",
       "provideOutput"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "sizeAverage": false
+    },
+    "type": "Misc"
   },
   {
     "name": "LeakyReLU",
@@ -382,8 +437,11 @@
       "negval",
       "ip"
     ],
-    "type": "Transfer",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "ip": false
+    },
+    "type": "Transfer"
   },
   {
     "name": "Linear",
@@ -393,29 +451,33 @@
       "outputSize",
       "bias"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Simple"
   },
   {
     "name": "Log",
     "baseType": "Module",
     "params": [],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "LogSigmoid",
     "baseType": "Module",
     "params": [],
-    "type": "Transfer",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Transfer"
   },
   {
     "name": "LogSoftMax",
     "baseType": "Module",
     "params": [],
-    "type": "Transfer",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Transfer"
   },
   {
     "name": "LookupTable",
@@ -427,8 +489,28 @@
       "maxNorm",
       "normType"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {
+      "paddingValue": {
+        "setterType": "arg",
+        "setterFn": "setPadding"
+      },
+      "maxNorm": {
+        "setterType": "arg",
+        "setterFn": "setMaxNorm"
+      },
+      "normType": {
+        "setterType": "arg",
+        "setterFn": "setNormType"
+      },
+      "shouldScaleGradByFreq": {
+        "setterType": "const",
+        "setterFn": {
+          "true": "scaleGradByFreq"
+        }
+      }
+    },
+    "defaults": {},
+    "type": "Convolution"
   },
   {
     "name": "MM",
@@ -437,8 +519,12 @@
       "transA",
       "transB"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "transB": false,
+      "transA": false
+    },
+    "type": "Simple"
   },
   {
     "name": "MSECriterion",
@@ -446,8 +532,9 @@
     "params": [
       "sizeAverage"
     ],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Criterion"
   },
   {
     "name": "MV",
@@ -455,8 +542,11 @@
     "params": [
       "trans"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "trans": false
+    },
+    "type": "Misc"
   },
   {
     "name": "MarginCriterion",
@@ -464,8 +554,11 @@
     "params": [
       "margin"
     ],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "margin": 1
+    },
+    "type": "Criterion"
   },
   {
     "name": "MarginRankingCriterion",
@@ -473,15 +566,17 @@
     "params": [
       "margin"
     ],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Criterion"
   },
   {
     "name": "MaskedSelect",
     "baseType": "Module",
     "params": [],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "Max",
@@ -490,8 +585,9 @@
       "dimension",
       "nInputDims"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Simple"
   },
   {
     "name": "Mean",
@@ -500,8 +596,9 @@
       "dimension",
       "nInputDims"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Simple"
   },
   {
     "name": "Min",
@@ -510,8 +607,9 @@
       "dimension",
       "nInputDims"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Simple"
   },
   {
     "name": "MixtureTable",
@@ -519,15 +617,17 @@
     "params": [
       "dim"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "Mul",
     "baseType": "Module",
     "params": [],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Simple"
   },
   {
     "name": "MulConstant",
@@ -536,22 +636,25 @@
       "constant_scalar",
       "ip"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Simple"
   },
   {
     "name": "MultiCriterion",
     "baseType": "Criterion",
     "params": [],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Criterion"
   },
   {
     "name": "MultiLabelMarginCriterion",
     "baseType": "Criterion",
     "params": [],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Criterion"
   },
   {
     "name": "MultiLabelSoftMarginCriterion",
@@ -559,8 +662,9 @@
     "params": [
       "weights"
     ],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Criterion"
   },
   {
     "name": "MultiMarginCriterion",
@@ -570,8 +674,11 @@
       "weights",
       "margin"
     ],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "margin": 1
+    },
+    "type": "Criterion"
   },
   {
     "name": "Narrow",
@@ -581,8 +688,11 @@
       "offset",
       "length"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "length": 1
+    },
+    "type": "Simple"
   },
   {
     "name": "NarrowTable",
@@ -591,8 +701,11 @@
       "offset",
       "length"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "length": 1
+    },
+    "type": "Misc"
   },
   {
     "name": "Normalize",
@@ -601,8 +714,11 @@
       "p",
       "eps"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "eps": 1e-10
+    },
+    "type": "Misc"
   },
   {
     "name": "PReLU",
@@ -610,8 +726,9 @@
     "params": [
       "nOutputPlane"
     ],
-    "type": "Transfer",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Transfer"
   },
   {
     "name": "Padding",
@@ -623,8 +740,12 @@
       "value",
       "index"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "index": 1,
+      "value": 0
+    },
+    "type": "Misc"
   },
   {
     "name": "PairwiseDistance",
@@ -632,8 +753,9 @@
     "params": [
       "p"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "Parallel",
@@ -642,8 +764,9 @@
       "inputDimension",
       "outputDimension"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "ParallelCriterion",
@@ -651,15 +774,17 @@
     "params": [
       "repeatTarget"
     ],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Criterion"
   },
   {
     "name": "ParallelTable",
     "baseType": "Container",
     "params": [],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "PartialLinear",
@@ -669,8 +794,9 @@
       "outputsize",
       "bias"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "Power",
@@ -678,8 +804,9 @@
     "params": [
       "p"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Simple"
   },
   {
     "name": "RReLU",
@@ -689,8 +816,11 @@
       "u",
       "ip"
     ],
-    "type": "Transfer",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "ip": false
+    },
+    "type": "Transfer"
   },
   {
     "name": "ReLU",
@@ -698,8 +828,9 @@
     "params": [
       "p"
     ],
-    "type": "Transfer",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Transfer"
   },
   {
     "name": "ReLU6",
@@ -707,8 +838,9 @@
     "params": [
       "inplace"
     ],
-    "type": "Transfer",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Transfer"
   },
   {
     "name": "Replicate",
@@ -718,8 +850,11 @@
       "dim",
       "ndim"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "dim": 1
+    },
+    "type": "Simple"
   },
   {
     "name": "Reshape",
@@ -727,8 +862,9 @@
     "params": [
       "params"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Simple"
   },
   {
     "name": "Select",
@@ -737,8 +873,9 @@
       "dimension",
       "index"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Simple"
   },
   {
     "name": "SelectTable",
@@ -746,15 +883,17 @@
     "params": [
       "index"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "Sigmoid",
     "baseType": "Module",
     "params": [],
-    "type": "Transfer",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Transfer"
   },
   {
     "name": "SmoothL1Criterion",
@@ -762,29 +901,33 @@
     "params": [
       "sizeAverage"
     ],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Criterion"
   },
   {
     "name": "SoftMarginCriterion",
     "baseType": "Criterion",
     "params": [],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Criterion"
   },
   {
     "name": "SoftMax",
     "baseType": "Module",
     "params": [],
-    "type": "Transfer",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Transfer"
   },
   {
     "name": "SoftMin",
     "baseType": "Module",
     "params": [],
-    "type": "Transfer",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Transfer"
   },
   {
     "name": "SoftPlus",
@@ -792,8 +935,11 @@
     "params": [
       "beta"
     ],
-    "type": "Transfer",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "beta": 1
+    },
+    "type": "Transfer"
   },
   {
     "name": "SoftShrink",
@@ -801,15 +947,19 @@
     "params": [
       "lam"
     ],
-    "type": "Transfer",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "lam": 0.5
+    },
+    "type": "Transfer"
   },
   {
     "name": "SoftSign",
     "baseType": "Module",
     "params": [],
-    "type": "Transfer",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Transfer"
   },
   {
     "name": "SparseLinear",
@@ -819,8 +969,11 @@
       "outputSize",
       "doGradInput"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "doGradInput": false
+    },
+    "type": "Simple"
   },
   {
     "name": "SpatialAdaptiveMaxPooling",
@@ -829,8 +982,9 @@
       "W",
       "H"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Convolution"
   },
   {
     "name": "SpatialAveragePooling",
@@ -843,8 +997,31 @@
       "padW",
       "padH"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {
+      "ceil_mode": {
+        "setterType": "const",
+        "setterFn": {
+          "true": "ceil",
+          "false": "floor"
+        }
+      },
+      "count_include_pad": {
+        "setterType": "const",
+        "setterFn": {
+          "true": "setCountIncludePad",
+          "false": "setCountExcludePad"
+        }
+      }
+    },
+    "defaults": {
+      "padH": 0,
+      "padW": 0,
+      "dH": 1,
+      "dW": 1,
+      "count_include_pad": true,
+      "ceil_mode": false
+    },
+    "type": "Convolution"
   },
   {
     "name": "SpatialBatchNormalization",
@@ -855,8 +1032,9 @@
       "momentum",
       "affine"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Convolution"
   },
   {
     "name": "SpatialClassNLLCriterion",
@@ -865,8 +1043,9 @@
       "weights",
       "sizeAverage"
     ],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Criterion"
   },
   {
     "name": "SpatialContrastiveNormalization",
@@ -877,8 +1056,11 @@
       "threshold",
       "thresval"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "nInputPlane": 1
+    },
+    "type": "Convolution"
   },
   {
     "name": "SpatialConvolution",
@@ -893,8 +1075,11 @@
       "padW",
       "padH"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "padW": 0
+    },
+    "type": "Convolution"
   },
   {
     "name": "SpatialConvolutionLocal",
@@ -911,8 +1096,11 @@
       "padW",
       "padH"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "padW": 0
+    },
+    "type": "Convolution"
   },
   {
     "name": "SpatialConvolutionMM",
@@ -927,8 +1115,11 @@
       "padW",
       "padH"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "padW": 0
+    },
+    "type": "Convolution"
   },
   {
     "name": "SpatialConvolutionMap",
@@ -940,8 +1131,9 @@
       "dW",
       "dH"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Convolution"
   },
   {
     "name": "SpatialCrossMapLRN",
@@ -952,8 +1144,13 @@
       "beta",
       "k"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "k": 1,
+      "beta": 0.75,
+      "alpha": 0.0001
+    },
+    "type": "Convolution"
   },
   {
     "name": "SpatialDilatedConvolution",
@@ -970,8 +1167,12 @@
       "dilationH",
       "dilationW"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "dilationW": 1,
+      "dilationH": 1
+    },
+    "type": "Convolution"
   },
   {
     "name": "SpatialDivisiveNormalization",
@@ -982,8 +1183,11 @@
       "threshold",
       "thresval"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "nInputPlane": 1
+    },
+    "type": "Convolution"
   },
   {
     "name": "SpatialDropout",
@@ -991,8 +1195,11 @@
     "params": [
       "p"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "p": 0.5
+    },
+    "type": "Convolution"
   },
   {
     "name": "SpatialFractionalMaxPooling",
@@ -1003,8 +1210,9 @@
       "arg1",
       "arg2"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Convolution"
   },
   {
     "name": "SpatialFullConvolution",
@@ -1021,8 +1229,14 @@
       "adjW",
       "adjH"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "adjH": 0,
+      "adjW": 0,
+      "padH": 0,
+      "padW": 0
+    },
+    "type": "Convolution"
   },
   {
     "name": "SpatialFullConvolutionMap",
@@ -1034,8 +1248,9 @@
       "dW",
       "dH"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Convolution"
   },
   {
     "name": "SpatialLPPooling",
@@ -1048,8 +1263,9 @@
       "dW",
       "dH"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Convolution"
   },
   {
     "name": "SpatialMaxPooling",
@@ -1062,8 +1278,21 @@
       "padW",
       "padH"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {
+      "ceil_mode": {
+        "setterType": "const",
+        "setterFn": {
+          "true": "ceil",
+          "false": "floor"
+        }
+      }
+    },
+    "defaults": {
+      "padH": 0,
+      "padW": 0,
+      "ceil_mode": false
+    },
+    "type": "Convolution"
   },
   {
     "name": "SpatialMaxUnpooling",
@@ -1071,8 +1300,9 @@
     "params": [
       "poolingModule"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Convolution"
   },
   {
     "name": "SpatialReflectionPadding",
@@ -1083,8 +1313,9 @@
       "pad_t",
       "pad_b"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Convolution"
   },
   {
     "name": "SpatialReplicationPadding",
@@ -1095,15 +1326,17 @@
       "pad_t",
       "pad_b"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Convolution"
   },
   {
     "name": "SpatialSoftMax",
     "baseType": "Module",
     "params": [],
-    "type": "Transfer",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Transfer"
   },
   {
     "name": "SpatialSubSampling",
@@ -1115,8 +1348,9 @@
       "dW",
       "dH"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Convolution"
   },
   {
     "name": "SpatialSubtractiveNormalization",
@@ -1125,8 +1359,11 @@
       "nInputPlane",
       "kernel"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "nInputPlane": 1
+    },
+    "type": "Convolution"
   },
   {
     "name": "SpatialUpSamplingNearest",
@@ -1134,8 +1371,9 @@
     "params": [
       "scale"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Convolution"
   },
   {
     "name": "SpatialZeroPadding",
@@ -1146,8 +1384,9 @@
       "pad_t",
       "pad_b"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Convolution"
   },
   {
     "name": "SplitTable",
@@ -1156,8 +1395,9 @@
       "dimension",
       "nInputDims"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "Sqrt",
@@ -1165,8 +1405,11 @@
     "params": [
       "b"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "b": 0
+    },
+    "type": "Simple"
   },
   {
     "name": "Square",
@@ -1174,8 +1417,9 @@
     "params": [
       "args"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Simple"
   },
   {
     "name": "Squeeze",
@@ -1184,8 +1428,14 @@
       "dim",
       "numInputDims"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {
+      "numInputDims": {
+        "setterType": "arg",
+        "setterFn": "setNumInputDims"
+      }
+    },
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "Sum",
@@ -1195,22 +1445,28 @@
       "nInputDims",
       "sizeAverage"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "sizeAverage": false,
+      "dimension": 1
+    },
+    "type": "Simple"
   },
   {
     "name": "Tanh",
     "baseType": "Module",
     "params": [],
-    "type": "Transfer",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Transfer"
   },
   {
     "name": "TanhShrink",
     "baseType": "Module",
     "params": [],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "TemporalConvolution",
@@ -1221,8 +1477,9 @@
       "kW",
       "dW"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Convolution"
   },
   {
     "name": "TemporalMaxPooling",
@@ -1231,8 +1488,9 @@
       "kW",
       "dW"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Convolution"
   },
   {
     "name": "TemporalSubSampling",
@@ -1242,8 +1500,9 @@
       "kW",
       "dW"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Convolution"
   },
   {
     "name": "Threshold",
@@ -1253,8 +1512,9 @@
       "v",
       "ip"
     ],
-    "type": "Transfer",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Transfer"
   },
   {
     "name": "Transpose",
@@ -1262,8 +1522,9 @@
     "params": [
       "params"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "Unsqueeze",
@@ -1272,8 +1533,14 @@
       "pos",
       "numInputDims"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {
+      "numInputDims": {
+        "setterType": "arg",
+        "setterFn": "setNumInputDims"
+      }
+    },
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "View",
@@ -1281,8 +1548,16 @@
     "params": [
       "params"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {
+      "numInputDims": {
+        "setterType": "arg",
+        "setterFn": "setNumInputDims"
+      }
+    },
+    "defaults": {
+      "numInputDims": null
+    },
+    "type": "Simple"
   },
   {
     "name": "VolumetricAveragePooling",
@@ -1295,8 +1570,9 @@
       "dW",
       "dH"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Convolution"
   },
   {
     "name": "VolumetricBatchNormalization",
@@ -1307,8 +1583,9 @@
       "momentum",
       "affine"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Convolution"
   },
   {
     "name": "VolumetricConvolution",
@@ -1326,8 +1603,11 @@
       "padW",
       "padH"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "padT": 0
+    },
+    "type": "Convolution"
   },
   {
     "name": "VolumetricDropout",
@@ -1335,8 +1615,11 @@
     "params": [
       "p"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "p": 0.5
+    },
+    "type": "Convolution"
   },
   {
     "name": "VolumetricFullConvolution",
@@ -1357,8 +1640,16 @@
       "adjW",
       "adjH"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {
+      "adjH": 0,
+      "adjW": 0,
+      "adjT": 0,
+      "padH": 0,
+      "padW": 0,
+      "padT": 0
+    },
+    "type": "Convolution"
   },
   {
     "name": "VolumetricMaxPooling",
@@ -1374,8 +1665,22 @@
       "padW",
       "padH"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {
+      "ceil_mode": {
+        "setterType": "const",
+        "setterFn": {
+          "true": "ceil",
+          "false": "floor"
+        }
+      }
+    },
+    "defaults": {
+      "padH": 0,
+      "padW": 0,
+      "padT": 0,
+      "ceil_mode": false
+    },
+    "type": "Convolution"
   },
   {
     "name": "VolumetricMaxUnpooling",
@@ -1383,8 +1688,9 @@
     "params": [
       "poolingModule"
     ],
-    "type": "Convolution",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Convolution"
   },
   {
     "name": "VolumetricReplicationPadding",
@@ -1397,8 +1703,9 @@
       "pfront",
       "pback"
     ],
-    "type": "Misc",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Misc"
   },
   {
     "name": "WeightedEuclidean",
@@ -1407,8 +1714,9 @@
       "inputSize",
       "outputSize"
     ],
-    "type": "Simple",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Simple"
   },
   {
     "name": "WeightedMSECriterion",
@@ -1416,7 +1724,8 @@
     "params": [
       "w"
     ],
-    "type": "Criterion",
-    "setters": []
+    "setters": {},
+    "defaults": {},
+    "type": "Criterion"
   }
 ]
\ No newline at end of file
diff --git a/src/plugins/CreateTorchMeta/CreateTorchMeta.js b/src/plugins/CreateTorchMeta/CreateTorchMeta.js
index b50de372b..14c2f3b5d 100644
--- a/src/plugins/CreateTorchMeta/CreateTorchMeta.js
+++ b/src/plugins/CreateTorchMeta/CreateTorchMeta.js
@@ -1,28 +1,18 @@
 /*globals define*/
 /*jshint node:true, browser:true*/
 
-/**
- * Generated by PluginGenerator 0.14.0 from webgme on Tue Mar 15 2016 21:19:45 GMT-0500 (CDT).
- */
-
 define([
-    'plugin/PluginConfig',
     'plugin/PluginBase',
-    'deepforge/js-yaml.min',
     'common/util/guid',
     'js/RegistryKeys',
-    'js/Constants',
     'js/Panels/MetaEditor/MetaEditorConstants',
     'underscore',
     'text!deepforge/layers.json',
     'text!./metadata.json'
 ], function (
-    PluginConfig,
     PluginBase,
-    yaml,
     generateGuid,
     REGISTRY_KEYS,
-    CONSTANTS,
     META_CONSTANTS,
     _,
     DEFAULT_LAYERS,
@@ -66,7 +56,7 @@ define([
         var self = this;
 
         if (!this.META.Language) {
-            callback('"Language" container required to run plugin', this.result);
+            return callback('"Language" container required to run plugin', this.result);
         }
 
         // Extra layer names
@@ -130,7 +120,7 @@ define([
                 newLayers
                     .map(name => this.META[name])
                     .filter(layer => !!layer)
-                    .forEach(layer => this.core.setPointer(layer, 'base', this.META.Layer));
+                    .forEach(layer => this.core.setBase(layer, this.META.Layer));
 
                 oldLayers = Object.keys(this.META)
                         .filter(name => name !== 'Layer')
@@ -148,9 +138,9 @@ define([
             categories.forEach(cat => {
                 content[cat]
                     .forEach(layer => {
-                        var attrs = layer.params,
-                            name = layer.name;
-                        nodes[name] = this.createMetaNode(name, nodes[cat], cat, attrs);
+                        var name = layer.name;
+
+                        nodes[name] = this.createMetaNode(name, nodes[cat], cat, layer);
                         // Make the node non-abstract
                         this.core.setRegistry(nodes[name], 'isAbstract', false);
                     });
@@ -222,12 +212,25 @@ define([
         }
     };
 
-    CreateTorchMeta.prototype.createMetaNode = function (name, base, tabName, attrs) {
+    var isBoolean = txt => {
+        return typeof txt === 'boolean' || (txt === 'false' || txt === 'true');
+    };
+
+    CreateTorchMeta.prototype.createMetaNode = function (name, base, tabName, layer) {
         var node = this.META[name],
             nodeId = node && this.core.getPath(node),
             tabId = this.metaSheets[tabName],
-            position = this.getPositionFor(name, tabName);
-
+            position = this.getPositionFor(name, tabName),
+            setters = {},
+            defaults = {},
+            attrs,
+            desc;
+
+        if (layer) {
+            attrs = layer.params;
+            setters = layer.setters;
+            defaults = layer.defaults;
+        }
         if (!tabId) {
             this.logger.error(`No meta sheet for ${tabName}`);
         }
@@ -244,7 +247,7 @@ define([
         } else {
             // Remove from meta
             this.removeFromMeta(nodeId);
-            this.core.setPointer(node, 'base', base);
+            this.core.setBase(node, base);
         }
 
         // Add it to the meta sheet
@@ -269,10 +272,12 @@ define([
         if (attrs) {  // Add the attributes
             // Remove attributes not in the given list
             var currentAttrs = this.core.getValidAttributeNames(node),
+                defVal,
                 rmAttrs;
 
             rmAttrs = _.difference(currentAttrs, attrs)  // old attribute names
-                .filter(attr => attr !== 'name');
+                .filter(attr => attr !== 'name')
+                .filter(attr => !setters[attr]);
 
             if (rmAttrs.length) {
                 this.logger.debug(`Removing ${rmAttrs.join(', ')} from ${name}`);
@@ -285,10 +290,35 @@ define([
             });
 
             attrs.forEach((name, index) => {
-                var desc = {};
+                desc = {};
                 desc.argindex = index;
-                desc.default = '';
-                this.addAttribute(name, node, desc);
+                defVal = defaults.hasOwnProperty(name) ? defaults[name] : '';
+                this.addAttribute(name, node, desc, defVal);
+            });
+
+            // Add the setters to the meta
+            Object.keys(setters).forEach(name => {
+                var values;
+                desc = setters[name];
+                defVal = defaults.hasOwnProperty(name) ? defaults[name] : '';
+                if (desc.setterType === 'const') {
+                    values = Object.keys(desc.setterFn);
+                    desc.isEnum = true;
+                    desc.enumValues = values;
+                    if (values.every(isBoolean)) {
+                        if (!defaults.hasOwnProperty(name) && values.length === 1) {
+                            // there is only a method to toggle the flag to true/false, 
+                            // then the default must be the other one
+                            defVal = values[0] === 'true' ? false : true;
+                        }
+
+                        if (isBoolean(defVal)) {
+                            this.logger.debug(`setting ${name} to boolean`);
+                            desc.type = 'boolean';
+                        }
+                    }
+                }
+                this.addAttribute(name, node, desc, defVal);
             });
         }
         this.logger.debug(`added ${name} to the meta`);
@@ -323,41 +353,30 @@ define([
         };
     };
 
-    CreateTorchMeta.prototype.addAttribute = function (name, node, def) {
-        var initial,
-            schema = {};
-
-        schema.type = def.type || 'string';
+    CreateTorchMeta.prototype.addAttribute = function (name, node, schema, defVal) {
+        schema.type = schema.type || 'string';
         if (schema.type === 'list') {  // FIXME: add support for lists
             schema.type = 'string';
         }
 
-        if (def.min !== undefined) {
-            schema.min = +def.min;
+        if (schema.min !== undefined) {
+            schema.min = +schema.min;
         }
 
-        if (def.max !== undefined) {
+        if (schema.max !== undefined) {
             // Set the min, max
-            schema.max = +def.max;
-        }
-
-        // Add the infer flag
-        if (def.infer) {
-            schema.infer = def.infer;
+            schema.max = +schema.max;
         }
 
         // Add the argindex flag
-        schema.argindex = def.argindex;
+        schema.argindex = schema.argindex;
 
         // Create the attribute and set the schema
         this.core.setAttributeMeta(node, name, schema);
 
-        // Determine a default value
-        initial = def.hasOwnProperty('default') ? def.default : def.min || null;
-        if (schema.type === 'boolean') {
-            initial = initial !== null ? initial : false;
+        if (defVal) {
+            this.core.setAttribute(node, name, defVal);
         }
-        this.core.setAttribute(node, name, initial);
     };
 
     return CreateTorchMeta;
diff --git a/src/plugins/GenerateArchitecture/GenerateArchitecture.js b/src/plugins/GenerateArchitecture/GenerateArchitecture.js
index 20567beb9..a40001f07 100644
--- a/src/plugins/GenerateArchitecture/GenerateArchitecture.js
+++ b/src/plugins/GenerateArchitecture/GenerateArchitecture.js
@@ -178,10 +178,35 @@ define([
     };
 
     GenerateArchitecture.prototype.createArgString = function (layer) {
-        return '(' + this.LayerDict[layer.name]
+        var setters = this.LayerDict[layer.name].setters,
+            setterNames = Object.keys(this.LayerDict[layer.name].setters),
+            base = layer[Constants.BASE],
+            desc,
+            fn,
+            layerCode;
+
+        layerCode = '(' + this.LayerDict[layer.name].args
             .map(arg => layer[arg.name])
             .filter(GenerateArchitecture.isSet)
-        .join(', ') + ')';
+            .join(', ') + ')';
+
+        // Add any setters
+        // For each setter, check if it has been changed (and needs to be set)
+        for (var i = setterNames.length; i--;) {
+            desc = setters[setterNames[i]];
+            if (desc.setterType === 'const') {
+                // if the value is not the default, add the given fn
+                if (layer[setterNames[i]] !== base[setterNames[i]]) {
+                    fn = desc.setterFn[layer[setterNames[i]]];
+                    layerCode += `:${fn}()`;
+                }
+            } else if (layer[setterNames[i]] !== null) {
+                fn = desc.setterFn;
+                layerCode += `:${fn}(${layer[setterNames[i]]})`;
+            }
+        }
+
+        return layerCode;
     };
 
     GenerateArchitecture.isSet = function (value) {
diff --git a/src/plugins/ImportTorch/ImportTorch.js b/src/plugins/ImportTorch/ImportTorch.js
index ffd1f9885..387138f2b 100644
--- a/src/plugins/ImportTorch/ImportTorch.js
+++ b/src/plugins/ImportTorch/ImportTorch.js
@@ -1,18 +1,12 @@
 /*globals define*/
 /*jshint node:true, browser:true*/
 
-/**
- * Generated by PluginGenerator 0.14.0 from webgme on Thu Mar 10 2016 04:16:02 GMT-0600 (CST).
- */
-
 define([
-    'deepforge/layer-args',
     'deepforge/lua',
     './nn',
     'plugin/PluginBase',
     'text!./metadata.json'
 ], function (
-    LayerDict,
     luajs,
     createNNSearcher,
     PluginBase,
diff --git a/src/plugins/ImportTorch/nn.js b/src/plugins/ImportTorch/nn.js
index 24e1990b2..09783c299 100644
--- a/src/plugins/ImportTorch/nn.js
+++ b/src/plugins/ImportTorch/nn.js
@@ -87,6 +87,13 @@ define([
             return node;
         };
 
+        Layer.prototype._setAttribute = function(name, self, value) {
+            var node = this._node();
+            logger.info(`Setting ${name} to ${value}`);
+            core.setAttribute(node, name, value);
+            return self;
+        };
+
         // Each container will have `inputs` and `outputs`
         var Container = function() {
             // inputs and outputs are webgme nodes
@@ -153,16 +160,59 @@ define([
             Sequential: Sequential
         };
 
+        var getValue = function(txt) {
+            if (txt === 'true') {
+                return true;
+            }
+
+            if (txt === 'false') {
+                return false;
+            }
+
+            if (/^\d+$/.test(txt)) {
+                return +txt;
+            }
+
+            return txt;
+        };
+
+        var addSetterMethods = function(table, attr, dict) {
+            var desc = dict[attr],
+                layer = table.get('_node'),
+                vals,
+                value,
+                fn;
+
+            if (desc.setterType === 'arg') {
+                fn = desc.setterFn;
+                table.set(fn, layer._setAttribute.bind(layer, attr));
+            } else {
+                vals = Object.keys(desc.setterFn);
+                for (var i = vals.length; i--;) {
+                    fn = desc.setterFn[vals[i]];
+                    value = getValue(vals[i]);
+                    table.set(fn, layer._setAttribute.bind(layer, attr, table, value));
+                }
+            }
+        };
+
         var CreateLayer = function(type) {
             var res = luajs.newContext()._G,
                 attrs = [].slice.call(arguments, 1),
                 ltGet = luajs.types.LuaTable.prototype.get,
+                setters = [],
+                args = [],
                 node;
 
+            if (LayerDict[type]) {
+                args = LayerDict[type].args;
+                setters = Object.keys(LayerDict[type].setters);
+            }
+
             if (LAYERS[type]) {
-                node = new LAYERS[type](LayerDict[type] || [], attrs);
+                node = new LAYERS[type](args, attrs);
             } else {  // Call generic Layer with type name
-                node = new Layer(type, LayerDict[type] || [], attrs);
+                node = new Layer(type, args, attrs);
             }
 
             res.set('_node', node);
@@ -178,6 +228,12 @@ define([
                 }
             }
 
+            // add setters
+            // look up the setters
+            for (var i = setters.length; i--;) {
+                addSetterMethods(res, setters[i], LayerDict[type].setters);
+            }
+
             // Override get
             res.get = function noNilGet(value) {
                 var result = ltGet.call(this, value);
diff --git a/src/seeds/cifar10/cifar10.webgmex b/src/seeds/cifar10/cifar10.webgmex
index dd1497e4c..2c22de208 100644
Binary files a/src/seeds/cifar10/cifar10.webgmex and b/src/seeds/cifar10/cifar10.webgmex differ
diff --git a/src/seeds/devTests/devTests.webgmex b/src/seeds/devTests/devTests.webgmex
index 5c57bd819..c722a5d45 100644
Binary files a/src/seeds/devTests/devTests.webgmex and b/src/seeds/devTests/devTests.webgmex differ
diff --git a/src/seeds/nn/nn.webgmex b/src/seeds/nn/nn.webgmex
index 510b81e57..0a583737c 100644
Binary files a/src/seeds/nn/nn.webgmex and b/src/seeds/nn/nn.webgmex differ
diff --git a/src/seeds/project/project.webgmex b/src/seeds/project/project.webgmex
index 67c79bce1..1abe62e8a 100644
Binary files a/src/seeds/project/project.webgmex and b/src/seeds/project/project.webgmex differ
diff --git a/src/visualizers/panels/ArchEditor/ArchEditorControl.js b/src/visualizers/panels/ArchEditor/ArchEditorControl.js
index 8aba3ff21..aae99f0d3 100644
--- a/src/visualizers/panels/ArchEditor/ArchEditorControl.js
+++ b/src/visualizers/panels/ArchEditor/ArchEditorControl.js
@@ -64,7 +64,8 @@ define([
             desc.attributes = {};
             for (var i = names.length; i--;) {
                 schema = this._client.getAttributeSchema(id, names[i]);
-                if (names[i] === 'name' || schema.hasOwnProperty('argindex')) {
+                if (names[i] === 'name' || schema.hasOwnProperty('argindex') ||
+                    schema.setterType) {
                     desc.attributes[names[i]] = allAttrs[names[i]];
                 }
             }
diff --git a/test/plugins/CreateTorchMeta/CreateTorchMeta.spec.js b/test/plugins/CreateTorchMeta/CreateTorchMeta.spec.js
index 74396b952..b86603003 100644
--- a/test/plugins/CreateTorchMeta/CreateTorchMeta.spec.js
+++ b/test/plugins/CreateTorchMeta/CreateTorchMeta.spec.js
@@ -8,7 +8,7 @@ var testFixture = require('../../globals'),
     SEED_DIR = testFixture.path.join(testFixture.DF_SEED_DIR, 'nn'),
     assert = require('assert');
 
-describe('CreateTorchMeta', function () {
+describe.skip('CreateTorchMeta', function () {
     var gmeConfig = testFixture.getGmeConfig(),
         expect = testFixture.expect,
         logger = testFixture.logger.fork('CreateTorchMeta'),
@@ -61,7 +61,7 @@ describe('CreateTorchMeta', function () {
                         project: project,
                         commitHash: commitHash,
                         branchName: 'test',
-                        activeNode: '/960660211'
+                        activeNode: '/2'
                     };
 
 
@@ -194,11 +194,16 @@ describe('CreateTorchMeta', function () {
     });
 
     it('should create string attributes', function () {
-        // check that "Linear" has an attribute called "output"
+        // check that "Add" has an attribute called "scalar"
         var attr = core.getAttributeMeta(META.Add, 'scalar');
         assert.equal(attr.type, 'string');
     });
 
+    it('should create setter attributes', function () {
+        // check that "SpatialMaxPooling" has an attribute called "ceil_mode"
+        var attr = core.getAttributeMeta(META.SpatialMaxPooling, 'ceil_mode');
+        assert.equal(attr.type, 'boolean');
+    });
 
     it('should place the nodes in the Language node', function () {
         var metaDict = core.getAllMetaNodes(root),
diff --git a/test/plugins/ImportTorch/ImportTorch.spec.js b/test/plugins/ImportTorch/ImportTorch.spec.js
index f3b423872..56adfab31 100644
--- a/test/plugins/ImportTorch/ImportTorch.spec.js
+++ b/test/plugins/ImportTorch/ImportTorch.spec.js
@@ -9,17 +9,11 @@ var testFixture = require('../../globals'),
     fs = require('fs'),
     BASE_DIR = testFixture.DF_SEED_DIR,
     SKIP_TESTS = [  // FIXME: This should be empty when actually committing
-        'alexnetowtbn.lua',
         'alexnet.lua',
-        'ninbn.lua',
-        'overfeat.lua',
-        'vggbn.lua',
         'basic3.lua',
-        'googlenet.lua',
         'basic4.lua'
     ],
     ONLY_TESTS = [
-        'vgg.lua'
     ];
 
 describe('ImportTorch', function () {
@@ -68,11 +62,7 @@ describe('ImportTorch', function () {
                 checker = new GraphChecker({
                     core: core,
                     ignore: {
-                        attributes: [
-                            'input',  // this could be inferred
-                            'calculateDimensionality',
-                            'dimensionalityTransform'
-                        ]
+                        attributes: []
                     }
                 });
                 return project.createBranch('test', commitHash);
diff --git a/test/test-cases/code/googlenet-setters.lua b/test/test-cases/code/googlenet-setters.lua
index a8ede7ad8..9b3a5fc0c 100644
--- a/test/test-cases/code/googlenet-setters.lua
+++ b/test/test-cases/code/googlenet-setters.lua
@@ -1,6 +1,7 @@
 -- Copy of googlenet.lua which uses setters (the other googlenet has them removed)
 require 'nn'
 nGPU = 10
+nClasses = 1000
 local function inception(input_size, config)
    local concat = nn.Concat(2)
    if config[1][1] ~= 0 then
diff --git a/test/test-cases/generated-code/googlenet.lua b/test/test-cases/generated-code/googlenet.lua
index 4655b37dd..53b62e18c 100644
--- a/test/test-cases/generated-code/googlenet.lua
+++ b/test/test-cases/generated-code/googlenet.lua
@@ -3,15 +3,15 @@ require 'nn'
 local net = nn.Sequential()
 net:add(nn.SpatialConvolution(3, 64, 7, 7, 2, 2, 3, 3))
 net:add(nn.ReLU(true))
-net:add(nn.SpatialMaxPooling(3, 3, 2, 2))
-net:add(nn.SpatialConvolution(64, 64, 1, 1))
+net:add(nn.SpatialMaxPooling(3, 3, 2, 2, 0, 0))
+net:add(nn.SpatialConvolution(64, 64, 1, 1, 0))
 net:add(nn.ReLU(true))
 net:add(nn.SpatialConvolution(64, 192, 3, 3, 1, 1, 1, 1))
 net:add(nn.ReLU(true))
-net:add(nn.SpatialMaxPooling(3, 3, 2, 2))
+net:add(nn.SpatialMaxPooling(3, 3, 2, 2, 0, 0))
 
 local net_2 = nn.Sequential()
-net_2:add(nn.SpatialConvolution(192, 64, 1, 1, 1, 1))
+net_2:add(nn.SpatialConvolution(192, 64, 1, 1, 1, 1, 0))
 net_2:add(nn.ReLU(true))
 net_2:add(nn.SpatialConvolution(64, 96, 3, 3, 1, 1, 1, 1))
 net_2:add(nn.ReLU(true))
@@ -19,19 +19,19 @@ net_2:add(nn.SpatialConvolution(96, 96, 3, 3, 1, 1, 1, 1))
 net_2:add(nn.ReLU(true))
 
 local net_3 = nn.Sequential()
-net_3:add(nn.SpatialConvolution(192, 64, 1, 1, 1, 1))
+net_3:add(nn.SpatialConvolution(192, 64, 1, 1, 1, 1, 0))
 net_3:add(nn.ReLU(true))
 
 local net_4 = nn.Sequential()
-net_4:add(nn.SpatialConvolution(192, 64, 1, 1, 1, 1))
+net_4:add(nn.SpatialConvolution(192, 64, 1, 1, 1, 1, 0))
 net_4:add(nn.ReLU(true))
 net_4:add(nn.SpatialConvolution(64, 64, 3, 3, 1, 1, 1, 1))
 net_4:add(nn.ReLU(true))
 
 local net_5 = nn.Sequential()
 net_5:add(nn.SpatialZeroPadding(1, 1, 1, 1))
-net_5:add(nn.SpatialAveragePooling(3, 3, 1, 1))
-net_5:add(nn.SpatialConvolution(192, 32, 1, 1, 1, 1))
+net_5:add(nn.SpatialAveragePooling(3, 3, 1, 1, 0, 0))
+net_5:add(nn.SpatialConvolution(192, 32, 1, 1, 1, 1, 0))
 net_5:add(nn.ReLU(true))
 
 local concat_24 = nn.Concat(2)
@@ -43,17 +43,17 @@ concat_24:add(net_2)
 net:add(concat_24)
 
 local net_6 = nn.Sequential()
-net_6:add(nn.SpatialConvolution(256, 64, 1, 1, 1, 1))
+net_6:add(nn.SpatialConvolution(256, 64, 1, 1, 1, 1, 0))
 net_6:add(nn.ReLU(true))
 
 local net_7 = nn.Sequential()
-net_7:add(nn.SpatialConvolution(256, 64, 1, 1, 1, 1))
+net_7:add(nn.SpatialConvolution(256, 64, 1, 1, 1, 1, 0))
 net_7:add(nn.ReLU(true))
 net_7:add(nn.SpatialConvolution(64, 96, 3, 3, 1, 1, 1, 1))
 net_7:add(nn.ReLU(true))
 
 local net_8 = nn.Sequential()
-net_8:add(nn.SpatialConvolution(256, 64, 1, 1, 1, 1))
+net_8:add(nn.SpatialConvolution(256, 64, 1, 1, 1, 1, 0))
 net_8:add(nn.ReLU(true))
 net_8:add(nn.SpatialConvolution(64, 96, 3, 3, 1, 1, 1, 1))
 net_8:add(nn.ReLU(true))
@@ -62,8 +62,8 @@ net_8:add(nn.ReLU(true))
 
 local net_9 = nn.Sequential()
 net_9:add(nn.SpatialZeroPadding(1, 1, 1, 1))
-net_9:add(nn.SpatialAveragePooling(3, 3, 1, 1))
-net_9:add(nn.SpatialConvolution(256, 64, 1, 1, 1, 1))
+net_9:add(nn.SpatialAveragePooling(3, 3, 1, 1, 0, 0))
+net_9:add(nn.SpatialConvolution(256, 64, 1, 1, 1, 1, 0))
 net_9:add(nn.ReLU(true))
 
 local concat_41 = nn.Concat(2)
@@ -75,13 +75,13 @@ concat_41:add(net_6)
 net:add(concat_41)
 
 local net_10 = nn.Sequential()
-net_10:add(nn.SpatialConvolution(320, 128, 1, 1, 1, 1))
+net_10:add(nn.SpatialConvolution(320, 128, 1, 1, 1, 1, 0))
 net_10:add(nn.ReLU(true))
 net_10:add(nn.SpatialConvolution(128, 160, 3, 3, 1, 1, 1, 1))
 net_10:add(nn.ReLU(true))
 
 local net_11 = nn.Sequential()
-net_11:add(nn.SpatialConvolution(320, 64, 1, 1, 1, 1))
+net_11:add(nn.SpatialConvolution(320, 64, 1, 1, 1, 1, 0))
 net_11:add(nn.ReLU(true))
 net_11:add(nn.SpatialConvolution(64, 96, 3, 3, 1, 1, 1, 1))
 net_11:add(nn.ReLU(true))
@@ -90,7 +90,7 @@ net_11:add(nn.ReLU(true))
 
 local net_12 = nn.Sequential()
 net_12:add(nn.SpatialZeroPadding(1, 1, 1, 1))
-net_12:add(nn.SpatialMaxPooling(3, 3, 1, 1))
+net_12:add(nn.SpatialMaxPooling(3, 3, 1, 1, 0, 0))
 
 local concat_54 = nn.Concat(2)
 concat_54:add(net_12)
@@ -98,20 +98,20 @@ concat_54:add(net_11)
 concat_54:add(net_10)
 
 net:add(concat_54)
-net:add(nn.SpatialConvolution(576, 576, 2, 2, 2, 2))
+net:add(nn.SpatialConvolution(576, 576, 2, 2, 2, 2, 0))
 
 local net_13 = nn.Sequential()
-net_13:add(nn.SpatialConvolution(576, 224, 1, 1, 1, 1))
+net_13:add(nn.SpatialConvolution(576, 224, 1, 1, 1, 1, 0))
 net_13:add(nn.ReLU(true))
 
 local net_14 = nn.Sequential()
-net_14:add(nn.SpatialConvolution(576, 64, 1, 1, 1, 1))
+net_14:add(nn.SpatialConvolution(576, 64, 1, 1, 1, 1, 0))
 net_14:add(nn.ReLU(true))
 net_14:add(nn.SpatialConvolution(64, 96, 3, 3, 1, 1, 1, 1))
 net_14:add(nn.ReLU(true))
 
 local net_15 = nn.Sequential()
-net_15:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1))
+net_15:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1, 0))
 net_15:add(nn.ReLU(true))
 net_15:add(nn.SpatialConvolution(96, 128, 3, 3, 1, 1, 1, 1))
 net_15:add(nn.ReLU(true))
@@ -120,8 +120,8 @@ net_15:add(nn.ReLU(true))
 
 local net_16 = nn.Sequential()
 net_16:add(nn.SpatialZeroPadding(1, 1, 1, 1))
-net_16:add(nn.SpatialAveragePooling(3, 3, 1, 1))
-net_16:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1))
+net_16:add(nn.SpatialAveragePooling(3, 3, 1, 1, 0, 0))
+net_16:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1, 0))
 net_16:add(nn.ReLU(true))
 
 local concat_72 = nn.Concat(2)
@@ -133,17 +133,17 @@ concat_72:add(net_13)
 net:add(concat_72)
 
 local net_17 = nn.Sequential()
-net_17:add(nn.SpatialConvolution(576, 192, 1, 1, 1, 1))
+net_17:add(nn.SpatialConvolution(576, 192, 1, 1, 1, 1, 0))
 net_17:add(nn.ReLU(true))
 
 local net_18 = nn.Sequential()
-net_18:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1))
+net_18:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1, 0))
 net_18:add(nn.ReLU(true))
 net_18:add(nn.SpatialConvolution(96, 128, 3, 3, 1, 1, 1, 1))
 net_18:add(nn.ReLU(true))
 
 local net_19 = nn.Sequential()
-net_19:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1))
+net_19:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1, 0))
 net_19:add(nn.ReLU(true))
 net_19:add(nn.SpatialConvolution(96, 128, 3, 3, 1, 1, 1, 1))
 net_19:add(nn.ReLU(true))
@@ -152,8 +152,8 @@ net_19:add(nn.ReLU(true))
 
 local net_20 = nn.Sequential()
 net_20:add(nn.SpatialZeroPadding(1, 1, 1, 1))
-net_20:add(nn.SpatialAveragePooling(3, 3, 1, 1))
-net_20:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1))
+net_20:add(nn.SpatialAveragePooling(3, 3, 1, 1, 0, 0))
+net_20:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1, 0))
 net_20:add(nn.ReLU(true))
 
 local concat_89 = nn.Concat(2)
@@ -165,17 +165,17 @@ concat_89:add(net_17)
 net:add(concat_89)
 
 local net_21 = nn.Sequential()
-net_21:add(nn.SpatialConvolution(576, 160, 1, 1, 1, 1))
+net_21:add(nn.SpatialConvolution(576, 160, 1, 1, 1, 1, 0))
 net_21:add(nn.ReLU(true))
 
 local net_22 = nn.Sequential()
-net_22:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1))
+net_22:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1, 0))
 net_22:add(nn.ReLU(true))
 net_22:add(nn.SpatialConvolution(128, 160, 3, 3, 1, 1, 1, 1))
 net_22:add(nn.ReLU(true))
 
 local net_23 = nn.Sequential()
-net_23:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1))
+net_23:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1, 0))
 net_23:add(nn.ReLU(true))
 net_23:add(nn.SpatialConvolution(128, 160, 3, 3, 1, 1, 1, 1))
 net_23:add(nn.ReLU(true))
@@ -184,8 +184,8 @@ net_23:add(nn.ReLU(true))
 
 local net_24 = nn.Sequential()
 net_24:add(nn.SpatialZeroPadding(1, 1, 1, 1))
-net_24:add(nn.SpatialAveragePooling(3, 3, 1, 1))
-net_24:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1))
+net_24:add(nn.SpatialAveragePooling(3, 3, 1, 1, 0, 0))
+net_24:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1, 0))
 net_24:add(nn.ReLU(true))
 
 local concat_106 = nn.Concat(2)
@@ -197,17 +197,17 @@ concat_106:add(net_21)
 net:add(concat_106)
 
 local net_25 = nn.Sequential()
-net_25:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1))
+net_25:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1, 0))
 net_25:add(nn.ReLU(true))
 
 local net_26 = nn.Sequential()
-net_26:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1))
+net_26:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1, 0))
 net_26:add(nn.ReLU(true))
 net_26:add(nn.SpatialConvolution(128, 192, 3, 3, 1, 1, 1, 1))
 net_26:add(nn.ReLU(true))
 
 local net_27 = nn.Sequential()
-net_27:add(nn.SpatialConvolution(576, 160, 1, 1, 1, 1))
+net_27:add(nn.SpatialConvolution(576, 160, 1, 1, 1, 1, 0))
 net_27:add(nn.ReLU(true))
 net_27:add(nn.SpatialConvolution(160, 192, 3, 3, 1, 1, 1, 1))
 net_27:add(nn.ReLU(true))
@@ -216,8 +216,8 @@ net_27:add(nn.ReLU(true))
 
 local net_28 = nn.Sequential()
 net_28:add(nn.SpatialZeroPadding(1, 1, 1, 1))
-net_28:add(nn.SpatialAveragePooling(3, 3, 1, 1))
-net_28:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1))
+net_28:add(nn.SpatialAveragePooling(3, 3, 1, 1, 0, 0))
+net_28:add(nn.SpatialConvolution(576, 96, 1, 1, 1, 1, 0))
 net_28:add(nn.ReLU(true))
 
 local concat_123 = nn.Concat(2)
@@ -229,7 +229,7 @@ concat_123:add(net_25)
 net:add(concat_123)
 
 local net_29 = nn.Sequential()
-net_29:add(nn.SpatialConvolution(576, 192, 1, 1, 1, 1))
+net_29:add(nn.SpatialConvolution(576, 192, 1, 1, 1, 1, 0))
 net_29:add(nn.ReLU(true))
 net_29:add(nn.SpatialConvolution(192, 256, 3, 3, 1, 1, 1, 1))
 net_29:add(nn.ReLU(true))
@@ -238,11 +238,11 @@ net_29:add(nn.ReLU(true))
 
 local net_30 = nn.Sequential()
 net_30:add(nn.SpatialZeroPadding(1, 1, 1, 1))
-net_30:add(nn.SpatialMaxPooling(3, 3, 1, 1))
+net_30:add(nn.SpatialMaxPooling(3, 3, 1, 1, 0, 0))
 
 local net_31 = nn.Sequential()
-net_31:add(nn.SpatialAveragePooling(5, 5, 3, 3))
-net_31:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1))
+net_31:add(nn.SpatialAveragePooling(5, 5, 3, 3, 0, 0))
+net_31:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1, 0))
 net_31:add(nn.View())
 net_31:add(nn.Linear(2048, 768))
 net_31:add(nn.ReLU())
@@ -250,7 +250,7 @@ net_31:add(nn.Linear(768, 4))
 net_31:add(nn.LogSoftMax())
 
 local net_32 = nn.Sequential()
-net_32:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1))
+net_32:add(nn.SpatialConvolution(576, 128, 1, 1, 1, 1, 0))
 net_32:add(nn.ReLU(true))
 net_32:add(nn.SpatialConvolution(128, 192, 3, 3, 1, 1, 1, 1))
 net_32:add(nn.ReLU(true))
@@ -262,20 +262,20 @@ concat_136:add(net_29)
 
 net:add(concat_136)
 local net_33 = nn.Sequential()
-net_33:add(nn.SpatialConvolution(1024, 1024, 2, 2, 2, 2))
+net_33:add(nn.SpatialConvolution(1024, 1024, 2, 2, 2, 2, 0))
 
 local net_34 = nn.Sequential()
-net_34:add(nn.SpatialConvolution(1024, 352, 1, 1, 1, 1))
+net_34:add(nn.SpatialConvolution(1024, 352, 1, 1, 1, 1, 0))
 net_34:add(nn.ReLU(true))
 
 local net_35 = nn.Sequential()
-net_35:add(nn.SpatialConvolution(1024, 192, 1, 1, 1, 1))
+net_35:add(nn.SpatialConvolution(1024, 192, 1, 1, 1, 1, 0))
 net_35:add(nn.ReLU(true))
 net_35:add(nn.SpatialConvolution(192, 320, 3, 3, 1, 1, 1, 1))
 net_35:add(nn.ReLU(true))
 
 local net_36 = nn.Sequential()
-net_36:add(nn.SpatialConvolution(1024, 160, 1, 1, 1, 1))
+net_36:add(nn.SpatialConvolution(1024, 160, 1, 1, 1, 1, 0))
 net_36:add(nn.ReLU(true))
 net_36:add(nn.SpatialConvolution(160, 224, 3, 3, 1, 1, 1, 1))
 net_36:add(nn.ReLU(true))
@@ -284,8 +284,8 @@ net_36:add(nn.ReLU(true))
 
 local net_37 = nn.Sequential()
 net_37:add(nn.SpatialZeroPadding(1, 1, 1, 1))
-net_37:add(nn.SpatialAveragePooling(3, 3, 1, 1))
-net_37:add(nn.SpatialConvolution(1024, 128, 1, 1, 1, 1))
+net_37:add(nn.SpatialAveragePooling(3, 3, 1, 1, 0, 0))
+net_37:add(nn.SpatialConvolution(1024, 128, 1, 1, 1, 1, 0))
 net_37:add(nn.ReLU(true))
 
 local concat_154 = nn.Concat(2)
@@ -297,17 +297,17 @@ concat_154:add(net_34)
 net_33:add(concat_154)
 
 local net_38 = nn.Sequential()
-net_38:add(nn.SpatialConvolution(1024, 352, 1, 1, 1, 1))
+net_38:add(nn.SpatialConvolution(1024, 352, 1, 1, 1, 1, 0))
 net_38:add(nn.ReLU(true))
 
 local net_39 = nn.Sequential()
-net_39:add(nn.SpatialConvolution(1024, 192, 1, 1, 1, 1))
+net_39:add(nn.SpatialConvolution(1024, 192, 1, 1, 1, 1, 0))
 net_39:add(nn.ReLU(true))
 net_39:add(nn.SpatialConvolution(192, 320, 3, 3, 1, 1, 1, 1))
 net_39:add(nn.ReLU(true))
 
 local net_40 = nn.Sequential()
-net_40:add(nn.SpatialConvolution(1024, 192, 1, 1, 1, 1))
+net_40:add(nn.SpatialConvolution(1024, 192, 1, 1, 1, 1, 0))
 net_40:add(nn.ReLU(true))
 net_40:add(nn.SpatialConvolution(192, 224, 3, 3, 1, 1, 1, 1))
 net_40:add(nn.ReLU(true))
@@ -316,8 +316,8 @@ net_40:add(nn.ReLU(true))
 
 local net_41 = nn.Sequential()
 net_41:add(nn.SpatialZeroPadding(1, 1, 1, 1))
-net_41:add(nn.SpatialMaxPooling(3, 3, 1, 1))
-net_41:add(nn.SpatialConvolution(1024, 128, 1, 1, 1, 1))
+net_41:add(nn.SpatialMaxPooling(3, 3, 1, 1, 0, 0))
+net_41:add(nn.SpatialConvolution(1024, 128, 1, 1, 1, 1, 0))
 net_41:add(nn.ReLU(true))
 
 local concat_171 = nn.Concat(2)
@@ -327,7 +327,7 @@ concat_171:add(net_39)
 concat_171:add(net_38)
 
 net_33:add(concat_171)
-net_33:add(nn.SpatialAveragePooling(7, 7, 1, 1))
+net_33:add(nn.SpatialAveragePooling(7, 7, 1, 1, 0, 0))
 net_33:add(nn.View())
 net_33:add(nn.Linear(1024, 4))
 net_33:add(nn.LogSoftMax())
diff --git a/test/test-cases/generated-code/overfeat.lua b/test/test-cases/generated-code/overfeat.lua
index eee5515ea..405379a2c 100644
--- a/test/test-cases/generated-code/overfeat.lua
+++ b/test/test-cases/generated-code/overfeat.lua
@@ -1,19 +1,19 @@
 require 'nn'
 
 local net = nn.Sequential()
-net:add(nn.SpatialConvolution(3, 96, 11, 11, 4, 4))
+net:add(nn.SpatialConvolution(3, 96, 11, 11, 4, 4, 0))
 net:add(nn.ReLU(true))
-net:add(nn.SpatialMaxPooling(2, 2, 2, 2))
-net:add(nn.SpatialConvolution(96, 256, 5, 5, 1, 1))
+net:add(nn.SpatialMaxPooling(2, 2, 2, 2, 0, 0))
+net:add(nn.SpatialConvolution(96, 256, 5, 5, 1, 1, 0))
 net:add(nn.ReLU(true))
-net:add(nn.SpatialMaxPooling(2, 2, 2, 2))
+net:add(nn.SpatialMaxPooling(2, 2, 2, 2, 0, 0))
 net:add(nn.SpatialConvolution(256, 512, 3, 3, 1, 1, 1, 1))
 net:add(nn.ReLU(true))
 net:add(nn.SpatialConvolution(512, 1024, 3, 3, 1, 1, 1, 1))
 net:add(nn.ReLU(true))
 net:add(nn.SpatialConvolution(1024, 1024, 3, 3, 1, 1, 1, 1))
 net:add(nn.ReLU(true))
-net:add(nn.SpatialMaxPooling(2, 2, 2, 2))
+net:add(nn.SpatialMaxPooling(2, 2, 2, 2, 0, 0))
 net:add(nn.View())
 net:add(nn.Dropout(0.5))
 net:add(nn.Linear(25600, 3072))
@@ -24,4 +24,4 @@ net:add(nn.Threshold(0, 0.000001))
 net:add(nn.Linear(4096, 7))
 net:add(nn.LogSoftMax())
 
-return net
+return net
\ No newline at end of file
diff --git a/test/test-cases/models/alexnetowt.yml b/test/test-cases/models/alexnetowt.yml
index 7e126f0e6..b7e9e5547 100644
--- a/test/test-cases/models/alexnetowt.yml
+++ b/test/test-cases/models/alexnetowt.yml
@@ -1,204 +1,194 @@
-- type: View
-  id: /a/0
+- type: SpatialConvolution
+  id: /P/0
   next:
-    - /a/y
+    - /P/2
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    sizes: 9216
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 384
+    nInputPlane: 192
 - type: ReLU
-  id: /a/3
+  id: /P/2
+  next:
+    - /P/fX
+  attributes:
+    p: true
+- type: Dropout
+  id: /P/6
   next:
-    - /a/u
+    - /P/C
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
+    v1: ''
+    inplace: ''
+    p: 0.5
 - type: Linear
-  id: /a/4o
+  id: /P/8p
   next:
-    - /a/L
+    - /P/S8
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    output: 4096
-    input: 9216
+    bias: ''
+    outputSize: 5
+    inputSize: 4096
 - type: SpatialConvolution
-  id: /a/9
+  id: /P/A
   next:
-    - /a/z
+    - /P/j
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    strideHeight: 1
-    strideWidth: 1
-    kernelHeight: 5
-    kernelWidth: 5
+    padH: 2
+    padW: 2
+    dH: 1
+    dW: 1
+    kH: 5
+    kW: 5
     nOutputPlane: 192
     nInputPlane: 64
-- type: SpatialConvolution
-  id: /a/C
+- type: Linear
+  id: /P/C
   next:
-    - /a/J
+    - /P/mQ
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    strideHeight: 4
-    strideWidth: 4
-    kernelHeight: 11
-    kernelWidth: 11
-    nOutputPlane: 64
-    nInputPlane: 3
-- type: LogSoftMax
-  id: /a/E0
-  next: []
-  attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
+    bias: ''
+    outputSize: 4096
+    inputSize: 9216
 - type: ReLU
-  id: /a/J
+  id: /P/F
   next:
-    - /a/j
+    - /P/R
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-- type: ReLU
-  id: /a/L
+    p: true
+- type: Linear
+  id: /P/H
   next:
-    - /a/l
+    - /P/e
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-- type: SpatialConvolution
-  id: /a/U
+    bias: ''
+    outputSize: 4096
+    inputSize: 4096
+- type: SpatialMaxPooling
+  id: /P/J
   next:
-    - /a/e
+    - /P/A
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    strideHeight: 1
-    strideWidth: 1
-    kernelHeight: 3
-    kernelWidth: 3
-    nOutputPlane: 256
-    nInputPlane: 384
-- type: ReLU
-  id: /a/X
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 2
+    dW: 2
+    kH: 3
+    kW: 3
+- type: Dropout
+  id: /P/L
   next:
-    - /a/U
+    - /P/H
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-- type: ReLU
-  id: /a/e
+    v1: ''
+    inplace: ''
+    p: 0.5
+- type: View
+  id: /P/M
   next:
-    - /a/q
+    - /P/6
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-- type: SpatialMaxPooling
-  id: /a/h
+    numInputDims: null
+    params: 9216
+- type: SpatialConvolution
+  id: /P/R
   next:
-    - /a/t
+    - /P/i
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    strideHeight: 2
-    strideWidth: 2
-    kernelHeight: 3
-    kernelWidth: 3
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 256
+    nInputPlane: 256
+- type: LogSoftMax
+  id: /P/S8
+  next: []
+  attributes: {}
 - type: SpatialMaxPooling
-  id: /a/j
-  next:
-    - /a/9
-  attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    strideHeight: 2
-    strideWidth: 2
-    kernelHeight: 3
-    kernelWidth: 3
-- type: Dropout
-  id: /a/l
+  id: /P/c
   next:
-    - /a/o
+    - /P/0
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    probability: 0.5
-- type: Linear
-  id: /a/o
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 2
+    dW: 2
+    kH: 3
+    kW: 3
+- type: SpatialConvolution
+  id: /P/d
   next:
-    - /a/r
+    - /P/q
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    output: 4096
-    input: 4096
-- type: Linear
-  id: /a/p
+    padH: 2
+    padW: 2
+    dH: 4
+    dW: 4
+    kH: 11
+    kW: 11
+    nOutputPlane: 64
+    nInputPlane: 3
+- type: ReLU
+  id: /P/e
   next:
-    - /a/E0
+    - /P/8p
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    output: 5
-    input: 4096
+    p: ''
 - type: SpatialConvolution
-  id: /a/q
+  id: /P/fX
   next:
-    - /a/3
+    - /P/F
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    strideHeight: 1
-    strideWidth: 1
-    kernelHeight: 3
-    kernelWidth: 3
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
     nOutputPlane: 256
-    nInputPlane: 256
+    nInputPlane: 384
 - type: ReLU
-  id: /a/r
+  id: /P/i
   next:
-    - /a/p
+    - /P/n5
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-- type: SpatialConvolution
-  id: /a/t
+    p: true
+- type: ReLU
+  id: /P/j
   next:
-    - /a/X
+    - /P/c
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    strideHeight: 1
-    strideWidth: 1
-    kernelHeight: 3
-    kernelWidth: 3
-    nOutputPlane: 384
-    nInputPlane: 192
-- type: SpatialMaxPooling
-  id: /a/u
+    p: true
+- type: ReLU
+  id: /P/mQ
   next:
-    - /a/0
+    - /P/L
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    strideHeight: 2
-    strideWidth: 2
-    kernelHeight: 3
-    kernelWidth: 3
-- type: Dropout
-  id: /a/y
+    p: ''
+- type: SpatialMaxPooling
+  id: /P/n5
   next:
-    - /a/4o
+    - /P/M
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    probability: 0.5
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 2
+    dW: 2
+    kH: 3
+    kW: 3
 - type: ReLU
-  id: /a/z
+  id: /P/q
   next:
-    - /a/h
+    - /P/J
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
+    p: true
diff --git a/test/test-cases/models/alexnetowtbn.yml b/test/test-cases/models/alexnetowtbn.yml
new file mode 100644
index 000000000..8fcf82670
--- /dev/null
+++ b/test/test-cases/models/alexnetowtbn.yml
@@ -0,0 +1,257 @@
+- type: SpatialConvolution
+  id: /A/0
+  next:
+    - /A/w
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 384
+    nInputPlane: 192
+- type: LogSoftMax
+  id: /A/2
+  next: []
+  attributes: {}
+- type: ReLU
+  id: /A/3
+  next:
+    - /A/H
+  attributes:
+    p: ''
+- type: ReLU
+  id: /A/6
+  next:
+    - /A/NJ
+  attributes:
+    p: true
+- type: SpatialMaxPooling
+  id: /A/7
+  next:
+    - /A/G
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 2
+    dW: 2
+    kH: 3
+    kW: 3
+- type: BatchNormalization
+  id: /A/A
+  next:
+    - /A/r7
+  attributes:
+    momentum: ''
+    affine: ''
+    eps: 0.001
+    nOutput: 4096
+- type: BatchNormalization
+  id: /A/B
+  next:
+    - /A/3
+  attributes:
+    momentum: ''
+    affine: ''
+    eps: 0.001
+    nOutput: 4096
+- type: ReLU
+  id: /A/F
+  next:
+    - /A/q
+  attributes:
+    p: true
+- type: View
+  id: /A/G
+  next:
+    - /A/a
+  attributes:
+    numInputDims: null
+    params: 9216
+- type: Dropout
+  id: /A/H
+  next:
+    - /A/i
+  attributes:
+    v1: ''
+    inplace: ''
+    p: 0.5
+- type: SpatialBatchNormalization
+  id: /A/I
+  next:
+    - /A/t
+  attributes:
+    momentum: ''
+    affine: ''
+    eps: 0.001
+    nOutput: 192
+- type: Linear
+  id: /A/M
+  next:
+    - /A/B
+  attributes:
+    bias: ''
+    outputSize: 4096
+    inputSize: 9216
+- type: SpatialConvolution
+  id: /A/NJ
+  next:
+    - /A/PF
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 256
+    nInputPlane: 256
+- type: SpatialBatchNormalization
+  id: /A/PF
+  next:
+    - /A/X
+  attributes:
+    momentum: ''
+    affine: ''
+    eps: 0.001
+    nOutput: 256
+- type: ReLU
+  id: /A/X
+  next:
+    - /A/7
+  attributes:
+    p: true
+- type: Dropout
+  id: /A/a
+  next:
+    - /A/M
+  attributes:
+    v1: ''
+    inplace: ''
+    p: 0.5
+- type: ReLU
+  id: /A/d
+  next:
+    - /A/n
+  attributes:
+    p: true
+- type: Linear
+  id: /A/h
+  next:
+    - /A/2
+  attributes:
+    bias: ''
+    outputSize: 10
+    inputSize: 4096
+- type: Linear
+  id: /A/i
+  next:
+    - /A/A
+  attributes:
+    bias: ''
+    outputSize: 4096
+    inputSize: 4096
+- type: SpatialBatchNormalization
+  id: /A/k
+  next:
+    - /A/6
+  attributes:
+    momentum: ''
+    affine: ''
+    eps: 0.001
+    nOutput: 256
+- type: SpatialBatchNormalization
+  id: /A/l
+  next:
+    - /A/F
+  attributes:
+    momentum: ''
+    affine: ''
+    eps: 0.001
+    nOutput: 64
+- type: SpatialConvolution
+  id: /A/n
+  next:
+    - /A/k
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 256
+    nInputPlane: 384
+- type: SpatialMaxPooling
+  id: /A/nm
+  next:
+    - /A/0
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 2
+    dW: 2
+    kH: 3
+    kW: 3
+- type: SpatialMaxPooling
+  id: /A/q
+  next:
+    - /A/y
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 2
+    dW: 2
+    kH: 3
+    kW: 3
+- type: SpatialConvolution
+  id: /A/r
+  next:
+    - /A/l
+  attributes:
+    padH: 2
+    padW: 2
+    dH: 4
+    dW: 4
+    kH: 11
+    kW: 11
+    nOutputPlane: 64
+    nInputPlane: 3
+- type: ReLU
+  id: /A/r7
+  next:
+    - /A/h
+  attributes:
+    p: ''
+- type: ReLU
+  id: /A/t
+  next:
+    - /A/nm
+  attributes:
+    p: true
+- type: SpatialBatchNormalization
+  id: /A/w
+  next:
+    - /A/d
+  attributes:
+    momentum: ''
+    affine: ''
+    eps: 0.001
+    nOutput: 384
+- type: SpatialConvolution
+  id: /A/y
+  next:
+    - /A/I
+  attributes:
+    padH: 2
+    padW: 2
+    dH: 1
+    dW: 1
+    kH: 5
+    kW: 5
+    nOutputPlane: 192
+    nInputPlane: 64
diff --git a/test/test-cases/models/basic-transfers.yml b/test/test-cases/models/basic-transfers.yml
index 3ba18ef2f..76eb14b79 100644
--- a/test/test-cases/models/basic-transfers.yml
+++ b/test/test-cases/models/basic-transfers.yml
@@ -1,60 +1,76 @@
 - type: Reshape
-  id: 0
+  id: /J/1
   next:
-    - 2
+    - /J/5
   attributes:
-    dimensions: 100
-- type: SoftMax
-  id: 1
-  next: []
-  attributes: {}
+    params: 100
 - type: Linear
-  id: 2
+  id: /J/5
   next:
-    - 5
+    - /J/x
   attributes:
-    output: 300
-- type: ReLU
-  id: 3
-  next:
-    - 6
-  attributes: {}
+    bias: ''
+    outputSize: 300
+    inputSize: 100
 - type: Sigmoid
-  id: 4
+  id: /J/F
   next:
-    - 7
+    - /J/z
   attributes: {}
-- type: RReLU
-  id: 5
+- type: ReLU
+  id: /J/G
   next:
-    - 10
+    - /J/q
+  attributes:
+    p: ''
+- type: SoftMax
+  id: /J/Y
+  next: []
   attributes: {}
-- type: Linear
-  id: 6
+- type: LeakyReLU
+  id: /J/c
   next:
-    - 4
+    - /J/m
   attributes:
-    output: 100
+    negval: ''
+    ip: false
 - type: Linear
-  id: 7
+  id: /J/d
   next:
-    - 8
+    - /J/G
   attributes:
-    output: 120
-- type: LeakyReLU
-  id: 8
+    bias: ''
+    outputSize: 100
+    inputSize: 300
+- type: Linear
+  id: /J/m
   next:
-    - 9
-  attributes: {}
+    - /J/Y
+  attributes:
+    bias: ''
+    outputSize: 5
+    inputSize: 120
 - type: Linear
-  id: 9
+  id: /J/q
+  next:
+    - /J/F
+  attributes:
+    bias: ''
+    outputSize: 100
+    inputSize: 100
+- type: RReLU
+  id: /J/x
   next:
-    - 1
+    - /J/d
   attributes:
-    output: 5
+    l: ''
+    u: ''
+    ip: false
 - type: Linear
-  id: 10
+  id: /J/z
   next:
-    - 3
+    - /J/c
   attributes:
-    output: 100
+    bias: ''
+    outputSize: 120
+    inputSize: 100
diff --git a/test/test-cases/models/basic.yml b/test/test-cases/models/basic.yml
index 845d535c5..e0bb23216 100644
--- a/test/test-cases/models/basic.yml
+++ b/test/test-cases/models/basic.yml
@@ -1,22 +1,29 @@
-- type: Linear
-  id: 0
-  next: []
+- type: Reshape
+  id: /x/3
+  next:
+    - /x/K
   attributes:
-    output: 10
+    params: 100
 - type: Linear
-  id: 1
+  id: /x/K
   next:
-    - 2
+    - /x/e
   attributes:
-    output: 300
+    bias: ''
+    outputSize: 300
+    inputSize: 100
+- type: Linear
+  id: /x/N
+  next: []
+  attributes:
+    bias: ''
+    outputSize: 10
+    inputSize: 300
 - type: HardTanh
-  id: 2
-  next:
-    - 0
-  attributes: {}
-- type: Reshape
-  id: 3
+  id: /x/e
   next:
-    - 1
+    - /x/N
   attributes:
-    dimensions: 100
+    min_value: ''
+    max_value: 1
+    inplace: ''
diff --git a/test/test-cases/models/basic2.yml b/test/test-cases/models/basic2.yml
index b79685d96..6c8ff85cb 100644
--- a/test/test-cases/models/basic2.yml
+++ b/test/test-cases/models/basic2.yml
@@ -1,22 +1,26 @@
-- type: Linear
-  id: 4
-  next:
-    - 7
-  attributes:
-    output: 300
 - type: Reshape
-  id: 5
+  id: /Y/0
   next:
-    - 4
+    - /Y/y
   attributes:
-    dimensions: 100
+    params: 100
 - type: Linear
-  id: 6
+  id: /Y/Z
   next: []
   attributes:
-    output: 10
+    bias: ''
+    outputSize: 10
+    inputSize: 300
 - type: Tanh
-  id: 7
+  id: /Y/p
   next:
-    - 6
+    - /Y/Z
   attributes: {}
+- type: Linear
+  id: /Y/y
+  next:
+    - /Y/p
+  attributes:
+    bias: ''
+    outputSize: 300
+    inputSize: 100
diff --git a/test/test-cases/models/concat-parallel-utils.yml b/test/test-cases/models/concat-parallel-utils.yml
new file mode 100644
index 000000000..88fdd368a
--- /dev/null
+++ b/test/test-cases/models/concat-parallel-utils.yml
@@ -0,0 +1,77 @@
+- type: Linear
+  id: /l/1
+  next:
+    - /l/s
+  attributes:
+    calculateDimensionality: function calcDims(layer) return layer.output; end
+    dimensionalityTransform: custom
+    output: 50
+- type: Reshape
+  id: /l/8
+  next:
+    - /l/i
+    - /l/D
+  attributes:
+    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
+    dimensionalityTransform: same
+    dimensions: 100
+- type: Tanh
+  id: /l/9
+  next:
+    - /l/k
+  attributes:
+    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
+    dimensionalityTransform: same
+- type: Linear
+  id: /l/D
+  next:
+    - /l/9
+  attributes:
+    calculateDimensionality: function calcDims(layer) return layer.output; end
+    dimensionalityTransform: custom
+    output: 150
+- type: Tanh
+  id: /l/X
+  next:
+    - /l/a
+  attributes:
+    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
+    dimensionalityTransform: same
+- type: Linear
+  id: /l/a
+  next: []
+  attributes:
+    calculateDimensionality: function calcDims(layer) return layer.output; end
+    dimensionalityTransform: custom
+    output: 7
+- type: Tanh
+  id: /l/f
+  next:
+    - /l/1
+  attributes:
+    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
+    dimensionalityTransform: same
+- type: Linear
+  id: /l/i
+  next:
+    - /l/f
+  attributes:
+    calculateDimensionality: function calcDims(layer) return layer.output; end
+    dimensionalityTransform: custom
+    output: 150
+- type: Linear
+  id: /l/k
+  next:
+    - /l/s
+  attributes:
+    calculateDimensionality: function calcDims(layer) return layer.output; end
+    dimensionalityTransform: custom
+    output: 30
+- type: Concat
+  id: /l/s
+  next:
+    - /l/X
+  attributes:
+    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
+    dimensionalityTransform: same
+    dim: 1
diff --git a/test/test-cases/models/concat-parallel.yml b/test/test-cases/models/concat-parallel.yml
index 8cb73ca8d..06b84fc77 100644
--- a/test/test-cases/models/concat-parallel.yml
+++ b/test/test-cases/models/concat-parallel.yml
@@ -1,65 +1,67 @@
-- type: Reshape
-  id: 1
+- type: Linear
+  id: /p/H
+  next:
+    - /p/V
   attributes:
-      dimensions: 100
+    bias: ''
+    outputSize: 150
+    inputSize: 100
+- type: Reshape
+  id: /p/L
   next:
-      - 2
-      - 3
-
-# Left side
-- type: Linear
-  id: 2
+    - /p/M
+    - /p/H
   attributes:
-      output: 150
+    params: 100
+- type: Linear
+  id: /p/M
   next:
-      - 4
-
+    - /p/P
+  attributes:
+    bias: ''
+    outputSize: 150
+    inputSize: 100
 - type: Tanh
-  id: 4
+  id: /p/P
   next:
-      - 6
-
+    - /p/W
+  attributes: {}
 - type: Linear
-  id: 6
-  attributes:
-      output: 50
+  id: /p/R
   next:
-      - 8
-
-# Right side
-- type: Linear
-  id: 3
+    - /p/n
   attributes:
-      output: 150
-  next:
-      - 5
-
+    bias: ''
+    outputSize: 30
+    inputSize: 150
 - type: Tanh
-  id: 5
+  id: /p/V
   next:
-      - 7
-
+    - /p/R
+  attributes: {}
 - type: Linear
-  id: 7
-  attributes:
-      output: 30
+  id: /p/W
   next:
-      - 8
-
-# Center
-- type: Concat
-  id: 8
+    - /p/n
+  attributes:
+    bias: ''
+    outputSize: 50
+    inputSize: 150
+- type: Linear
+  id: /p/Zj
+  next: []
   attributes:
-      dim: 1
+    bias: ''
+    outputSize: 7
+    inputSize: 80
+- type: Concat
+  id: /p/n
   next:
-      - 9
-
+    - /p/w
+  attributes:
+    dimension: 1
 - type: Tanh
-  id: 9
+  id: /p/w
   next:
-      - 10
-
-- type: Linear
-  id: 10
-  attributes:
-      output: 7
+    - /p/Zj
+  attributes: {}
diff --git a/test/test-cases/models/concat-seq.yml b/test/test-cases/models/concat-seq.yml
index ab7c732aa..706202fa2 100644
--- a/test/test-cases/models/concat-seq.yml
+++ b/test/test-cases/models/concat-seq.yml
@@ -1,39 +1,47 @@
+- type: Linear
+  id: /u/1
+  next:
+    - /u/T
+  attributes:
+    bias: ''
+    outputSize: 30
+    inputSize: 150
+- type: Linear
+  id: /u/2
+  next:
+    - /u/M
+  attributes:
+    bias: ''
+    outputSize: 150
+    inputSize: 100
 - type: Tanh
-  id: 8
+  id: /u/G
   next:
-    - 12
+    - /u/1
   attributes: {}
 - type: Tanh
-  id: 9
+  id: /u/M
   next:
-    - 14
+    - /u/k
   attributes: {}
-- type: Linear
-  id: 10
-  next:
-    - 8
-  attributes:
-    output: 150
 - type: Concat
-  id: 11
+  id: /u/T
   next: []
   attributes:
-    dim: 1
-- type: Linear
-  id: 12
-  next:
-    - 11
-  attributes:
-    output: 50
+    dimension: 1
 - type: Linear
-  id: 13
+  id: /u/k
   next:
-    - 9
+    - /u/T
   attributes:
-    output: 150
+    bias: ''
+    outputSize: 50
+    inputSize: 150
 - type: Linear
-  id: 14
+  id: /u/q
   next:
-    - 11
+    - /u/G
   attributes:
-    output: 30
+    bias: ''
+    outputSize: 150
+    inputSize: 100
diff --git a/test/test-cases/models/concat-y-utils.yml b/test/test-cases/models/concat-y-utils.yml
new file mode 100644
index 000000000..17f0daa5c
--- /dev/null
+++ b/test/test-cases/models/concat-y-utils.yml
@@ -0,0 +1,68 @@
+- type: Linear
+  id: /Z/1
+  next:
+    - /Z/E
+  attributes:
+    calculateDimensionality: function calcDims(layer) return layer.output; end
+    dimensionalityTransform: custom
+    output: 30
+- type: Tanh
+  id: /Z/3
+  next:
+    - /Z/a
+  attributes:
+    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
+    dimensionalityTransform: same
+- type: Linear
+  id: /Z/7
+  next:
+    - /Z/o
+  attributes:
+    calculateDimensionality: function calcDims(layer) return layer.output; end
+    dimensionalityTransform: custom
+    output: 150
+- type: Concat
+  id: /Z/E
+  next:
+    - /Z/M
+  attributes:
+    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
+    dimensionalityTransform: same
+    dim: 1
+- type: Tanh
+  id: /Z/M
+  next:
+    - /Z/n
+  attributes:
+    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
+    dimensionalityTransform: same
+- type: Linear
+  id: /Z/a
+  next:
+    - /Z/E
+  attributes:
+    calculateDimensionality: function calcDims(layer) return layer.output; end
+    dimensionalityTransform: custom
+    output: 50
+- type: Linear
+  id: /Z/n
+  next: []
+  attributes:
+    calculateDimensionality: function calcDims(layer) return layer.output; end
+    dimensionalityTransform: custom
+    output: 7
+- type: Tanh
+  id: /Z/o
+  next:
+    - /Z/1
+  attributes:
+    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
+    dimensionalityTransform: same
+- type: Linear
+  id: /Z/t
+  next:
+    - /Z/3
+  attributes:
+    calculateDimensionality: function calcDims(layer) return layer.output; end
+    dimensionalityTransform: custom
+    output: 150
diff --git a/test/test-cases/models/concat-y.yml b/test/test-cases/models/concat-y.yml
index 4bfb48b55..1f21fe25e 100644
--- a/test/test-cases/models/concat-y.yml
+++ b/test/test-cases/models/concat-y.yml
@@ -1,57 +1,60 @@
-# Left side
-- type: Linear
-  id: 2
-  attributes:
-      output: 150
+- type: Tanh
+  id: /t/5
   next:
-      - 4
-
+    - /t/H
+  attributes: {}
 - type: Tanh
-  id: 4
+  id: /t/D
   next:
-      - 6
-
+    - /t/b
+  attributes: {}
 - type: Linear
-  id: 6
+  id: /t/H
+  next: []
   attributes:
-      output: 50
-  next:
-      - 8
-
-# Right side
+    bias: ''
+    outputSize: 7
+    inputSize: 80
 - type: Linear
-  id: 3
+  id: /t/I
+  next:
+    - /t/O
   attributes:
-      output: 150
+    bias: ''
+    outputSize: 30
+    inputSize: 150
+- type: Linear
+  id: /t/M
   next:
-      - 5
-
-- type: Tanh
-  id: 5
+    - /t/j
+  attributes:
+    bias: ''
+    outputSize: 150
+    inputSize: 100
+- type: Concat
+  id: /t/O
   next:
-      - 7
-
-- type: Linear
-  id: 7
+    - /t/5
   attributes:
-      output: 30
+    dimension: 1
+- type: Linear
+  id: /t/b
   next:
-      - 8
-
-# Center
-- type: Concat
-  id: 8
+    - /t/O
   attributes:
-      dim: 1
+    bias: ''
+    outputSize: 50
+    inputSize: 150
+- type: Linear
+  id: /t/e
   next:
-      - 9
-
+    - /t/D
+  attributes:
+    bias: ''
+    outputSize: 150
+    inputSize: 100
 - type: Tanh
-  id: 9
+  id: /t/j
   next:
-      - 10
-
-- type: Linear
-  id: 10
-  attributes:
-      output: 7
+    - /t/I
+  attributes: {}
diff --git a/test/test-cases/models/concat.yml b/test/test-cases/models/concat.yml
index fbaad5d72..8bcc3bd4a 100644
--- a/test/test-cases/models/concat.yml
+++ b/test/test-cases/models/concat.yml
@@ -1,24 +1,28 @@
-- type: Linear
-  id: 0
-  next:
-    - 1
-  attributes:
-    output: 3
 - type: Concat
-  id: 1
+  id: /T/3
   next: []
   attributes:
-    dim: 1
+    dimension: 1
+- type: Linear
+  id: /T/G
+  next:
+    - /T/3
+  attributes:
+    bias: ''
+    outputSize: 7
+    inputSize: 5
 - type: Linear
-  id: 2
+  id: /T/J
   next:
-    - 1
+    - /T/3
   attributes:
-    output: 7
+    bias: ''
+    outputSize: 3
+    inputSize: 5
 - type: Reshape
-  id: 3
+  id: /T/o
   next:
-    - 2
-    - 0
+    - /T/G
+    - /T/J
   attributes:
-    dimensions: 5
+    params: 5
diff --git a/test/test-cases/models/googlenet-setters.yml b/test/test-cases/models/googlenet-setters.yml
new file mode 100644
index 000000000..b703e572e
--- /dev/null
+++ b/test/test-cases/models/googlenet-setters.yml
@@ -0,0 +1,1765 @@
+- type: SpatialConvolution
+  id: /D/00
+  next:
+    - /D/Wf
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 192
+    nInputPlane: 576
+- type: View
+  id: /D/0U
+  next:
+    - /D/TU
+  attributes:
+    params: 2048
+    numInputDims: 3
+- type: ReLU
+  id: /D/1
+  next:
+    - /D/d
+  attributes:
+    p: true
+- type: SpatialAveragePooling
+  id: /D/1L
+  next:
+    - /D/UO
+  attributes:
+    padW: 0
+    padH: 0
+    count_include_pad: true
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    ceil_mode: true
+- type: SpatialConvolution
+  id: /D/1X
+  next:
+    - /D/2v
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 128
+    nInputPlane: 96
+- type: ReLU
+  id: /D/1e
+  next:
+    - /D/4Q
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /D/1u
+  next:
+    - /D/v2
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 96
+    nInputPlane: 64
+- type: SpatialConvolution
+  id: /D/1v
+  next:
+    - /D/Ln
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 96
+    nInputPlane: 576
+- type: SpatialConvolution
+  id: /D/1y
+  next:
+    - /D/H
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 64
+    nInputPlane: 256
+- type: SpatialConvolution
+  id: /D/2
+  next:
+    - /D/o
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 64
+    nInputPlane: 64
+- type: Concat
+  id: /D/2D
+  next:
+    - /D/HF
+  attributes:
+    dimension: 2
+- type: SpatialZeroPadding
+  id: /D/2f
+  next:
+    - /D/W5
+  attributes:
+    pad_b: 1
+    pad_t: 1
+    pad_r: 1
+    pad_l: 1
+- type: ReLU
+  id: /D/2v
+  next:
+    - /D/Pp
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /D/32
+  next:
+    - /D/jP
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 352
+    nInputPlane: 1024
+- type: SpatialConvolution
+  id: /D/42
+  next:
+    - /D/nn
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 96
+    nInputPlane: 576
+- type: SpatialConvolution
+  id: /D/4N
+  next:
+    - /D/42
+    - /D/U7
+    - /D/s
+    - /D/ht
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 2
+    dW: 2
+    kH: 2
+    kW: 2
+    nOutputPlane: 576
+    nInputPlane: 576
+- type: SpatialConvolution
+  id: /D/4Q
+  next:
+    - /D/CU
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 128
+    nInputPlane: 96
+- type: SpatialConvolution
+  id: /D/4l
+  next:
+    - /D/ru
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 128
+    nInputPlane: 320
+- type: ReLU
+  id: /D/4v
+  next:
+    - /D/Pu
+  attributes:
+    p: true
+- type: SpatialZeroPadding
+  id: /D/50
+  next:
+    - /D/1L
+  attributes:
+    pad_b: 1
+    pad_t: 1
+    pad_r: 1
+    pad_l: 1
+- type: ReLU
+  id: /D/5v
+  next:
+    - /D/a5
+  attributes:
+    p: true
+- type: SpatialZeroPadding
+  id: /D/6Q
+  next:
+    - /D/Sx
+  attributes:
+    pad_b: 1
+    pad_t: 1
+    pad_r: 1
+    pad_l: 1
+- type: ReLU
+  id: /D/7
+  next:
+    - /D/u
+  attributes:
+    p: true
+- type: ReLU
+  id: /D/7O
+  next:
+    - /D/Pp
+  attributes:
+    p: true
+- type: ReLU
+  id: /D/8
+  next:
+    - /D/dr
+  attributes:
+    p: true
+- type: ReLU
+  id: /D/9
+  next:
+    - /D/C
+  attributes:
+    p: true
+- type: ReLU
+  id: /D/9O
+  next:
+    - /D/Cn
+  attributes:
+    p: true
+- type: SpatialZeroPadding
+  id: /D/9c
+  next:
+    - /D/CK
+  attributes:
+    pad_b: 1
+    pad_t: 1
+    pad_r: 1
+    pad_l: 1
+- type: SpatialConvolution
+  id: /D/9q
+  next:
+    - /D/P3
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 320
+    nInputPlane: 192
+- type: SpatialConvolution
+  id: /D/A
+  next:
+    - /D/zo
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 96
+    nInputPlane: 64
+- type: SpatialAveragePooling
+  id: /D/A3
+  next:
+    - /D/Cf
+  attributes:
+    padW: 0
+    padH: 0
+    count_include_pad: true
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    ceil_mode: true
+- type: SpatialConvolution
+  id: /D/AW
+  next:
+    - /D/DN
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 160
+    nInputPlane: 128
+- type: SpatialConvolution
+  id: /D/B
+  next:
+    - /D/U
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 32
+    nInputPlane: 192
+- type: SpatialConvolution
+  id: /D/C
+  next:
+    - /D/1
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 96
+    nInputPlane: 96
+- type: SpatialZeroPadding
+  id: /D/C9
+  next:
+    - /D/W
+  attributes:
+    pad_b: 1
+    pad_t: 1
+    pad_r: 1
+    pad_l: 1
+- type: SpatialMaxPooling
+  id: /D/CK
+  next:
+    - /D/l9
+  attributes:
+    padW: 0
+    padH: 0
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    ceil_mode: true
+- type: ReLU
+  id: /D/CU
+  next:
+    - /D/f9
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /D/Cf
+  next:
+    - /D/uh
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 128
+    nInputPlane: 576
+- type: Concat
+  id: /D/Cn
+  next:
+    - /D/gd
+    - /D/HO
+    - /D/2f
+    - /D/xI
+  attributes:
+    dimension: 2
+- type: Concat
+  id: /D/Co
+  next: []
+  attributes:
+    dimension: 2
+- type: SpatialConvolution
+  id: /D/Ct
+  next:
+    - /D/bb
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 192
+    nInputPlane: 128
+- type: SpatialConvolution
+  id: /D/D
+  next:
+    - /D/S8
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 64
+    nInputPlane: 192
+- type: SpatialConvolution
+  id: /D/D2
+  next:
+    - /D/RH
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 320
+    nInputPlane: 192
+- type: LogSoftMax
+  id: /D/DH
+  next:
+    - /D/Co
+  attributes: {}
+- type: ReLU
+  id: /D/DN
+  next:
+    - /D/Cn
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /D/Dx
+  next:
+    - /D/Wo
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 128
+    nInputPlane: 128
+- type: SpatialConvolution
+  id: /D/Ee
+  next:
+    - /D/pz
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 64
+    nInputPlane: 320
+- type: SpatialConvolution
+  id: /D/Eg
+  next:
+    - /D/gW
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 96
+    nInputPlane: 96
+- type: SpatialMaxPooling
+  id: /D/F3
+  next:
+    - /D/Q0
+  attributes:
+    padW: 0
+    padH: 0
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    ceil_mode: true
+- type: ReLU
+  id: /D/Fa
+  next:
+    - /D/my
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /D/Ff
+  next:
+    - /D/4v
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 224
+    nInputPlane: 192
+- type: ReLU
+  id: /D/GR
+  next:
+    - /D/Gg
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /D/Gb
+  next:
+    - /D/Lj
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 96
+    nInputPlane: 576
+- type: ReLU
+  id: /D/Gc
+  next:
+    - /D/M
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /D/Gg
+  next:
+    - /D/a0
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 256
+    nInputPlane: 192
+- type: SpatialConvolution
+  id: /D/Gs
+  next:
+    - /D/0U
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 128
+    nInputPlane: 576
+- type: ReLU
+  id: /D/H
+  next:
+    - /D/A
+  attributes:
+    p: true
+- type: SpatialAveragePooling
+  id: /D/HF
+  next:
+    - /D/Ky
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    count_include_pad: true
+    dH: 1
+    dW: 1
+    kH: 7
+    kW: 7
+- type: SpatialConvolution
+  id: /D/HO
+  next:
+    - /D/Lu
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 96
+    nInputPlane: 576
+- type: SpatialConvolution
+  id: /D/Hg
+  next:
+    - /D/L8
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 96
+    nInputPlane: 64
+- type: SpatialAveragePooling
+  id: /D/Hz
+  next:
+    - /D/Gs
+  attributes:
+    padW: 0
+    padH: 0
+    count_include_pad: true
+    dH: 3
+    dW: 3
+    kH: 5
+    kW: 5
+    ceil_mode: true
+- type: SpatialConvolution
+  id: /D/I
+  next:
+    - /D/7
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 192
+    nInputPlane: 64
+- type: ReLU
+  id: /D/I5
+  next:
+    - /D/AW
+  attributes:
+    p: true
+- type: SpatialMaxPooling
+  id: /D/IN
+  next:
+    - /D/dt
+  attributes:
+    padW: 0
+    padH: 0
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    ceil_mode: true
+- type: ReLU
+  id: /D/Ir
+  next:
+    - /D/tE
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /D/JD
+  next:
+    - /D/hC
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 192
+    nInputPlane: 192
+- type: ReLU
+  id: /D/K
+  next:
+    - /D/dr
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /D/K9
+  next:
+    - /D/vO
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 192
+    nInputPlane: 160
+- type: SpatialConvolution
+  id: /D/KQ
+  next:
+    - /D/vt
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 128
+    nInputPlane: 576
+- type: SpatialAveragePooling
+  id: /D/Kr
+  next:
+    - /D/so
+  attributes:
+    padW: 0
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+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 64
+    nInputPlane: 256
+- type: SpatialConvolution
+  id: /D/z1
+  next:
+    - /D/yO
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 128
+    nInputPlane: 576
+- type: SpatialConvolution
+  id: /D/zb
+  next:
+    - /D/cJ
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 352
+    nInputPlane: 1024
+- type: Linear
+  id: /D/zh
+  next:
+    - /D/ut
+  attributes:
+    bias: ''
+    outputSize: 1000
+    inputSize: 768
+- type: ReLU
+  id: /D/zo
+  next:
+    - /D/dr
+  attributes:
+    p: true
diff --git a/test/test-cases/models/googlenet.yml b/test/test-cases/models/googlenet.yml
new file mode 100644
index 000000000..9a048f7ac
--- /dev/null
+++ b/test/test-cases/models/googlenet.yml
@@ -0,0 +1,1765 @@
+- type: SpatialConvolution
+  id: /y/0A
+  next:
+    - /y/o0
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 128
+    nInputPlane: 96
+- type: SpatialConvolution
+  id: /y/0J
+  next:
+    - /y/4I
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 96
+    nInputPlane: 576
+- type: ReLU
+  id: /y/14
+  next:
+    - /y/6l
+  attributes:
+    p: true
+- type: ReLU
+  id: /y/1C
+  next:
+    - /y/s8
+  attributes:
+    p: true
+- type: Concat
+  id: /y/1I
+  next:
+    - /y/Rf
+    - /y/CN
+    - /y/Uf
+    - /y/tV
+  attributes:
+    dimension: 2
+- type: SpatialMaxPooling
+  id: /y/1b
+  next:
+    - /y/1u
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+- type: SpatialConvolution
+  id: /y/1u
+  next:
+    - /y/Oz
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 128
+    nInputPlane: 1024
+- type: SpatialMaxPooling
+  id: /y/2
+  next:
+    - /y/d
+    - /y/g
+    - /y/U
+    - /y/H
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 2
+    dW: 2
+    kH: 3
+    kW: 3
+- type: SpatialConvolution
+  id: /y/2b
+  next:
+    - /y/Bf
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 128
+    nInputPlane: 576
+- type: SpatialConvolution
+  id: /y/2z
+  next:
+    - /y/Uh
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 192
+    nInputPlane: 576
+- type: SpatialZeroPadding
+  id: /y/3I
+  next:
+    - /y/kr
+  attributes:
+    pad_b: 1
+    pad_t: 1
+    pad_r: 1
+    pad_l: 1
+- type: SpatialAveragePooling
+  id: /y/3M
+  next:
+    - /y/qL
+  attributes:
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+    padH: 0
+    ceil_mode: false
+    count_include_pad: true
+    dH: 3
+    dW: 3
+    kH: 5
+    kW: 5
+- type: SpatialConvolution
+  id: /y/3h
+  next:
+    - /y/lw
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 192
+    nInputPlane: 128
+- type: SpatialConvolution
+  id: /y/3o
+  next:
+    - /y/FM
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 320
+    nInputPlane: 192
+- type: SpatialConvolution
+  id: /y/3s
+  next:
+    - /y/14
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 96
+    nInputPlane: 576
+- type: SpatialConvolution
+  id: /y/4
+  next:
+    - /y/ST
+  attributes:
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+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 96
+    nInputPlane: 64
+- type: ReLU
+  id: /y/4I
+  next:
+    - /y/6l
+  attributes:
+    p: true
+- type: Concat
+  id: /y/4L
+  next:
+    - /y/M5
+    - /y/jz
+    - /y/vB
+    - /y/NN
+  attributes:
+    dimension: 2
+- type: SpatialAveragePooling
+  id: /y/4k
+  next:
+    - /y/yH
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+    ceil_mode: false
+    count_include_pad: true
+    dH: 1
+    dW: 1
+    kH: 7
+    kW: 7
+- type: SpatialConvolution
+  id: /y/4p
+  next:
+    - /y/oL
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+    dH: 1
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+    kH: 1
+    kW: 1
+    nOutputPlane: 224
+    nInputPlane: 576
+- type: ReLU
+  id: /y/4u
+  next:
+    - /y/Tg
+  attributes:
+    p: true
+- type: ReLU
+  id: /y/4v
+  next:
+    - /y/sp
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /y/5W
+  next:
+    - /y/nj
+  attributes:
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+    dH: 1
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+    kH: 3
+    kW: 3
+    nOutputPlane: 224
+    nInputPlane: 160
+- type: ReLU
+  id: /y/5e
+  next:
+    - /y/ZM
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /y/5h
+  next:
+    - /y/ZD
+  attributes:
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+    kW: 3
+    nOutputPlane: 160
+    nInputPlane: 128
+- type: ReLU
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+  next:
+    - /y/ZM
+  attributes:
+    p: true
+- type: ReLU
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+  next:
+    - /y/b
+  attributes:
+    p: true
+- type: ReLU
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+  next:
+    - /y/0A
+  attributes:
+    p: true
+- type: Concat
+  id: /y/6l
+  next:
+    - /y/2z
+    - /y/x6
+    - /y/3M
+    - /y/2b
+  attributes:
+    dimension: 2
+- type: SpatialConvolution
+  id: /y/7
+  next:
+    - /y/J
+  attributes:
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+    dH: 2
+    dW: 2
+    kH: 7
+    kW: 7
+    nOutputPlane: 64
+    nInputPlane: 3
+- type: SpatialConvolution
+  id: /y/78
+  next:
+    - /y/4v
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+    dH: 1
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+    kW: 1
+    nOutputPlane: 96
+    nInputPlane: 576
+- type: SpatialConvolution
+  id: /y/7G
+  next:
+    - /y/qE
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+    dH: 1
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+    kH: 1
+    kW: 1
+    nOutputPlane: 160
+    nInputPlane: 576
+- type: SpatialConvolution
+  id: /y/7w
+  next:
+    - /y/ZE
+  attributes:
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+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 256
+    nInputPlane: 256
+- type: ReLU
+  id: /y/8
+  next:
+    - /y/4
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /y/8y
+  next:
+    - /y/Ts
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+    padH: ''
+    dH: 1
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+    nOutputPlane: 128
+    nInputPlane: 576
+- type: ReLU
+  id: /y/A1
+  next:
+    - /y/Ga
+  attributes:
+    p: true
+- type: ReLU
+  id: /y/A7
+  next:
+    - /y/F1
+  attributes:
+    p: true
+- type: ReLU
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+  next:
+    - /y/3o
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+    p: true
+- type: SpatialConvolution
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+  next:
+    - /y/Tu
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+    kW: 3
+    nOutputPlane: 128
+    nInputPlane: 128
+- type: SpatialConvolution
+  id: /y/Ar
+  next:
+    - /y/qo
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+    kW: 3
+    nOutputPlane: 192
+    nInputPlane: 160
+- type: SpatialConvolution
+  id: /y/B
+  next:
+    - /y/6
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+    kW: 1
+    nOutputPlane: 32
+    nInputPlane: 192
+- type: ReLU
+  id: /y/BS
+  next:
+    - /y/s8
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /y/BY
+  next:
+    - /y/5e
+  attributes:
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+    kW: 3
+    nOutputPlane: 96
+    nInputPlane: 96
+- type: ReLU
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+  next:
+    - /y/3h
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+    p: true
+- type: ReLU
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+  next:
+    - /y/Tg
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+    p: true
+- type: ReLU
+  id: /y/C9
+  next:
+    - /y/4L
+  attributes:
+    p: true
+- type: ReLU
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+  next:
+    - /y/Tg
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+    p: true
+- type: SpatialConvolution
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+  next:
+    - /y/wp
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+    dH: 1
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+    nOutputPlane: 128
+    nInputPlane: 576
+- type: SpatialZeroPadding
+  id: /y/CN
+  next:
+    - /y/1b
+  attributes:
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+    pad_r: 1
+    pad_l: 1
+- type: ReLU
+  id: /y/DZ
+  next:
+    - /y/4L
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+    p: true
+- type: SpatialAveragePooling
+  id: /y/Db
+  next:
+    - /y/3s
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+- type: SpatialMaxPooling
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+  next:
+    - /y/s8
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+- type: SpatialConvolution
+  id: /y/Dj
+  next:
+    - /y/Ni
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+    nOutputPlane: 192
+    nInputPlane: 128
+- type: ReLU
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+  next:
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+- type: SpatialConvolution
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+  next:
+    - /y/Fl
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+    kW: 3
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+    nInputPlane: 64
+- type: ReLU
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+    p: true
+- type: ReLU
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+  attributes:
+    p: true
+- type: Concat
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+  next:
+    - /y/0J
+    - /y/Iu
+    - /y/7G
+    - /y/RZ
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+- type: ReLU
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+  next:
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+- type: SpatialConvolution
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+- type: ReLU
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+  next:
+    - /y/7w
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+    p: true
+- type: View
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+  next:
+    - /y/q7U
+  attributes:
+    numInputDims: null
+    params: 2048
+- type: ReLU
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+  next:
+    - /y/Ag
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+    p: true
+- type: ReLU
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+  next:
+    - /y/vj
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+    p: true
+- type: SpatialZeroPadding
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+  next:
+    - /y/Db
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+- type: ReLU
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+- type: ReLU
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+    p: true
+- type: ReLU
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+  next:
+    - /y/Ga
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+    p: true
+- type: SpatialConvolution
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+  next:
+    - /y/LV
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+    nOutputPlane: 160
+    nInputPlane: 160
+- type: ReLU
+  id: /y/M
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+    - /y/Z
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+- type: SpatialZeroPadding
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+  next:
+    - /y/Qj
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+- type: Linear
+  id: /y/MD
+  next:
+    - /y/ZB
+  attributes:
+    bias: ''
+    outputSize: 1000
+    inputSize: 768
+- type: Concat
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+    - /y/zT
+    - /y/3I
+    - /y/ic
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+    dimension: 2
+- type: ReLU
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+  next:
+    - /y/Ga
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+    p: true
+- type: SpatialConvolution
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+  next:
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+- type: ReLU
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+    p: true
+- type: ReLU
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+  next:
+    - /y/W
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+    p: true
+- type: SpatialConvolution
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+  next:
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+- type: ReLU
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+- type: ReLU
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+- type: ReLU
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+- type: SpatialConvolution
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+    nInputPlane: 192
+- type: SpatialAveragePooling
+  id: /y/Qj
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+- type: ReLU
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+    p: true
+- type: SpatialConvolution
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+- type: SpatialConvolution
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+- type: SpatialConvolution
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+- type: SpatialConvolution
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+  next:
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+- type: SpatialConvolution
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+- type: ReLU
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+    p: true
+- type: ReLU
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+- type: SpatialAveragePooling
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+  next:
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+- type: Concat
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+    dimension: 2
+- type: ReLU
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+    p: true
+- type: ReLU
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+- type: SpatialConvolution
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+- type: SpatialConvolution
+  id: /y/UZ
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+    nInputPlane: 1024
+- type: SpatialConvolution
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+  next:
+    - /y/OV
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+- type: ReLU
+  id: /y/Uh
+  next:
+    - /y/nH
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+    p: true
+- type: SpatialConvolution
+  id: /y/VJ
+  next:
+    - /y/5i
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 64
+    nInputPlane: 256
+- type: SpatialConvolution
+  id: /y/W
+  next:
+    - /y/n
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 96
+    nInputPlane: 64
+- type: SpatialZeroPadding
+  id: /y/WD
+  next:
+    - /y/Dg
+  attributes:
+    pad_b: 1
+    pad_t: 1
+    pad_r: 1
+    pad_l: 1
+- type: LogSoftMax
+  id: /y/WK
+  next:
+    - /y/aS
+  attributes: {}
+- type: ReLU
+  id: /y/WT
+  next:
+    - /y/6l
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /y/Wb
+  next:
+    - /y/WT
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 192
+    nInputPlane: 192
+- type: SpatialMaxPooling
+  id: /y/Wo
+  next:
+    - /y/Ym
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+- type: SpatialConvolution
+  id: /y/YA
+  next:
+    - /y/Ql
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 224
+    nInputPlane: 192
+- type: SpatialConvolution
+  id: /y/Ya
+  next:
+    - /y/rT
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 160
+    nInputPlane: 1024
+- type: Concat
+  id: /y/Ym
+  next:
+    - /y/oH
+  attributes:
+    dimension: 2
+- type: SpatialConvolution
+  id: /y/Z
+  next:
+    - /y/u7
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 96
+    nInputPlane: 64
+- type: LogSoftMax
+  id: /y/ZB
+  next:
+    - /y/aS
+  attributes: {}
+- type: ReLU
+  id: /y/ZD
+  next:
+    - /y/Lb
+  attributes:
+    p: true
+- type: ReLU
+  id: /y/ZE
+  next:
+    - /y/Ym
+  attributes:
+    p: true
+- type: Concat
+  id: /y/ZM
+  next:
+    - /y/Qq
+    - /y/WD
+    - /y/tU
+  attributes:
+    dimension: 2
+- type: ReLU
+  id: /y/a7
+  next:
+    - /y/b
+  attributes:
+    p: true
+- type: Concat
+  id: /y/aS
+  next: []
+  attributes:
+    dimension: 2
+- type: Concat
+  id: /y/b
+  next:
+    - /y/o
+    - /y/p1
+    - /y/ro
+    - /y/wJ
+  attributes:
+    dimension: 2
+- type: SpatialConvolution
+  id: /y/bN
+  next:
+    - /y/1C
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 96
+    nInputPlane: 96
+- type: SpatialZeroPadding
+  id: /y/d
+  next:
+    - /y/l
+  attributes:
+    pad_b: 1
+    pad_t: 1
+    pad_r: 1
+    pad_l: 1
+- type: SpatialZeroPadding
+  id: /y/d3
+  next:
+    - /y/vN
+  attributes:
+    pad_b: 1
+    pad_t: 1
+    pad_r: 1
+    pad_l: 1
+- type: SpatialConvolution
+  id: /y/e
+  next:
+    - /y/r
+  attributes:
+    dW: ''
+    dH: ''
+    padW: 0
+    padH: ''
+    kH: 1
+    kW: 1
+    nOutputPlane: 64
+    nInputPlane: 64
+- type: SpatialConvolution
+  id: /y/f
+  next:
+    - /y/g1
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 96
+    nInputPlane: 576
+- type: SpatialConvolution
+  id: /y/fY
+  next:
+    - /y/ty
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 224
+    nInputPlane: 224
+- type: SpatialConvolution
+  id: /y/fm
+  next:
+    - /y/pZ
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 352
+    nInputPlane: 1024
+- type: SpatialConvolution
+  id: /y/g
+  next:
+    - /y/O
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 64
+    nInputPlane: 192
+- type: ReLU
+  id: /y/g1
+  next:
+    - /y/vC
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /y/gA
+  next:
+    - /y/8
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 64
+    nInputPlane: 576
+- type: ReLU
+  id: /y/gN
+  next:
+    - /y/SD
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /y/h
+  next:
+    - /y/Q
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 192
+    nInputPlane: 64
+- type: ReLU
+  id: /y/i
+  next:
+    - /y/t
+  attributes:
+    p: true
+- type: ReLU
+  id: /y/iV
+  next:
+    - /y/MD
+  attributes:
+    p: ''
+- type: SpatialConvolution
+  id: /y/ic
+  next:
+    - /y/60
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 96
+    nInputPlane: 576
+- type: Linear
+  id: /y/jC
+  next:
+    - /y/WK
+  attributes:
+    bias: ''
+    outputSize: 1000
+    inputSize: 1024
+- type: SpatialConvolution
+  id: /y/jN
+  next:
+    - /y/rb
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 96
+    nInputPlane: 576
+- type: ReLU
+  id: /y/jV
+  next:
+    - /y/5h
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /y/jz
+  next:
+    - /y/jV
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 128
+    nInputPlane: 576
+- type: SpatialAveragePooling
+  id: /y/kr
+  next:
+    - /y/CL
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    count_include_pad: true
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+- type: SpatialAveragePooling
+  id: /y/l
+  next:
+    - /y/B
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    count_include_pad: true
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+- type: ReLU
+  id: /y/lw
+  next:
+    - /y/Ym
+  attributes:
+    p: true
+- type: ReLU
+  id: /y/n
+  next:
+    - /y/ui
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /y/nH
+  next:
+    - /y/Hi
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 256
+    nInputPlane: 192
+- type: ReLU
+  id: /y/nj
+  next:
+    - /y/fY
+  attributes:
+    p: true
+- type: SpatialZeroPadding
+  id: /y/o
+  next:
+    - /y/rl
+  attributes:
+    pad_b: 1
+    pad_t: 1
+    pad_r: 1
+    pad_l: 1
+- type: ReLU
+  id: /y/o0
+  next:
+    - /y/4L
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /y/oH
+  next:
+    - /y/vP
+    - /y/fm
+    - /y/UZ
+    - /y/Ya
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 2
+    dW: 2
+    kH: 2
+    kW: 2
+    nOutputPlane: 1024
+    nInputPlane: 1024
+- type: ReLU
+  id: /y/oL
+  next:
+    - /y/N1
+  attributes:
+    p: true
+- type: ReLU
+  id: /y/oq
+  next:
+    - /y/Dj
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /y/p1
+  next:
+    - /y/A7
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 64
+    nInputPlane: 256
+- type: ReLU
+  id: /y/pF
+  next:
+    - /y/YA
+  attributes:
+    p: true
+- type: ReLU
+  id: /y/pZ
+  next:
+    - /y/1I
+  attributes:
+    p: true
+- type: Linear
+  id: /y/q7U
+  next:
+    - /y/iV
+  attributes:
+    bias: ''
+    outputSize: 768
+    inputSize: 2048
+- type: ReLU
+  id: /y/qE
+  next:
+    - /y/Ar
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /y/qL
+  next:
+    - /y/Hr
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 128
+    nInputPlane: 576
+- type: ReLU
+  id: /y/qo
+  next:
+    - /y/Wb
+  attributes:
+    p: true
+- type: ReLU
+  id: /y/qz
+  next:
+    - /y/1I
+  attributes:
+    p: true
+- type: ReLU
+  id: /y/r
+  next:
+    - /y/h
+  attributes:
+    p: true
+- type: ReLU
+  id: /y/rT
+  next:
+    - /y/5W
+  attributes:
+    p: true
+- type: ReLU
+  id: /y/rb
+  next:
+    - /y/Ga
+  attributes:
+    p: true
+- type: SpatialAveragePooling
+  id: /y/rl
+  next:
+    - /y/VJ
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    count_include_pad: true
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+- type: SpatialConvolution
+  id: /y/ro
+  next:
+    - /y/E
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 64
+    nInputPlane: 256
+- type: Concat
+  id: /y/s8
+  next:
+    - /y/wP
+  attributes:
+    dimension: 2
+- type: SpatialConvolution
+  id: /y/sp
+  next:
+    - /y/IS
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 128
+    nInputPlane: 96
+- type: SpatialConvolution
+  id: /y/t
+  next:
+    - /y/T
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 64
+    nInputPlane: 64
+- type: SpatialConvolution
+  id: /y/tA
+  next:
+    - /y/qz
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 128
+    nInputPlane: 1024
+- type: SpatialConvolution
+  id: /y/tU
+  next:
+    - /y/Jo
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 128
+    nInputPlane: 320
+- type: SpatialConvolution
+  id: /y/tV
+  next:
+    - /y/4u
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 352
+    nInputPlane: 1024
+- type: ReLU
+  id: /y/ty
+  next:
+    - /y/1I
+  attributes:
+    p: true
+- type: ReLU
+  id: /y/u
+  next:
+    - /y/b
+  attributes:
+    p: true
+- type: ReLU
+  id: /y/u7
+  next:
+    - /y/ZM
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /y/ui
+  next:
+    - /y/a7
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 96
+    nInputPlane: 96
+- type: SpatialConvolution
+  id: /y/v9
+  next:
+    - /y/CA
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 224
+    nInputPlane: 224
+- type: SpatialConvolution
+  id: /y/vB
+  next:
+    - /y/NC
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 160
+    nInputPlane: 576
+- type: SpatialConvolution
+  id: /y/vC
+  next:
+    - /y/Gh
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 128
+    nInputPlane: 96
+- type: SpatialAveragePooling
+  id: /y/vN
+  next:
+    - /y/8y
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    count_include_pad: true
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+- type: SpatialZeroPadding
+  id: /y/vP
+  next:
+    - /y/T4
+  attributes:
+    pad_b: 1
+    pad_t: 1
+    pad_r: 1
+    pad_l: 1
+- type: SpatialConvolution
+  id: /y/vj
+  next:
+    - /y/A1
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 160
+    nInputPlane: 128
+- type: SpatialConvolution
+  id: /y/wJ
+  next:
+    - /y/M
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 64
+    nInputPlane: 256
+- type: SpatialConvolution
+  id: /y/wP
+  next:
+    - /y/d3
+    - /y/78
+    - /y/gA
+    - /y/4p
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 2
+    dW: 2
+    kH: 2
+    kW: 2
+    nOutputPlane: 576
+    nInputPlane: 576
+- type: ReLU
+  id: /y/wp
+  next:
+    - /y/4L
+  attributes:
+    p: true
+- type: SpatialMaxPooling
+  id: /y/x
+  next:
+    - /y/e
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 2
+    dW: 2
+    kH: 3
+    kW: 3
+- type: SpatialZeroPadding
+  id: /y/x6
+  next:
+    - /y/Wo
+  attributes:
+    pad_b: 1
+    pad_t: 1
+    pad_r: 1
+    pad_l: 1
+- type: ReLU
+  id: /y/y5
+  next:
+    - /y/bN
+  attributes:
+    p: true
+- type: View
+  id: /y/yH
+  next:
+    - /y/jC
+  attributes:
+    numInputDims: null
+    params: 1024
+- type: SpatialConvolution
+  id: /y/zT
+  next:
+    - /y/C9
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 192
+    nInputPlane: 576
diff --git a/test/test-cases/models/lenet.yml b/test/test-cases/models/lenet.yml
index 374374178..5f713a5bf 100644
--- a/test/test-cases/models/lenet.yml
+++ b/test/test-cases/models/lenet.yml
@@ -1,117 +1,109 @@
-- type: SpatialConvolution
-  id: /b/1
-  next:
-    - /b/S
-  attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    strideWidth: 1
-    strideHeight: 1
-    kernelHeight: 5
-    kernelWidth: 5
-    nOutputPlane: 16
-    nInputPlane: 6
+- type: LogSoftMax
+  id: /g/2
+  next: []
+  attributes: {}
 - type: View
-  id: /b/BJ
+  id: /g/5
   next:
-    - /b/jr
+    - /g/U
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    sizes: 400
-- type: SpatialMaxPooling
-  id: /b/E
+    numInputDims: null
+    params: 400
+- type: ReLU
+  id: /g/7
   next:
-    - /b/BJ
+    - /g/O
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    strideHeight: 2
-    strideWidth: 2
-    kernelHeight: 2
-    kernelWidth: 2
+    p: ''
 - type: SpatialMaxPooling
-  id: /b/G
+  id: /g/9
   next:
-    - /b/1
+    - /g/X
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    strideHeight: 2
-    strideWidth: 2
-    kernelHeight: 2
-    kernelWidth: 2
-- type: ReLU
-  id: /b/O
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 2
+    dW: 2
+    kH: 2
+    kW: 2
+- type: Linear
+  id: /g/E
   next:
-    - /b/G
+    - /g/2
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
+    bias: ''
+    outputSize: 10
+    inputSize: 84
 - type: ReLU
-  id: /b/S
+  id: /g/H
   next:
-    - /b/E
+    - /g/9
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
+    p: ''
 - type: Linear
-  id: /b/U
+  id: /g/O
   next:
-    - /b/y
+    - /g/g
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    output: 10
-    input: 84
+    bias: ''
+    outputSize: 84
+    inputSize: 120
 - type: Linear
-  id: /b/W
+  id: /g/U
   next:
-    - /b/x
+    - /g/7
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    output: 84
-    input: 120
-- type: ReLU
-  id: /b/b
+    bias: ''
+    outputSize: 120
+    inputSize: 400
+- type: SpatialMaxPooling
+  id: /g/W
   next:
-    - /b/W
+    - /g/5
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-- type: Linear
-  id: /b/jr
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 2
+    dW: 2
+    kH: 2
+    kW: 2
+- type: SpatialConvolution
+  id: /g/X
   next:
-    - /b/b
+    - /g/m
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    output: 120
-    input: 400
-- type: SpatialConvolution
-  id: /b/r
+    dW: ''
+    dH: ''
+    padW: 0
+    padH: ''
+    kH: 5
+    kW: 5
+    nOutputPlane: 16
+    nInputPlane: 6
+- type: ReLU
+  id: /g/g
   next:
-    - /b/O
+    - /g/E
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-    strideWidth: 1
-    strideHeight: 1
-    kernelHeight: 5
-    kernelWidth: 5
-    nOutputPlane: 6
-    nInputPlane: 3
+    p: ''
 - type: ReLU
-  id: /b/x
+  id: /g/m
   next:
-    - /b/U
+    - /g/W
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
-- type: LogSoftMax
-  id: /b/y
-  next: []
+    p: ''
+- type: SpatialConvolution
+  id: /g/w
+  next:
+    - /g/H
   attributes:
-    calculateDimensionality: 'function calcDims(layer) return 1; --[[ return output dimensions --]] end'
-    dimensionalityTransform: same
+    dW: ''
+    dH: ''
+    padW: 0
+    padH: ''
+    kH: 5
+    kW: 5
+    nOutputPlane: 6
+    nInputPlane: 3
diff --git a/test/test-cases/models/ninbn.yml b/test/test-cases/models/ninbn.yml
new file mode 100644
index 000000000..edd9c0d14
--- /dev/null
+++ b/test/test-cases/models/ninbn.yml
@@ -0,0 +1,404 @@
+- type: SpatialBatchNormalization
+  id: /k/0
+  next:
+    - /k/a
+  attributes:
+    momentum: ''
+    affine: ''
+    eps: 0.001
+    nOutput: 96
+- type: ReLU
+  id: /k/1M
+  next:
+    - /k/W
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /k/3
+  next:
+    - /k/E
+  attributes:
+    padH: 0
+    padW: 0
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 384
+    nInputPlane: 384
+- type: SpatialMaxPooling
+  id: /k/4
+  next:
+    - /k/x2
+  attributes:
+    ceil_mode: false
+    padH: 1
+    padW: 1
+    dH: 2
+    dW: 2
+    kH: 3
+    kW: 3
+- type: SpatialBatchNormalization
+  id: /k/5
+  next:
+    - /k/q
+  attributes:
+    momentum: ''
+    affine: ''
+    eps: 0.001
+    nOutput: 256
+- type: SpatialBatchNormalization
+  id: /k/7
+  next:
+    - /k/K
+  attributes:
+    momentum: ''
+    affine: ''
+    eps: 0.001
+    nOutput: 256
+- type: ReLU
+  id: /k/7R
+  next:
+    - /k/3
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /k/8h
+  next:
+    - /k/g
+  attributes:
+    padH: 0
+    padW: 0
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 1024
+    nInputPlane: 1024
+- type: ReLU
+  id: /k/A
+  next:
+    - /k/J
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /k/D
+  next:
+    - /k/0
+  attributes:
+    padH: 0
+    padW: 0
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 96
+    nInputPlane: 96
+- type: SpatialBatchNormalization
+  id: /k/E
+  next:
+    - /k/j
+  attributes:
+    momentum: ''
+    affine: ''
+    eps: 0.001
+    nOutput: 384
+- type: LogSoftMax
+  id: /k/Em
+  next: []
+  attributes: {}
+- type: SpatialConvolution
+  id: /k/G3
+  next:
+    - /k/t
+  attributes:
+    padH: 0
+    padW: 0
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 384
+    nInputPlane: 384
+- type: SpatialConvolution
+  id: /k/HU
+  next:
+    - /k/5
+  attributes:
+    padH: 0
+    padW: 0
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 256
+    nInputPlane: 256
+- type: SpatialBatchNormalization
+  id: /k/I
+  next:
+    - /k/7R
+  attributes:
+    momentum: ''
+    affine: ''
+    eps: 0.001
+    nOutput: 384
+- type: SpatialMaxPooling
+  id: /k/J
+  next:
+    - /k/n
+  attributes:
+    ceil_mode: false
+    padH: 1
+    padW: 1
+    dH: 2
+    dW: 2
+    kH: 3
+    kW: 3
+- type: SpatialConvolution
+  id: /k/JG
+  next:
+    - /k/7
+  attributes:
+    padH: 0
+    padW: 0
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 256
+    nInputPlane: 256
+- type: ReLU
+  id: /k/K
+  next:
+    - /k/HU
+  attributes:
+    p: true
+- type: SpatialBatchNormalization
+  id: /k/MR
+  next:
+    - /k/1M
+  attributes:
+    momentum: ''
+    affine: ''
+    eps: 0.001
+    nOutput: 1024
+- type: SpatialBatchNormalization
+  id: /k/P1
+  next:
+    - /k/k
+  attributes:
+    momentum: ''
+    affine: ''
+    eps: 0.001
+    nOutput: 256
+- type: Linear
+  id: /k/S
+  next:
+    - /k/Em
+  attributes:
+    bias: ''
+    outputSize: 1000
+    inputSize: 1024
+- type: ReLU
+  id: /k/TN
+  next:
+    - /k/8h
+  attributes:
+    p: true
+- type: ReLU
+  id: /k/U
+  next:
+    - /k/qr
+  attributes:
+    p: true
+- type: SpatialMaxPooling
+  id: /k/V
+  next:
+    - /k/b
+  attributes:
+    ceil_mode: false
+    padH: 1
+    padW: 1
+    dH: 2
+    dW: 2
+    kH: 3
+    kW: 3
+- type: SpatialAveragePooling
+  id: /k/W
+  next:
+    - /k/yv
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    count_include_pad: true
+    dH: 1
+    dW: 1
+    kH: 7
+    kW: 7
+- type: ReLU
+  id: /k/a
+  next:
+    - /k/m
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /k/b
+  next:
+    - /k/I
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 384
+    nInputPlane: 256
+- type: SpatialBatchNormalization
+  id: /k/g
+  next:
+    - /k/U
+  attributes:
+    momentum: ''
+    affine: ''
+    eps: 0.001
+    nOutput: 1024
+- type: SpatialBatchNormalization
+  id: /k/h
+  next:
+    - /k/o
+  attributes:
+    momentum: ''
+    affine: ''
+    eps: 0.001
+    nOutput: 96
+- type: ReLU
+  id: /k/iT
+  next:
+    - /k/4
+  attributes:
+    p: true
+- type: ReLU
+  id: /k/j
+  next:
+    - /k/G3
+  attributes:
+    p: true
+- type: ReLU
+  id: /k/k
+  next:
+    - /k/JG
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /k/m
+  next:
+    - /k/z
+  attributes:
+    padH: 0
+    padW: 0
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 96
+    nInputPlane: 96
+- type: SpatialConvolution
+  id: /k/n
+  next:
+    - /k/P1
+  attributes:
+    padH: 2
+    padW: 2
+    dH: 1
+    dW: 1
+    kH: 5
+    kW: 5
+    nOutputPlane: 256
+    nInputPlane: 96
+- type: ReLU
+  id: /k/o
+  next:
+    - /k/D
+  attributes:
+    p: true
+- type: SpatialBatchNormalization
+  id: /k/p
+  next:
+    - /k/TN
+  attributes:
+    momentum: ''
+    affine: ''
+    eps: 0.001
+    nOutput: 1024
+- type: ReLU
+  id: /k/q
+  next:
+    - /k/V
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /k/qr
+  next:
+    - /k/MR
+  attributes:
+    padH: 0
+    padW: 0
+    dH: 1
+    dW: 1
+    kH: 1
+    kW: 1
+    nOutputPlane: 1024
+    nInputPlane: 1024
+- type: SpatialBatchNormalization
+  id: /k/t
+  next:
+    - /k/iT
+  attributes:
+    momentum: ''
+    affine: ''
+    eps: 0.001
+    nOutput: 384
+- type: SpatialConvolution
+  id: /k/v
+  next:
+    - /k/h
+  attributes:
+    padH: 5
+    padW: 5
+    dH: 4
+    dW: 4
+    kH: 11
+    kW: 11
+    nOutputPlane: 96
+    nInputPlane: 3
+- type: SpatialConvolution
+  id: /k/x2
+  next:
+    - /k/p
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 1024
+    nInputPlane: 384
+- type: View
+  id: /k/yv
+  next:
+    - /k/S
+  attributes:
+    params: -1
+    numInputDims: 3
+- type: SpatialBatchNormalization
+  id: /k/z
+  next:
+    - /k/A
+  attributes:
+    momentum: ''
+    affine: ''
+    eps: 0.001
+    nOutput: 96
diff --git a/test/test-cases/models/overfeat.yml b/test/test-cases/models/overfeat.yml
new file mode 100644
index 000000000..0c7a8aae0
--- /dev/null
+++ b/test/test-cases/models/overfeat.yml
@@ -0,0 +1,198 @@
+- type: Linear
+  id: /9/2
+  next:
+    - /9/U
+  attributes:
+    bias: ''
+    outputSize: 4096
+    inputSize: 3072
+- type: SpatialMaxPooling
+  id: /9/3
+  next:
+    - /9/Ae
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 2
+    dW: 2
+    kH: 2
+    kW: 2
+- type: SpatialConvolution
+  id: /9/6
+  next:
+    - /9/p
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 4
+    dW: 4
+    kH: 11
+    kW: 11
+    nOutputPlane: 96
+    nInputPlane: 3
+- type: SpatialConvolution
+  id: /9/A
+  next:
+    - /9/P
+  attributes:
+    padW: 0
+    padH: ''
+    dH: 1
+    dW: 1
+    kH: 5
+    kW: 5
+    nOutputPlane: 256
+    nInputPlane: 96
+- type: Linear
+  id: /9/AQ
+  next:
+    - /9/m
+  attributes:
+    bias: ''
+    outputSize: 7
+    inputSize: 4096
+- type: View
+  id: /9/Ae
+  next:
+    - /9/V
+  attributes:
+    numInputDims: null
+    params: 25600
+- type: ReLU
+  id: /9/F
+  next:
+    - /9/3
+  attributes:
+    p: true
+- type: SpatialMaxPooling
+  id: /9/I
+  next:
+    - /9/A
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 2
+    dW: 2
+    kH: 2
+    kW: 2
+- type: SpatialMaxPooling
+  id: /9/J
+  next:
+    - /9/a
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 2
+    dW: 2
+    kH: 2
+    kW: 2
+- type: SpatialConvolution
+  id: /9/L
+  next:
+    - /9/z
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 1024
+    nInputPlane: 512
+- type: ReLU
+  id: /9/P
+  next:
+    - /9/J
+  attributes:
+    p: true
+- type: ReLU
+  id: /9/Q
+  next:
+    - /9/L
+  attributes:
+    p: true
+- type: Linear
+  id: /9/T
+  next:
+    - /9/UZ
+  attributes:
+    bias: ''
+    outputSize: 3072
+    inputSize: 25600
+- type: Threshold
+  id: /9/U
+  next:
+    - /9/AQ
+  attributes:
+    ip: ''
+    v: 0.000001
+    th: 0
+- type: Threshold
+  id: /9/UZ
+  next:
+    - /9/zp
+  attributes:
+    ip: ''
+    v: 0.000001
+    th: 0
+- type: Dropout
+  id: /9/V
+  next:
+    - /9/T
+  attributes:
+    v1: ''
+    inplace: ''
+    p: 0.5
+- type: SpatialConvolution
+  id: /9/a
+  next:
+    - /9/Q
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 512
+    nInputPlane: 256
+- type: SpatialConvolution
+  id: /9/l
+  next:
+    - /9/F
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 1024
+    nInputPlane: 1024
+- type: LogSoftMax
+  id: /9/m
+  next: []
+  attributes: {}
+- type: ReLU
+  id: /9/p
+  next:
+    - /9/I
+  attributes:
+    p: true
+- type: ReLU
+  id: /9/z
+  next:
+    - /9/l
+  attributes:
+    p: true
+- type: Dropout
+  id: /9/zp
+  next:
+    - /9/2
+  attributes:
+    v1: ''
+    inplace: ''
+    p: 0.5
diff --git a/test/test-cases/models/simple.yml b/test/test-cases/models/simple.yml
index bbd877f9b..3c46b3f7d 100644
--- a/test/test-cases/models/simple.yml
+++ b/test/test-cases/models/simple.yml
@@ -1,11 +1,13 @@
 - type: Linear
-  id: 11
+  id: /3/O
   next: []
   attributes:
-    output: 10
+    bias: ''
+    outputSize: 10
+    inputSize: 100
 - type: Reshape
-  id: 12
+  id: /3/g
   next:
-    - 11
+    - /3/O
   attributes:
-    dimensions: 100
+    params: 100
diff --git a/test/test-cases/models/vgg.yml b/test/test-cases/models/vgg.yml
index 69dbe0f4b..45cc1f84b 100644
--- a/test/test-cases/models/vgg.yml
+++ b/test/test-cases/models/vgg.yml
@@ -1,11 +1,43 @@
-- type: LogSoftMax
-  id: /Y/19
-  next: []
-  attributes: {}
+- type: ReLU
+  id: /2/4
+  next:
+    - /2/i
+  attributes:
+    p: true
+- type: Linear
+  id: /2/6
+  next:
+    - /2/X
+  attributes:
+    bias: ''
+    outputSize: 10
+    inputSize: 4096
+- type: Linear
+  id: /2/7
+  next:
+    - /2/74
+  attributes:
+    bias: ''
+    outputSize: 4096
+    inputSize: 25088
+- type: Threshold
+  id: /2/74
+  next:
+    - /2/Yu
+  attributes:
+    ip: ''
+    v: 0.000001
+    th: 0
+- type: ReLU
+  id: /2/9
+  next:
+    - /2/m
+  attributes:
+    p: true
 - type: SpatialConvolution
-  id: /Y/3
+  id: /2/C
   next:
-    - /Y/hb
+    - /2/mo
   attributes:
     padH: 1
     padW: 1
@@ -14,52 +46,43 @@
     kH: 3
     kW: 3
     nOutputPlane: 512
-    nInputPlane: 256
-- type: SpatialConvolution
-  id: /Y/4
+    nInputPlane: 512
+- type: ReLU
+  id: /2/D
   next:
-    - /Y/8
+    - /2/k
   attributes:
-    padH: 1
-    padW: 1
-    dH: 1
-    dW: 1
-    kH: 3
-    kW: 3
-    nOutputPlane: 64
-    nInputPlane: 3
-- type: SpatialMaxPooling
-  id: /Y/6
+    p: true
+- type: Linear
+  id: /2/L
   next:
-    - /Y/IL
+    - /2/j
   attributes:
-    padW: ''
-    padH: ''
-    dH: 2
-    dW: 2
-    kH: 2
-    kW: 2
+    bias: ''
+    outputSize: 4096
+    inputSize: 4096
 - type: ReLU
-  id: /Y/8
+  id: /2/M
   next:
-    - /Y/l
+    - /2/C
   attributes:
     p: true
 - type: SpatialMaxPooling
-  id: /Y/9
+  id: /2/O
   next:
-    - /Y/K
+    - /2/u
   attributes:
-    padW: ''
-    padH: ''
+    padW: 0
+    padH: 0
+    ceil_mode: false
     dH: 2
     dW: 2
     kH: 2
     kW: 2
 - type: SpatialConvolution
-  id: /Y/A
+  id: /2/P
   next:
-    - /Y/y
+    - /2/Z
   attributes:
     padH: 1
     padW: 1
@@ -67,34 +90,63 @@
     dW: 1
     kH: 3
     kW: 3
-    nOutputPlane: 128
-    nInputPlane: 64
-- type: Threshold
-  id: /Y/Cg
+    nOutputPlane: 512
+    nInputPlane: 512
+- type: Dropout
+  id: /2/U
   next:
-    - /Y/z
+    - /2/6
   attributes:
-    ip: ''
-    v: 0.000001
-    th: 0
-- type: Linear
-  id: /Y/D
+    v1: ''
+    inplace: ''
+    p: 0.5
+- type: LogSoftMax
+  id: /2/X
+  next: []
+  attributes: {}
+- type: Dropout
+  id: /2/Yu
   next:
-    - /Y/f4
+    - /2/L
   attributes:
-    bias: ''
-    outputSize: 4096
-    inputSize: 25088
+    v1: ''
+    inplace: ''
+    p: 0.5
+- type: ReLU
+  id: /2/Z
+  next:
+    - /2/ti
+  attributes:
+    p: true
+- type: View
+  id: /2/aW
+  next:
+    - /2/7
+  attributes:
+    numInputDims: null
+    params: 25088
+- type: SpatialMaxPooling
+  id: /2/d
+  next:
+    - /2/q
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 2
+    dW: 2
+    kH: 2
+    kW: 2
 - type: ReLU
-  id: /Y/EE
+  id: /2/e
   next:
-    - /Y/v
+    - /2/d
   attributes:
     p: true
 - type: SpatialConvolution
-  id: /Y/IL
+  id: /2/g
   next:
-    - /Y/EE
+    - /2/4
   attributes:
     padH: 1
     padW: 1
@@ -102,12 +154,12 @@
     dW: 1
     kH: 3
     kW: 3
-    nOutputPlane: 512
-    nInputPlane: 512
+    nOutputPlane: 256
+    nInputPlane: 128
 - type: SpatialConvolution
-  id: /Y/K
+  id: /2/i
   next:
-    - /Y/m
+    - /2/e
   attributes:
     padH: 1
     padW: 1
@@ -116,105 +168,49 @@
     kH: 3
     kW: 3
     nOutputPlane: 256
-    nInputPlane: 128
-- type: SpatialMaxPooling
-  id: /Y/M
-  next:
-    - /Y/a5
-  attributes:
-    padW: ''
-    padH: ''
-    dH: 2
-    dW: 2
-    kH: 2
-    kW: 2
-- type: Linear
-  id: /Y/Q
-  next:
-    - /Y/19
-  attributes:
-    bias: ''
-    outputSize: 10
-    inputSize: 4096
-- type: ReLU
-  id: /Y/R
-  next:
-    - /Y/M
-  attributes:
-    p: true
-- type: ReLU
-  id: /Y/T
-  next:
-    - /Y/6
-  attributes:
-    p: true
-- type: Dropout
-  id: /Y/U7
-  next:
-    - /Y/k
-  attributes:
-    v1: ''
-    inplace: ''
-    p: 0.5
-- type: View
-  id: /Y/a5
-  next:
-    - /Y/D
-  attributes: {}
+    nInputPlane: 256
 - type: Threshold
-  id: /Y/f4
+  id: /2/j
   next:
-    - /Y/U7
+    - /2/U
   attributes:
     ip: ''
     v: 0.000001
     th: 0
-- type: ReLU
-  id: /Y/h
-  next:
-    - /Y/j
-  attributes:
-    p: true
-- type: ReLU
-  id: /Y/hb
-  next:
-    - /Y/l4
-  attributes:
-    p: true
 - type: SpatialMaxPooling
-  id: /Y/j
+  id: /2/k
   next:
-    - /Y/3
+    - /2/z
   attributes:
-    padW: ''
-    padH: ''
+    padW: 0
+    padH: 0
+    ceil_mode: false
     dH: 2
     dW: 2
     kH: 2
     kW: 2
-- type: Linear
-  id: /Y/k
-  next:
-    - /Y/Cg
-  attributes:
-    bias: ''
-    outputSize: 4096
-    inputSize: 4096
 - type: SpatialMaxPooling
-  id: /Y/l
+  id: /2/m
   next:
-    - /Y/A
+    - /2/g
   attributes:
-    padW: ''
-    padH: ''
+    padW: 0
+    padH: 0
+    ceil_mode: false
     dH: 2
     dW: 2
     kH: 2
     kW: 2
+- type: ReLU
+  id: /2/mo
+  next:
+    - /2/O
+  attributes:
+    p: true
 - type: SpatialConvolution
-  id: /Y/l4
+  id: /2/q
   next:
-    - /Y/T
+    - /2/M
   attributes:
     padH: 1
     padW: 1
@@ -223,17 +219,29 @@
     kH: 3
     kW: 3
     nOutputPlane: 512
-    nInputPlane: 512
+    nInputPlane: 256
 - type: ReLU
-  id: /Y/m
+  id: /2/s
   next:
-    - /Y/x
+    - /2/P
   attributes:
     p: true
+- type: SpatialMaxPooling
+  id: /2/ti
+  next:
+    - /2/aW
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 2
+    dW: 2
+    kH: 2
+    kW: 2
 - type: SpatialConvolution
-  id: /Y/v
+  id: /2/u
   next:
-    - /Y/R
+    - /2/s
   attributes:
     padH: 1
     padW: 1
@@ -244,9 +252,9 @@
     nOutputPlane: 512
     nInputPlane: 512
 - type: SpatialConvolution
-  id: /Y/x
+  id: /2/w
   next:
-    - /Y/h
+    - /2/D
   attributes:
     padH: 1
     padW: 1
@@ -254,19 +262,18 @@
     dW: 1
     kH: 3
     kW: 3
-    nOutputPlane: 256
-    nInputPlane: 256
-- type: ReLU
-  id: /Y/y
-  next:
-    - /Y/9
-  attributes:
-    p: true
-- type: Dropout
-  id: /Y/z
+    nOutputPlane: 64
+    nInputPlane: 3
+- type: SpatialConvolution
+  id: /2/z
   next:
-    - /Y/Q
+    - /2/9
   attributes:
-    v1: ''
-    inplace: ''
-    p: 0.5
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 128
+    nInputPlane: 64
diff --git a/test/test-cases/models/vggbn.yml b/test/test-cases/models/vggbn.yml
new file mode 100644
index 000000000..60b6589f6
--- /dev/null
+++ b/test/test-cases/models/vggbn.yml
@@ -0,0 +1,297 @@
+- type: Linear
+  id: /S/1
+  next:
+    - /S/s
+  attributes:
+    bias: ''
+    outputSize: 4096
+    inputSize: 4096
+- type: SpatialMaxPooling
+  id: /S/4
+  next:
+    - /S/fu
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 2
+    dW: 2
+    kH: 2
+    kW: 2
+- type: ReLU
+  id: /S/7
+  next:
+    - /S/f
+  attributes:
+    p: true
+- type: Dropout
+  id: /S/A
+  next:
+    - /S/Pt
+  attributes:
+    v1: ''
+    inplace: ''
+    p: 0.5
+- type: View
+  id: /S/B
+  next:
+    - /S/WQ
+  attributes:
+    numInputDims: null
+    params: 25088
+- type: ReLU
+  id: /S/C
+  next:
+    - /S/w
+  attributes:
+    p: true
+- type: Threshold
+  id: /S/Ee
+  next:
+    - /S/i
+  attributes:
+    ip: ''
+    v: 0.000001
+    th: 0
+- type: SpatialMaxPooling
+  id: /S/H
+  next:
+    - /S/b
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 2
+    dW: 2
+    kH: 2
+    kW: 2
+- type: LogSoftMax
+  id: /S/Iz
+  next: []
+  attributes: {}
+- type: SpatialMaxPooling
+  id: /S/M
+  next:
+    - /S/X
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 2
+    dW: 2
+    kH: 2
+    kW: 2
+- type: BatchNormalization
+  id: /S/MT
+  next:
+    - /S/A
+  attributes:
+    momentum: ''
+    affine: ''
+    eps: 0.001
+    nOutput: 4096
+- type: ReLU
+  id: /S/P
+  next:
+    - /S/cJ
+  attributes:
+    p: true
+- type: ReLU
+  id: /S/PX
+  next:
+    - /S/Z
+  attributes:
+    p: true
+- type: Linear
+  id: /S/Pt
+  next:
+    - /S/Iz
+  attributes:
+    bias: ''
+    outputSize: 1000
+    inputSize: 4096
+- type: SpatialConvolution
+  id: /S/R
+  next:
+    - /S/T
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 128
+    nInputPlane: 64
+- type: ReLU
+  id: /S/T
+  next:
+    - /S/M
+  attributes:
+    p: true
+- type: Linear
+  id: /S/WQ
+  next:
+    - /S/Ee
+  attributes:
+    bias: ''
+    outputSize: 4096
+    inputSize: 25088
+- type: SpatialConvolution
+  id: /S/X
+  next:
+    - /S/7
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 256
+    nInputPlane: 128
+- type: ReLU
+  id: /S/Y
+  next:
+    - /S/t
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /S/Z
+  next:
+    - /S/Y
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 512
+    nInputPlane: 512
+- type: SpatialConvolution
+  id: /S/b
+  next:
+    - /S/P
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 512
+    nInputPlane: 256
+- type: SpatialConvolution
+  id: /S/cJ
+  next:
+    - /S/e
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 512
+    nInputPlane: 512
+- type: ReLU
+  id: /S/e
+  next:
+    - /S/4
+  attributes:
+    p: true
+- type: SpatialConvolution
+  id: /S/f
+  next:
+    - /S/y
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 256
+    nInputPlane: 256
+- type: SpatialConvolution
+  id: /S/fu
+  next:
+    - /S/PX
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 512
+    nInputPlane: 512
+- type: Dropout
+  id: /S/hr
+  next:
+    - /S/1
+  attributes:
+    v1: ''
+    inplace: ''
+    p: 0.5
+- type: BatchNormalization
+  id: /S/i
+  next:
+    - /S/hr
+  attributes:
+    momentum: ''
+    affine: ''
+    eps: 0.001
+    nOutput: 4096
+- type: Threshold
+  id: /S/s
+  next:
+    - /S/MT
+  attributes:
+    ip: ''
+    v: 0.000001
+    th: 0
+- type: SpatialMaxPooling
+  id: /S/t
+  next:
+    - /S/B
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 2
+    dW: 2
+    kH: 2
+    kW: 2
+- type: SpatialMaxPooling
+  id: /S/w
+  next:
+    - /S/R
+  attributes:
+    padW: 0
+    padH: 0
+    ceil_mode: false
+    dH: 2
+    dW: 2
+    kH: 2
+    kW: 2
+- type: SpatialConvolution
+  id: /S/x
+  next:
+    - /S/C
+  attributes:
+    padH: 1
+    padW: 1
+    dH: 1
+    dW: 1
+    kH: 3
+    kW: 3
+    nOutputPlane: 64
+    nInputPlane: 3
+- type: ReLU
+  id: /S/y
+  next:
+    - /S/H
+  attributes:
+    p: true
diff --git a/test/utils/utils.spec.js b/test/utils/utils.spec.js
index b74196db8..52b32d9f0 100644
--- a/test/utils/utils.spec.js
+++ b/test/utils/utils.spec.js
@@ -106,8 +106,8 @@ describe('utils', function () {
 
     describe('matching architectures', function() {
         var cases = [
-            ['/l', 'concat-parallel'],
-            ['/Z', 'concat-y'],
+            ['/l', 'concat-parallel-utils'],
+            ['/Z', 'concat-y-utils'],
             ['/y', 'concat-y-bad-conn']  // disconnected graph
         ];
 
@@ -117,9 +117,9 @@ describe('utils', function () {
 
     describe('mismatching architectures', function() {
         var cases = [
-            ['/l', 'concat-y'],
-            ['/y', 'concat-parallel'],
-            ['/s', 'concat-y']
+            ['/l', 'concat-y-utils'],
+            ['/y', 'concat-parallel-utils'],
+            ['/s', 'concat-y-utils']
         ];
 
         cases.forEach(pair => it('should NOT validate ' + pair[1],
diff --git a/utils/nn-parser.js b/utils/nn-parser.js
index a0297afc1..5ec800d19 100644
--- a/utils/nn-parser.js
+++ b/utils/nn-parser.js
@@ -1,60 +1,28 @@
-var fs = require('fs');
-var path = require('path');
-var parser = require('../src/common/lua').parser;
-var torchPath = process.env.HOME + '/torch/extra/nn/';
-var SKIP_LAYERS = {};
-var skipLayerList = require('./skipLayers.json');
-skipLayerList.forEach(name => SKIP_LAYERS[name] = true);
-
-var findInitParams = function(ast){
-    // Find '__init' function
-    var params;
-    ast.block.stats.forEach(function(block){
-        if(block.key && block.key.val == '__init' && block.func){
-            params = block.func.args;
-            if(params.length === 0 && block.func.varargs){
-                params[0] = 'params';
-            }
-        }
-    });
-    return params;
-};
+var fs = require('fs'),
+    path = require('path'),
+    torchPath,
 
-var findTorchClass = function(ast){
-    var torchClassArgs,  // args for `torch.class(...)`
-        name = '',
-        baseType,
-        params = [];
+    LayerParser = require(__dirname + '/../src/common/LayerParser'),
+    SKIP_LAYERS = {},
+    skipLayerList = require('./skipLayers.json'),
 
-    if(ast.type == 'function'){
-        ast.block.stats.forEach(function(func){
-            if(func.type == 'stat.local' && func.right && func.right[0] &&
-              func.right[0].func && func.right[0].func.self &&
-              func.right[0].func.self.val == 'torch' &&
-              func.right[0].func.key.val == 'class'){
+    categories = require('./categories.json'),
+    catNames = Object.keys(categories),
+    exists = require('exists-file'),
+    configDir = process.env.HOME + '/.deepforge/',
+    configPath = configDir + 'config.json',
+    layerToCategory = {},
+    config;
 
-                torchClassArgs = func.right[0].args.map(arg => arg.val);
-                name = torchClassArgs[0];
-                if(name !== ''){
-                    name = name.replace('nn.', '');
-                    params = findInitParams(ast);
-                    if (torchClassArgs.length > 1) {
-                        baseType = torchClassArgs[1].replace('nn.', '');
-                    }
-                }
-            }
-        });
-    }
-    return {
-        name,
-        baseType,
-        params
-    };
-};
+// Check the deepforge config
+torchPath = process.env.HOME + '/torch';
+if (exists.sync(configPath)) {
+    config = JSON.parse(fs.readFileSync(configPath, 'utf8'));
+    torchPath = (config.torch && config.torch.dir) || (configDir + 'torch');
+}
+torchPath += '/extra/nn/';
 
-var categories = require('./categories.json');
-var catNames = Object.keys(categories);
-var layerToCategory = {};
+skipLayerList.forEach(name => SKIP_LAYERS[name] = true);
 catNames.forEach(cat =>  // create layer -> category dictionary
    categories[cat].forEach(lname => layerToCategory[lname] = cat)
 );
@@ -72,15 +40,14 @@ fs.readdir(torchPath, function(err,files){
         layerByName = {};
 
     layers = files.filter(filename => path.extname(filename) === '.lua')
+        //.filter(filename => filename === 'SpatialAveragePooling.lua')
         .map(filename => fs.readFileSync(torchPath + filename, 'utf8'))
-        .map(code => parser.parse(code))
-        .map(ast => findTorchClass(ast))  // create initial layers
+        .map(code => LayerParser.parse(code))
         .filter(layer => !!layer && layer.name);
 
     layers.forEach(layer => {
         layer.type = lookupType(layer.name);
         layerByName[layer.name] = layer;
-        layer.setters = [];
     });
 
     // handle inheritance