617 lines
20 KiB
C++
Executable File
617 lines
20 KiB
C++
Executable File
#include "UnaryTestsF16.h"
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#include <stdio.h>
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#include "Error.h"
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#define SNR_THRESHOLD 57
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/*
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Reference patterns are generated with
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a double precision computation.
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*/
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#define REL_ERROR (1.1e-3)
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#define ABS_ERROR (1.1e-3)
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/*
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Comparisons for inverse
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*/
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/* Not very accurate for big matrix.
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But big matrix needed for checking the vectorized code */
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#define SNR_THRESHOLD_INV 45
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#define REL_ERROR_INV (3.0e-2)
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#define ABS_ERROR_INV (3.0e-2)
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#define REL_ERROR_SOLVE (6.0e-2)
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#define ABS_ERROR_SOLVE (2.0e-2)
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/*
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Comparison for Cholesky
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*/
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#define SNR_THRESHOLD_CHOL 45
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#define REL_ERROR_CHOL (3.0e-3)
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#define ABS_ERROR_CHOL (3.0e-2)
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/* Upper bound of maximum matrix dimension used by Python */
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#define MAXMATRIXDIM 40
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#define LOADDATA2() \
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const float16_t *inp1=input1.ptr(); \
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const float16_t *inp2=input2.ptr(); \
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\
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float16_t *ap=a.ptr(); \
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float16_t *bp=b.ptr(); \
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\
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float16_t *outp=output.ptr(); \
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int16_t *dimsp = dims.ptr(); \
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int nbMatrixes = dims.nbSamples() >> 1;\
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int rows,columns; \
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int i;
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#define LOADDATA1() \
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const float16_t *inp1=input1.ptr(); \
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\
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float16_t *ap=a.ptr(); \
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\
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float16_t *outp=output.ptr(); \
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int16_t *dimsp = dims.ptr(); \
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int nbMatrixes = dims.nbSamples() >> 1;\
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int rows,columns; \
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int i;
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#define PREPAREDATA2() \
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in1.numRows=rows; \
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in1.numCols=columns; \
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memcpy((void*)ap,(const void*)inp1,sizeof(float16_t)*rows*columns);\
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in1.pData = ap; \
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\
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in2.numRows=rows; \
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in2.numCols=columns; \
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memcpy((void*)bp,(const void*)inp2,sizeof(float16_t)*rows*columns);\
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in2.pData = bp; \
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\
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out.numRows=rows; \
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out.numCols=columns; \
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out.pData = outp;
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#define PREPAREDATALT() \
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in1.numRows=rows; \
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in1.numCols=rows; \
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memcpy((void*)ap,(const void*)inp1,sizeof(float16_t)*rows*rows); \
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in1.pData = ap; \
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\
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in2.numRows=rows; \
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in2.numCols=columns; \
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memcpy((void*)bp,(const void*)inp2,sizeof(float16_t)*rows*columns);\
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in2.pData = bp; \
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\
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out.numRows=rows; \
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out.numCols=columns; \
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out.pData = outp;
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#define PREPAREDATA1(TRANSPOSED) \
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in1.numRows=rows; \
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in1.numCols=columns; \
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memcpy((void*)ap,(const void*)inp1,sizeof(float16_t)*rows*columns);\
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in1.pData = ap; \
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\
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if (TRANSPOSED) \
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{ \
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out.numRows=columns; \
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out.numCols=rows; \
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} \
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else \
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{ \
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out.numRows=rows; \
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out.numCols=columns; \
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} \
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out.pData = outp;
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#define PREPAREDATA1C(TRANSPOSED) \
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in1.numRows=rows; \
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in1.numCols=columns; \
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memcpy((void*)ap,(const void*)inp1,2*sizeof(float16_t)*rows*columns);\
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in1.pData = ap; \
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\
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if (TRANSPOSED) \
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{ \
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out.numRows=columns; \
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out.numCols=rows; \
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} \
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else \
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{ \
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out.numRows=rows; \
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out.numCols=columns; \
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} \
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out.pData = outp;
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#define LOADVECDATA2() \
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const float16_t *inp1=input1.ptr(); \
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const float16_t *inp2=input2.ptr(); \
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\
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float16_t *ap=a.ptr(); \
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float16_t *bp=b.ptr(); \
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\
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float16_t *outp=output.ptr(); \
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int16_t *dimsp = dims.ptr(); \
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int nbMatrixes = dims.nbSamples() / 2;\
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int rows,internal; \
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int i;
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#define PREPAREVECDATA2() \
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in1.numRows=rows; \
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in1.numCols=internal; \
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memcpy((void*)ap,(const void*)inp1,sizeof(float16_t)*rows*internal);\
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in1.pData = ap; \
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\
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memcpy((void*)bp,(const void*)inp2,sizeof(float16_t)*internal);
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void UnaryTestsF16::test_mat_vec_mult_f16()
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{
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LOADVECDATA2();
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for(i=0;i < nbMatrixes ; i ++)
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{
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rows = *dimsp++;
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internal = *dimsp++;
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PREPAREVECDATA2();
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arm_mat_vec_mult_f16(&this->in1, bp, outp);
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outp += rows ;
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}
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ASSERT_EMPTY_TAIL(output);
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ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD);
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ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR,REL_ERROR);
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}
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void UnaryTestsF16::test_mat_add_f16()
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{
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LOADDATA2();
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arm_status status;
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for(i=0;i < nbMatrixes ; i ++)
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{
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rows = *dimsp++;
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columns = *dimsp++;
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PREPAREDATA2();
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status=arm_mat_add_f16(&this->in1,&this->in2,&this->out);
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ASSERT_TRUE(status==ARM_MATH_SUCCESS);
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outp += (rows * columns);
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}
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ASSERT_EMPTY_TAIL(output);
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ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD);
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ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR,REL_ERROR);
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}
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void UnaryTestsF16::test_mat_sub_f16()
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{
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LOADDATA2();
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arm_status status;
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for(i=0;i < nbMatrixes ; i ++)
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{
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rows = *dimsp++;
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columns = *dimsp++;
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PREPAREDATA2();
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status=arm_mat_sub_f16(&this->in1,&this->in2,&this->out);
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ASSERT_TRUE(status==ARM_MATH_SUCCESS);
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outp += (rows * columns);
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}
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ASSERT_EMPTY_TAIL(output);
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ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD);
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ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR,REL_ERROR);
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}
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void UnaryTestsF16::test_mat_scale_f16()
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{
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LOADDATA1();
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arm_status status;
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for(i=0;i < nbMatrixes ; i ++)
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{
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rows = *dimsp++;
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columns = *dimsp++;
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PREPAREDATA1(false);
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status=arm_mat_scale_f16(&this->in1,0.5f,&this->out);
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ASSERT_TRUE(status==ARM_MATH_SUCCESS);
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outp += (rows * columns);
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}
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ASSERT_EMPTY_TAIL(output);
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ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD);
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ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR,REL_ERROR);
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}
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void UnaryTestsF16::test_mat_trans_f16()
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{
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LOADDATA1();
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arm_status status;
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for(i=0;i < nbMatrixes ; i ++)
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{
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rows = *dimsp++;
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columns = *dimsp++;
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PREPAREDATA1(true);
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status=arm_mat_trans_f16(&this->in1,&this->out);
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ASSERT_TRUE(status==ARM_MATH_SUCCESS);
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outp += (rows * columns);
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}
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ASSERT_EMPTY_TAIL(output);
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ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD);
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ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR,REL_ERROR);
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}
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void UnaryTestsF16::test_mat_cmplx_trans_f16()
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{
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LOADDATA1();
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arm_status status;
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for(i=0;i < nbMatrixes ; i ++)
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{
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rows = *dimsp++;
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columns = *dimsp++;
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PREPAREDATA1C(true);
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status=arm_mat_cmplx_trans_f16(&this->in1,&this->out);
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ASSERT_TRUE(status==ARM_MATH_SUCCESS);
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outp += 2*(rows * columns);
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}
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ASSERT_EMPTY_TAIL(output);
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ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD);
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ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR,REL_ERROR);
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}
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static void refInnerTail(float16_t *b)
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{
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b[0] = 1.0f;
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b[1] = -2.0f;
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b[2] = 3.0f;
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b[3] = -4.0f;
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}
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static void checkInnerTail(float16_t *b)
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{
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ASSERT_TRUE(b[0] == 1.0f);
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ASSERT_TRUE(b[1] == -2.0f);
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ASSERT_TRUE(b[2] == 3.0f);
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ASSERT_TRUE(b[3] == -4.0f);
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}
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void UnaryTestsF16::test_mat_inverse_f16()
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{
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const float16_t *inp1=input1.ptr();
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float16_t *ap=a.ptr();
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float16_t *outp=output.ptr();
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int16_t *dimsp = dims.ptr();
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int nbMatrixes = dims.nbSamples();
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int rows,columns;
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int i;
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arm_status status;
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for(i=0;i < nbMatrixes ; i ++)
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{
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rows = *dimsp++;
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columns = rows;
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PREPAREDATA1(false);
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refInnerTail(outp+(rows * columns));
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status=arm_mat_inverse_f16(&this->in1,&this->out);
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ASSERT_TRUE(status==ARM_MATH_SUCCESS);
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outp += (rows * columns);
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inp1 += (rows * columns);
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checkInnerTail(outp);
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}
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ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD_INV);
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ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR_INV,REL_ERROR_INV);
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}
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void UnaryTestsF16::test_mat_cholesky_dpo_f16()
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{
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float16_t *ap=a.ptr();
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const float16_t *inp1=input1.ptr();
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float16_t *outp=output.ptr();
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int16_t *dimsp = dims.ptr();
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int nbMatrixes = dims.nbSamples();
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int rows,columns;
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int i;
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arm_status status;
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for(i=0;i < nbMatrixes ; i ++)
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{
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rows = *dimsp++;
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columns = rows;
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PREPAREDATA1(false);
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status=arm_mat_cholesky_f16(&this->in1,&this->out);
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ASSERT_TRUE(status==ARM_MATH_SUCCESS);
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outp += (rows * columns);
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inp1 += (rows * columns);
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}
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ASSERT_EMPTY_TAIL(output);
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ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD_CHOL);
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ASSERT_CLOSE_ERROR(ref,output,ABS_ERROR_CHOL,REL_ERROR_CHOL);
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}
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void UnaryTestsF16::test_solve_upper_triangular_f16()
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{
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float16_t *ap=a.ptr();
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const float16_t *inp1=input1.ptr();
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float16_t *bp=b.ptr();
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const float16_t *inp2=input2.ptr();
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float16_t *outp=output.ptr();
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int16_t *dimsp = dims.ptr();
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int nbMatrixes = dims.nbSamples() >> 1;
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int rows,columns;
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int i;
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arm_status status;
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for(i=0;i < nbMatrixes ; i ++)
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{
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rows = *dimsp++;
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columns = *dimsp++;
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PREPAREDATALT();
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status=arm_mat_solve_upper_triangular_f16(&this->in1,&this->in2,&this->out);
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ASSERT_TRUE(status==ARM_MATH_SUCCESS);
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outp += (rows * columns);
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inp1 += (rows * rows);
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inp2 += (rows * columns);
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}
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ASSERT_EMPTY_TAIL(output);
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ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD);
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ASSERT_CLOSE_ERROR(ref,output,ABS_ERROR_SOLVE,REL_ERROR_SOLVE);
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}
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void UnaryTestsF16::test_solve_lower_triangular_f16()
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{
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float16_t *ap=a.ptr();
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const float16_t *inp1=input1.ptr();
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float16_t *bp=b.ptr();
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const float16_t *inp2=input2.ptr();
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float16_t *outp=output.ptr();
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int16_t *dimsp = dims.ptr();
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int nbMatrixes = dims.nbSamples()>>1;
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int rows,columns;
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int i;
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arm_status status;
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for(i=0;i < nbMatrixes ; i ++)
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{
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rows = *dimsp++;
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columns = *dimsp++;
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PREPAREDATALT();
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status=arm_mat_solve_lower_triangular_f16(&this->in1,&this->in2,&this->out);
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ASSERT_TRUE(status==ARM_MATH_SUCCESS);
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outp += (rows * columns);
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inp1 += (rows * rows);
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inp2 += (rows * columns);
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}
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ASSERT_EMPTY_TAIL(output);
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ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD);
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ASSERT_CLOSE_ERROR(ref,output,ABS_ERROR_SOLVE,REL_ERROR_SOLVE);
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}
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void UnaryTestsF16::setUp(Testing::testID_t id,std::vector<Testing::param_t>& params,Client::PatternMgr *mgr)
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{
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(void)params;
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switch(id)
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{
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case TEST_MAT_ADD_F16_1:
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input1.reload(UnaryTestsF16::INPUTS1_F16_ID,mgr);
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input2.reload(UnaryTestsF16::INPUTS2_F16_ID,mgr);
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dims.reload(UnaryTestsF16::DIMSUNARY1_S16_ID,mgr);
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ref.reload(UnaryTestsF16::REFADD1_F16_ID,mgr);
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output.create(ref.nbSamples(),UnaryTestsF16::OUT_F16_ID,mgr);
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a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPA_F16_ID,mgr);
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b.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPB_F16_ID,mgr);
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break;
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case TEST_MAT_SUB_F16_2:
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input1.reload(UnaryTestsF16::INPUTS1_F16_ID,mgr);
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input2.reload(UnaryTestsF16::INPUTS2_F16_ID,mgr);
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dims.reload(UnaryTestsF16::DIMSUNARY1_S16_ID,mgr);
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ref.reload(UnaryTestsF16::REFSUB1_F16_ID,mgr);
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output.create(ref.nbSamples(),UnaryTestsF16::OUT_F16_ID,mgr);
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a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPA_F16_ID,mgr);
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b.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPB_F16_ID,mgr);
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break;
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case TEST_MAT_SCALE_F16_3:
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input1.reload(UnaryTestsF16::INPUTS1_F16_ID,mgr);
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dims.reload(UnaryTestsF16::DIMSUNARY1_S16_ID,mgr);
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ref.reload(UnaryTestsF16::REFSCALE1_F16_ID,mgr);
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output.create(ref.nbSamples(),UnaryTestsF16::OUT_F16_ID,mgr);
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a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPA_F16_ID,mgr);
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break;
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case TEST_MAT_TRANS_F16_4:
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input1.reload(UnaryTestsF16::INPUTS1_F16_ID,mgr);
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dims.reload(UnaryTestsF16::DIMSUNARY1_S16_ID,mgr);
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ref.reload(UnaryTestsF16::REFTRANS1_F16_ID,mgr);
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output.create(ref.nbSamples(),UnaryTestsF16::OUT_F16_ID,mgr);
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a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPA_F16_ID,mgr);
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break;
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case TEST_MAT_INVERSE_F16_5:
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input1.reload(UnaryTestsF16::INPUTSINV_F16_ID,mgr);
|
|
dims.reload(UnaryTestsF16::DIMSINVERT1_S16_ID,mgr);
|
|
|
|
ref.reload(UnaryTestsF16::REFINV1_F16_ID,mgr);
|
|
|
|
output.create(ref.nbSamples(),UnaryTestsF16::OUT_F16_ID,mgr);
|
|
a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPA_F16_ID,mgr);
|
|
break;
|
|
|
|
case TEST_MAT_VEC_MULT_F16_6:
|
|
input1.reload(UnaryTestsF16::INPUTS1_F16_ID,mgr);
|
|
input2.reload(UnaryTestsF16::INPUTVEC1_F16_ID,mgr);
|
|
dims.reload(UnaryTestsF16::DIMSUNARY1_S16_ID,mgr);
|
|
|
|
ref.reload(UnaryTestsF16::REFVECMUL1_F16_ID,mgr);
|
|
|
|
output.create(ref.nbSamples(),UnaryTestsF16::OUT_F16_ID,mgr);
|
|
a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPA_F16_ID,mgr);
|
|
b.create(MAXMATRIXDIM,UnaryTestsF16::TMPB_F16_ID,mgr);
|
|
break;
|
|
|
|
case TEST_MAT_CMPLX_TRANS_F16_7:
|
|
input1.reload(UnaryTestsF16::INPUTSC1_F16_ID,mgr);
|
|
dims.reload(UnaryTestsF16::DIMSUNARY1_S16_ID,mgr);
|
|
|
|
ref.reload(UnaryTestsF16::REFTRANSC1_F16_ID,mgr);
|
|
|
|
output.create(ref.nbSamples(),UnaryTestsF16::OUT_F16_ID,mgr);
|
|
a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPA_F16_ID,mgr);
|
|
break;
|
|
|
|
case TEST_MAT_CHOLESKY_DPO_F16_8:
|
|
input1.reload(UnaryTestsF16::INPUTSCHOLESKY1_DPO_F16_ID,mgr);
|
|
dims.reload(UnaryTestsF16::DIMSCHOLESKY1_DPO_S16_ID,mgr);
|
|
|
|
ref.reload(UnaryTestsF16::REFCHOLESKY1_DPO_F16_ID,mgr);
|
|
|
|
output.create(ref.nbSamples(),UnaryTestsF16::OUT_F16_ID,mgr);
|
|
a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPA_F16_ID,mgr);
|
|
break;
|
|
|
|
case TEST_SOLVE_UPPER_TRIANGULAR_F16_9:
|
|
input1.reload(UnaryTestsF16::INPUT_MAT_UTSOLVE_F16_ID,mgr);
|
|
input2.reload(UnaryTestsF16::INPUT_VEC_LTSOLVE_F16_ID,mgr);
|
|
dims.reload(UnaryTestsF16::DIM_LTSOLVE_F16_ID,mgr);
|
|
|
|
ref.reload(UnaryTestsF16::REF_UT_SOLVE_F16_ID,mgr);
|
|
|
|
output.create(ref.nbSamples(),UnaryTestsF16::OUT_F16_ID,mgr);
|
|
a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPA_F16_ID,mgr);
|
|
b.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPB_F16_ID,mgr);
|
|
break;
|
|
|
|
case TEST_SOLVE_LOWER_TRIANGULAR_F16_10:
|
|
input1.reload(UnaryTestsF16::INPUT_MAT_LTSOLVE_F16_ID,mgr);
|
|
input2.reload(UnaryTestsF16::INPUT_VEC_LTSOLVE_F16_ID,mgr);
|
|
dims.reload(UnaryTestsF16::DIM_LTSOLVE_F16_ID,mgr);
|
|
|
|
ref.reload(UnaryTestsF16::REF_LT_SOLVE_F16_ID,mgr);
|
|
|
|
output.create(ref.nbSamples(),UnaryTestsF16::OUT_F16_ID,mgr);
|
|
a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPA_F16_ID,mgr);
|
|
b.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPB_F16_ID,mgr);
|
|
break;
|
|
}
|
|
|
|
|
|
|
|
}
|
|
|
|
void UnaryTestsF16::tearDown(Testing::testID_t id,Client::PatternMgr *mgr)
|
|
{
|
|
(void)id;
|
|
//output.dump(mgr);
|
|
(void)mgr;
|
|
}
|