| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315316317318319320321322323324325326327328329330331332333334335336337338339340341342343344345346347348349350351352353354355356357358359360361362363364365366367368369370371372373374375376377378379380381382383384385386387388389390391392393394395396397398399400401402403404405406407408409410411412413414415416417418419420421422423424425426427428429430431432433434435436437438439440441442443444445446447448449450451452453454455456457458459460461462463464465466467468469470471472473474475476477478479480481482483484485486487488489490491492493494495496497498499500501502503504505506507508509510511512513514515516517518519520521522523524525526527528529530531532533534535536537538539540541542543544545546547548549550551552553554555556557558559560561562563564565566567568569570571572573574575576577578579580581582583584585586587588589590591592593594595596597598599600601602603604605606607608609610611612613614615616617618619620621622623624625626627628629630631632633634635636637638639640641642643644645646647648649650651652653654655656657658659660661662663664665666667668669670671672673674675676677678679680681682683684685686687688689690691692693694695696697698699700701702703704705706707708709710711712713714715716717718719720721722723724725726727728729730731732733734735736737738739740741742743744745746747748749750751752753754755756757758759760761762763764765766767768769770771772773774775776777778779780781782783784785786787788789790791792793794795796797798799800801802803804805806807808809810811812813814815816817818819820821822823824825826827828829830831832833834835836837838839840841842843844845846847848849850851852853854855856857858859860861862863864865866867868869870871872873874875876877878879880881882883884885886887888889890891 |
- #include "UnaryTestsF32.h"
- #include "Error.h"
- #define SNR_THRESHOLD 120
- /*
- Reference patterns are generated with
- a double precision computation.
- */
- #define REL_ERROR (1.0e-5)
- #define ABS_ERROR (1.0e-5)
- /*
- Comparisons for inverse
- */
- /* Not very accurate for big matrix.
- But big matrix needed for checking the vectorized code */
- #define SNR_THRESHOLD_INV 67
- #define REL_ERROR_INV (1.0e-3)
- #define ABS_ERROR_INV (1.0e-3)
- /*
- Comparison for Cholesky
- */
- #define SNR_THRESHOLD_CHOL 92
- #define REL_ERROR_CHOL (1.0e-5)
- #define ABS_ERROR_CHOL (5.0e-4)
- /* LDLT comparison */
- #define REL_ERROR_LDLT (1e-5)
- #define ABS_ERROR_LDLT (1e-5)
- #define REL_ERROR_LDLT_SPDO (1e-5)
- #define ABS_ERROR_LDLT_SDPO (2e-1)
- /* Upper bound of maximum matrix dimension used by Python */
- #define MAXMATRIXDIM 40
- static void checkInnerTailOverflow(float32_t *b)
- {
- ASSERT_TRUE(b[0] == 0);
- ASSERT_TRUE(b[1] == 0);
- ASSERT_TRUE(b[2] == 0);
- ASSERT_TRUE(b[3] == 0);
- }
- #define LOADDATA2() \
- const float32_t *inp1=input1.ptr(); \
- const float32_t *inp2=input2.ptr(); \
- \
- float32_t *ap=a.ptr(); \
- float32_t *bp=b.ptr(); \
- \
- float32_t *outp=output.ptr(); \
- int16_t *dimsp = dims.ptr(); \
- int nbMatrixes = dims.nbSamples() >> 1;\
- int rows,columns; \
- int i;
- #define LOADDATA1() \
- const float32_t *inp1=input1.ptr(); \
- \
- float32_t *ap=a.ptr(); \
- \
- float32_t *outp=output.ptr(); \
- int16_t *dimsp = dims.ptr(); \
- int nbMatrixes = dims.nbSamples() >> 1;\
- int rows,columns; \
- int i;
- #define PREPAREDATA2() \
- in1.numRows=rows; \
- in1.numCols=columns; \
- memcpy((void*)ap,(const void*)inp1,sizeof(float32_t)*rows*columns);\
- in1.pData = ap; \
- \
- in2.numRows=rows; \
- in2.numCols=columns; \
- memcpy((void*)bp,(const void*)inp2,sizeof(float32_t)*rows*columns);\
- in2.pData = bp; \
- \
- out.numRows=rows; \
- out.numCols=columns; \
- out.pData = outp;
- #define PREPAREDATALT() \
- in1.numRows=rows; \
- in1.numCols=rows; \
- memcpy((void*)ap,(const void*)inp1,sizeof(float32_t)*rows*rows); \
- in1.pData = ap; \
- \
- in2.numRows=rows; \
- in2.numCols=columns; \
- memcpy((void*)bp,(const void*)inp2,sizeof(float32_t)*rows*columns);\
- in2.pData = bp; \
- \
- out.numRows=rows; \
- out.numCols=columns; \
- out.pData = outp;
- #define PREPAREDATA1(TRANSPOSED) \
- in1.numRows=rows; \
- in1.numCols=columns; \
- memcpy((void*)ap,(const void*)inp1,sizeof(float32_t)*rows*columns);\
- in1.pData = ap; \
- \
- if (TRANSPOSED) \
- { \
- out.numRows=columns; \
- out.numCols=rows; \
- } \
- else \
- { \
- out.numRows=rows; \
- out.numCols=columns; \
- } \
- out.pData = outp;
- #define PREPAREDATA1C(TRANSPOSED) \
- in1.numRows=rows; \
- in1.numCols=columns; \
- memcpy((void*)ap,(const void*)inp1,2*sizeof(float32_t)*rows*columns);\
- in1.pData = ap; \
- \
- if (TRANSPOSED) \
- { \
- out.numRows=columns; \
- out.numCols=rows; \
- } \
- else \
- { \
- out.numRows=rows; \
- out.numCols=columns; \
- } \
- out.pData = outp;
- #define LOADVECDATA2() \
- const float32_t *inp1=input1.ptr(); \
- const float32_t *inp2=input2.ptr(); \
- \
- float32_t *ap=a.ptr(); \
- float32_t *bp=b.ptr(); \
- \
- float32_t *outp=output.ptr(); \
- int16_t *dimsp = dims.ptr(); \
- int nbMatrixes = dims.nbSamples() / 2;\
- int rows,internal; \
- int i;
- #define PREPAREVECDATA2() \
- in1.numRows=rows; \
- in1.numCols=internal; \
- memcpy((void*)ap,(const void*)inp1,sizeof(float32_t)*rows*internal);\
- in1.pData = ap; \
- \
- memcpy((void*)bp,(const void*)inp2,sizeof(float32_t)*internal);
-
- #define PREPAREDATALL1() \
- in1.numRows=rows; \
- in1.numCols=columns; \
- memcpy((void*)ap,(const void*)inp1,sizeof(float32_t)*rows*columns);\
- in1.pData = ap; \
- \
- outll.numRows=rows; \
- outll.numCols=columns; \
- \
- outll.pData = outllp;
- #define SWAP_ROWS(A,i,j) \
- for(int w=0;w < n; w++) \
- { \
- float64_t tmp; \
- tmp = A[i*n + w]; \
- A[i*n + w] = A[j*n + w];\
- A[j*n + w] = tmp; \
- }
- void UnaryTestsF32::test_mat_vec_mult_f32()
- {
- LOADVECDATA2();
- for(i=0;i < nbMatrixes ; i ++)
- {
- rows = *dimsp++;
- internal = *dimsp++;
- PREPAREVECDATA2();
- arm_mat_vec_mult_f32(&this->in1, bp, outp);
- outp += rows ;
- checkInnerTailOverflow(outp);
- }
- ASSERT_EMPTY_TAIL(output);
- ASSERT_SNR(output,ref,(float32_t)SNR_THRESHOLD);
- ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR,REL_ERROR);
- }
- void UnaryTestsF32::test_mat_add_f32()
- {
- LOADDATA2();
- arm_status status;
- for(i=0;i < nbMatrixes ; i ++)
- {
- rows = *dimsp++;
- columns = *dimsp++;
- PREPAREDATA2();
- status=arm_mat_add_f32(&this->in1,&this->in2,&this->out);
- ASSERT_TRUE(status==ARM_MATH_SUCCESS);
- outp += (rows * columns);
- checkInnerTailOverflow(outp);
- }
- ASSERT_EMPTY_TAIL(output);
- ASSERT_SNR(output,ref,(float32_t)SNR_THRESHOLD);
- ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR,REL_ERROR);
- }
- void UnaryTestsF32::test_mat_sub_f32()
- {
- LOADDATA2();
- arm_status status;
- for(i=0;i < nbMatrixes ; i ++)
- {
- rows = *dimsp++;
- columns = *dimsp++;
- PREPAREDATA2();
- status=arm_mat_sub_f32(&this->in1,&this->in2,&this->out);
- ASSERT_TRUE(status==ARM_MATH_SUCCESS);
- outp += (rows * columns);
- checkInnerTailOverflow(outp);
- }
- ASSERT_EMPTY_TAIL(output);
- ASSERT_SNR(output,ref,(float32_t)SNR_THRESHOLD);
- ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR,REL_ERROR);
- }
- void UnaryTestsF32::test_mat_scale_f32()
- {
- LOADDATA1();
- arm_status status;
- for(i=0;i < nbMatrixes ; i ++)
- {
- rows = *dimsp++;
- columns = *dimsp++;
- PREPAREDATA1(false);
- status=arm_mat_scale_f32(&this->in1,0.5f,&this->out);
- ASSERT_TRUE(status==ARM_MATH_SUCCESS);
- outp += (rows * columns);
- checkInnerTailOverflow(outp);
- }
- ASSERT_EMPTY_TAIL(output);
- ASSERT_SNR(output,ref,(float32_t)SNR_THRESHOLD);
- ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR,REL_ERROR);
- }
- void UnaryTestsF32::test_mat_trans_f32()
- {
- LOADDATA1();
- arm_status status;
- for(i=0;i < nbMatrixes ; i ++)
- {
- rows = *dimsp++;
- columns = *dimsp++;
- PREPAREDATA1(true);
- status=arm_mat_trans_f32(&this->in1,&this->out);
- ASSERT_TRUE(status==ARM_MATH_SUCCESS);
- outp += (rows * columns);
- checkInnerTailOverflow(outp);
- }
- ASSERT_EMPTY_TAIL(output);
- ASSERT_SNR(output,ref,(float32_t)SNR_THRESHOLD);
- ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR,REL_ERROR);
- }
- void UnaryTestsF32::test_mat_cmplx_trans_f32()
- {
- LOADDATA1();
- arm_status status;
- for(i=0;i < nbMatrixes ; i ++)
- {
- rows = *dimsp++;
- columns = *dimsp++;
- PREPAREDATA1C(true);
- status=arm_mat_cmplx_trans_f32(&this->in1,&this->out);
- ASSERT_TRUE(status==ARM_MATH_SUCCESS);
- outp += 2*(rows * columns);
- checkInnerTailOverflow(outp);
- }
- ASSERT_EMPTY_TAIL(output);
- ASSERT_SNR(output,ref,(float32_t)SNR_THRESHOLD);
- ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR,REL_ERROR);
- }
- static void refInnerTail(float32_t *b)
- {
- b[0] = 1.0f;
- b[1] = -2.0f;
- b[2] = 3.0f;
- b[3] = -4.0f;
- }
- static void checkInnerTail(float32_t *b)
- {
- ASSERT_TRUE(b[0] == 1.0f);
- ASSERT_TRUE(b[1] == -2.0f);
- ASSERT_TRUE(b[2] == 3.0f);
- ASSERT_TRUE(b[3] == -4.0f);
- }
- void UnaryTestsF32::test_mat_inverse_f32()
- {
- const float32_t *inp1=input1.ptr();
-
- float32_t *ap=a.ptr();
-
- float32_t *outp=output.ptr();
- int16_t *dimsp = dims.ptr();
- int nbMatrixes = dims.nbSamples();
- int rows,columns;
- int i;
- arm_status status;
- for(i=0;i < nbMatrixes ; i ++)
- {
- rows = *dimsp++;
- columns = rows;
- PREPAREDATA1(false);
- refInnerTail(outp+(rows * columns));
- status=arm_mat_inverse_f32(&this->in1,&this->out);
- ASSERT_TRUE(status==ARM_MATH_SUCCESS);
- outp += (rows * columns);
- inp1 += (rows * columns);
- checkInnerTail(outp);
- }
- ASSERT_SNR(output,ref,(float32_t)SNR_THRESHOLD_INV);
- ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR_INV,REL_ERROR_INV);
- }
- void UnaryTestsF32::test_mat_cholesky_dpo_f32()
- {
- float32_t *ap=a.ptr();
- const float32_t *inp1=input1.ptr();
-
-
- float32_t *outp=output.ptr();
- int16_t *dimsp = dims.ptr();
- int nbMatrixes = dims.nbSamples();
- int rows,columns;
- int i;
- arm_status status;
- for(i=0;i < nbMatrixes ; i ++)
- {
- rows = *dimsp++;
- columns = rows;
- PREPAREDATA1(false);
- status=arm_mat_cholesky_f32(&this->in1,&this->out);
- ASSERT_TRUE(status==ARM_MATH_SUCCESS);
- outp += (rows * columns);
- inp1 += (rows * columns);
- checkInnerTailOverflow(outp);
- }
- ASSERT_EMPTY_TAIL(output);
- ASSERT_SNR(output,ref,(float32_t)SNR_THRESHOLD_CHOL);
- ASSERT_CLOSE_ERROR(ref,output,ABS_ERROR_CHOL,REL_ERROR_CHOL);
- }
- void UnaryTestsF32::test_solve_upper_triangular_f32()
- {
- float32_t *ap=a.ptr();
- const float32_t *inp1=input1.ptr();
- float32_t *bp=b.ptr();
- const float32_t *inp2=input2.ptr();
-
-
- float32_t *outp=output.ptr();
- int16_t *dimsp = dims.ptr();
- int nbMatrixes = dims.nbSamples()>>1;
- int rows,columns;
- int i;
- arm_status status;
- for(i=0;i < nbMatrixes ; i ++)
- {
- rows = *dimsp++;
- columns = *dimsp++;
- PREPAREDATALT();
- status=arm_mat_solve_upper_triangular_f32(&this->in1,&this->in2,&this->out);
- ASSERT_TRUE(status==ARM_MATH_SUCCESS);
- outp += (rows * columns);
- inp1 += (rows * rows);
- inp2 += (rows * columns);
- checkInnerTailOverflow(outp);
- }
- ASSERT_EMPTY_TAIL(output);
- ASSERT_SNR(output,ref,(float32_t)SNR_THRESHOLD);
- ASSERT_CLOSE_ERROR(ref,output,ABS_ERROR,REL_ERROR);
- }
- void UnaryTestsF32::test_solve_lower_triangular_f32()
- {
- float32_t *ap=a.ptr();
- const float32_t *inp1=input1.ptr();
- float32_t *bp=b.ptr();
- const float32_t *inp2=input2.ptr();
-
-
- float32_t *outp=output.ptr();
- int16_t *dimsp = dims.ptr();
- int nbMatrixes = dims.nbSamples() >> 1;
- int rows,columns;
- int i;
- arm_status status;
- for(i=0;i < nbMatrixes ; i ++)
- {
- rows = *dimsp++;
- columns = *dimsp++;
- PREPAREDATALT();
- status=arm_mat_solve_lower_triangular_f32(&this->in1,&this->in2,&this->out);
- ASSERT_TRUE(status==ARM_MATH_SUCCESS);
- outp += (rows * columns);
- inp1 += (rows * rows);
- inp2 += (rows * columns);
- checkInnerTailOverflow(outp);
- }
- ASSERT_EMPTY_TAIL(output);
- ASSERT_SNR(output,ref,(float32_t)SNR_THRESHOLD);
- ASSERT_CLOSE_ERROR(ref,output,ABS_ERROR,REL_ERROR);
- }
- static void trans_f64(const float64_t *src, float64_t *dst, int n)
- {
- for(int r=0; r<n ; r++)
- {
- for(int c=0; c<n ; c++)
- {
- dst[c*n+r] = src[r*n+c];
- }
- }
- }
- static void trans_f32_f64(const float32_t *src, float64_t *dst, int n)
- {
- for(int r=0; r<n ; r++)
- {
- for(int c=0; c<n ; c++)
- {
- dst[c*n+r] = (float64_t)src[r*n+c];
- }
- }
- }
- static void mult_f32_f64(const float32_t *srcA, const float64_t *srcB, float64_t *dst,int n)
- {
- for(int r=0; r<n ; r++)
- {
- for(int c=0; c<n ; c++)
- {
- float64_t sum=0.0;
- for(int k=0; k < n ; k++)
- {
- sum += (float64_t)srcA[r*n+k] * srcB[k*n+c];
- }
- dst[r*n+c] = sum;
- }
- }
- }
- static void mult_f64_f64(const float64_t *srcA, const float64_t *srcB, float64_t *dst,int n)
- {
- for(int r=0; r<n ; r++)
- {
- for(int c=0; c<n ; c++)
- {
- float64_t sum=0.0;
- for(int k=0; k < n ; k++)
- {
- sum += srcA[r*n+k] * srcB[k*n+c];
- }
- dst[r*n+c] = sum;
- }
- }
- }
-
- void UnaryTestsF32::compute_ldlt_error(const int n,const int16_t *outpp)
- {
- float64_t *tmpa = tmpapat.ptr() ;
- float64_t *tmpb = tmpbpat.ptr() ;
- float64_t *tmpc = tmpcpat.ptr() ;
-
-
- /* Compute P A P^t */
- // Create identiy matrix
- for(int r=0; r < n; r++)
- {
- for(int c=0; c < n; c++)
- {
- if (r == c)
- {
- tmpa[r*n+c] = 1.0;
- }
- else
- {
- tmpa[r*n+c] = 0.0;
- }
- }
- }
-
- // Create permutation matrix
- for(int r=0;r < n; r++)
- {
- SWAP_ROWS(tmpa,r,outpp[r]);
- }
-
- trans_f64((const float64_t*)tmpa,tmpb,n);
- mult_f32_f64((const float32_t*)this->in1.pData,(const float64_t*)tmpb,tmpc,n);
- mult_f64_f64((const float64_t*)tmpa,(const float64_t*)tmpc,outa,n);
-
- /* Compute L D L^t */
- trans_f32_f64((const float32_t*)this->outll.pData,tmpc,n);
- mult_f32_f64((const float32_t*)this->outd.pData,(const float64_t*)tmpc,tmpa,n);
- mult_f32_f64((const float32_t*)this->outll.pData,(const float64_t*)tmpa,outb,n);
-
-
- }
- void UnaryTestsF32::test_mat_ldl_f32()
- {
- float32_t *ap=a.ptr();
- const float32_t *inp1=input1.ptr();
-
- float32_t *outllp=outputll.ptr();
- float32_t *outdp=outputd.ptr();
- int16_t *outpp=outputp.ptr();
- outa=outputa.ptr();
- outb=outputb.ptr();
- int16_t *dimsp = dims.ptr();
- int nbMatrixes = dims.nbSamples();
- int rows,columns;
- int i;
- arm_status status;
- for(i=0;i < nbMatrixes ; i ++)
- {
- rows = *dimsp++;
- columns = rows;
- PREPAREDATALL1();
- outd.numRows=rows;
- outd.numCols=columns;
- outd.pData=outdp;
- memset(outpp,0,rows*sizeof(uint16_t));
- memset(outdp,0,columns*rows*sizeof(float32_t));
- status=arm_mat_ldlt_f32(&this->in1,&this->outll,&this->outd,(uint16_t*)outpp);
- ASSERT_TRUE(status==ARM_MATH_SUCCESS);
-
- compute_ldlt_error(rows,outpp);
-
- outllp += (rows * columns);
- outdp += (rows * columns);
- outpp += rows;
- outa += (rows * columns);
- outb +=(rows * columns);
- inp1 += (rows * columns);
- checkInnerTailOverflow(outllp);
- checkInnerTailOverflow(outdp);
- }
- ASSERT_EMPTY_TAIL(outputll);
- ASSERT_EMPTY_TAIL(outputd);
- ASSERT_EMPTY_TAIL(outputp);
- ASSERT_EMPTY_TAIL(outputa);
- ASSERT_EMPTY_TAIL(outputb);
- ASSERT_CLOSE_ERROR(outputa,outputb,snrAbs,snrRel);
-
- }
- void UnaryTestsF32::setUp(Testing::testID_t id,std::vector<Testing::param_t>& params,Client::PatternMgr *mgr)
- {
- (void)params;
- switch(id)
- {
- case TEST_MAT_ADD_F32_1:
- input1.reload(UnaryTestsF32::INPUTS1_F32_ID,mgr);
- input2.reload(UnaryTestsF32::INPUTS2_F32_ID,mgr);
- dims.reload(UnaryTestsF32::DIMSUNARY1_S16_ID,mgr);
- ref.reload(UnaryTestsF32::REFADD1_F32_ID,mgr);
- output.create(ref.nbSamples(),UnaryTestsF32::OUT_F32_ID,mgr);
- a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPA_F32_ID,mgr);
- b.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPB_F32_ID,mgr);
- break;
- case TEST_MAT_SUB_F32_2:
- input1.reload(UnaryTestsF32::INPUTS1_F32_ID,mgr);
- input2.reload(UnaryTestsF32::INPUTS2_F32_ID,mgr);
- dims.reload(UnaryTestsF32::DIMSUNARY1_S16_ID,mgr);
- ref.reload(UnaryTestsF32::REFSUB1_F32_ID,mgr);
- output.create(ref.nbSamples(),UnaryTestsF32::OUT_F32_ID,mgr);
- a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPA_F32_ID,mgr);
- b.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPB_F32_ID,mgr);
- break;
- case TEST_MAT_SCALE_F32_3:
- input1.reload(UnaryTestsF32::INPUTS1_F32_ID,mgr);
- dims.reload(UnaryTestsF32::DIMSUNARY1_S16_ID,mgr);
- ref.reload(UnaryTestsF32::REFSCALE1_F32_ID,mgr);
- output.create(ref.nbSamples(),UnaryTestsF32::OUT_F32_ID,mgr);
- a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPA_F32_ID,mgr);
- break;
- case TEST_MAT_TRANS_F32_4:
- input1.reload(UnaryTestsF32::INPUTS1_F32_ID,mgr);
- dims.reload(UnaryTestsF32::DIMSUNARY1_S16_ID,mgr);
- ref.reload(UnaryTestsF32::REFTRANS1_F32_ID,mgr);
- output.create(ref.nbSamples(),UnaryTestsF32::OUT_F32_ID,mgr);
- a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPA_F32_ID,mgr);
- break;
- case TEST_MAT_INVERSE_F32_5:
- input1.reload(UnaryTestsF32::INPUTSINV_F32_ID,mgr);
- dims.reload(UnaryTestsF32::DIMSINVERT1_S16_ID,mgr);
- ref.reload(UnaryTestsF32::REFINV1_F32_ID,mgr);
- output.create(ref.nbSamples(),UnaryTestsF32::OUT_F32_ID,mgr);
- a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPA_F32_ID,mgr);
- break;
- case TEST_MAT_VEC_MULT_F32_6:
- input1.reload(UnaryTestsF32::INPUTS1_F32_ID,mgr);
- input2.reload(UnaryTestsF32::INPUTVEC1_F32_ID,mgr);
- dims.reload(UnaryTestsF32::DIMSUNARY1_S16_ID,mgr);
- ref.reload(UnaryTestsF32::REFVECMUL1_F32_ID,mgr);
- output.create(ref.nbSamples(),UnaryTestsF32::OUT_F32_ID,mgr);
- a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPA_F32_ID,mgr);
- b.create(MAXMATRIXDIM,UnaryTestsF32::TMPB_F32_ID,mgr);
- break;
- case TEST_MAT_CMPLX_TRANS_F32_7:
- input1.reload(UnaryTestsF32::INPUTSC1_F32_ID,mgr);
- dims.reload(UnaryTestsF32::DIMSUNARY1_S16_ID,mgr);
- ref.reload(UnaryTestsF32::REFTRANSC1_F32_ID,mgr);
- output.create(ref.nbSamples(),UnaryTestsF32::OUT_F32_ID,mgr);
- a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPA_F32_ID,mgr);
- break;
- case TEST_MAT_CHOLESKY_DPO_F32_8:
- input1.reload(UnaryTestsF32::INPUTSCHOLESKY1_DPO_F32_ID,mgr);
- dims.reload(UnaryTestsF32::DIMSCHOLESKY1_DPO_S16_ID,mgr);
- ref.reload(UnaryTestsF32::REFCHOLESKY1_DPO_F32_ID,mgr);
- output.create(ref.nbSamples(),UnaryTestsF32::OUT_F32_ID,mgr);
- a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPA_F32_ID,mgr);
-
- break;
- case TEST_SOLVE_UPPER_TRIANGULAR_F32_9:
- input1.reload(UnaryTestsF32::INPUT_MAT_UTSOLVE_F32_ID,mgr);
- input2.reload(UnaryTestsF32::INPUT_VEC_LTSOLVE_F32_ID,mgr);
- dims.reload(UnaryTestsF32::DIM_LTSOLVE_F32_ID,mgr);
- ref.reload(UnaryTestsF32::REF_UT_SOLVE_F32_ID,mgr);
- output.create(ref.nbSamples(),UnaryTestsF32::OUT_F32_ID,mgr);
- a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPA_F32_ID,mgr);
- b.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPB_F32_ID,mgr);
- break;
- case TEST_SOLVE_LOWER_TRIANGULAR_F32_10:
- input1.reload(UnaryTestsF32::INPUT_MAT_LTSOLVE_F32_ID,mgr);
- input2.reload(UnaryTestsF32::INPUT_VEC_LTSOLVE_F32_ID,mgr);
- dims.reload(UnaryTestsF32::DIM_LTSOLVE_F32_ID,mgr);
- ref.reload(UnaryTestsF32::REF_LT_SOLVE_F32_ID,mgr);
- output.create(ref.nbSamples(),UnaryTestsF32::OUT_F32_ID,mgr);
- a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPA_F32_ID,mgr);
- b.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPB_F32_ID,mgr);
- break;
- case TEST_MAT_LDL_F32_11:
- // Definite positive test
- input1.reload(UnaryTestsF32::INPUTSCHOLESKY1_DPO_F32_ID,mgr);
- dims.reload(UnaryTestsF32::DIMSCHOLESKY1_DPO_S16_ID,mgr);
- outputll.create(input1.nbSamples(),UnaryTestsF32::LL_F32_ID,mgr);
- outputd.create(input1.nbSamples(),UnaryTestsF32::D_F32_ID,mgr);
- outputp.create(input1.nbSamples(),UnaryTestsF32::PERM_S16_ID,mgr);
- outputa.create(input1.nbSamples(),UnaryTestsF32::OUTA_F64_ID,mgr);
- outputb.create(input1.nbSamples(),UnaryTestsF32::OUTB_F64_ID,mgr);
- a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPA_F32_ID,mgr);
-
- tmpapat.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPB_F64_ID,mgr);
- tmpbpat.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPC_F64_ID,mgr);
- tmpcpat.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPD_F64_ID,mgr);
- this->snrRel=REL_ERROR_LDLT;
- this->snrAbs=ABS_ERROR_LDLT;
- break;
- case TEST_MAT_LDL_F32_12:
- // Semi definite positive test
- input1.reload(UnaryTestsF32::INPUTSCHOLESKY1_SDPO_F32_ID,mgr);
- dims.reload(UnaryTestsF32::DIMSCHOLESKY1_SDPO_S16_ID,mgr);
-
- outputll.create(input1.nbSamples(),UnaryTestsF32::LL_F32_ID,mgr);
- outputd.create(input1.nbSamples(),UnaryTestsF32::D_F32_ID,mgr);
- outputp.create(input1.nbSamples(),UnaryTestsF32::PERM_S16_ID,mgr);
- outputa.create(input1.nbSamples(),UnaryTestsF32::OUTA_F64_ID,mgr);
- outputb.create(input1.nbSamples(),UnaryTestsF32::OUTB_F64_ID,mgr);
- a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPA_F32_ID,mgr);
-
- tmpapat.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPB_F64_ID,mgr);
- tmpbpat.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPC_F64_ID,mgr);
- tmpcpat.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF32::TMPD_F64_ID,mgr);
- this->snrRel=REL_ERROR_LDLT_SPDO;
- this->snrAbs=ABS_ERROR_LDLT_SDPO;
- break;
- }
-
-
- }
- void UnaryTestsF32::tearDown(Testing::testID_t id,Client::PatternMgr *mgr)
- {
- (void)id;
- (void)mgr;
- switch(id)
- {
- case TEST_MAT_LDL_F32_11:
- //outputll.dump(mgr);
- break;
- }
- //output.dump(mgr);
- }
|