From 672cc3c2fae530f11411620d1dd59469a471e360 Mon Sep 17 00:00:00 2001
From: fanasina <rafanasin@gmail.com>
Date: Thu, 1 Feb 2024 17:14:36 +0100
Subject: [PATCH] create cl test

---
 tensor_t/test_cl/Makefile   |  75 +++++
 tensor_t/test_cl/compile.sh |  24 ++
 tensor_t/test_cl/is_good.c  | 546 ++++++++++++++++++++++++++++++++++++
 3 files changed, 645 insertions(+)
 create mode 100644 tensor_t/test_cl/Makefile
 create mode 100644 tensor_t/test_cl/compile.sh
 create mode 100644 tensor_t/test_cl/is_good.c

diff --git a/tensor_t/test_cl/Makefile b/tensor_t/test_cl/Makefile
new file mode 100644
index 0000000..32b85e0
--- /dev/null
+++ b/tensor_t/test_cl/Makefile
@@ -0,0 +1,75 @@
+
+
+
+
+NAME_TEST=is_good
+CC=gcc
+ROOT_DIR=$(PWD)
+YTESTDIR=$(PWD)/../../ytest_t
+YPERMDIR=$(PWD)/../../ypermutation_t
+
+TENSDIR=$(PWD)/..
+DIMDIR=$(PWD)/../../dimension_t
+INCLUDE_DIR=$(PWD)/../src
+CFLAGS=-I$(INCLUDE_DIR) -I$(YPERMDIR)/src -I$(YTESTDIR)/include_ytest/include -I$(DIMDIR)/src -I$(TENSDIR)/src
+LDFLAGS=-L$(YTESTDIR) -lytest -lOpenCL
+
+#SRC_DIR=$(ROOT_DIR)/src
+#SRC=$(wildcard */*/*.c) 
+SRC=$(wildcard **/**/*.c) 
+#HEADS=$(OBJS:.o=.h)
+TEST_DIR=$(PWD)
+
+EXECSRC=$(NAME_TEST).c
+#EXECSRC=openF.c
+
+EXEC=launch_$(NAME_TEST)_m
+
+TENSRC=$(TENSDIR)/src/tensor_t/tensor_t.c
+TENSRC_O=$(TENSRC:.c=.o)
+
+clTENSRC=$(TENSDIR)/src/tensor_t/cl_tensor_t.c
+clTENSRC_O=$(clTENSRC:.c=.o)
+
+
+PERMSRC_O=$(YPERMDIR)/src/permutation_t/permutation_t.o
+
+DIMSRC_O=$(DIMDIR)/src/dimension_t/dimension_t.o
+
+TOPTARGETS := all clean 
+
+DEPS=$(DIMDIR) $(YPERMDIR) $(YTESTDIR) $(TENSDIR)
+
+OBJ=$(DIMSRC_O) $(PERMSRC_O) $(TENSRC_O) $(clTENSRC_O)
+
+LIB_YTEST=$(YTESTDIR)/libytest.so
+
+
+$(TOPTARGETS): $(DEPS) 
+
+$(DEPS):
+	$(MAKE) -C $@ $(MAKECMDGOALS)
+
+
+#PERMSRC_O=$(PERMSRC:.c=.o)
+#SETTSRC_O=$(PWD)/../src/set_theoric_t/set_theoric_t.o
+#SETTSRC_O=$(SETTSRC:.c=.o)
+#TOOLSRC=$(TOOLDIR)/src/tools_t/tools_t.c
+#TOOLSRC_O=$(TOOLSRC:.c=.o)
+
+
+all: $(EXEC) $(LIB_YTEST)
+
+$(EXEC):	$(EXECSRC) $(OBJ)
+	$(CC) -o $@ $^ $(CFLAGS) $(LDFLAGS)
+
+.PHONY: clean mrproper
+
+clean:
+	rm -f $(OBJ)
+
+mrproper: clean
+	rm -f $(EXEC)
+
+run: $(EXEC)
+	$(EXEC) -h
diff --git a/tensor_t/test_cl/compile.sh b/tensor_t/test_cl/compile.sh
new file mode 100644
index 0000000..56bb1dd
--- /dev/null
+++ b/tensor_t/test_cl/compile.sh
@@ -0,0 +1,24 @@
+#!/bin/bash
+
+if [ "$#" -le 0 ] ; then
+  echo "Usage: $0 is_good.c" >&2
+  echo "for example to compile: is_good.c" >&2
+  exit 1
+fi
+if [ "$#" -le 1 ] ; then
+  echo "Usage: $0 $1" >&2
+  echo " we can add more option for example '-D DEBUG=1' to have debug print, '-D HK' to have gtest like prompt, od '-g' to gbd" >&2
+  echo "for example: $0 $1 \"-D DEBUG=1 -D HK -g\""
+fi
+
+DIR_YTEST=$PWD/../../ytest_t
+SRC=../src
+PERMSRC=$PWD/../../ypermutation_t/src
+
+gcc -o launch_is_good_c $1 -L$DIR_YTEST $2 -lytest -I$DIR_YTEST/include_ytest/include $PERMSRC/permutation_t/permutation_t.o $PERMSRC/set_theoric_t/set_theoric_t.o $SRC/dimension_t/dimension_t.c -I$SRC -I$PERMSRC
+#gcc -o launch_is_good_c $1 $2 -lytest -I../include_ytest src/permutation_t/permutation_t.o src/set_theoric_t/set_theoric_t.o -I./src 
+
+export LD_LIBRARY_PATH=$DIR_YTEST/:LD_LIBRARY_PATH
+
+
+#gcc $1 src/ftest/ftest.c src/fmock/fmock.c src/tools_t/tools_t.c src/bar_progress/bar_progress.c src/permutation_t/permutation_t.c src/set_theoric_t/set_theoric_t.c -I./include $2 -o launch_is_good_c -lpthread 
diff --git a/tensor_t/test_cl/is_good.c b/tensor_t/test_cl/is_good.c
new file mode 100644
index 0000000..eee207a
--- /dev/null
+++ b/tensor_t/test_cl/is_good.c
@@ -0,0 +1,546 @@
+#include <stdio.h>
+#include <stdlib.h>
+#include <stdbool.h>
+
+// for sleep !
+#ifdef __linux__ 
+  #include <unistd.h>
+#elif _WIN32 
+  #include <windows.h>
+#endif
+
+#include "ftest/ftest.h"
+#include "ftest/ftest_array.h"
+#include "fmock/fmock.h"
+
+
+//#include "permutation_t/permutation_t.h"
+#include "tensor_t/tensor_t.h"
+#include "tensor_t/cl_tensor_t.h"
+
+TEST(rank){
+  dimension *D=create_dim(4);
+  D->perm[0]=2;
+  D->perm[1]=3;
+  D->perm[2]=5;
+  D->perm[3]=6;
+
+  updateRankDim(D);
+  tensor_TYPE_FLOAT *tf = CREATE_TENSOR_TYPE_FLOAT(D);
+  EXPECT_EQ(tf->dim->rank, 180);
+
+}
+
+void print_tensor_float(tensor_TYPE_FLOAT *M, char *msg){
+  LOG("================= %s ===============\n",msg);
+  for(size_t i=0; i<M->dim->rank;++i)
+      LOG("[%ld]: %f ",i,M->x[i]);
+  
+    LOG("%s","\n");
+}
+
+
+void print_tensor_double(tensor_TYPE_DOUBLE *M, char *msg){
+  LOG("================= %s ===============\n",msg);
+  for(size_t i=0; i<M->dim->rank;++i)
+      LOG("[%ld]: %lf ",i,M->x[i]);
+  
+    LOG("%s","\n");
+}
+
+
+TEST(tensorProd ){
+  dimension *d0=create_dim(3);
+  dimension *d1=create_dim(2);
+
+  d0->perm[0]=2;
+  d0->perm[1]=3;
+  d0->perm[2]=2;
+  
+  d1->perm[0]=2;
+  d1->perm[1]=3;
+
+  updateRankDim(d0);
+  updateRankDim(d1);
+
+
+  tensor_TYPE_FLOAT *M0 = CREATE_TENSOR_TYPE_FLOAT(d0);
+  tensor_TYPE_FLOAT *M1 = CREATE_TENSOR_TYPE_FLOAT(d1);
+
+  LOG("M0->dim->rank = %ld\n",M0->dim->rank);
+  LOG("M1->dim->rank = %ld\n",M1->dim->rank);
+  for(size_t i=0; i<M0->dim->rank;++i) M0->x[i]=i*0.1 +1;
+  for(size_t i=0; i<M1->dim->rank;++i) M1->x[i]=i*0.003 + 2;
+
+  print_tensor_float(M0,"M0");
+  print_tensor_float(M1,"M1");
+
+
+  tensor_TYPE_FLOAT *M; 
+  tensor_TYPE_FLOAT *Mn; 
+
+  tensorProd_TYPE_FLOAT(&M,M0,M1);
+  tensorProdNotOpt_TYPE_FLOAT(&Mn,M0,M1);
+  LOG("M->dim->rank = %ld\n",M->dim->rank);
+
+  print_tensor_float(M,"M");
+
+  EXPECT_ARRAY_EQ_TYPE_FLOAT(M->x,M->dim->rank,Mn->x,Mn->dim->rank);
+
+  print_tensor_float(Mn,"Mn");
+}
+
+TEST(tensorContractnProd_TYPE_FLOAT ){
+  dimension *d0=create_dim(3);
+  dimension *d1=create_dim(2);
+
+  d0->perm[0]=2;
+  d0->perm[1]=3;
+  d0->perm[2]=2;
+
+  d1->perm[0]=2;
+  d1->perm[1]=3;
+
+  updateRankDim(d0);
+  updateRankDim(d1);
+
+
+  tensor_TYPE_FLOAT *M0 = CREATE_TENSOR_TYPE_FLOAT(d0);
+  tensor_TYPE_FLOAT *M1 = CREATE_TENSOR_TYPE_FLOAT(d1);
+
+  LOG("M0->dim->rank = %ld\n",M0->dim->rank);
+  LOG("M1->dim->rank = %ld\n",M1->dim->rank);
+  for(size_t i=0; i<M0->dim->rank;++i) M0->x[i]=i*0.1 +1;
+  for(size_t i=0; i<M1->dim->rank;++i) M1->x[i]=i*0.003 + 2;
+
+  print_tensor_float(M0,"M0");
+  print_tensor_float(M1,"M1");
+
+  tensor_TYPE_FLOAT *M;
+  tensor_TYPE_FLOAT *MnO;
+
+  tensorContractnProd_TYPE_FLOAT(&M, M0,M1,1);
+  tensorContractnProdNotOpt_TYPE_FLOAT(&MnO, M0,M1,1);
+
+
+  print_tensor_float(M,"M");
+  print_tensor_float(MnO,"MnO");
+ 
+  // for(size_t i=0;i<M->dim->rank;++i)
+  //  EXPECT_EQ_TYPE_FLOAT(M->x[i],MnO->x[i]);
+    
+  EXPECT_ARRAY_EQ_TYPE_FLOAT(M->x,M->dim->rank,MnO->x,MnO->dim->rank);
+
+
+}
+
+TEST(tensorContractnProd_TYPE_FLOAT2 ){
+  dimension *d0=create_dim(3);
+  dimension *d1=create_dim(3);
+
+  d0->perm[0]=35;
+  d0->perm[1]=32; //3;
+  d0->perm[2]=23;
+
+  d1->perm[0]=32;
+  d1->perm[1]=23;//3;
+  d1->perm[2]=44;
+
+  updateRankDim(d0);
+  updateRankDim(d1);
+
+
+  tensor_TYPE_FLOAT *M0 = CREATE_TENSOR_TYPE_FLOAT(d0);
+  tensor_TYPE_FLOAT *M1 = CREATE_TENSOR_TYPE_FLOAT(d1);
+
+  LOG("M0->dim->rank = %ld\n",M0->dim->rank);
+  LOG("M1->dim->rank = %ld\n",M1->dim->rank);
+  for(size_t i=0; i<M0->dim->rank;++i) M0->x[i]=i*0.1 +1;
+  for(size_t i=0; i<M1->dim->rank;++i) M1->x[i]=i*0.003 + 2;
+
+//  print_tensor_float(M0,"M0");
+//  print_tensor_float(M1,"M1");
+
+  tensor_TYPE_FLOAT *M;
+  tensor_TYPE_FLOAT *MnO;
+
+  tensorContractnProd_TYPE_FLOAT(&M, M0,M1,2);
+//  print_tensor_float(M,"M");
+  tensorContractnProdNotOpt_TYPE_FLOAT(&MnO, M0,M1,2);
+
+
+//  print_tensor_float(MnO,"MnO");
+ 
+  // for(size_t i=0;i<M->dim->rank;++i)
+  //    EXPECT_EQ_TYPE_FLOAT(M->x[i],MnO->x[i]);
+    
+  //EXPECT_ARRAY_EQ_TYPE_FLOAT(M->x,M->dim->rank,MnO->x,MnO->dim->rank);
+
+
+}
+
+TEST(cl_tensorContractnProd_TYPE_FLOAT2 ){
+  dimension *d0=create_dim(3);
+  dimension *d1=create_dim(3);
+  
+  d0->perm[0]=35;
+  d0->perm[1]=32; //3;
+  d0->perm[2]=23;
+
+  d1->perm[0]=32;
+  d1->perm[1]=23;//3;
+  d1->perm[2]=44;
+
+  updateRankDim(d0);
+  updateRankDim(d1);
+
+
+  tensor_TYPE_FLOAT *M0 = CREATE_TENSOR_TYPE_FLOAT(d0);
+  tensor_TYPE_FLOAT *M1 = CREATE_TENSOR_TYPE_FLOAT(d1);
+
+  LOG("M0->dim->rank = %ld\n",M0->dim->rank);
+  LOG("M1->dim->rank = %ld\n",M1->dim->rank);
+  for(size_t i=0; i<M0->dim->rank;++i) M0->x[i]=i*0.1 +1;
+  for(size_t i=0; i<M1->dim->rank;++i) M1->x[i]=i*0.003 + 2;
+
+//  print_tensor_float(M0,"M0");
+//  print_tensor_float(M1,"M1");
+
+  tensor_TYPE_FLOAT *M;
+  tensor_TYPE_FLOAT *MnO;
+
+  tensorContractnProdNotOpt_TYPE_FLOAT(&M, M0,M1,2);
+//  print_tensor_float(M,"M");
+  cl_tensorContractnProd_TYPE_FLOAT(&MnO, M0,M1,2);
+
+
+//  print_tensor_float(MnO,"MnO");
+ 
+  // for(size_t i=0;i<M->dim->rank;++i)
+  //    EXPECT_EQ_TYPE_FLOAT(M->x[i],MnO->x[i]);
+    
+  //EXPECT_ARRAY_EQ_TYPE_FLOAT(M->x,M->dim->rank,MnO->x,MnO->dim->rank);
+
+
+}
+
+TEST(cl_tensorContractnProd_TYPE_DOUBLE2 ){
+  dimension *d0=create_dim(3);
+  dimension *d1=create_dim(3);
+
+  d0->perm[0]=125;
+  d0->perm[1]=52; //3;
+  d0->perm[2]=63;
+
+  d1->perm[0]=52;
+  d1->perm[1]=63;//3;
+  d1->perm[2]=54;
+
+  updateRankDim(d0);
+  updateRankDim(d1);
+
+
+  tensor_TYPE_DOUBLE *M0 = CREATE_TENSOR_TYPE_DOUBLE(d0);
+  tensor_TYPE_DOUBLE *M1 = CREATE_TENSOR_TYPE_DOUBLE(d1);
+
+  LOG("M0->dim->rank = %ld\n",M0->dim->rank);
+  LOG("M1->dim->rank = %ld\n",M1->dim->rank);
+  for(size_t i=0; i<M0->dim->rank;++i) M0->x[i]=i*0.1 +1;
+  for(size_t i=0; i<M1->dim->rank;++i) M1->x[i]=i*0.003 + 2;
+
+  //print_tensor_double(M0,"M0");
+  //print_tensor_double(M1,"M1");
+
+  tensor_TYPE_DOUBLE *M;
+  tensor_TYPE_DOUBLE *MnO;
+
+  tensorContractnProdNotOpt_TYPE_DOUBLE(&M, M0,M1,2);
+  //tensorContractnProd_TYPE_DOUBLE(&M, M0,M1,2);
+  //print_tensor_double(M,"M");
+  cl_tensorContractnProd_TYPE_DOUBLE(&MnO, M0,M1,2);
+
+
+  //print_tensor_double(MnO,"MnO");
+ 
+  // for(size_t i=0;i<M->dim->rank;++i)
+  //    EXPECT_EQ_TYPE_DOUBLE(M->x[i],MnO->x[i]);
+    
+  EXPECT_ARRAY_EQ_TYPE_DOUBLE(M->x,M->dim->rank,MnO->x,MnO->dim->rank);
+
+
+}
+
+
+TEST(tensorContractnProd_TYPE_DOUBLE2 ){
+  dimension *d0=create_dim(3);
+  dimension *d1=create_dim(3);
+
+  d0->perm[0]=125;
+  d0->perm[1]=52; //3;
+  d0->perm[2]=63;
+
+  d1->perm[0]=52;
+  d1->perm[1]=63;//3;
+  d1->perm[2]=54;
+
+  updateRankDim(d0);
+  updateRankDim(d1);
+
+
+  tensor_TYPE_DOUBLE *M0 = CREATE_TENSOR_TYPE_DOUBLE(d0);
+  tensor_TYPE_DOUBLE *M1 = CREATE_TENSOR_TYPE_DOUBLE(d1);
+
+  LOG("M0->dim->rank = %ld\n",M0->dim->rank);
+  LOG("M1->dim->rank = %ld\n",M1->dim->rank);
+  for(size_t i=0; i<M0->dim->rank;++i) M0->x[i]=i*0.1 +1;
+  for(size_t i=0; i<M1->dim->rank;++i) M1->x[i]=i*0.003 + 2;
+
+  //print_tensor_double(M0,"M0");
+  //print_tensor_double(M1,"M1");
+
+  tensor_TYPE_DOUBLE *M;
+  tensor_TYPE_DOUBLE *MnO;
+
+  tensorContractnProd_TYPE_DOUBLE(&M, M0,M1,2);
+  //print_tensor_double(M,"M");
+  //cl_tensorContractnProd_TYPE_DOUBLE(&MnO, M0,M1,2);
+  tensorContractnProdNotOpt_TYPE_DOUBLE(&MnO, M0,M1,2);
+
+  //print_tensor_double(MnO,"MnO");
+ 
+  // for(size_t i=0;i<M->dim->rank;++i)
+  //    EXPECT_EQ_TYPE_DOUBLE(M->x[i],MnO->x[i]);
+    
+  EXPECT_ARRAY_EQ_TYPE_DOUBLE(M->x,M->dim->rank,MnO->x,MnO->dim->rank);
+
+
+}
+
+TEST(TensorProdCL){
+  dimension *d0=create_dim(3);
+  dimension *d1=create_dim(2);
+
+  d0->perm[0]=2;
+  d0->perm[1]=3;
+  d0->perm[2]=2;
+  
+  d1->perm[0]=2;
+  d1->perm[1]=3;
+
+  updateRankDim(d0);
+  updateRankDim(d1);
+
+
+  tensor_TYPE_FLOAT *M0 = CREATE_TENSOR_TYPE_FLOAT(d0);
+  tensor_TYPE_FLOAT *M1 = CREATE_TENSOR_TYPE_FLOAT(d1);
+
+  LOG("M0->dim->rank = %ld\n",M0->dim->rank);
+  LOG("M1->dim->rank = %ld\n",M1->dim->rank);
+  for(size_t i=0; i<M0->dim->rank;++i) M0->x[i]=i*0.1 +1;
+  for(size_t i=0; i<M1->dim->rank;++i) M1->x[i]=i*0.003 + 2;
+
+  print_tensor_float(M0,"M0");
+  print_tensor_float(M1,"M1");
+
+
+  tensor_TYPE_FLOAT *M; 
+  tensor_TYPE_FLOAT *Mn; 
+
+  tensorProd_TYPE_FLOAT(&M,M0,M1);
+  cl_tensorProd_TYPE_FLOAT(&Mn,M0,M1);
+  LOG("M->dim->rank = %ld\n",M->dim->rank);
+
+  print_tensor_float(M,"M");
+  
+  EXPECT_ARRAY_EQ_TYPE_FLOAT(M->x,M->dim->rank,Mn->x,Mn->dim->rank);
+
+
+  print_tensor_float(Mn,"Mn");
+}
+
+TEST(VS_cl_tensorContractnProd_TYPE_DOUBLE2 ){
+  dimension *d0=create_dim(3);
+  dimension *d1=create_dim(3);
+
+
+  d0->perm[0]=125;
+  d0->perm[1]=52; //3;
+  d0->perm[2]=63;
+
+  d1->perm[0]=52;
+  d1->perm[1]=63;//3;
+  d1->perm[2]=154;
+
+  updateRankDim(d0);
+  updateRankDim(d1);
+
+
+  tensor_TYPE_DOUBLE *M0 = CREATE_TENSOR_TYPE_DOUBLE(d0);
+  tensor_TYPE_DOUBLE *M1 = CREATE_TENSOR_TYPE_DOUBLE(d1);
+
+  LOG("M0->dim->rank = %ld\n",M0->dim->rank);
+  LOG("M1->dim->rank = %ld\n",M1->dim->rank);
+  for(size_t i=0; i<M0->dim->rank;++i) M0->x[i]=i*0.1 +1;
+  for(size_t i=0; i<M1->dim->rank;++i) M1->x[i]=i*0.003 + 2;
+
+  //print_tensor_double(M0,"M0");
+  //print_tensor_double(M1,"M1");
+
+  //tensor_TYPE_DOUBLE *M;
+  tensor_TYPE_DOUBLE *MnO;
+
+  //tensorContractnProdNotOpt_TYPE_DOUBLE(&M, M0,M1,2);
+  //tensorContractnProd_TYPE_DOUBLE(&M, M0,M1,2);
+  //print_tensor_double(M,"M");
+  cl_tensorContractnProd_TYPE_DOUBLE(&MnO, M0,M1,2);
+
+
+  //print_tensor_double(MnO,"MnO");
+ 
+  // for(size_t i=0;i<M->dim->rank;++i)
+  //    EXPECT_EQ_TYPE_DOUBLE(M->x[i],MnO->x[i]);
+    
+  //EXPECT_ARRAY_EQ_TYPE_DOUBLE(M->x,M->dim->rank,MnO->x,MnO->dim->rank);
+
+
+}
+
+
+TEST(VStensorContractnProd_TYPE_DOUBLE2 ){
+  dimension *d0=create_dim(3);
+  dimension *d1=create_dim(3);
+
+  d0->perm[0]=125;
+  d0->perm[1]=52; //3;
+  d0->perm[2]=63;
+
+  d1->perm[0]=52;
+  d1->perm[1]=63;//3;
+  d1->perm[2]=154;
+
+  updateRankDim(d0);
+  updateRankDim(d1);
+
+
+  tensor_TYPE_DOUBLE *M0 = CREATE_TENSOR_TYPE_DOUBLE(d0);
+  tensor_TYPE_DOUBLE *M1 = CREATE_TENSOR_TYPE_DOUBLE(d1);
+
+  LOG("M0->dim->rank = %ld\n",M0->dim->rank);
+  LOG("M1->dim->rank = %ld\n",M1->dim->rank);
+  for(size_t i=0; i<M0->dim->rank;++i) M0->x[i]=i*0.1 +1;
+  for(size_t i=0; i<M1->dim->rank;++i) M1->x[i]=i*0.003 + 2;
+
+  //print_tensor_double(M0,"M0");
+  //print_tensor_double(M1,"M1");
+
+  tensor_TYPE_DOUBLE *M;
+  //tensor_TYPE_DOUBLE *MnO;
+
+  tensorContractnProd_TYPE_DOUBLE(&M, M0,M1,2);
+  //print_tensor_double(M,"M");
+  //cl_tensorContractnProd_TYPE_DOUBLE(&MnO, M0,M1,2);
+  //tensorContractnProdNotOpt_TYPE_DOUBLE(&MnO, M0,M1,2);
+
+  //print_tensor_double(MnO,"MnO");
+ 
+  // for(size_t i=0;i<M->dim->rank;++i)
+  //    EXPECT_EQ_TYPE_DOUBLE(M->x[i],MnO->x[i]);
+    
+  //EXPECT_ARRAY_EQ_TYPE_DOUBLE(M->x,M->dim->rank,MnO->x,MnO->dim->rank);
+
+
+}
+TEST(tensorProd_vs2d ){
+  dimension *d0=create_dim(3);
+  dimension *d1=create_dim(2);
+
+  d0->perm[0]=24;
+  d0->perm[1]=32;
+  d0->perm[2]=2;
+
+  d1->perm[0]=64;
+  d1->perm[1]=16;
+
+  updateRankDim(d0);
+  updateRankDim(d1);
+
+
+  tensor_TYPE_FLOAT *M0 = CREATE_TENSOR_TYPE_FLOAT(d0);
+  tensor_TYPE_FLOAT *M1 = CREATE_TENSOR_TYPE_FLOAT(d1);
+
+  LOG("M0->dim->rank = %ld\n",M0->dim->rank);
+  LOG("M1->dim->rank = %ld\n",M1->dim->rank);
+  for(size_t i=0; i<M0->dim->rank;++i) M0->x[i]=i*0.1 +1;
+  for(size_t i=0; i<M1->dim->rank;++i) M1->x[i]=i*0.003 + 2;
+
+  /*print_tensor_float(M0,"M0");
+  print_tensor_float(M1,"M1");*/
+
+
+  tensor_TYPE_FLOAT *M;
+  tensor_TYPE_FLOAT *Mn;
+
+  cl_tensorProd_TYPE_FLOAT(&M,M0,M1);
+  tensorProd_TYPE_FLOAT(&Mn,M0,M1);
+  LOG("M->dim->rank = %ld\n",M->dim->rank);
+
+  //print_tensor_float(M,"M");
+
+  EXPECT_ARRAY_EQ_TYPE_FLOAT(M->x,M->dim->rank,Mn->x,Mn->dim->rank);
+
+  //print_tensor_float(Mn,"Mn");
+}
+
+
+
+TEST(tensorProd_vs2d ){
+  dimension *d0=create_dim(3);
+  dimension *d1=create_dim(2);
+
+  d0->perm[0]=24;
+  d0->perm[1]=32;
+  d0->perm[2]=2;
+
+  d1->perm[0]=64;
+  d1->perm[1]=24;
+
+  updateRankDim(d0);
+  updateRankDim(d1);
+
+
+  tensor_TYPE_FLOAT *M0 = CREATE_TENSOR_TYPE_FLOAT(d0);
+  tensor_TYPE_FLOAT *M1 = CREATE_TENSOR_TYPE_FLOAT(d1);
+
+  LOG("M0->dim->rank = %ld\n",M0->dim->rank);
+  LOG("M1->dim->rank = %ld\n",M1->dim->rank);
+  for(size_t i=0; i<M0->dim->rank;++i) M0->x[i]=i*0.1 +1;
+  for(size_t i=0; i<M1->dim->rank;++i) M1->x[i]=i*0.003 + 2;
+
+  /*print_tensor_float(M0,"M0");
+  print_tensor_float(M1,"M1");*/
+
+
+  tensor_TYPE_FLOAT *M;
+  tensor_TYPE_FLOAT *Mn;
+
+  tensorProd_TYPE_FLOAT(&M,M0,M1);
+  //cl2d_tensorProd_TYPE_FLOAT(&Mn,M0,M1,24,24);
+  //cl2d_tensorProd_TYPE_FLOAT(&Mn,M0,M1,32,32);
+  cl2d_tensorProd_TYPE_FLOAT(&Mn,M0,M1,64,16);
+  LOG("M->dim->rank = %ld\n",M->dim->rank);
+
+  //print_tensor_float(M,"M");
+
+  EXPECT_ARRAY_EQ_TYPE_FLOAT(M->x,M->dim->rank,Mn->x,Mn->dim->rank);
+
+  //print_tensor_float(Mn,"Mn");
+}
+
+
+int main(int argc, char **argv){
+  
+
+  run_all_tests_args(argc, argv);
+
+  return 0;
+}