static void load_array_to_lua(lua_State *L, chtk::htkarray& arr){ int ndims = 2; //based on code from mattorch with stride fix int k; THLongStorage *size = THLongStorage_newWithSize(ndims); THLongStorage *stride = THLongStorage_newWithSize(ndims); THLongStorage_set(size,0 , arr.nsamples); THLongStorage_set(size,1,arr.samplesize/4*(2*arr.frm_ext+1)); THLongStorage_set(stride,1,1); THLongStorage_set(stride,0,arr.samplesize/4*(2*arr.frm_ext+1)); void * tensorDataPtr = NULL; size_t numBytes = 0; THFloatTensor *tensor = THFloatTensor_newWithSize(size, stride); tensorDataPtr = (void *)(THFloatTensor_data(tensor)); numBytes = THFloatTensor_nElement(tensor) * 4; luaT_pushudata(L, tensor, luaT_checktypename2id(L, "torch.FloatTensor")); // now copy the data assert(tensorDataPtr); memcpy(tensorDataPtr, (void *)(arr.data<void>()), numBytes); }
static void load_array_to_lua(lua_State *L, cnpy::NpyArray& arr){ int ndims = arr.shape.size(); //based on code from mattorch with stride fix int k; THLongStorage *size = THLongStorage_newWithSize(ndims); THLongStorage *stride = THLongStorage_newWithSize(ndims); for (k=0; k<ndims; k++) { THLongStorage_set(size, k, arr.shape[k]); if (k > 0) THLongStorage_set(stride, ndims-k-1, arr.shape[ndims-k]*THLongStorage_get(stride,ndims-k)); else THLongStorage_set(stride, ndims-k-1, 1); } void * tensorDataPtr = NULL; size_t numBytes = 0; if ( arr.arrayType == 'f' ){ // float32/64 if ( arr.word_size == 4 ){ //float32 THFloatTensor *tensor = THFloatTensor_newWithSize(size, stride); tensorDataPtr = (void *)(THFloatTensor_data(tensor)); numBytes = THFloatTensor_nElement(tensor) * arr.word_size; luaT_pushudata(L, tensor, luaT_checktypename2id(L, "torch.FloatTensor")); }else if ( arr.word_size == 8){ //float 64 THDoubleTensor *tensor = THDoubleTensor_newWithSize(size, stride); tensorDataPtr = (void *)(THDoubleTensor_data(tensor)); numBytes = THDoubleTensor_nElement(tensor) * arr.word_size; luaT_pushudata(L, tensor, luaT_checktypename2id(L, "torch.DoubleTensor")); } }else if ( arr.arrayType == 'i' || arr.arrayType == 'u' ){ // does torch have unsigned types .. need to look if ( arr.word_size == 1 ){ //int8 THByteTensor *tensor = THByteTensor_newWithSize(size, stride); tensorDataPtr = (void *)(THByteTensor_data(tensor)); numBytes = THByteTensor_nElement(tensor) * arr.word_size; luaT_pushudata(L, tensor, luaT_checktypename2id(L, "torch.ByteTensor")); }else if ( arr.word_size == 2 ){ //int16 THShortTensor *tensor = THShortTensor_newWithSize(size, stride); tensorDataPtr = (void *)(THShortTensor_data(tensor)); numBytes = THShortTensor_nElement(tensor) * arr.word_size; luaT_pushudata(L, tensor, luaT_checktypename2id(L, "torch.ShortTensor")); }else if ( arr.word_size == 4 ){ //int32 THIntTensor *tensor = THIntTensor_newWithSize(size, stride); tensorDataPtr = (void *)(THIntTensor_data(tensor)); numBytes = THIntTensor_nElement(tensor) * arr.word_size; luaT_pushudata(L, tensor, luaT_checktypename2id(L, "torch.IntTensor")); }else if ( arr.word_size == 8){ //long 64 THLongTensor *tensor = THLongTensor_newWithSize(size, stride); tensorDataPtr = (void *)(THLongTensor_data(tensor)); numBytes = THLongTensor_nElement(tensor) * arr.word_size; luaT_pushudata(L, tensor, luaT_checktypename2id(L, "torch.LongTensor")); } }else{ printf("array type unsupported"); throw std::runtime_error("unsupported data type"); } // now copy the data assert(tensorDataPtr); memcpy(tensorDataPtr, (void *)(arr.data<void>()), numBytes); }