nn package now complies with new luaT API

29 files changed, 241 insertions, 242 deletions

diff --git a/generic/Abs.c b/generic/Abs.c
index 8c65813..e37b30d 100644
--- a/generic/Abs.c
+++ b/generic/Abs.c
@@ -4,8 +4,8 @@
 
 static int nn_(Abs_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
 
   THTensor_(resizeAs)(output, input);
 
@@ -16,9 +16,9 @@ static int nn_(Abs_updateOutput)(lua_State *L)
 
 static int nn_(Abs_updateGradInput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
 
   THTensor_(resizeAs)(gradInput, input);
   TH_TENSOR_APPLY3(real, gradInput, real, gradOutput, real, input, \
@@ -35,7 +35,7 @@ static const struct luaL_Reg nn_(Abs__) [] = {
 
 static void nn_(Abs_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(Abs__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/AbsCriterion.c b/generic/AbsCriterion.c
index b9b948d..397e9dd 100644
--- a/generic/AbsCriterion.c
+++ b/generic/AbsCriterion.c
@@ -4,8 +4,8 @@
 
 static int nn_(AbsCriterion_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));  
-  THTensor *target = luaT_checkudata(L, 3, torch_(Tensor_id));  
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);  
+  THTensor *target = luaT_checkudata(L, 3, torch_Tensor);  
   int sizeAverage = luaT_getfieldcheckboolean(L, 1, "sizeAverage");
   real sum;
 
@@ -25,10 +25,10 @@ static int nn_(AbsCriterion_updateOutput)(lua_State *L)
 
 static int nn_(AbsCriterion_updateGradInput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *target = luaT_checkudata(L, 3, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *target = luaT_checkudata(L, 3, torch_Tensor);
   int sizeAverage = luaT_getfieldcheckboolean(L, 1, "sizeAverage");
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
   real norm = (sizeAverage ? 1./((real)THTensor_(nElement)(input)) : 1.);
 
   THTensor_(resizeAs)(gradInput, input);
@@ -46,7 +46,7 @@ static const struct luaL_Reg nn_(AbsCriterion__) [] = {
 
 static void nn_(AbsCriterion_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(AbsCriterion__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/Exp.c b/generic/Exp.c
index b56f379..3c3303f 100644
--- a/generic/Exp.c
+++ b/generic/Exp.c
@@ -4,8 +4,8 @@
 
 static int nn_(Exp_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
   
   THTensor_(resizeAs)(output, input);
 
@@ -17,9 +17,9 @@ static int nn_(Exp_updateOutput)(lua_State *L)
 
 static int nn_(Exp_updateGradInput)(lua_State *L)
 {
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
 
   THTensor_(resizeAs)(gradInput, output);
   TH_TENSOR_APPLY3(real, gradInput, real, gradOutput, real, output,     \
@@ -35,7 +35,7 @@ static const struct luaL_Reg nn_(Exp__) [] = {
 
 static void nn_(Exp_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(Exp__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/HardShrink.c b/generic/HardShrink.c
index be98ddc..6760036 100644
--- a/generic/HardShrink.c
+++ b/generic/HardShrink.c
@@ -4,9 +4,9 @@
 
 static int nn_(HardShrink_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
   real lambda = luaT_getfieldchecknumber(L, 1, "lambda");
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
 
   THTensor_(resizeAs)(output, input);
   
@@ -19,10 +19,10 @@ static int nn_(HardShrink_updateOutput)(lua_State *L)
 
 static int nn_(HardShrink_updateGradInput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
   real lambda = luaT_getfieldchecknumber(L, 1, "lambda");
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
 
   THTensor_(resizeAs)(gradInput, input);
   TH_TENSOR_APPLY3(real, gradInput, real, gradOutput, real, input,	\
@@ -42,7 +42,7 @@ static const struct luaL_Reg nn_(HardShrink__) [] = {
 
 static void nn_(HardShrink_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(HardShrink__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/HardTanh.c b/generic/HardTanh.c
index bfd1a42..79ccd1a 100644
--- a/generic/HardTanh.c
+++ b/generic/HardTanh.c
@@ -4,8 +4,8 @@
 
 static int nn_(HardTanh_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
 
   THTensor_(resizeAs)(output, input);
   
@@ -49,9 +49,9 @@ static int nn_(HardTanh_updateOutput)(lua_State *L)
 
 static int nn_(HardTanh_updateGradInput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
 
   THTensor_(resizeAs)(gradInput, input);
 
@@ -100,7 +100,7 @@ static const struct luaL_Reg nn_(HardTanh__) [] = {
 
 static void nn_(HardTanh_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(HardTanh__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/LogSigmoid.c b/generic/LogSigmoid.c
index b5bdae4..9b47a32 100644
--- a/generic/LogSigmoid.c
+++ b/generic/LogSigmoid.c
@@ -4,9 +4,9 @@
 
 static int nn_(LogSigmoid_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *buffer = luaT_getfieldcheckudata(L, 1, "buffer", torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *buffer = luaT_getfieldcheckudata(L, 1, "buffer", torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
 
   THTensor_(resizeAs)(output, input);
   THTensor_(resizeAs)(buffer, input);
@@ -21,9 +21,9 @@ static int nn_(LogSigmoid_updateOutput)(lua_State *L)
 
 static int nn_(LogSigmoid_updateGradInput)(lua_State *L)
 {
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
-  THTensor *buffer = luaT_getfieldcheckudata(L, 1, "buffer", torch_(Tensor_id));
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
+  THTensor *buffer = luaT_getfieldcheckudata(L, 1, "buffer", torch_Tensor);
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
 
   THTensor_(resizeAs)(gradInput, buffer);
   TH_TENSOR_APPLY3(real, gradInput, real, gradOutput, real, buffer,    \
@@ -41,7 +41,7 @@ static const struct luaL_Reg nn_(LogSigmoid__) [] = {
 
 static void nn_(LogSigmoid_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(LogSigmoid__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/LogSoftMax.c b/generic/LogSoftMax.c
index 5d4dbfc..7741e3b 100644
--- a/generic/LogSoftMax.c
+++ b/generic/LogSoftMax.c
@@ -4,8 +4,8 @@
 
 static int nn_(LogSoftMax_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
   real *input_data, *output_data;
   long nframe = 0, dim = 0;
   long t, d;
@@ -54,9 +54,9 @@ static int nn_(LogSoftMax_updateOutput)(lua_State *L)
 
 static int nn_(LogSoftMax_updateGradInput)(lua_State *L)
 {
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
   real *gradInput_data, *gradOutput_data, *output_data;
   long nframe = 0, dim = 0;
   long t, d;
@@ -103,7 +103,7 @@ static const struct luaL_Reg nn_(LogSoftMax__) [] = {
 
 void nn_(LogSoftMax_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(LogSoftMax__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/MSECriterion.c b/generic/MSECriterion.c
index c53735c..e46bb63 100644
--- a/generic/MSECriterion.c
+++ b/generic/MSECriterion.c
@@ -4,8 +4,8 @@
 
 static int nn_(MSECriterion_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));  
-  THTensor *target = luaT_checkudata(L, 3, torch_(Tensor_id));  
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);  
+  THTensor *target = luaT_checkudata(L, 3, torch_Tensor);  
   int sizeAverage = luaT_getfieldcheckboolean(L, 1, "sizeAverage");
   real sum;
 
@@ -26,10 +26,10 @@ static int nn_(MSECriterion_updateOutput)(lua_State *L)
 
 static int nn_(MSECriterion_updateGradInput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *target = luaT_checkudata(L, 3, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *target = luaT_checkudata(L, 3, torch_Tensor);
   int sizeAverage = luaT_getfieldcheckboolean(L, 1, "sizeAverage");
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
   real norm = (sizeAverage ? 2./((real)THTensor_(nElement)(input)) : 2.);
 
   THTensor_(resizeAs)(gradInput, input);
@@ -46,7 +46,7 @@ static const struct luaL_Reg nn_(MSECriterion__) [] = {
 
 static void nn_(MSECriterion_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(MSECriterion__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/Max.c b/generic/Max.c
index 87f52f1..fe76801 100644
--- a/generic/Max.c
+++ b/generic/Max.c
@@ -4,10 +4,10 @@
 
 static int nn_(Max_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
   int dimension = luaT_getfieldcheckint(L, 1, "dimension")-1;
-  THTensor *indices = luaT_getfieldcheckudata(L, 1, "indices", torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *indices = luaT_getfieldcheckudata(L, 1, "indices", torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
 
   THLongStorage *dim;
   long i;
@@ -43,11 +43,11 @@ static int nn_(Max_updateOutput)(lua_State *L)
 
 static int nn_(Max_updateGradInput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
-  THTensor *indices = luaT_getfieldcheckudata(L, 1, "indices", torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
+  THTensor *indices = luaT_getfieldcheckudata(L, 1, "indices", torch_Tensor);
   int dimension  = luaT_getfieldcheckint(L, 1, "dimension")-1;
-  THTensor *gradInput  = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *gradInput  = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
 
   THTensor *gradOutputPlusOneDim;
   THLongStorage *dim, *str;
@@ -92,7 +92,7 @@ static const struct luaL_Reg nn_(Max__) [] = {
 
 static void nn_(Max_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(Max__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/Min.c b/generic/Min.c
index d3309df..ab19c06 100644
--- a/generic/Min.c
+++ b/generic/Min.c
@@ -4,10 +4,10 @@
 
 static int nn_(Min_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
   int dimension = luaT_getfieldcheckint(L, 1, "dimension")-1;
-  THTensor *indices = luaT_getfieldcheckudata(L, 1, "indices", torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *indices = luaT_getfieldcheckudata(L, 1, "indices", torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
 
   THLongStorage *dim;
   long i;
@@ -43,11 +43,11 @@ static int nn_(Min_updateOutput)(lua_State *L)
 
 static int nn_(Min_updateGradInput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
-  THTensor *indices = luaT_getfieldcheckudata(L, 1, "indices", torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
+  THTensor *indices = luaT_getfieldcheckudata(L, 1, "indices", torch_Tensor);
   int dimension  = luaT_getfieldcheckint(L, 1, "dimension")-1;
-  THTensor *gradInput  = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *gradInput  = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
 
   THTensor *gradOutputPlusOneDim;
   THLongStorage *dim, *str;
@@ -92,7 +92,7 @@ static const struct luaL_Reg nn_(Min__) [] = {
 
 static void nn_(Min_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(Min__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/MultiLabelMarginCriterion.c b/generic/MultiLabelMarginCriterion.c
index f4c3914..6812b22 100644
--- a/generic/MultiLabelMarginCriterion.c
+++ b/generic/MultiLabelMarginCriterion.c
@@ -4,7 +4,7 @@
 
 static int nn_(MultiLabelMarginCriterion_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));  
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);  
   int sizeAverage = luaT_getfieldcheckboolean(L, 1, "sizeAverage");
   real *input_data, *target_data;
   long nframe, dim;
@@ -18,14 +18,14 @@ static int nn_(MultiLabelMarginCriterion_updateOutput)(lua_State *L)
   {
     nframe = 1;
     dim = input->size[0]; 
-    target = luaT_checkudata(L, 3, torch_(Tensor_id));
+    target = luaT_checkudata(L, 3, torch_Tensor);
     THArgCheck((target->nDimension == 1) && (target->size[0] == dim), 3, "inconsistent target size");
   }
   else
   {
     nframe = input->size[0];
     dim = input->size[1];
-    target = luaT_checkudata(L, 3, torch_(Tensor_id));
+    target = luaT_checkudata(L, 3, torch_Tensor);
     THArgCheck((target->nDimension == 2) && (target->size[0] == nframe) && (target->size[1] == dim), 3, "inconsistent target size");
   }
 
@@ -85,9 +85,9 @@ static int nn_(MultiLabelMarginCriterion_updateOutput)(lua_State *L)
 
 static int nn_(MultiLabelMarginCriterion_updateGradInput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
   int sizeAverage = luaT_getfieldcheckboolean(L, 1, "sizeAverage");
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
   real *input_data;
   real *gradInput_data;
   real *target_data;
@@ -102,14 +102,14 @@ static int nn_(MultiLabelMarginCriterion_updateGradInput)(lua_State *L)
   {
     nframe = 1;
     dim = input->size[0]; 
-    target = luaT_checkudata(L, 3, torch_(Tensor_id));
+    target = luaT_checkudata(L, 3, torch_Tensor);
     THArgCheck((target->nDimension == 1) && (target->size[0] == dim), 3, "inconsistent target size");
   }
   else
   {
     nframe = input->size[0];
     dim = input->size[1];
-    target = luaT_checkudata(L, 3, torch_(Tensor_id));
+    target = luaT_checkudata(L, 3, torch_Tensor);
     THArgCheck((target->nDimension == 2) && (target->size[0] == nframe) && (target->size[1] == dim), 3, "inconsistent target size");
   }
 
@@ -177,7 +177,7 @@ static const struct luaL_Reg nn_(MultiLabelMarginCriterion__) [] = {
 
 static void nn_(MultiLabelMarginCriterion_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(MultiLabelMarginCriterion__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/MultiMarginCriterion.c b/generic/MultiMarginCriterion.c
index 09cbaad..33f6e94 100644
--- a/generic/MultiMarginCriterion.c
+++ b/generic/MultiMarginCriterion.c
@@ -4,7 +4,7 @@
 
 static int nn_(MultiMarginCriterion_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));  
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);  
   int sizeAverage = luaT_getfieldcheckboolean(L, 1, "sizeAverage");
   real *input_data, *target_data;
   long nframe, dim;
@@ -27,7 +27,7 @@ static int nn_(MultiMarginCriterion_updateOutput)(lua_State *L)
   {
     nframe = input->size[0];
     dim = input->size[1];
-    target = luaT_checkudata(L, 3, torch_(Tensor_id));
+    target = luaT_checkudata(L, 3, torch_Tensor);
     THArgCheck((target->nDimension == 1) && (target->size[0] == nframe), 3, "inconsistent target size");
     target = THTensor_(newContiguous)(target);
   }
@@ -73,9 +73,9 @@ static int nn_(MultiMarginCriterion_updateOutput)(lua_State *L)
 
 static int nn_(MultiMarginCriterion_updateGradInput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
   int sizeAverage = luaT_getfieldcheckboolean(L, 1, "sizeAverage");
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
   real *input_data;
   real *gradInput_data;
   real *target_data;
@@ -99,7 +99,7 @@ static int nn_(MultiMarginCriterion_updateGradInput)(lua_State *L)
   {
     nframe = input->size[0];
     dim = input->size[1];
-    target = luaT_checkudata(L, 3, torch_(Tensor_id));
+    target = luaT_checkudata(L, 3, torch_Tensor);
     THArgCheck((target->nDimension == 1) && (target->size[0] == nframe), 3, "inconsistent target size");
     target = THTensor_(newContiguous)(target);
   }
@@ -153,7 +153,7 @@ static const struct luaL_Reg nn_(MultiMarginCriterion__) [] = {
 
 static void nn_(MultiMarginCriterion_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(MultiMarginCriterion__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/Sigmoid.c b/generic/Sigmoid.c
index 20348b9..057ebc4 100644
--- a/generic/Sigmoid.c
+++ b/generic/Sigmoid.c
@@ -4,8 +4,8 @@
 
 static int nn_(Sigmoid_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
 
   THTensor_(resizeAs)(output, input);
 
@@ -17,9 +17,9 @@ static int nn_(Sigmoid_updateOutput)(lua_State *L)
 
 static int nn_(Sigmoid_updateGradInput)(lua_State *L)
 {
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
 
   THTensor_(resizeAs)(gradInput, output);
   TH_TENSOR_APPLY3(real, gradInput, real, gradOutput, real, output, \
@@ -36,7 +36,7 @@ static const struct luaL_Reg nn_(Sigmoid__) [] = {
 
 static void nn_(Sigmoid_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(Sigmoid__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/SoftMax.c b/generic/SoftMax.c
index 3aaae65..fd73b3e 100644
--- a/generic/SoftMax.c
+++ b/generic/SoftMax.c
@@ -4,8 +4,8 @@
 
 static int nn_(SoftMax_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));  
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);  
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
   real *input_data, *output_data;
   long nframe = 0, dim = 0;
   long t, d;
@@ -57,9 +57,9 @@ static int nn_(SoftMax_updateOutput)(lua_State *L)
 
 static int nn_(SoftMax_updateGradInput)(lua_State *L)
 {
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
   real *gradInput_data, *gradOutput_data, *output_data;
   long nframe = 0, dim = 0;
   long t, d;
@@ -106,7 +106,7 @@ static const struct luaL_Reg nn_(SoftMax__) [] = {
 
 static void nn_(SoftMax_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(SoftMax__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/SoftPlus.c b/generic/SoftPlus.c
index 7a097fb..b4f62f7 100644
--- a/generic/SoftPlus.c
+++ b/generic/SoftPlus.c
@@ -4,8 +4,8 @@
 
 static int nn_(SoftPlus_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
   
   THTensor_(resizeAs)(output, input);
 
@@ -17,9 +17,9 @@ static int nn_(SoftPlus_updateOutput)(lua_State *L)
 
 static int nn_(SoftPlus_updateGradInput)(lua_State *L)
 {
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
 
   THTensor_(resizeAs)(gradInput, output);
   TH_TENSOR_APPLY3(real, gradInput, real, gradOutput, real, output,    \
@@ -36,7 +36,7 @@ static const struct luaL_Reg nn_(SoftPlus__) [] = {
 
 static void nn_(SoftPlus_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(SoftPlus__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/SoftShrink.c b/generic/SoftShrink.c
index 0bc4075..985196d 100644
--- a/generic/SoftShrink.c
+++ b/generic/SoftShrink.c
@@ -4,9 +4,9 @@
 
 static int nn_(SoftShrink_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
   real lambda = luaT_getfieldchecknumber(L, 1, "lambda");
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
 
   THTensor_(resizeAs)(output, input);
   
@@ -19,10 +19,10 @@ static int nn_(SoftShrink_updateOutput)(lua_State *L)
 
 static int nn_(SoftShrink_updateGradInput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
   real lambda = luaT_getfieldchecknumber(L, 1, "lambda");
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
 
   THTensor_(resizeAs)(gradInput, input);
   TH_TENSOR_APPLY3(real, gradInput, real, gradOutput, real, input,	\
@@ -42,7 +42,7 @@ static const struct luaL_Reg nn_(SoftShrink__) [] = {
 
 static void nn_(SoftShrink_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(SoftShrink__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/SparseLinear.c b/generic/SparseLinear.c
index e89b1ba..c602c2a 100644
--- a/generic/SparseLinear.c
+++ b/generic/SparseLinear.c
@@ -5,10 +5,10 @@
 static int nn_(SparseLinear_updateOutput)(lua_State *L)
 {
   long i;
-  THTensor * input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor * weight = luaT_getfieldcheckudata(L, 1, "weight", torch_(Tensor_id));
-  THTensor * bias = luaT_getfieldcheckudata(L, 1, "bias", torch_(Tensor_id));
-  THTensor * output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor * input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor * weight = luaT_getfieldcheckudata(L, 1, "weight", torch_Tensor);
+  THTensor * bias = luaT_getfieldcheckudata(L, 1, "bias", torch_Tensor);
+  THTensor * output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
   long dim = weight->size[0]; /* number of weights.. */
 
   THTensor_(copy)(output, bias);
@@ -35,13 +35,13 @@ static int nn_(SparseLinear_updateOutput)(lua_State *L)
 static int nn_(SparseLinear_accGradParameters)(lua_State *L)
 {
   long i;
-  THTensor * input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor * gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
+  THTensor * input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor * gradOutput = luaT_checkudata(L, 3, torch_Tensor);
   real scale = luaL_optnumber(L, 4, 1);
-  THTensor * weight = luaT_getfieldcheckudata(L, 1, "weight", torch_(Tensor_id));
-  THTensor * gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_(Tensor_id));
-  THTensor * gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_(Tensor_id));
-  THTensor * lastInput = luaT_getfieldcheckudata(L, 1, "lastInput", torch_(Tensor_id));
+  THTensor * weight = luaT_getfieldcheckudata(L, 1, "weight", torch_Tensor);
+  THTensor * gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_Tensor);
+  THTensor * gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_Tensor);
+  THTensor * lastInput = luaT_getfieldcheckudata(L, 1, "lastInput", torch_Tensor);
   real weightDecay = luaT_getfieldchecknumber(L, 1, "weightDecay");
   long dim = gradWeight->size[0]; /* number of weights.. */
 
@@ -83,11 +83,11 @@ int nn_(SparseLinear_updateParameters)(lua_State *L)
 {
   long i;
   real learningRate = luaL_checknumber(L, 2);
-  THTensor * weight = luaT_getfieldcheckudata(L, 1, "weight", torch_(Tensor_id));
-  THTensor * bias = luaT_getfieldcheckudata(L, 1, "bias", torch_(Tensor_id));
-  THTensor * gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_(Tensor_id));
-  THTensor * gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_(Tensor_id));
-  THTensor * lastInput = luaT_getfieldcheckudata(L, 1, "lastInput", torch_(Tensor_id));
+  THTensor * weight = luaT_getfieldcheckudata(L, 1, "weight", torch_Tensor);
+  THTensor * bias = luaT_getfieldcheckudata(L, 1, "bias", torch_Tensor);
+  THTensor * gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_Tensor);
+  THTensor * gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_Tensor);
+  THTensor * lastInput = luaT_getfieldcheckudata(L, 1, "lastInput", torch_Tensor);
   
   long dim = weight->size[0]; /* number of weights.. */
   THTensor_(cadd)(bias, bias, -learningRate, gradBias);
@@ -120,7 +120,7 @@ static const struct luaL_Reg nn_(SparseLinear__) [] = {
 
 void nn_(SparseLinear_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(SparseLinear__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/SpatialConvolution.c b/generic/SpatialConvolution.c
index 49ccc8d..bfe5698 100644
--- a/generic/SpatialConvolution.c
+++ b/generic/SpatialConvolution.c
@@ -4,13 +4,13 @@
 
 static int nn_(SpatialConvolution_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
   int dW = luaT_getfieldcheckint(L, 1, "dW");
   int dH = luaT_getfieldcheckint(L, 1, "dH");
 
-  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_(Tensor_id));
-  THTensor *bias = luaT_getfieldcheckudata(L, 1, "bias", torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_Tensor);
+  THTensor *bias = luaT_getfieldcheckudata(L, 1, "bias", torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
 
   luaL_argcheck(L, input->nDimension == 3 || input->nDimension == 4, 2, "3D or 4D(batch mode) tensor expected");
 
@@ -83,14 +83,14 @@ static int nn_(SpatialConvolution_updateOutput)(lua_State *L)
 
 static int nn_(SpatialConvolution_updateGradInput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
   int dW = luaT_getfieldcheckint(L, 1, "dW");
   int dH = luaT_getfieldcheckint(L, 1, "dH");
   int nOutputPlane = luaT_getfieldcheckint(L, 1, "nOutputPlane");
 
-  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_(Tensor_id));
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_Tensor);
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
 
   THArgCheck( nOutputPlane == gradOutput->size[input->nDimension == 4 ? 1 : 0], 1, "Number of output features is not equal to nOutputPlane" );
 
@@ -112,15 +112,15 @@ static int nn_(SpatialConvolution_updateGradInput)(lua_State *L)
 
 static int nn_(SpatialConvolution_accGradParameters)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
   real scale = luaL_optnumber(L, 4, 1);
   int dW = luaT_getfieldcheckint(L, 1, "dW");
   int dH = luaT_getfieldcheckint(L, 1, "dH");
   int nOutputPlane = luaT_getfieldcheckint(L, 1, "nOutputPlane");
 
-  THTensor *gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_(Tensor_id));
-  THTensor *gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_(Tensor_id));
+  THTensor *gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_Tensor);
+  THTensor *gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_Tensor);
 
   THArgCheck( nOutputPlane == gradOutput->size[input->nDimension == 4 ? 1 : 0], 1, "Number of output features is not equal to nOutputPlane" );
 
@@ -186,7 +186,7 @@ static const struct luaL_Reg nn_(SpatialConvolution__) [] = {
 
 static void nn_(SpatialConvolution_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(SpatialConvolution__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/SpatialConvolutionMap.c b/generic/SpatialConvolutionMap.c
index 81117f4..4c289fb 100644
--- a/generic/SpatialConvolutionMap.c
+++ b/generic/SpatialConvolutionMap.c
@@ -4,7 +4,7 @@
 
 static int nn_(SpatialConvolutionMap_updateOutput)(lua_State *L)
 {
- THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+ THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
   int kW = luaT_getfieldcheckint(L, 1, "kW");
   int kH = luaT_getfieldcheckint(L, 1, "kH");
   int dW = luaT_getfieldcheckint(L, 1, "dW");
@@ -12,10 +12,10 @@ static int nn_(SpatialConvolutionMap_updateOutput)(lua_State *L)
   int nInputPlane = luaT_getfieldcheckint(L, 1, "nInputPlane");
   int nOutputPlane = luaT_getfieldcheckint(L, 1, "nOutputPlane");
 
-  THTensor *connTable = luaT_getfieldcheckudata(L, 1, "connTable", torch_(Tensor_id));
-  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_(Tensor_id));
-  THTensor *bias = luaT_getfieldcheckudata(L, 1, "bias", torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *connTable = luaT_getfieldcheckudata(L, 1, "connTable", torch_Tensor);
+  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_Tensor);
+  THTensor *bias = luaT_getfieldcheckudata(L, 1, "bias", torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
 
   luaL_argcheck(L, input->nDimension == 3, 2, "3D tensor expected");
   luaL_argcheck(L, input->size[0] == nInputPlane, 2, "invalid number of input planes");
@@ -81,15 +81,15 @@ static int nn_(SpatialConvolutionMap_updateOutput)(lua_State *L)
 
 static int nn_(SpatialConvolutionMap_updateGradInput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
   int dW = luaT_getfieldcheckint(L, 1, "dW");
   int dH = luaT_getfieldcheckint(L, 1, "dH");
   int nInputPlane = luaT_getfieldcheckint(L, 1, "nInputPlane");
 
-  THTensor *connTable = luaT_getfieldcheckudata(L, 1, "connTable", torch_(Tensor_id));
-  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_(Tensor_id));
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *connTable = luaT_getfieldcheckudata(L, 1, "connTable", torch_Tensor);
+  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_Tensor);
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
 
   // contiguous
   gradInput = THTensor_(newContiguous)(gradInput);
@@ -145,17 +145,17 @@ static int nn_(SpatialConvolutionMap_updateGradInput)(lua_State *L)
 
 static int nn_(SpatialConvolutionMap_accGradParameters)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
   int dW = luaT_getfieldcheckint(L, 1, "dW");
   int dH = luaT_getfieldcheckint(L, 1, "dH");
   int nOutputPlane = luaT_getfieldcheckint(L, 1, "nOutputPlane");
   real scale = luaL_optnumber(L, 4, 1);
 
-  THTensor *connTable = luaT_getfieldcheckudata(L, 1, "connTable", torch_(Tensor_id));
-  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_(Tensor_id));
-  THTensor *gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_(Tensor_id));
-  THTensor *gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_(Tensor_id));
+  THTensor *connTable = luaT_getfieldcheckudata(L, 1, "connTable", torch_Tensor);
+  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_Tensor);
+  THTensor *gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_Tensor);
+  THTensor *gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_Tensor);
 
   // contiguous
   input = THTensor_(newContiguous)(input);
@@ -216,7 +216,7 @@ static const struct luaL_Reg nn_(SpatialConvolutionMap__) [] = {
 
 static void nn_(SpatialConvolutionMap_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(SpatialConvolutionMap__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/SpatialMaxPooling.c b/generic/SpatialMaxPooling.c
index d31c938..234e843 100644
--- a/generic/SpatialMaxPooling.c
+++ b/generic/SpatialMaxPooling.c
@@ -4,13 +4,13 @@
 
 static int nn_(SpatialMaxPooling_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
   int kW = luaT_getfieldcheckint(L, 1, "kW");
   int kH = luaT_getfieldcheckint(L, 1, "kH");
   int dW = luaT_getfieldcheckint(L, 1, "dW");
   int dH = luaT_getfieldcheckint(L, 1, "dH");
-  THTensor *indices = luaT_getfieldcheckudata(L, 1, "indices", torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *indices = luaT_getfieldcheckudata(L, 1, "indices", torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
 
   luaL_argcheck(L, input->nDimension == 3, 2, "3D tensor expected");
   luaL_argcheck(L, input->size[2] >= kW && input->size[1] >= kH, 2, "input image smaller than kernel size");
@@ -90,12 +90,12 @@ static int nn_(SpatialMaxPooling_updateOutput)(lua_State *L)
 
 static int nn_(SpatialMaxPooling_updateGradInput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
   int dW = luaT_getfieldcheckint(L, 1, "dW");
   int dH = luaT_getfieldcheckint(L, 1, "dH");
-  THTensor *indices = luaT_getfieldcheckudata(L, 1, "indices", torch_(Tensor_id));
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *indices = luaT_getfieldcheckudata(L, 1, "indices", torch_Tensor);
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
 
   // get contiguous gradOutput
   gradOutput = THTensor_(newContiguous)(gradOutput);
@@ -154,7 +154,7 @@ static const struct luaL_Reg nn_(SpatialMaxPooling__) [] = {
 
 static void nn_(SpatialMaxPooling_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(SpatialMaxPooling__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/SpatialSubSampling.c b/generic/SpatialSubSampling.c
index a1dde21..ed9c059 100644
--- a/generic/SpatialSubSampling.c
+++ b/generic/SpatialSubSampling.c
@@ -4,16 +4,16 @@
 
 static int nn_(SpatialSubSampling_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
   int kW = luaT_getfieldcheckint(L, 1, "kW");
   int kH = luaT_getfieldcheckint(L, 1, "kH");
   int dW = luaT_getfieldcheckint(L, 1, "dW");
   int dH = luaT_getfieldcheckint(L, 1, "dH");
   int nInputPlane = luaT_getfieldcheckint(L, 1, "nInputPlane");
 
-  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_(Tensor_id));
-  THTensor *bias = luaT_getfieldcheckudata(L, 1, "bias", torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_Tensor);
+  THTensor *bias = luaT_getfieldcheckudata(L, 1, "bias", torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
 
   real *weight_data = THTensor_(data)(weight);
   real *bias_data = THTensor_(data)(bias);
@@ -94,16 +94,16 @@ static int nn_(SpatialSubSampling_updateOutput)(lua_State *L)
 
 static int nn_(SpatialSubSampling_updateGradInput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
   int kW = luaT_getfieldcheckint(L, 1, "kW");
   int kH = luaT_getfieldcheckint(L, 1, "kH");
   int dW = luaT_getfieldcheckint(L, 1, "dW");
   int dH = luaT_getfieldcheckint(L, 1, "dH");
   int nInputPlane = luaT_getfieldcheckint(L, 1, "nInputPlane");
 
-  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_(Tensor_id));
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_Tensor);
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
 
   int dimw = 2;
   int dimh = 1;
@@ -169,8 +169,8 @@ static int nn_(SpatialSubSampling_updateGradInput)(lua_State *L)
 
 static int nn_(SpatialSubSampling_accGradParameters)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
   real scale = luaL_optnumber(L, 4, 1);
   int kW = luaT_getfieldcheckint(L, 1, "kW");
   int kH = luaT_getfieldcheckint(L, 1, "kH");
@@ -178,8 +178,8 @@ static int nn_(SpatialSubSampling_accGradParameters)(lua_State *L)
   int dH = luaT_getfieldcheckint(L, 1, "dH");
   int nInputPlane = luaT_getfieldcheckint(L, 1, "nInputPlane");
 
-  THTensor *gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_(Tensor_id));
-  THTensor *gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_(Tensor_id));
+  THTensor *gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_Tensor);
+  THTensor *gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_Tensor);
 
   long nbatch = 1;
   long dimw = 2;
@@ -255,7 +255,7 @@ static const struct luaL_Reg nn_(SpatialSubSampling__) [] = {
 
 static void nn_(SpatialSubSampling_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(SpatialSubSampling__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/Sqrt.c b/generic/Sqrt.c
index d40918b..0e7cbd7 100644
--- a/generic/Sqrt.c
+++ b/generic/Sqrt.c
@@ -4,9 +4,9 @@
 
 static int nn_(Sqrt_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
   real bias = luaT_getfieldchecknumber(L,1,"eps");
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
 
   THTensor_(resizeAs)(output, input);
   
@@ -29,10 +29,10 @@ static int nn_(Sqrt_updateOutput)(lua_State *L)
 
 static int nn_(Sqrt_updateGradInput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
 
   THTensor_(resizeAs)(gradInput, input);
 
@@ -65,7 +65,7 @@ static const struct luaL_Reg nn_(Sqrt__) [] = {
 
 static void nn_(Sqrt_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(Sqrt__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/Square.c b/generic/Square.c
index ba0c162..33feaa9 100644
--- a/generic/Square.c
+++ b/generic/Square.c
@@ -4,8 +4,8 @@
 
 static int nn_(Square_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
 
   THTensor_(resizeAs)(output, input);
   
@@ -28,9 +28,9 @@ static int nn_(Square_updateOutput)(lua_State *L)
 
 static int nn_(Square_updateGradInput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
 
   THTensor_(resizeAs)(gradInput, input);
 
@@ -63,7 +63,7 @@ static const struct luaL_Reg nn_(Square__) [] = {
 
 static void nn_(Square_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(Square__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/Tanh.c b/generic/Tanh.c
index 01e9bc0..235d23c 100644
--- a/generic/Tanh.c
+++ b/generic/Tanh.c
@@ -4,8 +4,8 @@
 
 static int nn_(Tanh_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
 
   THTensor_(resizeAs)(output, input);
 
@@ -30,15 +30,14 @@ static int nn_(Tanh_updateOutput)(lua_State *L)
   ptr_output[i] = tanh(ptr_input[i]);
     }
   }
-      
   return 1;
 }
 
 static int nn_(Tanh_updateGradInput)(lua_State *L)
 {
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
 
   THTensor_(resizeAs)(gradInput, output);
 
@@ -83,7 +82,7 @@ static const struct luaL_Reg nn_(Tanh__) [] = {
 
 static void nn_(Tanh_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(Tanh__), "nn");
   lua_pop(L,1);
 
diff --git a/generic/TemporalConvolution.c b/generic/TemporalConvolution.c
index fa14a22..091a0cd 100644
--- a/generic/TemporalConvolution.c
+++ b/generic/TemporalConvolution.c
@@ -4,15 +4,15 @@
 
 static int nn_(TemporalConvolution_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));  
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);  
   int kW = luaT_getfieldcheckint(L, 1, "kW");
   int dW = luaT_getfieldcheckint(L, 1, "dW");
   int inputFrameSize = luaT_getfieldcheckint(L, 1, "inputFrameSize");
   int outputFrameSize = luaT_getfieldcheckint(L, 1, "outputFrameSize");
 
-  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_(Tensor_id));
-  THTensor *bias = luaT_getfieldcheckudata(L, 1, "bias", torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_Tensor);
+  THTensor *bias = luaT_getfieldcheckudata(L, 1, "bias", torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
 
   THTensor *outputWindow, *inputWindow;
   int nInputFrame, nOutputFrame;
@@ -72,15 +72,15 @@ static int nn_(TemporalConvolution_updateOutput)(lua_State *L)
 
 static int nn_(TemporalConvolution_updateGradInput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));  
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));  
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);  
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);  
   int kW = luaT_getfieldcheckint(L, 1, "kW");
   int dW = luaT_getfieldcheckint(L, 1, "dW");
   long nInputFrame = input->size[0];
   long nOutputFrame = gradOutput->size[0];
 
-  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_(Tensor_id));
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_Tensor);
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
 
   THTensor *gradOutputWindow;
   THTensor *gradInputWindow;
@@ -121,16 +121,16 @@ static int nn_(TemporalConvolution_updateGradInput)(lua_State *L)
 
 static int nn_(TemporalConvolution_accGradParameters)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));  
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));  
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);  
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);  
   real scale = luaL_optnumber(L, 4, 1);
   int kW = luaT_getfieldcheckint(L, 1, "kW");
   int dW = luaT_getfieldcheckint(L, 1, "dW");
   long nInputFrame = input->size[0];
   long nOutputFrame = gradOutput->size[0];
 
-  THTensor *gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_(Tensor_id));
-  THTensor *gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_(Tensor_id));
+  THTensor *gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_Tensor);
+  THTensor *gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_Tensor);
 
   THTensor *gradOutputWindow;
   THTensor *inputWindow;
@@ -186,7 +186,7 @@ static const struct luaL_Reg nn_(TemporalConvolution__) [] = {
 
 static void nn_(TemporalConvolution_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(TemporalConvolution__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/TemporalMaxPooling.c b/generic/TemporalMaxPooling.c
index 56d0ef6..0111cb5 100644
--- a/generic/TemporalMaxPooling.c
+++ b/generic/TemporalMaxPooling.c
@@ -4,11 +4,11 @@
 
 static int nn_(TemporalMaxPooling_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
   int kW = luaT_getfieldcheckint(L, 1, "kW");
   int dW = luaT_getfieldcheckint(L, 1, "dW");
-  THTensor *indices = luaT_getfieldcheckudata(L, 1, "indices", torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *indices = luaT_getfieldcheckudata(L, 1, "indices", torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
 
   luaL_argcheck(L, input->nDimension == 2, 2, "2D tensor expected");
   luaL_argcheck(L, input->size[0] >= kW, 2, "input sequence smaller than kernel size");
@@ -68,11 +68,11 @@ static int nn_(TemporalMaxPooling_updateOutput)(lua_State *L)
 
 static int nn_(TemporalMaxPooling_updateGradInput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
   int dW = luaT_getfieldcheckint(L, 1, "dW");
-  THTensor *indices = luaT_getfieldcheckudata(L, 1, "indices", torch_(Tensor_id));
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *indices = luaT_getfieldcheckudata(L, 1, "indices", torch_Tensor);
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
 
   // get contiguous gradOutput
   gradOutput = THTensor_(newContiguous)(gradOutput);
@@ -119,7 +119,7 @@ static const struct luaL_Reg nn_(TemporalMaxPooling__) [] = {
 
 static void nn_(TemporalMaxPooling_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(TemporalMaxPooling__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/TemporalSubSampling.c b/generic/TemporalSubSampling.c
index 39e7f3b..1843f1c 100644
--- a/generic/TemporalSubSampling.c
+++ b/generic/TemporalSubSampling.c
@@ -4,14 +4,14 @@
 
 static int nn_(TemporalSubSampling_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));  
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
   int kW = luaT_getfieldcheckint(L, 1, "kW");
   int dW = luaT_getfieldcheckint(L, 1, "dW");
   int inputFrameSize = luaT_getfieldcheckint(L, 1, "inputFrameSize");
 
-  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_(Tensor_id));
-  THTensor *bias = luaT_getfieldcheckudata(L, 1, "bias", torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_Tensor);
+  THTensor *bias = luaT_getfieldcheckudata(L, 1, "bias", torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
 
   THTensor *outputFrame, *inputWindow;
   int nInputFrame, nOutputFrame;
@@ -48,13 +48,13 @@ static int nn_(TemporalSubSampling_updateOutput)(lua_State *L)
 
 static int nn_(TemporalSubSampling_updateGradInput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));  
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));  
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
   int kW = luaT_getfieldcheckint(L, 1, "kW");
   int dW = luaT_getfieldcheckint(L, 1, "dW");
 
-  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_(Tensor_id));
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_Tensor);
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
 
   THTensor *gradOutputFrame;
   THTensor *gradInputWindow, *buffer, *kwunit;
@@ -87,15 +87,15 @@ static int nn_(TemporalSubSampling_updateGradInput)(lua_State *L)
 
 static int nn_(TemporalSubSampling_accGradParameters)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));  
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));  
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
   real scale = luaL_optnumber(L, 4, 1);
 
   int kW = luaT_getfieldcheckint(L, 1, "kW");
   int dW = luaT_getfieldcheckint(L, 1, "dW");
 
-  THTensor *gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_(Tensor_id));
-  THTensor *gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_(Tensor_id));
+  THTensor *gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_Tensor);
+  THTensor *gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_Tensor);
 
   THTensor *gradOutputFrame;
   THTensor *inputWindow, *buffer;
@@ -131,7 +131,7 @@ static const struct luaL_Reg nn_(TemporalSubSampling__) [] = {
 
 static void nn_(TemporalSubSampling_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(TemporalSubSampling__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/Threshold.c b/generic/Threshold.c
index 760e842..c16b6f8 100644
--- a/generic/Threshold.c
+++ b/generic/Threshold.c
@@ -4,10 +4,10 @@
 
 static int nn_(Threshold_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
   real val = luaT_getfieldchecknumber(L, 1, "val");
   real threshold = luaT_getfieldchecknumber(L, 1, "threshold");
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
   
   THTensor_(resizeAs)(output, input);
   TH_TENSOR_APPLY2(real, output, real, input, \
@@ -18,10 +18,10 @@ static int nn_(Threshold_updateOutput)(lua_State *L)
 
 static int nn_(Threshold_updateGradInput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);
   real threshold = luaT_getfieldchecknumber(L, 1, "threshold");
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
 
   THTensor_(resizeAs)(gradInput, input);
   TH_TENSOR_APPLY3(real, gradInput, real, gradOutput, real, input,      \
@@ -39,7 +39,7 @@ static const struct luaL_Reg nn_(Threshold__) [] = {
 
 static void nn_(Threshold_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(Threshold__), "nn");
   lua_pop(L,1);
 }
diff --git a/generic/VolumetricConvolution.c b/generic/VolumetricConvolution.c
index 6949556..6e0b6d8 100644
--- a/generic/VolumetricConvolution.c
+++ b/generic/VolumetricConvolution.c
@@ -4,14 +4,14 @@
 
 static int nn_(VolumetricConvolution_updateOutput)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));  
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);  
   int dT = luaT_getfieldcheckint(L, 1, "dT");
   int dW = luaT_getfieldcheckint(L, 1, "dW");
   int dH = luaT_getfieldcheckint(L, 1, "dH");
 
-  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_(Tensor_id));
-  THTensor *bias = luaT_getfieldcheckudata(L, 1, "bias", torch_(Tensor_id));
-  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_Tensor);
+  THTensor *bias = luaT_getfieldcheckudata(L, 1, "bias", torch_Tensor);
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_Tensor);
 
   luaL_argcheck(L, input->nDimension == 4, 2, "4D tensor expected");
 
@@ -46,14 +46,14 @@ static int nn_(VolumetricConvolution_updateOutput)(lua_State *L)
 
 static int nn_(VolumetricConvolution_updateGradInput)(lua_State *L)
 {
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));  
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);  
   int dT = luaT_getfieldcheckint(L, 1, "dT");
   int dW = luaT_getfieldcheckint(L, 1, "dW");
   int dH = luaT_getfieldcheckint(L, 1, "dH");
   int nOutputPlane = luaT_getfieldcheckint(L, 1, "nOutputPlane");
 
-  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_(Tensor_id));
-  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+  THTensor *weight = luaT_getfieldcheckudata(L, 1, "weight", torch_Tensor);
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_Tensor);
   
   THArgCheck( nOutputPlane == gradOutput->size[0], 1, "Number of output features is not equal to nOutputPlane" );
 
@@ -67,16 +67,16 @@ static int nn_(VolumetricConvolution_updateGradInput)(lua_State *L)
 
 static int nn_(VolumetricConvolution_accGradParameters)(lua_State *L)
 {
-  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));  
-  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));  
+  THTensor *input = luaT_checkudata(L, 2, torch_Tensor);  
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_Tensor);  
   real scale = luaL_optnumber(L, 4, 1);
   int dT = luaT_getfieldcheckint(L, 1, "dT");
   int dW = luaT_getfieldcheckint(L, 1, "dW");
   int dH = luaT_getfieldcheckint(L, 1, "dH");
   int nOutputPlane = luaT_getfieldcheckint(L, 1, "nOutputPlane");
 
-  THTensor *gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_(Tensor_id));
-  THTensor *gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_(Tensor_id));
+  THTensor *gradWeight = luaT_getfieldcheckudata(L, 1, "gradWeight", torch_Tensor);
+  THTensor *gradBias = luaT_getfieldcheckudata(L, 1, "gradBias", torch_Tensor);
   
   THArgCheck( nOutputPlane == gradOutput->size[0], 1, "Number of output features is not equal to nOutputPlane" );
 
@@ -107,7 +107,7 @@ static const struct luaL_Reg nn_(VolumetricConvolution__) [] = {
 
 static void nn_(VolumetricConvolution_init)(lua_State *L)
 {
-  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_pushmetatable(L, torch_Tensor);
   luaT_registeratname(L, nn_(VolumetricConvolution__), "nn");
   lua_pop(L,1);
 }