From 05b53c2cd38482fd459f3b43e3ad152024e940da Mon Sep 17 00:00:00 2001 From: Ronan Collobert Date: Mon, 13 Aug 2012 14:30:48 +0200 Subject: nn package now complies with new luaT API --- generic/Abs.c | 12 ++++++------ generic/AbsCriterion.c | 12 ++++++------ generic/Exp.c | 12 ++++++------ generic/HardShrink.c | 12 ++++++------ generic/HardTanh.c | 12 ++++++------ generic/LogSigmoid.c | 14 +++++++------- generic/LogSoftMax.c | 12 ++++++------ generic/MSECriterion.c | 12 ++++++------ generic/Max.c | 16 ++++++++-------- generic/Min.c | 16 ++++++++-------- generic/MultiLabelMarginCriterion.c | 16 ++++++++-------- generic/MultiMarginCriterion.c | 12 ++++++------ generic/Sigmoid.c | 12 ++++++------ generic/SoftMax.c | 12 ++++++------ generic/SoftPlus.c | 12 ++++++------ generic/SoftShrink.c | 12 ++++++------ generic/SparseLinear.c | 32 ++++++++++++++++---------------- generic/SpatialConvolution.c | 26 +++++++++++++------------- generic/SpatialConvolutionMap.c | 34 +++++++++++++++++----------------- generic/SpatialMaxPooling.c | 16 ++++++++-------- generic/SpatialSubSampling.c | 26 +++++++++++++------------- generic/Sqrt.c | 14 +++++++------- generic/Square.c | 12 ++++++------ generic/Tanh.c | 13 ++++++------- generic/TemporalConvolution.c | 26 +++++++++++++------------- generic/TemporalMaxPooling.c | 16 ++++++++-------- generic/TemporalSubSampling.c | 26 +++++++++++++------------- generic/Threshold.c | 12 ++++++------ generic/VolumetricConvolution.c | 24 ++++++++++++------------ 29 files changed, 241 insertions(+), 242 deletions(-) (limited to 'generic') 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); } -- cgit v1.2.3