Rewrite Transform<FPP, GPU2> getNbRow/Col, size, multiply(const FPP&) to be...

Rewrite Transform<FPP, GPU2> getNbRow/Col, size, multiply(const FPP&) to be independent from gpu_mod.

src/faust_linear_operator/GPU2/faust_Transform_gpu.cpp.in

@@ -2,26 +2,6 @@
 namespace Faust
 {
 
-	template<>
-		int32_t Transform<@FAUST_SCALAR_FOR_GM@,GPU2>::getNbRow() const
-		{
-			auto marr_funcs = GPUModHandler::get_singleton()->marr_funcs((@FAUST_SCALAR_FOR_GM@)(0));
-			if(gpu_mat_arr)
-				return marr_funcs->nrows(gpu_mat_arr);
-			else
-				return -1;
-		}
-
-	template<>
-		int32_t Transform<@FAUST_SCALAR_FOR_GM@,GPU2>::getNbCol() const
-		{
-			auto marr_funcs = GPUModHandler::get_singleton()->marr_funcs((@FAUST_SCALAR_FOR_GM@)(0));
-			if(gpu_mat_arr)
-				return marr_funcs->ncols(gpu_mat_arr);
-			else
-				return -1;
-		}
-
 	template<>
 		Transform<@FAUST_SCALAR_FOR_GM@,GPU2>::Transform() : gpu_mat_arr(nullptr), dtor_delete_data(false), dtor_disabled(false), data(std::vector<MatGeneric<@FAUST_SCALAR_FOR_GM@,GPU2>*>())
 	{
@@ -68,14 +48,6 @@ namespace Faust
 			if(!dtor_delete_data) ref_man.acquire(const_cast<MatGeneric<@FAUST_SCALAR_FOR_GM@,GPU2>*>(pushed_M));
 		}
 
-	template<>
-		int32_t Transform<@FAUST_SCALAR_FOR_GM@,GPU2>::size() const
-		{
-			auto marr_funcs = GPUModHandler::get_singleton()->marr_funcs((@FAUST_SCALAR_FOR_GM@)(0));
-			if(gpu_mat_arr == nullptr) return 0;
-			return marr_funcs->size(gpu_mat_arr);
-		}
-
 	template<>
 		void Transform<@FAUST_SCALAR_FOR_GM@,GPU2>::Display(bool transpose/*=false*/) const
 		{
@@ -305,10 +277,4 @@ namespace Faust
 			return out;
 		}
 
-	template<>
-		void Transform<@FAUST_SCALAR_FOR_GM@,GPU2>::multiply(const @FAUST_SCALAR_FOR_GM@& a, const int32_t id/*=-1*/)
-		{
-			auto marr_funcs = GPUModHandler::get_singleton()->marr_funcs((@FAUST_SCALAR_FOR_GM@)(0));
-			marr_funcs->scalar_mul_id(this->gpu_mat_arr, reinterpret_cast<const @GM_SCALAR@*>(&a), id);
-		}
 }

src/faust_linear_operator/GPU2/faust_Transform_gpu.h

@@ -54,11 +54,11 @@ namespace Faust
 			bool is_fact_dense(int id) const;
 			bool is_fact_bsr(int id) const;
 			void transpose();
-			int32_t getNbRow()const;
-			int32_t getNbCol()const;
+			faust_unsigned_int getNbRow()const;
+			faust_unsigned_int getNbCol()const;
 			void Display(bool transpose=false) const;
 			std::string to_string(bool transpose=false) const;
-			int32_t size() const;
+			faust_unsigned_int size() const;
 			faust_unsigned_int get_fact_nnz(const faust_unsigned_int id) const;
 			faust_unsigned_int get_total_nnz() const;
 			void update_total_nnz() const;
@@ -70,7 +70,7 @@ namespace Faust
 			MatDense<FPP, GPU2> sliceMultiply(const Slice s[2], MatDense<FPP, GPU2>& gpu_X, const char opThis) const;
 			MatDense<FPP, GPU2> indexMultiply(faust_unsigned_int* ids[2], size_t id_lens[2], MatDense<FPP, GPU2>& gpu_X, const char opThis) const;
 			void multiplyLeft(const Transform<FPP,GPU2> & A);
-			void multiply(const FPP& a, const int32_t id=-1);
+			void multiply(const FPP& a);
 			Vect<FPP,GPU2> multiply(const Vect<FPP,GPU2>& x, const char opThis='N');
 			Real<FPP> spectralNorm(int32_t nb_iter_max, float threshold, int& flag);
 			FPP power_iteration(int32_t nb_iter_max, float threshold, int& flag);

src/faust_linear_operator/GPU2/faust_Transform_gpu.hpp

 namespace Faust
 {
 
+	template<typename FPP>
+		faust_unsigned_int Transform<FPP,GPU2>::getNbRow() const // TODO: factorize with CPU code
+		{
+			if (size() != 0)
+				return data[0]->getNbRow();
+			throw std::runtime_error("Empty Transform");
+		}
+
+	template<typename FPP>
+		faust_unsigned_int Transform<FPP,GPU2>::getNbCol() const // TODO: factorize with CPU code
+		{
+			if (size() != 0)
+				return data[size()-1]->getNbCol();
+			throw std::runtime_error("Empty Transform");
+		}
+
+
+	template<typename FPP>
+		faust_unsigned_int Transform<FPP,GPU2>::size() const
+		{
+			return data.size();
+		}
+
 	template<typename FPP>
 		RefManager Transform<FPP,GPU2>::ref_man([](void *fact)
 				{
@@ -242,6 +265,28 @@ namespace Faust
 			return v_out;
 		}
 
+	template<typename FPP>
+		void Transform<FPP,GPU2>::multiply(const FPP& scalar) //TODO: factorize with CPU code (scalarMultiply)
+		{
+			// find smallest factor
+			if (size() == 0)
+				throw std::runtime_error("Empty Transform");
+
+			auto sid = 0;
+			auto ssize = data[0]->getNbRow() * data[0]->getNbCol();
+			for(auto i = 0;i < data.size(); i++)
+			{
+				auto fac = data[i];
+				auto s = fac->getNbRow() * fac->getNbCol();
+				if(s < ssize)
+				{
+					ssize = s;
+					sid = i;
+				}
+			}
+			*(data[sid]) *= scalar;
+		}
+
 	template<typename FPP>
 		MatGeneric<FPP,GPU2>* Transform<FPP,GPU2>::iterator::operator*() const
 		{