oneAPI Deep Neural Network Library (oneDNN)  1.95.0
Performance library for Deep Learning
dnnl_types.h
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16 
19 
20 #ifndef DNNL_TYPES_H
21 #define DNNL_TYPES_H
22 
23 #ifdef __cplusplus
24 extern "C" {
25 #endif
26 
28 #include <stddef.h>
29 #include <stdint.h>
31 
34 
37 
39 typedef enum {
55 
57 
60 
62 typedef enum {
66  dnnl_f16 = 1,
68  dnnl_bf16 = 2,
70  dnnl_f32 = 3,
72  dnnl_s32 = 4,
74  dnnl_s8 = 5,
76  dnnl_u8 = 6,
78 
80 typedef enum {
95 
164 typedef enum {
170 
171  // Semantic agnostic section
172  // The physical order of dimensions is defined by the permutation of the
173  // characters, assuming that ab..z defines the natural order.
174 
175  // Plain formats
176 
183 
184  // Permuted plain formats
185 
206 
207  // Opaque blocked formats
208 
209  dnnl_Abc16a,
210  dnnl_ABc16a16b,
211  dnnl_ABc32a32b,
212  dnnl_ABc4a4b,
215  dnnl_ABc16b16a,
216  dnnl_Abc4a,
221  dnnl_ABc4b16a4b,
222  dnnl_ABc2b8a4b,
223  dnnl_ABc16b16a4b,
224  dnnl_ABc16b16a2b,
225  dnnl_ABc4b4a,
226  dnnl_ABc8a16b2a,
227  dnnl_ABc8a8b,
228  dnnl_ABc8a4b,
231  dnnl_ABc8b16a2b,
232  dnnl_BAc8a16b2a,
233  dnnl_ABc8b8a,
234  dnnl_Abcd16a,
235  dnnl_Abcd8a,
236  dnnl_ABcd16a16b,
237  dnnl_Abcd32a,
238  dnnl_ABcd32a32b,
241  dnnl_ABcd16b16a,
242  dnnl_aBCd16b16c,
243  dnnl_aBCd16c16b,
244  dnnl_Abcd4a,
249  dnnl_ABcd4b16a4b,
250  dnnl_ABcd16b16a4b,
251  dnnl_ABcd16b16a2b,
252  dnnl_ABcd4b4a,
253  dnnl_ABcd4a4b,
254  dnnl_aBCd2c4b2c,
255  dnnl_aBCd4b8c2b,
256  dnnl_aBCd4c16b4c,
257  dnnl_aBCd2c8b4c,
258  dnnl_aBCd16c16b4c,
259  dnnl_aBCd16c16b2c,
260  dnnl_aBCd4c4b,
261  dnnl_aBCd4b4c,
262  dnnl_ABcd8a16b2a,
263  dnnl_ABcd2b8a4b,
264  dnnl_ABcd8a8b,
265  dnnl_ABcd8a4b,
268  dnnl_aBCd4c8b2c,
269  dnnl_ABcd8b16a2b,
270  dnnl_aBCd8b16c2b,
271  dnnl_BAcd8a16b2a,
274  dnnl_aBCd8b8c,
275  dnnl_aBCd8b4c,
276  dnnl_aBCd8c16b2c,
277  dnnl_ABcde8a16b2a,
278  dnnl_aCBd8b16c2b,
279  dnnl_aBCd8c8b,
280  dnnl_Abcde16a,
281  dnnl_Abcde32a,
282  dnnl_ABcde16a16b,
283  dnnl_BAcde8a16b2a,
292  dnnl_ABcde16b16a,
293  dnnl_aBCde16b16c,
294  dnnl_aBCde16c16b,
295  dnnl_aBCde2c8b4c,
296  dnnl_Abcde4a,
301  dnnl_ABcde4b4a,
302  dnnl_ABcde4a4b,
303  dnnl_aBCde4b4c,
304  dnnl_aBCde2c4b2c,
305  dnnl_aBCde4b8c2b,
306  dnnl_aBCde4c16b4c,
307  dnnl_aBCde16c16b4c,
308  dnnl_aBCde16c16b2c,
309  dnnl_aBCde4c4b,
310  dnnl_Abcde8a,
311  dnnl_ABcde8a8b,
312  dnnl_ABcde8a4b,
313  dnnl_BAcde16b16a,
316  dnnl_ABcde8b16a2b,
317  dnnl_aBCde8b16c2b,
318  dnnl_aBCde4c8b2c,
319  dnnl_aCBde8b16c2b,
320  dnnl_ABcde8b8a,
321  dnnl_ABcde32a32b,
322  dnnl_aBCde8b8c,
323  dnnl_aBCde8b4c,
324  dnnl_ABc4a8b8a4b,
325  dnnl_ABcd4a8b8a4b,
326  dnnl_ABcde4a8b8a4b,
327  dnnl_BAc4b8a8b4a,
328  dnnl_BAcd4b8a8b4a,
329  dnnl_BAcde4b8a8b4a,
330  dnnl_ABcd2a8b8a2b,
331  dnnl_aBCd4b8c8b4c,
332  dnnl_aBCde4b8c8b4c,
333  dnnl_aBCde2b8c8b2c,
334  dnnl_aBCde8c16b2c,
335  dnnl_aBCde8c8b,
340  dnnl_aBCdef16b16c,
341  dnnl_aBCdef16c16b,
342  dnnl_aBCdef4c16b4c,
345  dnnl_aBCdef4c8b2c,
350  dnnl_aBCdef4c4b,
351  dnnl_aBCdef4b4c,
352  dnnl_aBCdef2c4b2c,
353  dnnl_aBCdef4b8c2b,
354  dnnl_aBCdef8b8c,
355  dnnl_aBCdef8b4c,
356  dnnl_aBCdef8c16b2c,
357  dnnl_aBCdef4b8c8b4c,
358  dnnl_aBCdef8b16c2b,
359  dnnl_aCBdef8b16c2b,
360  dnnl_aBCdef8c8b,
361  dnnl_aBdc16b,
362  dnnl_aBdC16b2c,
363  dnnl_aBdC16b4c,
364  dnnl_aBdc4b,
365  dnnl_aBdc8b,
366  dnnl_aBdec16b,
367  dnnl_aBdeC16b2c,
368  dnnl_aBdeC16b4c,
369  dnnl_aBdec32b,
370  dnnl_aBdec4b,
371  dnnl_aBdec8b,
372  dnnl_aBdefc16b,
373  dnnl_aBdefC16b2c,
374  dnnl_aCBdef16c16b,
375  dnnl_aBdefc4b,
376  dnnl_aBdefc8b,
377  dnnl_Abcdef16a,
378  dnnl_Abcdef32a,
379  dnnl_Acb16a,
380  dnnl_AcB16a2b,
381  dnnl_AcB16a4b,
382  dnnl_Acb4a,
383  dnnl_Acb8a,
384  dnnl_aCBd16b16c,
385  dnnl_aCBd16c16b,
386  dnnl_aCBde16b16c,
387  dnnl_aCBde16c16b,
388  dnnl_Acdb16a,
389  dnnl_AcdB16a2b,
390  dnnl_AcdB16a4b,
391  dnnl_Acdb32a,
392  dnnl_Acdb4a,
393  dnnl_Acdb8a,
394  dnnl_Acdeb16a,
395  dnnl_AcdeB16a2b,
396  dnnl_Acdeb4a,
397  dnnl_Acdeb8a,
398  dnnl_BAc16a16b,
399  dnnl_BAc16b16a,
400  dnnl_BAcd16a16b,
401  dnnl_BAcd16b16a,
402  dnnl_aCBd4c8b8c4b,
403  dnnl_aCBde4c8b8c4b,
404  dnnl_aCBdef4c8b8c4b,
405  dnnl_BAcde16a16b,
406  dnnl_aCBdef16b16c,
407 
411 
412  // Aliases
413 
438 
471 
488 
523 
524  // Opaque data types, are not to be used explicitly
525 
526  // data
563  dnnl_NCw16n16c = dnnl_ABc16a16b,
564  dnnl_NCdhw16n16c = dnnl_ABcde16a16b,
565  dnnl_NChw16n16c = dnnl_ABcd16a16b,
566  dnnl_NCw32n32c = dnnl_ABc32a32b,
567  dnnl_NChw32n32c = dnnl_ABcd32a32b,
568  dnnl_NCdhw32n32c = dnnl_ABcde32a32b,
569 
570  // weights, 3D
571  dnnl_IOw16o16i = dnnl_BAc16a16b,
572  dnnl_IOw16i16o = dnnl_BAc16b16a,
573  dnnl_OIw16i16o = dnnl_ABc16b16a,
574  dnnl_OIw16o16i = dnnl_ABc16a16b,
575  dnnl_Oiw16o = dnnl_Abc16a,
576  dnnl_OIw4i16o4i = dnnl_ABc4b16a4b,
577  dnnl_OIw2i8o4i = dnnl_ABc2b8a4b,
578  dnnl_OIw16i16o4i = dnnl_ABc16b16a4b,
579  dnnl_OIw16i16o2i = dnnl_ABc16b16a2b,
580  dnnl_OIw4i4o = dnnl_ABc4b4a,
581  dnnl_OIw4o4i = dnnl_ABc4a4b,
582  dnnl_Oiw4o = dnnl_Abc4a,
583  dnnl_OIw8i16o2i = dnnl_ABc8b16a2b,
584  dnnl_OIw8i8o = dnnl_ABc8b8a,
585  dnnl_OIw8o16i2o = dnnl_ABc8a16b2a,
586  dnnl_IOw8o16i2o = dnnl_BAc8a16b2a,
587  dnnl_OIw8o8i = dnnl_ABc8a8b,
588  dnnl_OIw8o4i = dnnl_ABc8a4b,
589  dnnl_Owi16o = dnnl_Acb16a,
590  dnnl_OwI16o2i = dnnl_AcB16a2b,
591  dnnl_OwI16o4i = dnnl_AcB16a4b,
592  dnnl_Owi4o = dnnl_Acb4a,
593  dnnl_Owi8o = dnnl_Acb8a,
594 
595  // weights, 4D
596  dnnl_IOhw16i16o = dnnl_BAcd16b16a,
597  dnnl_IOhw16o16i = dnnl_BAcd16a16b,
598  dnnl_Ohwi16o = dnnl_Acdb16a,
599  dnnl_OhwI16o2i = dnnl_AcdB16a2b,
600  dnnl_OhwI16o4i = dnnl_AcdB16a4b,
601  dnnl_Ohwi32o = dnnl_Acdb32a,
602  dnnl_Ohwi4o = dnnl_Acdb4a,
603  dnnl_Ohwi8o = dnnl_Acdb8a,
604  dnnl_OIhw16i16o = dnnl_ABcd16b16a,
605  dnnl_OIhw16o16i = dnnl_ABcd16a16b,
606  dnnl_Oihw16o = dnnl_Abcd16a,
607  dnnl_OIhw4i16o4i = dnnl_ABcd4b16a4b,
608  dnnl_OIhw16i16o4i = dnnl_ABcd16b16a4b,
609  dnnl_OIhw16i16o2i = dnnl_ABcd16b16a2b,
610  dnnl_OIhw4i4o = dnnl_ABcd4b4a,
611  dnnl_OIhw4o4i = dnnl_ABcd4a4b,
612  dnnl_Oihw4o = dnnl_Abcd4a,
613  dnnl_OIhw8i16o2i = dnnl_ABcd8b16a2b,
614  dnnl_OIhw8i8o = dnnl_ABcd8b8a,
615  dnnl_OIhw8o16i2o = dnnl_ABcd8a16b2a,
616  dnnl_OIhw2i8o4i = dnnl_ABcd2b8a4b,
617  dnnl_IOhw8o16i2o = dnnl_BAcd8a16b2a,
618  dnnl_OIhw8o8i = dnnl_ABcd8a8b,
619  dnnl_OIhw8o4i = dnnl_ABcd8a4b,
620 
621  // weights, 5D
622  dnnl_Odhwi16o = dnnl_Acdeb16a,
623  dnnl_OdhwI16o2i = dnnl_AcdeB16a2b,
624  dnnl_Odhwi4o = dnnl_Acdeb4a,
625  dnnl_Odhwi8o = dnnl_Acdeb8a,
626  dnnl_OIdhw16i16o = dnnl_ABcde16b16a,
627  dnnl_OIdhw16o16i = dnnl_ABcde16a16b,
628  dnnl_Oidhw16o = dnnl_Abcde16a,
629  dnnl_OIdhw4i4o = dnnl_ABcde4b4a,
630  dnnl_OIdhw4o4i = dnnl_ABcde4a4b,
631  dnnl_Oidhw4o = dnnl_Abcde4a,
632  dnnl_OIdhw8i16o2i = dnnl_ABcde8b16a2b,
633  dnnl_OIdhw8i8o = dnnl_ABcde8b8a,
634  dnnl_OIdhw8o16i2o = dnnl_ABcde8a16b2a,
635  dnnl_IOdhw8o16i2o = dnnl_BAcde8a16b2a,
636  dnnl_OIdhw4i16o4i = dnnl_ABcde4b16a4b,
637  dnnl_OIdhw2i8o4i = dnnl_ABcde2b8a4b,
638  dnnl_OIdhw8o8i = dnnl_ABcde8a8b,
639  dnnl_OIdhw8o4i = dnnl_ABcde8a4b,
640  dnnl_IOdhw16i16o = dnnl_BAcde16b16a,
641  dnnl_OIdhw4o8i8o4i = dnnl_ABcde4a8b8a4b,
642  dnnl_IOdhw16o16i = dnnl_BAcde16a16b,
643 
644  // weights w/ groups, 3D
645  dnnl_Goiw16g = dnnl_Abcd16a,
646  dnnl_Goiw8g = dnnl_Abcd8a,
647  dnnl_gIOw16o16i = dnnl_aCBd16b16c,
648  dnnl_gIOw16i16o = dnnl_aCBd16c16b,
649  dnnl_gOIw16i16o = dnnl_aBCd16c16b,
650  dnnl_gOIw16o16i = dnnl_aBCd16b16c,
651  dnnl_gOiw16o = dnnl_aBcd16b,
652  dnnl_gOIw4i16o4i = dnnl_aBCd4c16b4c,
653  dnnl_gOIw2i8o4i = dnnl_aBCd2c8b4c,
654  dnnl_gOIw16i16o4i = dnnl_aBCd16c16b4c,
655  dnnl_gOIw16i16o2i = dnnl_aBCd16c16b2c,
656  dnnl_gOIw4i4o = dnnl_aBCd4c4b,
657  dnnl_gOIw4o4i = dnnl_aBCd4b4c,
658  dnnl_gOiw4o = dnnl_aBcd4b,
659  dnnl_gOIw8i16o2i = dnnl_aBCd8c16b2c,
660  dnnl_gOIw8i8o = dnnl_aBCd8c8b,
661  dnnl_gOIw8o16i2o = dnnl_aBCd8b16c2b,
662  dnnl_gIOw8o16i2o = dnnl_aCBd8b16c2b,
663  dnnl_gOIw8o8i = dnnl_aBCd8b8c,
664  dnnl_gOIw8o4i = dnnl_aBCd8b4c,
665  dnnl_gOwi16o = dnnl_aBdc16b,
666  dnnl_gOwI16o2i = dnnl_aBdC16b2c,
667  dnnl_gOwI16o4i = dnnl_aBdC16b4c,
668  dnnl_gOwi4o = dnnl_aBdc4b,
669  dnnl_gOwi8o = dnnl_aBdc8b,
670  dnnl_Goiw32g = dnnl_Abcd32a,
671  dnnl_gOIw2i4o2i = dnnl_aBCd2c4b2c,
672  dnnl_gOIw2o4i2o = dnnl_aBCd2b4c2b,
673  dnnl_gOIw4i8o2i = dnnl_aBCd4c8b2c,
674  dnnl_gOIw4o8i2o = dnnl_aBCd4b8c2b,
675 
676  // weights w/ groups, 4D
677  dnnl_gIOhw16i16o = dnnl_aCBde16c16b,
678  dnnl_gIOhw16o16i = dnnl_aCBde16b16c,
679  dnnl_gOhwi16o = dnnl_aBdec16b,
680  dnnl_gOhwI16o2i = dnnl_aBdeC16b2c,
681  dnnl_gOhwI16o4i = dnnl_aBdeC16b4c,
682  dnnl_gOhwi32o = dnnl_aBdec32b,
683  dnnl_gOhwi4o = dnnl_aBdec4b,
684  dnnl_gOhwi8o = dnnl_aBdec8b,
685  dnnl_Goihw16g = dnnl_Abcde16a,
686  dnnl_gOIhw16i16o = dnnl_aBCde16c16b,
687  dnnl_gOIhw16o16i = dnnl_aBCde16b16c,
688  dnnl_gOihw16o = dnnl_aBcde16b,
689  dnnl_gOIhw2i8o4i = dnnl_aBCde2c8b4c,
690  dnnl_gOIhw4i16o4i = dnnl_aBCde4c16b4c,
691  dnnl_gOIhw16i16o4i = dnnl_aBCde16c16b4c,
692  dnnl_gOIhw16i16o2i = dnnl_aBCde16c16b2c,
693  dnnl_gOIhw4i4o = dnnl_aBCde4c4b,
694  dnnl_gOIhw4o4i = dnnl_aBCde4b4c,
695  dnnl_gOihw4o = dnnl_aBcde4b,
696  dnnl_Goihw8g = dnnl_Abcde8a,
697  dnnl_gOIhw8i16o2i = dnnl_aBCde8c16b2c,
698  dnnl_gOIhw8i8o = dnnl_aBCde8c8b,
699  dnnl_gOIhw8o16i2o = dnnl_aBCde8b16c2b,
700  dnnl_gIOhw8o16i2o = dnnl_aCBde8b16c2b,
701  dnnl_gOIhw8o8i = dnnl_aBCde8b8c,
702  dnnl_gOIhw8o4i = dnnl_aBCde8b4c,
703  dnnl_Goihw32g = dnnl_Abcde32a,
704 
705  dnnl_OIw4o8i8o4i = dnnl_ABc4a8b8a4b,
706  dnnl_OIhw4o8i8o4i = dnnl_ABcd4a8b8a4b,
707  dnnl_IOw4i8o8i4o = dnnl_BAc4b8a8b4a,
708  dnnl_IOhw4i8o8i4o = dnnl_BAcd4b8a8b4a,
709  dnnl_IOdhw4i8o8i4o = dnnl_BAcde4b8a8b4a,
710 
711  dnnl_OIhw2o8i8o2i = dnnl_ABcd2a8b8a2b,
712  dnnl_gOIw4o8i8o4i = dnnl_aBCd4b8c8b4c,
713  dnnl_gOIhw4o8i8o4i = dnnl_aBCde4b8c8b4c,
714  dnnl_gOIdhw4o8i8o4i = dnnl_aBCdef4b8c8b4c,
715  dnnl_gIOw4i8o8i4o = dnnl_aCBd4c8b8c4b,
716  dnnl_gIOhw4i8o8i4o = dnnl_aCBde4c8b8c4b,
717  dnnl_gIOdhw4i8o8i4o = dnnl_aCBdef4c8b8c4b,
718  dnnl_gOIhw2o8i8o2i = dnnl_aBCde2b8c8b2c,
719  dnnl_gOIhw2i4o2i = dnnl_aBCde2c4b2c,
720  dnnl_gOIhw2o4i2o = dnnl_aBCde2b4c2b,
721  dnnl_gOIhw4i8o2i = dnnl_aBCde4c8b2c,
722  dnnl_gOIhw4o8i2o = dnnl_aBCde4b8c2b,
723 
724  // weights w/ groups, 6D
725  dnnl_gIOdhw16i16o = dnnl_aCBdef16c16b,
726  dnnl_gIOdhw16o16i = dnnl_aCBdef16b16c,
727  dnnl_gOdhwi16o = dnnl_aBdefc16b,
728  dnnl_gOdhwI16o2i = dnnl_aBdefC16b2c,
729  dnnl_gOdhwi4o = dnnl_aBdefc4b,
730  dnnl_gOdhwi8o = dnnl_aBdefc8b,
731  dnnl_gOIdhw16i16o = dnnl_aBCdef16c16b,
732  dnnl_gOIdhw4i16o4i = dnnl_aBCdef4c16b4c,
733  dnnl_gOIdhw2i8o4i = dnnl_aBCdef2c8b4c,
734  dnnl_gOIdhw16o16i = dnnl_aBCdef16b16c,
735  dnnl_gOidhw16o = dnnl_aBcdef16b,
736  dnnl_gOIdhw4i4o = dnnl_aBCdef4c4b,
737  dnnl_gOIdhw4o4i = dnnl_aBCdef4b4c,
738  dnnl_gOidhw4o = dnnl_aBcdef4b,
739  dnnl_gOIdhw8i16o2i = dnnl_aBCdef8c16b2c,
740  dnnl_gOIdhw8i8o = dnnl_aBCdef8c8b,
741  dnnl_gOIdhw8o16i2o = dnnl_aBCdef8b16c2b,
742  dnnl_gIOdhw8o16i2o = dnnl_aCBdef8b16c2b,
743  dnnl_gOIdhw8o8i = dnnl_aBCdef8b8c,
744  dnnl_gOIdhw8o4i = dnnl_aBCdef8b4c,
745  dnnl_Goidhw16g = dnnl_Abcdef16a,
746  dnnl_Goidhw32g = dnnl_Abcdef32a,
747  dnnl_gOIdhw2i4o2i = dnnl_aBCdef2c4b2c,
748  dnnl_gOIdhw4i8o2i = dnnl_aBCdef4c8b2c,
749  dnnl_gOIdhw2o4i2o = dnnl_aBCdef2b4c2b,
750  dnnl_gOIdhw4o8i2o = dnnl_aBCdef4b8c2b,
752 
754 
759 
761 typedef enum {
762  // TODO: suggest renames
785 
788 typedef enum {
829 
834 
836 typedef enum {
837  dnnl_alg_kind_undef,
926  dnnl_lbr_gru = 0x4fff,
928  dnnl_binary_add = 0x1fff0,
930  dnnl_binary_mul = 0x1fff1,
932  dnnl_binary_max = 0x1fff2,
934  dnnl_binary_min = 0x1fff3,
940 
942 typedef enum {
952 
965 
978 
992 
995 
998 
1002 #define DNNL_MAX_NDIMS 12
1006 #define DNNL_RUNTIME_DIM_VAL INT64_MIN
1011 #define DNNL_RUNTIME_SIZE_VAL ((size_t)DNNL_RUNTIME_DIM_VAL)
1015 static const union {
1016  unsigned u;
1017  float f;
1018 } DNNL_RUNTIME_F32_VAL_REP = {0x7fc000d0};
1020 
1023 #define DNNL_RUNTIME_F32_VAL (DNNL_RUNTIME_F32_VAL_REP.f)
1026 static const int DNNL_RUNTIME_S32_VAL_REP = INT32_MIN;
1028 
1031 #define DNNL_RUNTIME_S32_VAL DNNL_RUNTIME_S32_VAL_REP
1034 typedef int64_t dnnl_dim_t;
1035 
1038 
1042 typedef struct {
1046  // Innermost section
1047  // ASSUMPTION: the innermost blocks are always dense
1056 
1058 typedef enum {
1061  // Tensors of weights for 2x3 winograd convolutions.
1065  // Tensor of weights for 4x3 convolution.
1068 
1070 typedef struct {
1071  dnnl_wino_memory_format_t wino_format;
1072  int r;
1073  int alpha;
1074  int ic;
1075  int oc;
1076  int ic_block;
1077  int oc_block;
1078  int ic2_block;
1079  int oc2_block;
1080  float adj_scale;
1081  size_t size;
1083 
1084 typedef enum {
1085  dnnl_packed_format_undef = 0,
1086  dnnl_ldigo_p,
1087  dnnl_ldgoi_p
1088 } dnnl_rnn_packed_memory_format_t;
1089 
1092 #define DNNL_RNN_MAX_N_PARTS 4
1095 typedef struct {
1096  dnnl_rnn_packed_memory_format_t format;
1097  int n_parts;
1098  int n;
1099  int ldb;
1100  int parts[DNNL_RNN_MAX_N_PARTS];
1101  size_t part_pack_size[DNNL_RNN_MAX_N_PARTS];
1102  unsigned pack_part[DNNL_RNN_MAX_N_PARTS];
1103  size_t offset_compensation;
1104  size_t size;
1105  char reserved[200];
1107 
1109 typedef enum {
1110  dnnl_memory_extra_flag_none = 0x0U,
1119  dnnl_memory_extra_flag_scale_adjust = 0x2U,
1120  dnnl_memory_extra_flag_gpu_rnn_u8s8_compensation = 0x4U,
1122 
1124 typedef struct {
1127  uint64_t flags;
1133  char reserved[64];
1135 
1140 typedef struct {
1142  int ndims;
1158 
1161 
1164 
1168 
1172 
1175  union {
1183  // ... other descriptions possible
1184  } format_desc;
1185 
1188 
1191 struct dnnl_memory;
1192 
1194 typedef struct dnnl_memory *dnnl_memory_t;
1195 
1197 typedef const struct dnnl_memory *const_dnnl_memory_t;
1198 
1199 #define DNNL_MEMORY_NONE (NULL)
1200 #define DNNL_MEMORY_ALLOCATE ((void *)(size_t)-1)
1201 
1203 
1208 
1210 typedef void *dnnl_op_desc_t;
1212 typedef const void *const_dnnl_op_desc_t;
1213 
1216 
1219 
1222 
1224 typedef struct {
1258  dnnl_dims_t padding[2];
1262 
1264 
1267 
1270 
1272 
1275 
1277 typedef struct {
1288  int axis;
1292 
1294 
1297 
1299 typedef struct {
1343  float alpha, beta;
1345 
1347 
1350 
1352 typedef struct {
1366 
1368 
1371 
1375 
1377 
1380 
1382 typedef struct {
1409  dnnl_dims_t padding[2];
1413 
1415 
1418 
1420 typedef struct {
1438  float lrn_alpha;
1440  float lrn_beta;
1442  float lrn_k;
1443 } dnnl_lrn_desc_t;
1444 
1446 
1449 
1451 typedef struct {
1468  dnnl_memory_desc_t diff_data_scaleshift_desc;
1475  unsigned flags;
1477 
1479 
1482 
1484 typedef struct {
1503  dnnl_memory_desc_t diff_data_scaleshift_desc;
1512  unsigned flags;
1514 
1516 
1519 
1521 typedef struct {
1548 
1550 
1553 
1555 typedef enum {
1557  dnnl_rnn_flags_undef = 0x0
1559 
1561 typedef enum {
1575 
1577 typedef struct {
1615 
1642 
1644  unsigned int flags;
1648  float alpha;
1649  float beta;
1650 
1651 } dnnl_rnn_desc_t;
1652 
1654 
1657 
1659 typedef struct {
1668  dnnl_memory_desc_t src_desc[2];
1672 
1674 
1677 
1685 typedef struct {
1700 
1702 
1705 
1707 typedef struct {
1726  float factors[DNNL_MAX_NDIMS];
1728 
1730 
1732 
1735 
1737 typedef enum {
1745 
1748 struct dnnl_engine;
1750 typedef struct dnnl_engine *dnnl_engine_t;
1751 #if 0
1752 // FIXME: looks like this never happens
1754 typedef const struct dnnl_engine *const_dnnl_engine_t;
1755 #endif
1756 
1758 
1763 
1767 
1770 
1772 typedef const struct dnnl_primitive_desc_iterator
1774 
1777 struct dnnl_primitive_desc;
1778 
1781 
1784 
1786 
1789 
1791 typedef enum {
1815 
1821 struct dnnl_primitive_attr;
1822 
1826 
1829 
1848 struct dnnl_post_ops;
1849 
1852 
1854 typedef const struct dnnl_post_ops *const_dnnl_post_ops_t;
1855 
1857 
1860 
1863 struct dnnl_primitive;
1868 
1870 #define DNNL_ARG_SRC_0 1
1871 #define DNNL_ARG_SRC DNNL_ARG_SRC_0
1874 #define DNNL_ARG_SRC_LAYER DNNL_ARG_SRC_0
1877 #define DNNL_ARG_FROM DNNL_ARG_SRC_0
1882 #define DNNL_ARG_SRC_1 2
1883 #define DNNL_ARG_SRC_ITER DNNL_ARG_SRC_1
1888 #define DNNL_ARG_SRC_2 3
1889 #define DNNL_ARG_SRC_ITER_C DNNL_ARG_SRC_2
1894 #define DNNL_ARG_DST_0 17
1895 #define DNNL_ARG_DST DNNL_ARG_DST_0
1898 #define DNNL_ARG_TO DNNL_ARG_DST_0
1901 #define DNNL_ARG_DST_LAYER DNNL_ARG_DST_0
1905 #define DNNL_ARG_DST_1 18
1906 #define DNNL_ARG_DST_ITER DNNL_ARG_DST_1
1911 #define DNNL_ARG_DST_2 19
1912 #define DNNL_ARG_DST_ITER_C DNNL_ARG_DST_2
1917 #define DNNL_ARG_WEIGHTS_0 33
1918 #define DNNL_ARG_WEIGHTS DNNL_ARG_WEIGHTS_0
1921 #define DNNL_ARG_SCALE_SHIFT DNNL_ARG_WEIGHTS_0
1924 #define DNNL_ARG_WEIGHTS_LAYER DNNL_ARG_WEIGHTS_0
1929 #define DNNL_ARG_WEIGHTS_1 34
1930 #define DNNL_ARG_WEIGHTS_ITER DNNL_ARG_WEIGHTS_1
1935 #define DNNL_ARG_WEIGHTS_2 35
1936 #define DNNL_ARG_WEIGHTS_PEEPHOLE DNNL_ARG_WEIGHTS_2
1941 #define DNNL_ARG_WEIGHTS_3 36
1942 #define DNNL_ARG_WEIGHTS_PROJECTION DNNL_ARG_WEIGHTS_3
1947 #define DNNL_ARG_BIAS 41
1950 #define DNNL_ARG_MEAN 49
1951 #define DNNL_ARG_VARIANCE 50
1956 #define DNNL_ARG_WORKSPACE 64
1957 #define DNNL_ARG_SCRATCHPAD 80
1961 #define DNNL_ARG_DIFF_SRC_0 129
1962 #define DNNL_ARG_DIFF_SRC DNNL_ARG_DIFF_SRC_0
1965 #define DNNL_ARG_DIFF_SRC_LAYER DNNL_ARG_DIFF_SRC_0
1970 #define DNNL_ARG_DIFF_SRC_1 130
1971 #define DNNL_ARG_DIFF_SRC_ITER DNNL_ARG_DIFF_SRC_1
1976 #define DNNL_ARG_DIFF_SRC_2 131
1977 #define DNNL_ARG_DIFF_SRC_ITER_C DNNL_ARG_DIFF_SRC_2
1982 #define DNNL_ARG_DIFF_DST_0 145
1983 #define DNNL_ARG_DIFF_DST DNNL_ARG_DIFF_DST_0
1986 #define DNNL_ARG_DIFF_DST_LAYER DNNL_ARG_DIFF_DST_0
1991 #define DNNL_ARG_DIFF_DST_1 146
1992 #define DNNL_ARG_DIFF_DST_ITER DNNL_ARG_DIFF_DST_1
1997 #define DNNL_ARG_DIFF_DST_2 147
1998 #define DNNL_ARG_DIFF_DST_ITER_C DNNL_ARG_DIFF_DST_2
2003 #define DNNL_ARG_DIFF_WEIGHTS_0 161
2004 #define DNNL_ARG_DIFF_WEIGHTS DNNL_ARG_DIFF_WEIGHTS_0
2007 #define DNNL_ARG_DIFF_SCALE_SHIFT DNNL_ARG_DIFF_WEIGHTS_0
2010 #define DNNL_ARG_DIFF_WEIGHTS_LAYER DNNL_ARG_DIFF_WEIGHTS_0
2015 #define DNNL_ARG_DIFF_WEIGHTS_1 162
2016 #define DNNL_ARG_DIFF_WEIGHTS_ITER DNNL_ARG_DIFF_WEIGHTS_1
2021 #define DNNL_ARG_DIFF_WEIGHTS_2 163
2022 #define DNNL_ARG_DIFF_WEIGHTS_PEEPHOLE DNNL_ARG_DIFF_WEIGHTS_2
2027 #define DNNL_ARG_DIFF_WEIGHTS_3 164
2028 #define DNNL_ARG_DIFF_WEIGHTS_PROJECTION DNNL_ARG_DIFF_WEIGHTS_3
2033 #define DNNL_ARG_DIFF_BIAS 169
2036 #define DNNL_ARG_ATTR_OUTPUT_SCALES 513
2040 #define DNNL_ARG_MULTIPLE_SRC 1024
2041 #define DNNL_ARG_MULTIPLE_DST 2048
2046 #define DNNL_ARG_ATTR_ZERO_POINTS 4096
2050 #define DNNL_ARG_ATTR_POST_OP_DW 8192
2054 typedef struct {
2055  int arg;
2057 } dnnl_exec_arg_t;
2058 
2060 
2063 
2093 typedef enum {
2095 
2098 
2101 
2104 
2109 
2112 
2115 
2117 
2118  // memory and op descriptor section
2137 
2138  // memory descriptor section
2149 
2150  // Max value to prevent UB for internal use only dnnl_query_t
2151  dnnl_query_max = 0x7fff,
2152 } dnnl_query_t;
2153 
2155 
2157 
2160 
2162 typedef enum {
2173 
2176 struct dnnl_stream;
2178 typedef struct dnnl_stream *dnnl_stream_t;
2180 typedef const struct dnnl_stream *const_dnnl_stream_t;
2181 
2183 struct dnnl_stream_attr;
2185 typedef struct dnnl_stream_attr *dnnl_stream_attr_t;
2187 typedef const struct dnnl_stream_attr *const_dnnl_stream_attr_t;
2188 
2190 
2193 
2195 #define DNNL_RUNTIME_NONE 0u
2198 #define DNNL_RUNTIME_SEQ 1u
2201 #define DNNL_RUNTIME_OMP 2u
2204 #define DNNL_RUNTIME_TBB 4u
2207 #define DNNL_RUNTIME_THREADPOOL 8u
2210 #define DNNL_RUNTIME_OCL 256u
2213 #define DNNL_RUNTIME_SYCL 512u
2216 #define DNNL_RUNTIME_DPCPP DNNL_RUNTIME_SYCL
2220 typedef struct {
2221  int major;
2222  int minor;
2223  int patch;
2224  const char *hash;
2225  unsigned cpu_runtime;
2226  unsigned gpu_runtime;
2227 } dnnl_version_t;
2228 
2230 #define DNNL_JIT_PROFILE_NONE 0u
2233 #define DNNL_JIT_PROFILE_VTUNE 1u
2236 #define DNNL_JIT_PROFILE_LINUX_PERFMAP 2u
2239 #define DNNL_JIT_PROFILE_LINUX_JITDUMP 4u
2243 #define DNNL_JIT_PROFILE_LINUX_JITDUMP_USE_TSC 8u
2246 #define DNNL_JIT_PROFILE_LINUX_PERF \
2247  (DNNL_JIT_PROFILE_LINUX_JITDUMP | DNNL_JIT_PROFILE_LINUX_PERFMAP)
2248 
2250 typedef enum {
2253 
2256 
2259 
2262 
2266 
2270 
2274 
2279 
2284 
2289 } dnnl_cpu_isa_t;
2290 
2292 
2294 
2295 #ifdef __cplusplus
2296 }
2297 #endif
2298 
2299 #endif
dnnl_lrn_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1426
dnnl_query_time_estimate_f64
@ dnnl_query_time_estimate_f64
runtime estimation (seconds)
Definition: dnnl_types.h:2102
dnnl_query_reorder_dst_engine
@ dnnl_query_reorder_dst_engine
destination engine
Definition: dnnl_types.h:2114
dnnl_pooling_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1385
dnnl_rnn_desc_t::bias_desc
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1600
dnnl_aBcdef4b
@ dnnl_aBcdef4b
6D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:349
dnnl_dhwigo
@ dnnl_dhwigo
6D CNN weights tensor (incl. groups), an alias to dnnl_defcab
Definition: dnnl_types.h:487
dnnl_convolution_desc_t::src_desc
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1236
dnnl_scratchpad_mode_library
@ dnnl_scratchpad_mode_library
The library manages the scratchpad allocation according to the policy specified by the DNNL_ENABLE_CO...
Definition: dnnl_types.h:1808
dnnl_goidhw
@ dnnl_goidhw
6D CNN weights tensor (incl. groups), an alias to dnnl_abcdef
Definition: dnnl_types.h:483
dnnl_wino_wei_aaOIoi
@ dnnl_wino_wei_aaOIoi
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:1062
dnnl_stream_attr_t
struct dnnl_stream_attr * dnnl_stream_attr_t
An execution stream attributes handle.
Definition: dnnl_types.h:2185
dnnl_io
@ dnnl_io
2D CNN weights tensor, an alias to dnnl_ba
Definition: dnnl_types.h:442
dnnl_convolution_desc_t::strides
dnnl_dims_t strides
Convolution strides in each spatial dimension.
Definition: dnnl_types.h:1252
dnnl_nc
@ dnnl_nc
2D CNN activations tensor, an alias to dnnl_ab
Definition: dnnl_types.h:417
dnnl_eltwise_desc_t::data_desc
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1320
dnnl_resampling_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1710
dnnl_s32
@ dnnl_s32
32-bit signed integer.
Definition: dnnl_types.h:72
dnnl_x
@ dnnl_x
1D tensor, an alias to dnnl_a
Definition: dnnl_types.h:415
dnnl_eltwise_round
@ dnnl_eltwise_round
Eltwise: round.
Definition: dnnl_types.h:888
dnnl_batch_normalization_desc_t::data_desc
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1459
dnnl_rnn_packed_desc_t
Description of tensor of packed weights for rnn.
Definition: dnnl_types.h:1095
dnnl_eltwise_relu_use_dst_for_bwd
@ dnnl_eltwise_relu_use_dst_for_bwd
Eltwise: ReLU (dst for backward)
Definition: dnnl_types.h:890
dnnl_layer_normalization_desc_t::layer_norm_epsilon
float layer_norm_epsilon
Layer normalization epsilon parameter.
Definition: dnnl_types.h:1511
dnnl_inner_product_desc_t::diff_weights_desc
dnnl_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: dnnl_types.h:1536
dnnl_query_pooling_d
@ dnnl_query_pooling_d
pooling descriptor
Definition: dnnl_types.h:2126
dnnl_ABcde2b8a4b
@ dnnl_ABcde2b8a4b
5D tensor blocked by 1st dimension with block size 8
Definition: dnnl_types.h:289
dnnl_wino_wei_aaOio
@ dnnl_wino_wei_aaOio
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:1063
dnnl_convolution_desc_t::alg_kind
dnnl_alg_kind_t alg_kind
The kind of the convolution algorithm.
Definition: dnnl_types.h:1234
dnnl_pooling_desc_t::alg_kind
dnnl_alg_kind_t alg_kind
The kind of pooling algorithm.
Definition: dnnl_types.h:1393
dnnl_aBCde2b4c2b
@ dnnl_aBCde2b4c2b
5D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:337
dnnl_query_memory_consumption_s64
@ dnnl_query_memory_consumption_s64
memory consumption – extra
Definition: dnnl_types.h:2103
dnnl_s8
@ dnnl_s8
8-bit signed integer.
Definition: dnnl_types.h:74
dnnl_format_tag_t
dnnl_format_tag_t
Memory format tag specification.
Definition: dnnl_types.h:164
dnnl_f16
@ dnnl_f16
16-bit/half-precision floating point.
Definition: dnnl_types.h:66
dnnl_inner_product
@ dnnl_inner_product
An inner product primitive.
Definition: dnnl_types.h:816
dnnl_unimplemented
@ dnnl_unimplemented
The operation failed because requested functionality is not implemented.
Definition: dnnl_types.h:47
dnnl_memory
dnnl_decab
@ dnnl_decab
permuted 5D tensor
Definition: dnnl_types.h:204
dnnl_primitive_desc_iterator
An opaque structure to describe a primitive descriptor iterator.
dnnl_batch_normalization
@ dnnl_batch_normalization
A batch normalization primitive.
Definition: dnnl_types.h:812
dnnl_query_logsoftmax_d
@ dnnl_query_logsoftmax_d
logsoftmax descriptor
Definition: dnnl_types.h:2134
dnnl_stream_t
struct dnnl_stream * dnnl_stream_t
An execution stream handle.
Definition: dnnl_types.h:2178
dnnl_pooling_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1388
dnnl_status_t
dnnl_status_t
Status values returned by the library functions.
Definition: dnnl_types.h:39
dnnl_query_reorder_src_engine
@ dnnl_query_reorder_src_engine
source engine
Definition: dnnl_types.h:2113
dnnl_wino_undef
@ dnnl_wino_undef
Undefined memory format, used for empty memory descriptors.
Definition: dnnl_types.h:1060
dnnl_rnn_desc_t::direction
dnnl_rnn_direction_t direction
The direction of RNN primitive execution.
Definition: dnnl_types.h:1588
dnnl_memory_extra_flag_compensation_conv_s8s8
@ dnnl_memory_extra_flag_compensation_conv_s8s8
Indicates the weights have an additional buffer, that depends on the compensation_mask.
Definition: dnnl_types.h:1118
dnnl_softmax
@ dnnl_softmax
A softmax primitive.
Definition: dnnl_types.h:806
dnnl_normalization_flags_none
@ dnnl_normalization_flags_none
Use no normalization flags.
Definition: dnnl_types.h:951
dnnl_query_rnn_d
@ dnnl_query_rnn_d
rnn descriptor
Definition: dnnl_types.h:2131
dnnl_inner_product_desc_t::dst_desc
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1542
dnnl_rnn_desc_t::flags
unsigned int flags
RNN cell flags.
Definition: dnnl_types.h:1644
dnnl_cn
@ dnnl_cn
2D CNN activations tensor, an alias to dnnl_ba
Definition: dnnl_types.h:419
DNNL_MAX_NDIMS
#define DNNL_MAX_NDIMS
Maximum number of dimensions a tensor can have.
Definition: dnnl_types.h:1002
dnnl_ldnc
@ dnnl_ldnc
4D RNN states tensor in the format (num_layers, num_directions, batch, state channels).
Definition: dnnl_types.h:495
dnnl_scratchpad_mode_user
@ dnnl_scratchpad_mode_user
The user manages the scratchpad allocation by querying and providing the scratchpad memory to primiti...
Definition: dnnl_types.h:1813
dnnl_batch_normalization_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1457
dnnl_defcab
@ dnnl_defcab
permuted 6D tensor
Definition: dnnl_types.h:205
dnnl_aBcde16b
@ dnnl_aBcde16b
5D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:291
dnnl_engine
An opaque structure to describe an engine.
dnnl_rnn_desc_t::src_iter_c_desc
dnnl_memory_desc_t src_iter_c_desc
Source iteration memory descriptor for cell state.
Definition: dnnl_types.h:1594
dnnl_batch_normalization_desc_t::stat_desc
dnnl_memory_desc_t stat_desc
Statistics memory descriptor.
Definition: dnnl_types.h:1472
dnnl_eltwise_relu
@ dnnl_eltwise_relu
Eltwise: ReLU.
Definition: dnnl_types.h:849
dnnl_acb
@ dnnl_acb
permuted 3D tensor
Definition: dnnl_types.h:188
dnnl_matmul_desc_t
A descriptor of a matrix multiplication operation.
Definition: dnnl_types.h:1685
dnnl_rnn_desc_t::diff_weights_projection_desc
dnnl_memory_desc_t diff_weights_projection_desc
Weights gradient projection memory descriptor.
Definition: dnnl_types.h:1641
dnnl_eltwise_abs
@ dnnl_eltwise_abs
Eltwise: abs.
Definition: dnnl_types.h:857
dnnl_shuffle_desc_t::group_size
dnnl_dim_t group_size
Number of groups.
Definition: dnnl_types.h:1290
dnnl_memory_extra_desc_t::scale_adjust
float scale_adjust
Scale applied to the data.
Definition: dnnl_types.h:1131
dnnl_oihw
@ dnnl_oihw
4D CNN weights tensor, an alias to dnnl_abcd
Definition: dnnl_types.h:452
dnnl_normalization_flags_t
dnnl_normalization_flags_t
Flags for normalization primitives.
Definition: dnnl_types.h:942
dnnl_eltwise_sqrt_use_dst_for_bwd
@ dnnl_eltwise_sqrt_use_dst_for_bwd
Eltwise: square root (dst for backward)
Definition: dnnl_types.h:896
dnnl_shuffle
@ dnnl_shuffle
A shuffle primitive.
Definition: dnnl_types.h:794
dnnl_query_shuffle_d
@ dnnl_query_shuffle_d
shuffle descriptor
Definition: dnnl_types.h:2123
dnnl_convolution_desc_t
A descriptor of a convolution operation.
Definition: dnnl_types.h:1224
dnnl_primitive_kind_t
dnnl_primitive_kind_t
Kinds of primitives.
Definition: dnnl_types.h:788
dnnl_rnn_flags_t
dnnl_rnn_flags_t
Flags for RNN cell.
Definition: dnnl_types.h:1555
dnnl_ldigo
@ dnnl_ldigo
5D RNN weights tensor in the format (num_layers, num_directions, input_channels, num_gates,...
Definition: dnnl_types.h:502
dnnl_pooling_max
@ dnnl_pooling_max
Max pooling.
Definition: dnnl_types.h:902
dnnl_exec_arg_t
A structure that contains an index and a memory object, and is used to pass arguments to dnnl_primiti...
Definition: dnnl_types.h:2054
dnnl_stream_flags_t
dnnl_stream_flags_t
Stream flags.
Definition: dnnl_types.h:2162
dnnl_query_t
dnnl_query_t
Primitive descriptor query specification.
Definition: dnnl_types.h:2093
dnnl_softmax_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1355
dnnl_lrn_desc_t::lrn_alpha
float lrn_alpha
LRN alpha parameter.
Definition: dnnl_types.h:1438
dnnl_bf16
@ dnnl_bf16
non-standard 16-bit (bfloat16 w/ 7 bit mantissa) floating point.
Definition: dnnl_types.h:68
dnnl_nhwc
@ dnnl_nhwc
4D CNN activations tensor, an alias to dnnl_acdb
Definition: dnnl_types.h:431
dnnl_rnn_desc_t
A descriptor for an RNN operation.
Definition: dnnl_types.h:1577
dnnl_rnn_direction_t
dnnl_rnn_direction_t
A direction of RNN primitive execution.
Definition: dnnl_types.h:1561
dnnl_bcdea
@ dnnl_bcdea
permuted 5D tensor
Definition: dnnl_types.h:199
dnnl_convolution_desc_t::diff_src_desc
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1238
dnnl_convolution_desc_t::weights_desc
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1240
dnnl_convolution_desc_t::dst_desc
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1248
dnnl_sum
@ dnnl_sum
A sum primitive.
Definition: dnnl_types.h:798
dnnl_oidhw
@ dnnl_oidhw
5D CNN weights tensor, an alias to dnnl_abcde
Definition: dnnl_types.h:462
dnnl_memory_desc_t::blocking
dnnl_blocking_desc_t blocking
Description of the data layout for memory formats that use blocking.
Definition: dnnl_types.h:1178
dnnl_backward_weights
@ dnnl_backward_weights
Backward weights propagation.
Definition: dnnl_types.h:781
dnnl_a
@ dnnl_a
plain 1D tensor
Definition: dnnl_types.h:177
const_dnnl_stream_t
const struct dnnl_stream * const_dnnl_stream_t
A constant execution stream handle.
Definition: dnnl_types.h:2180
dnnl_inner_product_desc_t
A descriptor of an inner product operation.
Definition: dnnl_types.h:1521
dnnl_matmul_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1688
dnnl_gpu
@ dnnl_gpu
GPU engine.
Definition: dnnl_types.h:1743
dnnl_layer_normalization_desc_t::data_desc
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1492
dnnl_inner_product_desc_t::bias_desc
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1538
dnnl_rnn_desc_t::weights_projection_desc
dnnl_memory_desc_t weights_projection_desc
Weights projection memory descriptor.
Definition: dnnl_types.h:1614
dnnl_softmax_desc_t::softmax_axis
int softmax_axis
The axis along which to perform the softmax.
Definition: dnnl_types.h:1364
dnnl_query_diff_weights_md
@ dnnl_query_diff_weights_md
weights grad. memory desc
Definition: dnnl_types.h:2143
dnnl_query_prop_kind
@ dnnl_query_prop_kind
propagation kind
Definition: dnnl_types.h:2116
dnnl_eltwise_logistic
@ dnnl_eltwise_logistic
Eltwise: logistic.
Definition: dnnl_types.h:867
dnnl_eltwise
@ dnnl_eltwise
An element-wise primitive.
Definition: dnnl_types.h:804
dnnl_stream_in_order
@ dnnl_stream_in_order
In-order execution.
Definition: dnnl_types.h:2167
dnnl_aBc16b
@ dnnl_aBc16b
3D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:214
dnnl_layer_normalization_desc_t::diff_data_desc
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1494
dnnl_oiw
@ dnnl_oiw
3D CNN weights tensor, an alias to dnnl_abc
Definition: dnnl_types.h:444
dnnl_convolution_auto
@ dnnl_convolution_auto
Convolution algorithm(either direct or Winograd) is chosen just in time.
Definition: dnnl_types.h:843
dnnl_eltwise_sqrt
@ dnnl_eltwise_sqrt
Eltwise: square root.
Definition: dnnl_types.h:859
dnnl_cdba
@ dnnl_cdba
permuted 4D tensor
Definition: dnnl_types.h:201
dnnl_cpu_isa_avx512_core
@ dnnl_cpu_isa_avx512_core
Intel AVX-512 subset for Intel Xeon Scalable processor family and Intel Core processor family.
Definition: dnnl_types.h:2273
dnnl_eltwise_bounded_relu
@ dnnl_eltwise_bounded_relu
Eltwise: bounded_relu.
Definition: dnnl_types.h:863
dnnl_rnn_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1580
dnnl_hwio
@ dnnl_hwio
4D CNN weights tensor, an alias to dnnl_cdba
Definition: dnnl_types.h:454
dnnl_forward_inference
@ dnnl_forward_inference
Forward data propagation (inference mode).
Definition: dnnl_types.h:771
dnnl_query_impl_info_str
@ dnnl_query_impl_info_str
for creating scratchpad memory
Definition: dnnl_types.h:2111
dnnl_query_dst_md
@ dnnl_query_dst_md
destination memory desc
Definition: dnnl_types.h:2144
dnnl_query_resampling_d
@ dnnl_query_resampling_d
resampling descriptor
Definition: dnnl_types.h:2136
dnnl_query_inner_product_d
@ dnnl_query_inner_product_d
inner product descriptor
Definition: dnnl_types.h:2130
dnnl_rnn_flags_undef
@ dnnl_rnn_flags_undef
Undefined RNN flags.
Definition: dnnl_types.h:1557
dnnl_nCdhw16c
@ dnnl_nCdhw16c
5D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcde16b
Definition: dnnl_types.h:532
dnnl_query_convolution_d
@ dnnl_query_convolution_d
convolution descriptor
Definition: dnnl_types.h:2121
dnnl_cpu_isa_avx512_core_amx
@ dnnl_cpu_isa_avx512_core_amx
Intel AVX-512, Intel DL Boost and bfloat16 support and Intel AMX with 8-bit integer and bfloat16 supp...
Definition: dnnl_types.h:2288
dnnl_aBCdef2c8b4c
@ dnnl_aBCdef2c8b4c
6D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:344
dnnl_bcda
@ dnnl_bcda
permuted 4D tensor
Definition: dnnl_types.h:198
dnnl_version_t::major
int major
Major version.
Definition: dnnl_types.h:2221
dnnl_eltwise_gelu_tanh
@ dnnl_eltwise_gelu_tanh
Eltwise: gelu.
Definition: dnnl_types.h:874
dnnl_bidirectional_concat
@ dnnl_bidirectional_concat
Bidirectional execution of RNN primitive with concatenation of the results.
Definition: dnnl_types.h:1568
dnnl_pooling_desc_t
A descriptor of a pooling operation.
Definition: dnnl_types.h:1382
dnnl_aBcd32b
@ dnnl_aBcd32b
4D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:246
dnnl_ba
@ dnnl_ba
permuted 2D tensor
Definition: dnnl_types.h:193
dnnl_data_type_t
dnnl_data_type_t
Data type specification.
Definition: dnnl_types.h:62
dnnl_pooling_desc_t::src_desc
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1395
dnnl_lrn_within_channel
@ dnnl_lrn_within_channel
LRN within a single channel.
Definition: dnnl_types.h:912
dnnl_engine_t
struct dnnl_engine * dnnl_engine_t
An engine handle.
Definition: dnnl_types.h:1750
dnnl_layer_normalization_desc_t::data_scaleshift_desc
dnnl_memory_desc_t data_scaleshift_desc
Scale and shift data and gradient memory descriptors.
Definition: dnnl_types.h:1502
dnnl_binary_mul
@ dnnl_binary_mul
Binary mul.
Definition: dnnl_types.h:930
dnnl_ihwo
@ dnnl_ihwo
4D CNN weights tensor, an alias to dnnl_bcda
Definition: dnnl_types.h:458
dnnl_rnn_desc_t::src_layer_desc
dnnl_memory_desc_t src_layer_desc
Source layer memory descriptor.
Definition: dnnl_types.h:1590
dnnl_format_tag_undef
@ dnnl_format_tag_undef
Undefined memory format tag.
Definition: dnnl_types.h:166
dnnl_binary_min
@ dnnl_binary_min
Binary min.
Definition: dnnl_types.h:934
dnnl_rnn_desc_t::diff_weights_peephole_desc
dnnl_memory_desc_t diff_weights_peephole_desc
Weights gradient peephole memory descriptor.
Definition: dnnl_types.h:1637
dnnl_format_kind_rnn_packed
@ dnnl_format_kind_rnn_packed
Packed weights format used in RNN.
Definition: dnnl_types.h:93
dnnl_goiw
@ dnnl_goiw
4D CNN weights tensor (incl. groups), an alias to dnnl_abcd
Definition: dnnl_types.h:473
const_dnnl_primitive_desc_iterator_t
const struct dnnl_primitive_desc_iterator * const_dnnl_primitive_desc_iterator_t
A constant primitive descriptor iterator handle.
Definition: dnnl_types.h:1772
dnnl_use_scaleshift
@ dnnl_use_scaleshift
Use scale and shift parameters.
Definition: dnnl_types.h:977
dnnl_eltwise_log
@ dnnl_eltwise_log
Eltwise: natural logarithm.
Definition: dnnl_types.h:880
dnnl_query_layer_normalization_d
@ dnnl_query_layer_normalization_d
layer normalization descriptor
Definition: dnnl_types.h:2129
dnnl_ldoi
@ dnnl_ldoi
4D LSTM projection tensor in the format (num_layers, num_directions, num_channels_in_recurrent_projec...
Definition: dnnl_types.h:515
dnnl_version_t::minor
int minor
Minor version.
Definition: dnnl_types.h:2222
dnnl_layer_normalization_desc_t::stat_desc
dnnl_memory_desc_t stat_desc
Mean and variance data memory descriptors.
Definition: dnnl_types.h:1509
dnnl_ABcd8b8a
@ dnnl_ABcd8b8a
4D tensor blocked by 1st and 2nd dimension with block size 8
Definition: dnnl_types.h:273
dnnl_resampling_linear
@ dnnl_resampling_linear
Linear Resampling Method.
Definition: dnnl_types.h:938
dnnl_blocking_desc_t::inner_blks
dnnl_dims_t inner_blks
The size of the blocks, e.g. {4, 16, 4} in case of OIhw_4i16o4i
Definition: dnnl_types.h:1051
dnnl_rnn_desc_t::diff_dst_iter_desc
dnnl_memory_desc_t diff_dst_iter_desc
Destination gradient iteration memory descriptor for hidden state.
Definition: dnnl_types.h:1631
dnnl_dhwio
@ dnnl_dhwio
5D CNN weights tensor, an alias to dnnl_cdeba
Definition: dnnl_types.h:466
dnnl_forward_training
@ dnnl_forward_training
Forward data propagation (training mode).
Definition: dnnl_types.h:767
dnnl_primitive_kind_max
@ dnnl_primitive_kind_max
Parameter to allow internal only primitives without undefined behavior.
Definition: dnnl_types.h:832
dnnl_eltwise_square
@ dnnl_eltwise_square
Eltwise: square.
Definition: dnnl_types.h:855
dnnl_bac
@ dnnl_bac
permuted 3D tensor
Definition: dnnl_types.h:194
dnnl_fuse_norm_relu
@ dnnl_fuse_norm_relu
Fuse with ReLU.
Definition: dnnl_types.h:990
dnnl_bacde
@ dnnl_bacde
permuted 5D tensor
Definition: dnnl_types.h:196
dnnl_cpu_isa_avx512_mic_4ops
@ dnnl_cpu_isa_avx512_mic_4ops
Intel AVX-512 subset for Intel Xeon Phi processors 7235, 7285, 7295 Series.
Definition: dnnl_types.h:2269
dnnl_tn
@ dnnl_tn
2D RNN statistics tensor, an alias to dnnl_ab
Definition: dnnl_types.h:421
const_dnnl_primitive_desc_t
const struct dnnl_primitive_desc * const_dnnl_primitive_desc_t
A constant primitive descriptor handle.
Definition: dnnl_types.h:1783
dnnl_rnn_desc_t::weights_layer_desc
dnnl_memory_desc_t weights_layer_desc
Weights layer memory descriptor.
Definition: dnnl_types.h:1596
dnnl_rnn_desc_t::weights_peephole_desc
dnnl_memory_desc_t weights_peephole_desc
Weights peephole memory descriptor.
Definition: dnnl_types.h:1610
dnnl_format_kind_wino
@ dnnl_format_kind_wino
Weights format used in 8bit Winograd convolution.
Definition: dnnl_types.h:91
const_dnnl_post_ops_t
const struct dnnl_post_ops * const_dnnl_post_ops_t
A constant post operation chain handle.
Definition: dnnl_types.h:1854
dnnl_blocking_desc_t::strides
dnnl_dims_t strides
The strides between the outermost blocks.
Definition: dnnl_types.h:1045
dnnl_convolution_winograd
@ dnnl_convolution_winograd
Winograd convolution.
Definition: dnnl_types.h:841
dnnl_iodhw
@ dnnl_iodhw
5D CNN weights tensor, an alias to dnnl_bacde
Definition: dnnl_types.h:464
dnnl_ABcde4b16a4b
@ dnnl_ABcde4b16a4b
5D tensor blocked by 1st dimension with block size 16
Definition: dnnl_types.h:287
dnnl_nChw8c
@ dnnl_nChw8c
4D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcd8b
Definition: dnnl_types.h:550
dnnl_engine_kind_t
dnnl_engine_kind_t
Kinds of engines.
Definition: dnnl_types.h:1737
dnnl_binary
@ dnnl_binary
A binary primitive.
Definition: dnnl_types.h:822
dnnl_cdeba
@ dnnl_cdeba
permuted 5D tensor
Definition: dnnl_types.h:203
dnnl_exec_arg_t::memory
dnnl_memory_t memory
Input/output memory.
Definition: dnnl_types.h:2056
dnnl_eltwise_tanh
@ dnnl_eltwise_tanh
Eltwise: hyperbolic tangent non-linearity (tanh)
Definition: dnnl_types.h:851
dnnl_convolution_desc_t::diff_weights_desc
dnnl_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: dnnl_types.h:1242
dnnl_aBc4b
@ dnnl_aBc4b
3D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:220
dnnl_abcde
@ dnnl_abcde
plain 5D tensor
Definition: dnnl_types.h:181
dnnl_nCw8c
@ dnnl_nCw8c
3D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBc8b
Definition: dnnl_types.h:562
dnnl_post_ops_t
struct dnnl_post_ops * dnnl_post_ops_t
A post operation chain handle.
Definition: dnnl_types.h:1851
dnnl_query_gemm_d
@ dnnl_query_gemm_d
GEMM descriptor (internal)
Definition: dnnl_types.h:2132
dnnl_memory_desc_t::dims
dnnl_dims_t dims
Dimensions in the following order:
Definition: dnnl_types.h:1157
dnnl_stream_default_order
@ dnnl_stream_default_order
Default order execution.
Definition: dnnl_types.h:2165
dnnl_pooling
@ dnnl_pooling
A pooling primitive.
Definition: dnnl_types.h:808
dnnl_acdb
@ dnnl_acdb
permuted 4D tensor
Definition: dnnl_types.h:191
dnnl_query_lrn_d
@ dnnl_query_lrn_d
lrn descriptor
Definition: dnnl_types.h:2127
dnnl_backward
@ dnnl_backward
Backward propagation (with respect to all parameters).
Definition: dnnl_types.h:777
dnnl_giohw
@ dnnl_giohw
5D CNN weights tensor (incl. groups), an alias to dnnl_acbde
Definition: dnnl_types.h:481
dnnl_softmax_desc_t
A descriptor of a Softmax operation.
Definition: dnnl_types.h:1352
dnnl_convolution_desc_t::dilates
dnnl_dims_t dilates
Convolution dilates in each spatial dimension.
Definition: dnnl_types.h:1254
dnnl_cpu_isa_avx512_core_bf16
@ dnnl_cpu_isa_avx512_core_bf16
Intel AVX-512, Intel DL Boost and bfloat16 support for Intel Xeon Scalable processor family and Intel...
Definition: dnnl_types.h:2283
dnnl_iterator_ends
@ dnnl_iterator_ends
Primitive iterator passed over last primitive descriptor.
Definition: dnnl_types.h:49
dnnl_resampling_desc_t::dst_desc
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1722
dnnl_blocking_desc_t::inner_nblks
int inner_nblks
The number of innermost blocks, e.g. 3 in case of OIhw_4i16o4i_
Definition: dnnl_types.h:1049
dnnl_primitive_desc
An opaque structure to describe a primitive descriptor.
dnnl_nCdhw8c
@ dnnl_nCdhw8c
5D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcde8b
Definition: dnnl_types.h:538
dnnl_pooling_avg
@ dnnl_pooling_avg
Average pooling (alias for dnnl_pooling_avg_exclude_padding)
Definition: dnnl_types.h:908
dnnl_vanilla_rnn
@ dnnl_vanilla_rnn
RNN cell.
Definition: dnnl_types.h:914
dnnl_unidirectional
@ dnnl_unidirectional
Alias for dnnl_unidirectional_left2right.
Definition: dnnl_types.h:1573
dnnl_abdc
@ dnnl_abdc
permuted 4D tensor
Definition: dnnl_types.h:186
dnnl_eltwise_pow
@ dnnl_eltwise_pow
Eltwise: pow.
Definition: dnnl_types.h:884
dnnl_ldio
@ dnnl_ldio
4D LSTM projection tensor in the format (num_layers, num_directions, num_channels_in_hidden_state,...
Definition: dnnl_types.h:512
dnnl_aBcd4b
@ dnnl_aBcd4b
4D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:248
dnnl_query_matmul_d
@ dnnl_query_matmul_d
matrix multiplication (matmul) descriptor
Definition: dnnl_types.h:2135
dnnl_primitive_desc_t
struct dnnl_primitive_desc * dnnl_primitive_desc_t
A primitive descriptor handle.
Definition: dnnl_types.h:1780
dnnl_version_t::hash
const char * hash
Git hash of the sources (may be absent)
Definition: dnnl_types.h:2224
dnnl_query_binary_d
@ dnnl_query_binary_d
binary descriptor
Definition: dnnl_types.h:2133
dnnl_lbr_gru
@ dnnl_lbr_gru
GRU cell with linear before reset.
Definition: dnnl_types.h:926
dnnl_forward
@ dnnl_forward
Forward data propagation (alias for dnnl_forward_training).
Definition: dnnl_types.h:775
dnnl_f32
@ dnnl_f32
32-bit/single-precision floating point.
Definition: dnnl_types.h:70
dnnl_acbdef
@ dnnl_acbdef
permuted 6D tensor
Definition: dnnl_types.h:190
dnnl_iwo
@ dnnl_iwo
3D CNN weights tensor, an alias to dnnl_bca
Definition: dnnl_types.h:450
dnnl_use_global_stats
@ dnnl_use_global_stats
Use global statistics.
Definition: dnnl_types.h:964
dnnl_lrn_across_channels
@ dnnl_lrn_across_channels
Local response normalization (LRN) across multiple channels.
Definition: dnnl_types.h:910
dnnl_concat
@ dnnl_concat
A (out-of-place) concat primitive.
Definition: dnnl_types.h:796
dnnl_ntc
@ dnnl_ntc
3D RNN data tensor in the format (batch, seq_length, input channels).
Definition: dnnl_types.h:492
dnnl_query_diff_dst_md
@ dnnl_query_diff_dst_md
destination grad. memory desc
Definition: dnnl_types.h:2145
dnnl_matmul_desc_t::dst_desc
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1696
dnnl_format_kind_undef
@ dnnl_format_kind_undef
Undefined memory format kind, used for empty memory descriptors.
Definition: dnnl_types.h:82
dnnl_layer_normalization_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1487
dnnl_version_t::cpu_runtime
unsigned cpu_runtime
CPU runtime.
Definition: dnnl_types.h:2225
dnnl_lrn_desc_t::diff_data_desc
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1433
dnnl_aBcdef16b
@ dnnl_aBcdef16b
6D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:339
dnnl_layer_normalization
@ dnnl_layer_normalization
A layer normalization primitive.
Definition: dnnl_types.h:814
dnnl_memory_desc_t::data_type
dnnl_data_type_t data_type
Data type of the tensor elements.
Definition: dnnl_types.h:1160
dnnl_convolution_desc_t::diff_dst_desc
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1250
dnnl_matmul_desc_t::accum_data_type
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1698
dnnl_primitive
dnnl_eltwise_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1305
dnnl_pooling_desc_t::dst_desc
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1399
dnnl_cpu_isa_all
@ dnnl_cpu_isa_all
Any ISA (excepting those listed as initial support)
Definition: dnnl_types.h:2252
dnnl_rnn_desc_t::diff_weights_layer_desc
dnnl_memory_desc_t diff_weights_layer_desc
Weights gradient layer memory descriptor.
Definition: dnnl_types.h:1623
dnnl_query_op_d
@ dnnl_query_op_d
op descriptor
Definition: dnnl_types.h:2120
dnnl_primitive_desc_iterator_t
struct dnnl_primitive_desc_iterator * dnnl_primitive_desc_iterator_t
A primitive descriptor iterator handle.
Definition: dnnl_types.h:1769
dnnl_out_of_memory
@ dnnl_out_of_memory
The operation failed due to an out-of-memory condition.
Definition: dnnl_types.h:43
dnnl_dim_t
int64_t dnnl_dim_t
A type to describe tensor dimension.
Definition: dnnl_types.h:1034
dnnl_shuffle_desc_t::axis
int axis
Axis for shuffling.
Definition: dnnl_types.h:1288
dnnl_softmax_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1358
dnnl_lrn_desc_t::lrn_beta
float lrn_beta
LRN beta parameter.
Definition: dnnl_types.h:1440
dnnl_idhwo
@ dnnl_idhwo
5D CNN weights tensor, an alias to dnnl_bcdea
Definition: dnnl_types.h:470
dnnl_abcd
@ dnnl_abcd
plain 4D tensor
Definition: dnnl_types.h:180
dnnl_u8
@ dnnl_u8
8-bit unsigned integer.
Definition: dnnl_types.h:76
dnnl_ncdhw
@ dnnl_ncdhw
5D CNN activations tensor, an alias to dnnl_abcde
Definition: dnnl_types.h:435
dnnl_query_workspace_md
@ dnnl_query_workspace_md
workspace memory desc
Definition: dnnl_types.h:2146
dnnl_format_tag_last
@ dnnl_format_tag_last
Just a sentinel, not real memory format tag.
Definition: dnnl_types.h:410
dnnl_query_deconvolution_d
@ dnnl_query_deconvolution_d
deconvolution descriptor
Definition: dnnl_types.h:2122
dnnl_memory_t
struct dnnl_memory * dnnl_memory_t
A memory handle.
Definition: dnnl_types.h:1194
dnnl_logsoftmax
@ dnnl_logsoftmax
A logsoftmax primitive.
Definition: dnnl_types.h:824
dnnl_format_tag_any
@ dnnl_format_tag_any
Undefined memory format tag.
Definition: dnnl_types.h:169
dnnl_deconvolution_direct
@ dnnl_deconvolution_direct
Direct deconvolution.
Definition: dnnl_types.h:845
dnnl_reorder
@ dnnl_reorder
A reorder primitive.
Definition: dnnl_types.h:792
dnnl_lrn_desc_t
A descriptor of a Local Response Normalization (LRN) operation.
Definition: dnnl_types.h:1420
dnnl_stream_default_flags
@ dnnl_stream_default_flags
Default stream configuration.
Definition: dnnl_types.h:2171
dnnl_shuffle_desc_t
A descriptor of a shuffle operation.
Definition: dnnl_types.h:1277
dnnl_owi
@ dnnl_owi
3D CNN weights tensor, an alias to dnnl_acb
Definition: dnnl_types.h:446
dnnl_rnn_desc_t::activation_kind
dnnl_alg_kind_t activation_kind
Activation function used for vanilla_rnn cell kind.
Definition: dnnl_types.h:1647
dnnl_backward_data
@ dnnl_backward_data
Backward data propagation.
Definition: dnnl_types.h:779
dnnl_acdeb
@ dnnl_acdeb
permuted 5D tensor
Definition: dnnl_types.h:192
dnnl_version_t
Structure containing version information as per Semantic Versioning
Definition: dnnl_types.h:2220
dnnl_batch_normalization_desc_t
A descriptor of a Batch Normalization operation.
Definition: dnnl_types.h:1451
dnnl_exec_arg_t::arg
int arg
An argument index, e.g. DNNL_ARG_SRC.
Definition: dnnl_types.h:2055
dnnl_eltwise_exp_use_dst_for_bwd
@ dnnl_eltwise_exp_use_dst_for_bwd
Eltwise: exp (dst for backward)
Definition: dnnl_types.h:900
dnnl_rnn_desc_t::weights_iter_desc
dnnl_memory_desc_t weights_iter_desc
Weights iteration memory descriptor.
Definition: dnnl_types.h:1598
dnnl_memory_desc_t::format_kind
dnnl_format_kind_t format_kind
Memory format kind.
Definition: dnnl_types.h:1174
dnnl_ldgo
@ dnnl_ldgo
4D RNN bias tensor in the format (num_layers, num_directions, num_gates, output_channels).
Definition: dnnl_types.h:522
dnnl_dims_t
dnnl_dim_t dnnl_dims_t[DNNL_MAX_NDIMS]
A type to describe tensor dimensions.
Definition: dnnl_types.h:1037
dnnl_eltwise_desc_t::alg_kind
dnnl_alg_kind_t alg_kind
The kind of eltwise algorithm.
Definition: dnnl_types.h:1318
dnnl_rnn_desc_t::diff_dst_iter_c_desc
dnnl_memory_desc_t diff_dst_iter_c_desc
Destination gradient iteration memory descriptor for cell state.
Definition: dnnl_types.h:1633
dnnl_eltwise_desc_t
A descriptor of a element-wise operation.
Definition: dnnl_types.h:1299
dnnl_rnn_desc_t::diff_src_iter_c_desc
dnnl_memory_desc_t diff_src_iter_c_desc
Source gradient iter memory descriptor for cell state.
Definition: dnnl_types.h:1621
dnnl_aBcd16b
@ dnnl_aBcd16b
4D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:240
dnnl_resampling_nearest
@ dnnl_resampling_nearest
Nearest Neighbor Resampling Method.
Definition: dnnl_types.h:936
dnnl_rnn
@ dnnl_rnn
A rnn primitive.
Definition: dnnl_types.h:818
dnnl_aBc32b
@ dnnl_aBc32b
3D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:218
dnnl_rnn_desc_t::diff_bias_desc
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1627
dnnl_query_num_of_outputs_s32
@ dnnl_query_num_of_outputs_s32
number of outputs expected
Definition: dnnl_types.h:2100
dnnl_cpu_isa_sse41
@ dnnl_cpu_isa_sse41
Intel Streaming SIMD Extensions 4.1 (Intel SSE4.1)
Definition: dnnl_types.h:2255
dnnl_format_kind_t
dnnl_format_kind_t
Memory format kind.
Definition: dnnl_types.h:80
dnnl_aBCd2b4c2b
@ dnnl_aBCd2b4c2b
4D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:285
dnnl_blocking_desc_t
Generic description of blocked data layout for most memory formats.
Definition: dnnl_types.h:1042
dnnl_softmax_desc_t::data_desc
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1360
const_dnnl_primitive_t
const struct dnnl_primitive * const_dnnl_primitive_t
A constant primitive handle.
Definition: dnnl_types.h:1867
dnnl_abdec
@ dnnl_abdec
permuted 5D tensor
Definition: dnnl_types.h:187
dnnl_pooling_desc_t::accum_data_type
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1411
dnnl_cpu_isa_avx2
@ dnnl_cpu_isa_avx2
Intel Advanced Vector Extensions 2 (Intel AVX2)
Definition: dnnl_types.h:2261
dnnl_cpu_isa_avx512_core_vnni
@ dnnl_cpu_isa_avx512_core_vnni
Intel AVX-512 and Intel Deep Learning Boost (Intel DL Boost) support for Intel Xeon Scalable processo...
Definition: dnnl_types.h:2278
dnnl_memory_desc_t::ndims
int ndims
Number of dimensions.
Definition: dnnl_types.h:1142
dnnl_aBc8b
@ dnnl_aBc8b
3D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:230
dnnl_layer_normalization_desc_t
A descriptor of a Layer Normalization operation.
Definition: dnnl_types.h:1484
dnnl_matmul_desc_t::bias_desc
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1694
dnnl_convolution_desc_t::diff_bias_desc
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1246
dnnl_not_required
@ dnnl_not_required
Queried element is not required for given primitive.
Definition: dnnl_types.h:53
dnnl_eltwise_clip
@ dnnl_eltwise_clip
Eltwise: clip.
Definition: dnnl_types.h:882
dnnl_inner_product_desc_t::src_desc
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1530
dnnl_eltwise_logistic_use_dst_for_bwd
@ dnnl_eltwise_logistic_use_dst_for_bwd
Eltwise: logistic (dst for backward)
Definition: dnnl_types.h:898
dnnl_wino_desc_t
Description of tensor of weights for winograd 2x3 convolution.
Definition: dnnl_types.h:1070
dnnl_batch_normalization_desc_t::diff_data_desc
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1461
dnnl_rnn_desc_t::src_iter_desc
dnnl_memory_desc_t src_iter_desc
Source iteration memory descriptor for hidden state.
Definition: dnnl_types.h:1592
dnnl_pooling_avg_include_padding
@ dnnl_pooling_avg_include_padding
Average pooling include padding.
Definition: dnnl_types.h:904
dnnl_hwigo
@ dnnl_hwigo
5D CNN weights tensor (incl. groups), an alias to dnnl_decab
Definition: dnnl_types.h:479
dnnl_rnn_desc_t::diff_src_iter_desc
dnnl_memory_desc_t diff_src_iter_desc
Source gradient iter memory descriptor for hidden state.
Definition: dnnl_types.h:1619
dnnl_inner_product_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1528
dnnl_deconvolution
@ dnnl_deconvolution
A deconvolution primitive.
Definition: dnnl_types.h:802
dnnl_aBcde4b
@ dnnl_aBcde4b
5D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:300
dnnl_batch_normalization_desc_t::data_scaleshift_desc
dnnl_memory_desc_t data_scaleshift_desc
Scale and shift data and gradient memory descriptors.
Definition: dnnl_types.h:1467
dnnl_stream_out_of_order
@ dnnl_stream_out_of_order
Out-of-order execution.
Definition: dnnl_types.h:2169
dnnl_gemm
@ dnnl_gemm
A matrix multiplication primitive (internal).
Definition: dnnl_types.h:820
dnnl_convolution
@ dnnl_convolution
A convolution primitive.
Definition: dnnl_types.h:800
dnnl_primitive_t
struct dnnl_primitive * dnnl_primitive_t
A primitive handle.
Definition: dnnl_types.h:1865
dnnl_lrn_desc_t::data_desc
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1431
const_dnnl_primitive_attr_t
const struct dnnl_primitive_attr * const_dnnl_primitive_attr_t
A constant primitive descriptor attributes handle.
Definition: dnnl_types.h:1828
dnnl_primitive_attr
An opaque structure for primitive descriptor attributes.
dnnl_rnn_desc_t::dst_layer_desc
dnnl_memory_desc_t dst_layer_desc
Destination layer memory descriptor.
Definition: dnnl_types.h:1602
dnnl_inner_product_desc_t::accum_data_type
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1546
dnnl_lrn
@ dnnl_lrn
An LRN primitive.
Definition: dnnl_types.h:810
dnnl_query_src_md
@ dnnl_query_src_md
source memory desc
Definition: dnnl_types.h:2140
dnnl_logsoftmax_desc_t
dnnl_softmax_desc_t dnnl_logsoftmax_desc_t
A descriptor of a LogSoftmax operation.
Definition: dnnl_types.h:1374
DNNL_RNN_MAX_N_PARTS
#define DNNL_RNN_MAX_N_PARTS
Maximum number of parts of RNN weights tensor that require separate computation.
Definition: dnnl_types.h:1092
dnnl_scratchpad_mode_t
dnnl_scratchpad_mode_t
Scratchpad mode.
Definition: dnnl_types.h:1791
dnnl_memory_desc_t::wino_desc
dnnl_wino_desc_t wino_desc
Tensor of weights for integer 8bit winograd convolution.
Definition: dnnl_types.h:1180
dnnl_data_type_undef
@ dnnl_data_type_undef
Undefined data type, used for empty memory descriptors.
Definition: dnnl_types.h:64
dnnl_nCdhw32c
@ dnnl_nCdhw32c
5D CNN activations tensor blocked by channels with block size 32, an alias to dnnl_aBcde32b
Definition: dnnl_types.h:529
dnnl_query_engine
@ dnnl_query_engine
execution engine
Definition: dnnl_types.h:2096
dnnl_wino_memory_format_t
dnnl_wino_memory_format_t
Winograd-specific formats.
Definition: dnnl_types.h:1058
dnnl_query_softmax_d
@ dnnl_query_softmax_d
softmax descriptor
Definition: dnnl_types.h:2125
dnnl_resampling_desc_t
A descriptor of resampling operation.
Definition: dnnl_types.h:1707
dnnl_batch_normalization_desc_t::batch_norm_epsilon
float batch_norm_epsilon
Batch normalization epsilon parameter.
Definition: dnnl_types.h:1474
dnnl_invalid_arguments
@ dnnl_invalid_arguments
The operation failed because of incorrect function arguments.
Definition: dnnl_types.h:45
dnnl_eltwise_elu_use_dst_for_bwd
@ dnnl_eltwise_elu_use_dst_for_bwd
Eltwise: exponential linear unit (elu) (dst for backward)
Definition: dnnl_types.h:894
dnnl_cpu
@ dnnl_cpu
CPU engine.
Definition: dnnl_types.h:1741
dnnl_post_ops
An opaque structure for a chain of post operations.
dnnl_query_undef
@ dnnl_query_undef
no query
Definition: dnnl_types.h:2094
dnnl_eltwise_swish
@ dnnl_eltwise_swish
Eltwise: swish.
Definition: dnnl_types.h:878
dnnl_ndhwc
@ dnnl_ndhwc
5D CNN activations tensor, an alias to dnnl_acdeb
Definition: dnnl_types.h:437
dnnl_rnn_desc_t::diff_dst_layer_desc
dnnl_memory_desc_t diff_dst_layer_desc
Destination gradient layer memory descriptor.
Definition: dnnl_types.h:1629
dnnl_convolution_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1227
dnnl_pooling_desc_t::kernel
dnnl_dims_t kernel
Pooling kernel spatial dimensions.
Definition: dnnl_types.h:1405
dnnl_wino_wei_OBaaIBOIio
@ dnnl_wino_wei_OBaaIBOIio
Internal weights format for 4x3 Winograd.
Definition: dnnl_types.h:1066
dnnl_inner_product_desc_t::weights_desc
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1534
dnnl_shuffle_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1280
dnnl_resampling_desc_t::diff_src_desc
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1720
dnnl_eltwise_gelu_erf
@ dnnl_eltwise_gelu_erf
Eltwise: erf-based gelu.
Definition: dnnl_types.h:886
dnnl_convolution_desc_t::bias_desc
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1244
dnnl_layer_normalization_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1490
dnnl_batch_normalization_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1454
dnnl_memory_desc_t
Memory descriptor.
Definition: dnnl_types.h:1140
dnnl_binary_desc_t::dst_desc
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1670
dnnl_backward_bias
@ dnnl_backward_bias
Backward bias propagation.
Definition: dnnl_types.h:783
dnnl_op_desc_t
void * dnnl_op_desc_t
A pointer to any of the operation descriptors.
Definition: dnnl_types.h:1210
dnnl_inner_product_desc_t::diff_src_desc
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1532
dnnl_ncw
@ dnnl_ncw
3D CNN activations tensor, an alias to dnnl_abc
Definition: dnnl_types.h:425
dnnl_matmul
@ dnnl_matmul
A matrix multiplication primitive.
Definition: dnnl_types.h:826
dnnl_version_t::patch
int patch
Patch version.
Definition: dnnl_types.h:2223
dnnl_cpu_isa_t
dnnl_cpu_isa_t
CPU instruction set flags.
Definition: dnnl_types.h:2250
dnnl_query_some_md
@ dnnl_query_some_md
stub
Definition: dnnl_types.h:2139
const_dnnl_stream_attr_t
const struct dnnl_stream_attr * const_dnnl_stream_attr_t
A constant execution stream attributes handle.
Definition: dnnl_types.h:2187
const_dnnl_memory_t
const struct dnnl_memory * const_dnnl_memory_t
A constant memory handle.
Definition: dnnl_types.h:1197
dnnl_matmul_desc_t::src_desc
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1690
dnnl_nChw4c
@ dnnl_nChw4c
4D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcd4b
Definition: dnnl_types.h:547
dnnl_memory_extra_desc_t::flags
uint64_t flags
The flags contain arbitrary extra information, such as compensation.
Definition: dnnl_types.h:1127
dnnl_inner_product_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1524
dnnl_softmax_desc_t::diff_desc
dnnl_memory_desc_t diff_desc
Source and Destination of gradient memory descriptor.
Definition: dnnl_types.h:1362
dnnl_oi
@ dnnl_oi
2D CNN weights tensor, an alias to dnnl_ab
Definition: dnnl_types.h:440
dnnl_eltwise_desc_t::diff_data_desc
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1322
dnnl_ohwi
@ dnnl_ohwi
4D CNN weights tensor, an alias to dnnl_acdb
Definition: dnnl_types.h:456
dnnl_bacd
@ dnnl_bacd
permuted 4D tensor
Definition: dnnl_types.h:195
dnnl_format_kind_any
@ dnnl_format_kind_any
Unspecified format kind.
Definition: dnnl_types.h:85
dnnl_tnc
@ dnnl_tnc
3D RNN data tensor in the format (seq_length, batch, input channels).
Definition: dnnl_types.h:490
dnnl_nChw16c
@ dnnl_nChw16c
4D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcd16b
Definition: dnnl_types.h:544
dnnl_shuffle_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1283
dnnl_query_eltwise_d
@ dnnl_query_eltwise_d
eltwise descriptor
Definition: dnnl_types.h:2124
dnnl_primitive_attr_t
struct dnnl_primitive_attr * dnnl_primitive_attr_t
A primitive descriptor attributes handle that controls primitive behavior.
Definition: dnnl_types.h:1825
dnnl_binary_max
@ dnnl_binary_max
Binary max.
Definition: dnnl_types.h:932
dnnl_cba
@ dnnl_cba
permuted 3D tensor
Definition: dnnl_types.h:200
dnnl_query_num_of_inputs_s32
@ dnnl_query_num_of_inputs_s32
number of inputs expected
Definition: dnnl_types.h:2099
dnnl_resampling_desc_t::diff_dst_desc
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1724
dnnl_acbde
@ dnnl_acbde
permuted 5D tensor
Definition: dnnl_types.h:189
dnnl_dcab
@ dnnl_dcab
permuted 4D tensor
Definition: dnnl_types.h:202
dnnl_alg_kind_t
dnnl_alg_kind_t
Kinds of algorithms.
Definition: dnnl_types.h:836
dnnl_deconvolution_winograd
@ dnnl_deconvolution_winograd
Winograd deconvolution.
Definition: dnnl_types.h:847
const_dnnl_op_desc_t
const void * const_dnnl_op_desc_t
A pointer to any of the operation descriptors (constant variant).
Definition: dnnl_types.h:1212
dnnl_cpu_isa_avx512_mic
@ dnnl_cpu_isa_avx512_mic
Intel Advanced Vector Extensions 512 (Intel AVX-512) subset for Intel Xeon Phi processors x200 Series...
Definition: dnnl_types.h:2265
dnnl_memory_desc_t::padded_offsets
dnnl_dims_t padded_offsets
Per-dimension offset from the padding to actual data, the top-level tensor with offsets applied must ...
Definition: dnnl_types.h:1167
dnnl_ldgoi
@ dnnl_ldgoi
5D RNN weights tensor in the format (num_layers, num_directions, num_gates, output_channels,...
Definition: dnnl_types.h:509
dnnl_success
@ dnnl_success
The operation was successful.
Definition: dnnl_types.h:41
dnnl_memory_desc_t::padded_dims
dnnl_dims_t padded_dims
Size of the data including padding in each dimension.
Definition: dnnl_types.h:1163
dnnl_eltwise_exp
@ dnnl_eltwise_exp
Eltwise: exponent.
Definition: dnnl_types.h:869
dnnl_abcdef
@ dnnl_abcdef
plain 6D tensor
Definition: dnnl_types.h:182
dnnl_aBCdef2b4c2b
@ dnnl_aBCdef2b4c2b
6D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:347
dnnl_binary_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1662
dnnl_goihw
@ dnnl_goihw
5D CNN weights tensor (incl. groups), an alias to dnnl_abcde
Definition: dnnl_types.h:477
dnnl_bidirectional_sum
@ dnnl_bidirectional_sum
Bidirectional execution of RNN primitive with summation of the results.
Definition: dnnl_types.h:1571
dnnl_eltwise_desc_t::alpha
float alpha
Algorithm specific parameter.
Definition: dnnl_types.h:1343
dnnl_eltwise_linear
@ dnnl_eltwise_linear
Eltwise: linear.
Definition: dnnl_types.h:861
dnnl_nCw16c
@ dnnl_nCw16c
3D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBc16b
Definition: dnnl_types.h:556
dnnl_vanilla_gru
@ dnnl_vanilla_gru
GRU cell.
Definition: dnnl_types.h:918
dnnl_rnn_desc_t::dst_iter_c_desc
dnnl_memory_desc_t dst_iter_c_desc
Destination iter memory descriptor for cell state.
Definition: dnnl_types.h:1606
dnnl_convolution_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1231
dnnl_binary_desc_t::alg_kind
dnnl_alg_kind_t alg_kind
The kind of the binary algorithm.
Definition: dnnl_types.h:1666
dnnl_abc
@ dnnl_abc
plain 3D tensor
Definition: dnnl_types.h:179
dnnl_nCw32c
@ dnnl_nCw32c
3D CNN activations tensor blocked by channels with block size 32, an alias to dnnl_aBc32b
Definition: dnnl_types.h:553
dnnl_stream
dnnl_blocking_desc_t::inner_idxs
dnnl_dims_t inner_idxs
The logical indices of the blocks, e.g.
Definition: dnnl_types.h:1054
dnnl_wigo
@ dnnl_wigo
4D CNN weights tensor (incl. groups), an alias to dnnl_dcab
Definition: dnnl_types.h:475
dnnl_binary_desc_t
A descriptor of a binary operation.
Definition: dnnl_types.h:1659
dnnl_matmul_desc_t::weights_desc
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1692
dnnl_memory_extra_desc_t::compensation_mask
int compensation_mask
Compensation mask.
Definition: dnnl_types.h:1129
dnnl_memory_extra_flags_t
dnnl_memory_extra_flags_t
Flags for memory special features.
Definition: dnnl_types.h:1109
dnnl_convolution_direct
@ dnnl_convolution_direct
Direct convolution.
Definition: dnnl_types.h:839
dnnl_version_t::gpu_runtime
unsigned gpu_runtime
GPU runtime.
Definition: dnnl_types.h:2226
dnnl_lrn_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1423
dnnl_pooling_desc_t::diff_dst_desc
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1401
dnnl_query_diff_src_md
@ dnnl_query_diff_src_md
source gradient memory desc
Definition: dnnl_types.h:2141
dnnl_resampling_desc_t::src_desc
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1718
dnnl_wio
@ dnnl_wio
3D CNN weights tensor, an alias to dnnl_cba
Definition: dnnl_types.h:448
dnnl_nChw32c
@ dnnl_nChw32c
4D CNN activations tensor blocked by channels with block size 32, an alias to dnnl_aBcd32b
Definition: dnnl_types.h:541
dnnl_rnn_desc_t::diff_src_layer_desc
dnnl_memory_desc_t diff_src_layer_desc
Source gradient layer memory descriptor.
Definition: dnnl_types.h:1617
dnnl_inner_product_desc_t::diff_dst_desc
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1544
dnnl_forward_scoring
@ dnnl_forward_scoring
Forward data propagation (alias for dnnl_forward_inference).
Definition: dnnl_types.h:773
dnnl_aBcde8b
@ dnnl_aBcde8b
5D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:315
dnnl_prop_kind_undef
@ dnnl_prop_kind_undef
Undefined propagation type.
Definition: dnnl_types.h:764
dnnl_blocked
@ dnnl_blocked
A tensor in a generic format described by the stride and blocking values in each dimension.
Definition: dnnl_types.h:89
dnnl_rnn_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1583
dnnl_query_primitive_kind
@ dnnl_query_primitive_kind
primitive kind
Definition: dnnl_types.h:2097
dnnl_unidirectional_left2right
@ dnnl_unidirectional_left2right
Unidirectional execution of RNN primitive from left to right.
Definition: dnnl_types.h:1563
dnnl_rnn_desc_t::diff_weights_iter_desc
dnnl_memory_desc_t diff_weights_iter_desc
Weights gradient iter memory descriptor.
Definition: dnnl_types.h:1625
dnnl_iohw
@ dnnl_iohw
4D CNN weights tensor, an alias to dnnl_bacd
Definition: dnnl_types.h:460
dnnl_eltwise_elu
@ dnnl_eltwise_elu
Eltwise: exponential linear unit (elu)
Definition: dnnl_types.h:853
dnnl_eltwise_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1302
dnnl_odhwi
@ dnnl_odhwi
5D CNN weights tensor, an alias to dnnl_acdeb
Definition: dnnl_types.h:468
dnnl_nwc
@ dnnl_nwc
3D CNN activations tensor, an alias to dnnl_acb
Definition: dnnl_types.h:427
dnnl_nCw4c
@ dnnl_nCw4c
3D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBc4b
Definition: dnnl_types.h:559
dnnl_aBcde32b
@ dnnl_aBcde32b
5D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:298
dnnl_vanilla_lstm
@ dnnl_vanilla_lstm
LSTM cell.
Definition: dnnl_types.h:916
dnnl_any_engine
@ dnnl_any_engine
An unspecified engine.
Definition: dnnl_types.h:1739
dnnl_nCdhw4c
@ dnnl_nCdhw4c
5D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcde4b
Definition: dnnl_types.h:535
dnnl_resampling
@ dnnl_resampling
A resampling primitive.
Definition: dnnl_types.h:828
dnnl_wino_wei_aaOBiOo
@ dnnl_wino_wei_aaOBiOo
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:1064
dnnl_cpu_isa_avx
@ dnnl_cpu_isa_avx
Intel Advanced Vector Extensions (Intel AVX)
Definition: dnnl_types.h:2258
dnnl_bca
@ dnnl_bca
permuted 3D tensor
Definition: dnnl_types.h:197
dnnl_prop_kind_t
dnnl_prop_kind_t
Kinds of propagation.
Definition: dnnl_types.h:761
dnnl_query_scratchpad_md
@ dnnl_query_scratchpad_md
scratchpad memory desc
Definition: dnnl_types.h:2147
dnnl_lrn_desc_t::lrn_k
float lrn_k
LRN k parameter.
Definition: dnnl_types.h:1442
dnnl_nchw
@ dnnl_nchw
4D CNN activations tensor, an alias to dnnl_abcd
Definition: dnnl_types.h:429
dnnl_resampling_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1713
dnnl_eltwise_gelu
@ dnnl_eltwise_gelu
Eltwise: tanh-based gelu (alias for dnnl_eltwise_gelu_tanh)
Definition: dnnl_types.h:876
dnnl_lrn_desc_t::alg_kind
dnnl_alg_kind_t alg_kind
LRN algorithm.
Definition: dnnl_types.h:1429
dnnl_lrn_desc_t::local_size
dnnl_dim_t local_size
The number of channels to sum over (for cross-channel LRN) or the side length of the square region to...
Definition: dnnl_types.h:1436
dnnl_query_weights_md
@ dnnl_query_weights_md
weights memory descriptor desc
Definition: dnnl_types.h:2142
dnnl_memory_extra_desc_t
Description of extra information stored in memory.
Definition: dnnl_types.h:1124
dnnl_inner_product_desc_t::diff_bias_desc
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1540
dnnl_resampling_desc_t::alg_kind
dnnl_alg_kind_t alg_kind
The kind of the resampling algorithm.
Definition: dnnl_types.h:1716
dnnl_pooling_desc_t::diff_src_desc
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1397
dnnl_shuffle_desc_t::data_desc
dnnl_memory_desc_t data_desc
Source and destination memory descriptor, and source and destination gradient memory descriptor.
Definition: dnnl_types.h:1286
dnnl_query_batch_normalization_d
@ dnnl_query_batch_normalization_d
batch normalization descriptor
Definition: dnnl_types.h:2128
dnnl_eltwise_tanh_use_dst_for_bwd
@ dnnl_eltwise_tanh_use_dst_for_bwd
Eltwise: hyperbolic tangent non-linearity (tanh) (dst for backward)
Definition: dnnl_types.h:892
dnnl_pooling_desc_t::strides
dnnl_dims_t strides
Pooling kernel strides for spatial dimensions.
Definition: dnnl_types.h:1403
dnnl_rnn_desc_t::dst_iter_desc
dnnl_memory_desc_t dst_iter_desc
Destination iter memory descriptor for hidden state.
Definition: dnnl_types.h:1604
dnnl_convolution_desc_t::accum_data_type
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1260
dnnl_chwn
@ dnnl_chwn
4D CNN activations tensor, an alias to dnnl_bcda
Definition: dnnl_types.h:433
dnnl_rnn_desc_t::cell_kind
dnnl_alg_kind_t cell_kind
RNN cell kind.
Definition: dnnl_types.h:1586
dnnl_undefined_primitive
@ dnnl_undefined_primitive
Undefined primitive.
Definition: dnnl_types.h:790
dnnl_eltwise_soft_relu
@ dnnl_eltwise_soft_relu
Eltwise: soft_relu.
Definition: dnnl_types.h:865
dnnl_nt
@ dnnl_nt
2D RNN statistics tensor, an alias to dnnl_ba
Definition: dnnl_types.h:423
dnnl_deconvolution_desc_t
dnnl_convolution_desc_t dnnl_deconvolution_desc_t
A descriptor of a deconvolution operation.
Definition: dnnl_types.h:1269
dnnl_memory_desc_t::offset0
dnnl_dim_t offset0
Offset from memory origin to the current block, non-zero only in a description of a memory sub-block.
Definition: dnnl_types.h:1171
dnnl_unidirectional_right2left
@ dnnl_unidirectional_right2left
Unidirectional execution of RNN primitive from right to left.
Definition: dnnl_types.h:1565
dnnl_aBcd8b
@ dnnl_aBcd8b
4D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:267
dnnl_ab
@ dnnl_ab
plain 2D tensor
Definition: dnnl_types.h:178
dnnl_memory_desc_t::rnn_packed_desc
dnnl_rnn_packed_desc_t rnn_packed_desc
Tensor of packed weights for RNN.
Definition: dnnl_types.h:1182
dnnl_query_scratchpad_engine
@ dnnl_query_scratchpad_engine
(scratch) memory, additional to all inputs and outputs memory (bytes)
Definition: dnnl_types.h:2108
dnnl_runtime_error
@ dnnl_runtime_error
Primitive or engine failed on execution.
Definition: dnnl_types.h:51
dnnl_giodhw
@ dnnl_giodhw
6D CNN weights tensor (incl. groups), an alias to dnnl_acbdef
Definition: dnnl_types.h:485
dnnl_query_exec_arg_md
@ dnnl_query_exec_arg_md
memory desc of an execute argument
Definition: dnnl_types.h:2148
dnnl_query_some_d
@ dnnl_query_some_d
stub
Definition: dnnl_types.h:2119
dnnl_pooling_avg_exclude_padding
@ dnnl_pooling_avg_exclude_padding
Average pooling exclude padding.
Definition: dnnl_types.h:906
dnnl_binary_add
@ dnnl_binary_add
Binary add.
Definition: dnnl_types.h:928