UnaryTestsF16.cpp 13 KB

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  1. #include "UnaryTestsF16.h"
  2. #include <stdio.h>
  3. #include "Error.h"
  4. #define SNR_THRESHOLD 60
  5. /*
  6. Reference patterns are generated with
  7. a double precision computation.
  8. */
  9. #define REL_ERROR (1.1e-3)
  10. #define ABS_ERROR (1.1e-3)
  11. /*
  12. Comparisons for inverse
  13. */
  14. /* Not very accurate for big matrix.
  15. But big matrix needed for checking the vectorized code */
  16. #define SNR_THRESHOLD_INV 45
  17. #define REL_ERROR_INV (3.0e-2)
  18. #define ABS_ERROR_INV (3.0e-2)
  19. /* Upper bound of maximum matrix dimension used by Python */
  20. #define MAXMATRIXDIM 40
  21. #define LOADDATA2() \
  22. const float16_t *inp1=input1.ptr(); \
  23. const float16_t *inp2=input2.ptr(); \
  24. \
  25. float16_t *ap=a.ptr(); \
  26. float16_t *bp=b.ptr(); \
  27. \
  28. float16_t *outp=output.ptr(); \
  29. int16_t *dimsp = dims.ptr(); \
  30. int nbMatrixes = dims.nbSamples() >> 1;\
  31. int rows,columns; \
  32. int i;
  33. #define LOADDATA1() \
  34. const float16_t *inp1=input1.ptr(); \
  35. \
  36. float16_t *ap=a.ptr(); \
  37. \
  38. float16_t *outp=output.ptr(); \
  39. int16_t *dimsp = dims.ptr(); \
  40. int nbMatrixes = dims.nbSamples() >> 1;\
  41. int rows,columns; \
  42. int i;
  43. #define PREPAREDATA2() \
  44. in1.numRows=rows; \
  45. in1.numCols=columns; \
  46. memcpy((void*)ap,(const void*)inp1,sizeof(float16_t)*rows*columns);\
  47. in1.pData = ap; \
  48. \
  49. in2.numRows=rows; \
  50. in2.numCols=columns; \
  51. memcpy((void*)bp,(const void*)inp2,sizeof(float16_t)*rows*columns);\
  52. in2.pData = bp; \
  53. \
  54. out.numRows=rows; \
  55. out.numCols=columns; \
  56. out.pData = outp;
  57. #define PREPAREDATA1(TRANSPOSED) \
  58. in1.numRows=rows; \
  59. in1.numCols=columns; \
  60. memcpy((void*)ap,(const void*)inp1,sizeof(float16_t)*rows*columns);\
  61. in1.pData = ap; \
  62. \
  63. if (TRANSPOSED) \
  64. { \
  65. out.numRows=columns; \
  66. out.numCols=rows; \
  67. } \
  68. else \
  69. { \
  70. out.numRows=rows; \
  71. out.numCols=columns; \
  72. } \
  73. out.pData = outp;
  74. #define PREPAREDATA1C(TRANSPOSED) \
  75. in1.numRows=rows; \
  76. in1.numCols=columns; \
  77. memcpy((void*)ap,(const void*)inp1,2*sizeof(float16_t)*rows*columns);\
  78. in1.pData = ap; \
  79. \
  80. if (TRANSPOSED) \
  81. { \
  82. out.numRows=columns; \
  83. out.numCols=rows; \
  84. } \
  85. else \
  86. { \
  87. out.numRows=rows; \
  88. out.numCols=columns; \
  89. } \
  90. out.pData = outp;
  91. #define LOADVECDATA2() \
  92. const float16_t *inp1=input1.ptr(); \
  93. const float16_t *inp2=input2.ptr(); \
  94. \
  95. float16_t *ap=a.ptr(); \
  96. float16_t *bp=b.ptr(); \
  97. \
  98. float16_t *outp=output.ptr(); \
  99. int16_t *dimsp = dims.ptr(); \
  100. int nbMatrixes = dims.nbSamples() / 2;\
  101. int rows,internal; \
  102. int i;
  103. #define PREPAREVECDATA2() \
  104. in1.numRows=rows; \
  105. in1.numCols=internal; \
  106. memcpy((void*)ap,(const void*)inp1,2*sizeof(float16_t)*rows*internal);\
  107. in1.pData = ap; \
  108. \
  109. memcpy((void*)bp,(const void*)inp2,2*sizeof(float16_t)*internal);
  110. void UnaryTestsF16::test_mat_vec_mult_f16()
  111. {
  112. LOADVECDATA2();
  113. for(i=0;i < nbMatrixes ; i ++)
  114. {
  115. rows = *dimsp++;
  116. internal = *dimsp++;
  117. PREPAREVECDATA2();
  118. arm_mat_vec_mult_f16(&this->in1, bp, outp);
  119. outp += rows ;
  120. }
  121. ASSERT_EMPTY_TAIL(output);
  122. ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD);
  123. ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR,REL_ERROR);
  124. }
  125. void UnaryTestsF16::test_mat_add_f16()
  126. {
  127. LOADDATA2();
  128. for(i=0;i < nbMatrixes ; i ++)
  129. {
  130. rows = *dimsp++;
  131. columns = *dimsp++;
  132. PREPAREDATA2();
  133. arm_mat_add_f16(&this->in1,&this->in2,&this->out);
  134. outp += (rows * columns);
  135. }
  136. ASSERT_EMPTY_TAIL(output);
  137. ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD);
  138. ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR,REL_ERROR);
  139. }
  140. void UnaryTestsF16::test_mat_sub_f16()
  141. {
  142. LOADDATA2();
  143. for(i=0;i < nbMatrixes ; i ++)
  144. {
  145. rows = *dimsp++;
  146. columns = *dimsp++;
  147. PREPAREDATA2();
  148. arm_mat_sub_f16(&this->in1,&this->in2,&this->out);
  149. outp += (rows * columns);
  150. }
  151. ASSERT_EMPTY_TAIL(output);
  152. ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD);
  153. ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR,REL_ERROR);
  154. }
  155. void UnaryTestsF16::test_mat_scale_f16()
  156. {
  157. LOADDATA1();
  158. for(i=0;i < nbMatrixes ; i ++)
  159. {
  160. rows = *dimsp++;
  161. columns = *dimsp++;
  162. PREPAREDATA1(false);
  163. arm_mat_scale_f16(&this->in1,0.5f,&this->out);
  164. outp += (rows * columns);
  165. }
  166. ASSERT_EMPTY_TAIL(output);
  167. ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD);
  168. ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR,REL_ERROR);
  169. }
  170. void UnaryTestsF16::test_mat_trans_f16()
  171. {
  172. LOADDATA1();
  173. for(i=0;i < nbMatrixes ; i ++)
  174. {
  175. rows = *dimsp++;
  176. columns = *dimsp++;
  177. PREPAREDATA1(true);
  178. arm_mat_trans_f16(&this->in1,&this->out);
  179. outp += (rows * columns);
  180. }
  181. ASSERT_EMPTY_TAIL(output);
  182. ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD);
  183. ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR,REL_ERROR);
  184. }
  185. void UnaryTestsF16::test_mat_cmplx_trans_f16()
  186. {
  187. LOADDATA1();
  188. for(i=0;i < nbMatrixes ; i ++)
  189. {
  190. rows = *dimsp++;
  191. columns = *dimsp++;
  192. PREPAREDATA1C(true);
  193. arm_mat_cmplx_trans_f16(&this->in1,&this->out);
  194. outp += 2*(rows * columns);
  195. }
  196. ASSERT_EMPTY_TAIL(output);
  197. ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD);
  198. ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR,REL_ERROR);
  199. }
  200. void UnaryTestsF16::test_mat_inverse_f16()
  201. {
  202. const float16_t *inp1=input1.ptr();
  203. float16_t *ap=a.ptr();
  204. float16_t *outp=output.ptr();
  205. int16_t *dimsp = dims.ptr();
  206. int nbMatrixes = dims.nbSamples();
  207. int rows,columns;
  208. int i;
  209. arm_status status;
  210. for(i=0;i < nbMatrixes ; i ++)
  211. {
  212. rows = *dimsp++;
  213. columns = rows;
  214. PREPAREDATA1(false);
  215. status=arm_mat_inverse_f16(&this->in1,&this->out);
  216. ASSERT_TRUE(status==ARM_MATH_SUCCESS);
  217. outp += (rows * columns);
  218. inp1 += (rows * columns);
  219. }
  220. ASSERT_EMPTY_TAIL(output);
  221. ASSERT_SNR(output,ref,(float16_t)SNR_THRESHOLD_INV);
  222. ASSERT_CLOSE_ERROR(output,ref,ABS_ERROR_INV,REL_ERROR_INV);
  223. }
  224. void UnaryTestsF16::setUp(Testing::testID_t id,std::vector<Testing::param_t>& params,Client::PatternMgr *mgr)
  225. {
  226. (void)params;
  227. switch(id)
  228. {
  229. case TEST_MAT_ADD_F16_1:
  230. input1.reload(UnaryTestsF16::INPUTS1_F16_ID,mgr);
  231. input2.reload(UnaryTestsF16::INPUTS2_F16_ID,mgr);
  232. dims.reload(UnaryTestsF16::DIMSUNARY1_S16_ID,mgr);
  233. ref.reload(UnaryTestsF16::REFADD1_F16_ID,mgr);
  234. output.create(ref.nbSamples(),UnaryTestsF16::OUT_F16_ID,mgr);
  235. a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPA_F16_ID,mgr);
  236. b.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPB_F16_ID,mgr);
  237. break;
  238. case TEST_MAT_SUB_F16_2:
  239. input1.reload(UnaryTestsF16::INPUTS1_F16_ID,mgr);
  240. input2.reload(UnaryTestsF16::INPUTS2_F16_ID,mgr);
  241. dims.reload(UnaryTestsF16::DIMSUNARY1_S16_ID,mgr);
  242. ref.reload(UnaryTestsF16::REFSUB1_F16_ID,mgr);
  243. output.create(ref.nbSamples(),UnaryTestsF16::OUT_F16_ID,mgr);
  244. a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPA_F16_ID,mgr);
  245. b.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPB_F16_ID,mgr);
  246. break;
  247. case TEST_MAT_SCALE_F16_3:
  248. input1.reload(UnaryTestsF16::INPUTS1_F16_ID,mgr);
  249. dims.reload(UnaryTestsF16::DIMSUNARY1_S16_ID,mgr);
  250. ref.reload(UnaryTestsF16::REFSCALE1_F16_ID,mgr);
  251. output.create(ref.nbSamples(),UnaryTestsF16::OUT_F16_ID,mgr);
  252. a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPA_F16_ID,mgr);
  253. break;
  254. case TEST_MAT_TRANS_F16_4:
  255. input1.reload(UnaryTestsF16::INPUTS1_F16_ID,mgr);
  256. dims.reload(UnaryTestsF16::DIMSUNARY1_S16_ID,mgr);
  257. ref.reload(UnaryTestsF16::REFTRANS1_F16_ID,mgr);
  258. output.create(ref.nbSamples(),UnaryTestsF16::OUT_F16_ID,mgr);
  259. a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPA_F16_ID,mgr);
  260. break;
  261. case TEST_MAT_INVERSE_F16_5:
  262. input1.reload(UnaryTestsF16::INPUTSINV_F16_ID,mgr);
  263. dims.reload(UnaryTestsF16::DIMSINVERT1_S16_ID,mgr);
  264. ref.reload(UnaryTestsF16::REFINV1_F16_ID,mgr);
  265. output.create(ref.nbSamples(),UnaryTestsF16::OUT_F16_ID,mgr);
  266. a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPA_F16_ID,mgr);
  267. break;
  268. case TEST_MAT_VEC_MULT_F16_6:
  269. input1.reload(UnaryTestsF16::INPUTS1_F16_ID,mgr);
  270. input2.reload(UnaryTestsF16::INPUTVEC1_F16_ID,mgr);
  271. dims.reload(UnaryTestsF16::DIMSUNARY1_S16_ID,mgr);
  272. ref.reload(UnaryTestsF16::REFVECMUL1_F16_ID,mgr);
  273. output.create(ref.nbSamples(),UnaryTestsF16::OUT_F16_ID,mgr);
  274. a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPA_F16_ID,mgr);
  275. b.create(MAXMATRIXDIM,UnaryTestsF16::TMPB_F16_ID,mgr);
  276. break;
  277. case TEST_MAT_CMPLX_TRANS_F16_7:
  278. input1.reload(UnaryTestsF16::INPUTSC1_F16_ID,mgr);
  279. dims.reload(UnaryTestsF16::DIMSUNARY1_S16_ID,mgr);
  280. ref.reload(UnaryTestsF16::REFTRANSC1_F16_ID,mgr);
  281. output.create(ref.nbSamples(),UnaryTestsF16::OUT_F16_ID,mgr);
  282. a.create(MAXMATRIXDIM*MAXMATRIXDIM,UnaryTestsF16::TMPA_F16_ID,mgr);
  283. break;
  284. }
  285. }
  286. void UnaryTestsF16::tearDown(Testing::testID_t id,Client::PatternMgr *mgr)
  287. {
  288. (void)id;
  289. output.dump(mgr);
  290. }