630 lines
20 KiB
C++
Executable File
630 lines
20 KiB
C++
Executable File
#include "UnaryTestsF64.h"
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#include "Error.h"
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#define SNR_THRESHOLD 120
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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 (1.0e-6)
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#define ABS_ERROR (1.0e-5)
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/*
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Comparison for Cholesky
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*/
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#define SNR_THRESHOLD_CHOL 270
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#define REL_ERROR_CHOL (1.0e-9)
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#define ABS_ERROR_CHOL (1.0e-9)
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/* LDLT comparison */
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#define REL_ERROR_LDLT (1e-5)
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#define ABS_ERROR_LDLT (1e-5)
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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 float64_t *inp1=input1.ptr(); \
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const float64_t *inp2=input2.ptr(); \
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\
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float64_t *ap=a.ptr(); \
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float64_t *bp=b.ptr(); \
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\
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float64_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 float64_t *inp1=input1.ptr(); \
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\
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float64_t *ap=a.ptr(); \
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\
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float64_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(float64_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(float64_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(float64_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(float64_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(float64_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 PREPAREDATALL1() \
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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(float64_t)*rows*columns);\
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in1.pData = ap; \
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\
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outll.numRows=rows; \
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outll.numCols=columns; \
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\
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outll.pData = outllp;
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#define SWAP_ROWS(A,i,j) \
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for(int w=0;w < n; w++) \
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{ \
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float64_t tmp; \
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tmp = A[i*n + w]; \
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A[i*n + w] = A[j*n + w];\
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A[j*n + w] = tmp; \
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}
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void UnaryTestsF64::test_mat_add_f64()
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{
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}
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void UnaryTestsF64::test_mat_sub_f64()
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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_f64(&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,(float64_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 UnaryTestsF64::test_mat_scale_f64()
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{
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}
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void UnaryTestsF64::test_mat_trans_f64()
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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_f64(&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,(float32_t)SNR_THRESHOLD);
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ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR,REL_ERROR);
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}
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/*
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Test framework is only adding 16 bytes of free memory after the end of a buffer.
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So, we limit to 2 float64 for checking out of buffer write.
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*/
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static void refInnerTail(float64_t *b)
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{
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b[0] = 1.0;
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b[1] = -2.0;
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}
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static void checkInnerTail(float64_t *b)
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{
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ASSERT_TRUE(b[0] == 1.0);
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ASSERT_TRUE(b[1] == -2.0);
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}
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void UnaryTestsF64::test_mat_inverse_f64()
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{
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const float64_t *inp1=input1.ptr();
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float64_t *ap=a.ptr();
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float64_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_f64(&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,(float64_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 UnaryTestsF64::test_mat_cholesky_dpo_f64()
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{
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float64_t *ap=a.ptr();
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const float64_t *inp1=input1.ptr();
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float64_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_f64(&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,(float64_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 UnaryTestsF64::test_solve_upper_triangular_f64()
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{
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float64_t *ap=a.ptr();
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const float64_t *inp1=input1.ptr();
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float64_t *bp=b.ptr();
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const float64_t *inp2=input2.ptr();
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float64_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_f64(&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,(float64_t)SNR_THRESHOLD);
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ASSERT_CLOSE_ERROR(ref,output,ABS_ERROR,REL_ERROR);
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}
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void UnaryTestsF64::test_solve_lower_triangular_f64()
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{
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float64_t *ap=a.ptr();
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const float64_t *inp1=input1.ptr();
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float64_t *bp=b.ptr();
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const float64_t *inp2=input2.ptr();
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float64_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_f64(&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,(float64_t)SNR_THRESHOLD);
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ASSERT_CLOSE_ERROR(ref,output,ABS_ERROR,REL_ERROR);
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}
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static void trans_f64(const float64_t *src, float64_t *dst, int n)
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{
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for(int r=0; r<n ; r++)
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{
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for(int c=0; c<n ; c++)
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{
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dst[c*n+r] = src[r*n+c];
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}
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}
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}
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static void mult_f64_f64(const float64_t *srcA, const float64_t *srcB, float64_t *dst,int n)
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{
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for(int r=0; r<n ; r++)
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{
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for(int c=0; c<n ; c++)
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{
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float64_t sum=0.0;
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for(int k=0; k < n ; k++)
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{
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sum += srcA[r*n+k] * srcB[k*n+c];
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}
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dst[r*n+c] = sum;
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}
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}
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}
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void UnaryTestsF64::compute_ldlt_error(const int n,const int16_t *outpp)
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{
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float64_t *tmpa = tmpapat.ptr() ;
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float64_t *tmpb = tmpbpat.ptr() ;
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float64_t *tmpc = tmpcpat.ptr() ;
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/* Compute P A P^t */
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// Create identiy matrix
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for(int r=0; r < n; r++)
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{
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for(int c=0; c < n; c++)
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{
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if (r == c)
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{
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tmpa[r*n+c] = 1.0;
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}
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else
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{
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tmpa[r*n+c] = 0.0;
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}
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}
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}
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// Create permutation matrix
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for(int r=0;r < n; r++)
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{
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SWAP_ROWS(tmpa,r,outpp[r]);
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}
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trans_f64((const float64_t*)tmpa,tmpb,n);
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mult_f64_f64((const float64_t*)this->in1.pData,(const float64_t*)tmpb,tmpc,n);
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mult_f64_f64((const float64_t*)tmpa,(const float64_t*)tmpc,outa,n);
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/* Compute L D L^t */
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trans_f64((const float64_t*)this->outll.pData,tmpc,n);
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mult_f64_f64((const float64_t*)this->outd.pData,(const float64_t*)tmpc,tmpa,n);
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mult_f64_f64((const float64_t*)this->outll.pData,(const float64_t*)tmpa,outb,n);
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}
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void UnaryTestsF64::test_mat_ldl_f64()
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{
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float64_t *ap=a.ptr();
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const float64_t *inp1=input1.ptr();
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float64_t *outllp=outputll.ptr();
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float64_t *outdp=outputd.ptr();
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int16_t *outpp=outputp.ptr();
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outa=outputa.ptr();
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outb=outputb.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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PREPAREDATALL1();
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outd.numRows=rows;
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outd.numCols=columns;
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outd.pData=outdp;
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memset(outpp,0,rows*sizeof(uint16_t));
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memset(outdp,0,columns*rows*sizeof(float64_t));
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status=arm_mat_ldlt_f64(&this->in1,&this->outll,&this->outd,(uint16_t*)outpp);
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ASSERT_TRUE(status==ARM_MATH_SUCCESS);
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compute_ldlt_error(rows,outpp);
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outllp += (rows * columns);
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outdp += (rows * columns);
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outpp += rows;
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outa += (rows * columns);
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outb +=(rows * columns);
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inp1 += (rows * columns);
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}
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ASSERT_EMPTY_TAIL(outputll);
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ASSERT_EMPTY_TAIL(outputd);
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ASSERT_EMPTY_TAIL(outputp);
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ASSERT_EMPTY_TAIL(outputa);
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ASSERT_EMPTY_TAIL(outputb);
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ASSERT_CLOSE_ERROR(outputa,outputb,ABS_ERROR_LDLT,REL_ERROR_LDLT);
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}
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void UnaryTestsF64::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_SUB_F64_2:
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input1.reload(UnaryTestsF64::INPUTS1_F64_ID,mgr);
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input2.reload(UnaryTestsF64::INPUTS2_F64_ID,mgr);
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dims.reload(UnaryTestsF64::DIMSUNARY1_S16_ID,mgr);
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ref.reload(UnaryTestsF64::REFSUB1_F64_ID,mgr);
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output.create(ref.nbSamples(),UnaryTestsF64::OUT_F64_ID,mgr);
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a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF64::TMPA_F64_ID,mgr);
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b.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF64::TMPB_F64_ID,mgr);
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break;
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case TEST_MAT_TRANS_F64_4:
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input1.reload(UnaryTestsF64::INPUTS1_F64_ID,mgr);
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dims.reload(UnaryTestsF64::DIMSUNARY1_S16_ID,mgr);
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ref.reload(UnaryTestsF64::REFTRANS1_F64_ID,mgr);
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output.create(ref.nbSamples(),UnaryTestsF64::OUT_F64_ID,mgr);
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a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF64::TMPA_F64_ID,mgr);
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break;
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case TEST_MAT_INVERSE_F64_5:
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input1.reload(UnaryTestsF64::INPUTSINV_F64_ID,mgr);
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dims.reload(UnaryTestsF64::DIMSINVERT1_S16_ID,mgr);
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ref.reload(UnaryTestsF64::REFINV1_F64_ID,mgr);
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output.create(ref.nbSamples(),UnaryTestsF64::OUT_F64_ID,mgr);
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a.create(ref.nbSamples(),UnaryTestsF64::TMPA_F64_ID,mgr);
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break;
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case TEST_MAT_CHOLESKY_DPO_F64_6:
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input1.reload(UnaryTestsF64::INPUTSCHOLESKY1_DPO_F64_ID,mgr);
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dims.reload(UnaryTestsF64::DIMSCHOLESKY1_DPO_S16_ID,mgr);
|
|
|
|
ref.reload(UnaryTestsF64::REFCHOLESKY1_DPO_F64_ID,mgr);
|
|
|
|
output.create(ref.nbSamples(),UnaryTestsF64::OUT_F64_ID,mgr);
|
|
a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF64::TMPA_F64_ID,mgr);
|
|
break;
|
|
|
|
case TEST_SOLVE_UPPER_TRIANGULAR_F64_7:
|
|
input1.reload(UnaryTestsF64::INPUT_MAT_UTSOLVE_F64_ID,mgr);
|
|
input2.reload(UnaryTestsF64::INPUT_VEC_LTSOLVE_F64_ID,mgr);
|
|
dims.reload(UnaryTestsF64::DIM_LTSOLVE_F64_ID,mgr);
|
|
|
|
ref.reload(UnaryTestsF64::REF_UT_SOLVE_F64_ID,mgr);
|
|
|
|
output.create(ref.nbSamples(),UnaryTestsF64::OUT_F64_ID,mgr);
|
|
a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF64::TMPA_F64_ID,mgr);
|
|
b.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF64::TMPB_F64_ID,mgr);
|
|
break;
|
|
|
|
case TEST_SOLVE_LOWER_TRIANGULAR_F64_8:
|
|
input1.reload(UnaryTestsF64::INPUT_MAT_LTSOLVE_F64_ID,mgr);
|
|
input2.reload(UnaryTestsF64::INPUT_VEC_LTSOLVE_F64_ID,mgr);
|
|
dims.reload(UnaryTestsF64::DIM_LTSOLVE_F64_ID,mgr);
|
|
|
|
ref.reload(UnaryTestsF64::REF_LT_SOLVE_F64_ID,mgr);
|
|
|
|
output.create(ref.nbSamples(),UnaryTestsF64::OUT_F64_ID,mgr);
|
|
a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF64::TMPA_F64_ID,mgr);
|
|
b.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF64::TMPB_F64_ID,mgr);
|
|
break;
|
|
|
|
case TEST_MAT_LDL_F64_9:
|
|
// Definite positive test
|
|
input1.reload(UnaryTestsF64::INPUTSCHOLESKY1_DPO_F64_ID,mgr);
|
|
dims.reload(UnaryTestsF64::DIMSCHOLESKY1_DPO_S16_ID,mgr);
|
|
|
|
outputll.create(input1.nbSamples(),UnaryTestsF64::LL_F64_ID,mgr);
|
|
outputd.create(input1.nbSamples(),UnaryTestsF64::D_F64_ID,mgr);
|
|
outputp.create(input1.nbSamples(),UnaryTestsF64::PERM_S16_ID,mgr);
|
|
|
|
outputa.create(input1.nbSamples(),UnaryTestsF64::OUTA_F64_ID,mgr);
|
|
outputb.create(input1.nbSamples(),UnaryTestsF64::OUTA_F64_ID,mgr);
|
|
|
|
a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF64::TMPA_F64_ID,mgr);
|
|
|
|
tmpapat.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF64::TMPDB_F64_ID,mgr);
|
|
tmpbpat.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF64::TMPDC_F64_ID,mgr);
|
|
tmpcpat.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF64::TMPDD_F64_ID,mgr);
|
|
|
|
break;
|
|
|
|
case TEST_MAT_LDL_F64_10:
|
|
// Semi definite positive test
|
|
input1.reload(UnaryTestsF64::INPUTSCHOLESKY1_SDPO_F64_ID,mgr);
|
|
dims.reload(UnaryTestsF64::DIMSCHOLESKY1_SDPO_S16_ID,mgr);
|
|
|
|
outputll.create(input1.nbSamples(),UnaryTestsF64::LL_F64_ID,mgr);
|
|
outputd.create(input1.nbSamples(),UnaryTestsF64::D_F64_ID,mgr);
|
|
outputp.create(input1.nbSamples(),UnaryTestsF64::PERM_S16_ID,mgr);
|
|
|
|
outputa.create(input1.nbSamples(),UnaryTestsF64::OUTA_F64_ID,mgr);
|
|
outputb.create(input1.nbSamples(),UnaryTestsF64::OUTA_F64_ID,mgr);
|
|
|
|
a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF64::TMPA_F64_ID,mgr);
|
|
|
|
tmpapat.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF64::TMPDB_F64_ID,mgr);
|
|
tmpbpat.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF64::TMPDC_F64_ID,mgr);
|
|
tmpcpat.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF64::TMPDD_F64_ID,mgr);
|
|
|
|
break;
|
|
|
|
}
|
|
|
|
|
|
|
|
}
|
|
|
|
void UnaryTestsF64::tearDown(Testing::testID_t id,Client::PatternMgr *mgr)
|
|
{
|
|
(void)id;
|
|
//output.dump(mgr);
|
|
(void)mgr;
|
|
}
|