oneAPI Deep Neural Network Library (oneDNN)
Performance library for Deep Learning
1.96.0
dnnl_types.h
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16 
19 
20 #ifndef ONEAPI_DNNL_DNNL_TYPES_H
21 #define ONEAPI_DNNL_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 
190 
191  // Permuted plain formats
192 
221 
222  // Opaque blocked formats
223 
224  dnnl_Abc16a,
225  dnnl_ABc16a16b,
226  dnnl_ABc32a32b,
227  dnnl_ABc4a4b,
230  dnnl_ABc16b16a,
231  dnnl_Abc4a,
236  dnnl_ABc4b16a4b,
237  dnnl_ABc2b8a4b,
238  dnnl_ABc16b16a4b,
239  dnnl_ABc16b16a2b,
240  dnnl_ABc4b4a,
241  dnnl_ABc8a16b2a,
242  dnnl_ABc8a8b,
243  dnnl_ABc8a4b,
246  dnnl_ABc8b16a2b,
247  dnnl_BAc8a16b2a,
248  dnnl_ABc8b8a,
249  dnnl_Abcd16a,
250  dnnl_Abcd8a,
251  dnnl_ABcd16a16b,
252  dnnl_Abcd32a,
253  dnnl_ABcd32a32b,
256  dnnl_ABcd16b16a,
257  dnnl_aBCd16b16c,
258  dnnl_aBCd16c16b,
259  dnnl_Abcd4a,
264  dnnl_ABcd4b16a4b,
265  dnnl_ABcd16b16a4b,
266  dnnl_ABcd16b16a2b,
267  dnnl_ABcd4b4a,
268  dnnl_ABcd4a4b,
269  dnnl_aBCd2c4b2c,
270  dnnl_aBCd4b8c2b,
271  dnnl_aBCd4c16b4c,
272  dnnl_aBCd2c8b4c,
273  dnnl_aBCd16c16b4c,
274  dnnl_aBCd16c16b2c,
275  dnnl_aBCd4c4b,
276  dnnl_aBCd4b4c,
277  dnnl_ABcd8a16b2a,
278  dnnl_ABcd2b8a4b,
279  dnnl_ABcd8a8b,
280  dnnl_ABcd8a4b,
283  dnnl_aBCd4c8b2c,
284  dnnl_ABcd8b16a2b,
285  dnnl_aBCd8b16c2b,
286  dnnl_BAcd8a16b2a,
289  dnnl_aBCd8b8c,
290  dnnl_aBCd8b4c,
291  dnnl_aBCd8c16b2c,
292  dnnl_ABcde8a16b2a,
293  dnnl_aCBd8b16c2b,
294  dnnl_aBCd8c8b,
295  dnnl_Abcde16a,
296  dnnl_Abcde32a,
297  dnnl_ABcde16a16b,
298  dnnl_BAcde8a16b2a,
307  dnnl_ABcde16b16a,
308  dnnl_aBCde16b16c,
309  dnnl_aBCde16c16b,
310  dnnl_aBCde2c8b4c,
311  dnnl_Abcde4a,
316  dnnl_ABcde4b4a,
317  dnnl_ABcde4a4b,
318  dnnl_aBCde4b4c,
319  dnnl_aBCde2c4b2c,
320  dnnl_aBCde4b8c2b,
321  dnnl_aBCde4c16b4c,
322  dnnl_aBCde16c16b4c,
323  dnnl_aBCde16c16b2c,
324  dnnl_aBCde4c4b,
325  dnnl_Abcde8a,
326  dnnl_ABcde8a8b,
327  dnnl_ABcde8a4b,
328  dnnl_BAcde16b16a,
331  dnnl_ABcde8b16a2b,
332  dnnl_aBCde8b16c2b,
333  dnnl_aBCde4c8b2c,
334  dnnl_aCBde8b16c2b,
335  dnnl_ABcde8b8a,
336  dnnl_ABcde32a32b,
337  dnnl_aBCde8b8c,
338  dnnl_aBCde8b4c,
339  dnnl_ABc4a8b8a4b,
340  dnnl_ABcd4a8b8a4b,
341  dnnl_ABcde4a8b8a4b,
342  dnnl_BAc4b8a8b4a,
343  dnnl_BAcd4b8a8b4a,
344  dnnl_BAcde4b8a8b4a,
345  dnnl_ABcd2a8b8a2b,
346  dnnl_aBCd4b8c8b4c,
347  dnnl_aBCde4b8c8b4c,
348  dnnl_aBCde2b8c8b2c,
349  dnnl_aBCde8c16b2c,
350  dnnl_aBCde8c8b,
355  dnnl_aBCdef16b16c,
356  dnnl_aBCdef16c16b,
357  dnnl_aBCdef4c16b4c,
360  dnnl_aBCdef4c8b2c,
365  dnnl_aBCdef4c4b,
366  dnnl_aBCdef4b4c,
367  dnnl_aBCdef2c4b2c,
368  dnnl_aBCdef4b8c2b,
369  dnnl_aBCdef8b8c,
370  dnnl_aBCdef8b4c,
371  dnnl_aBCdef8c16b2c,
372  dnnl_aBCdef4b8c8b4c,
373  dnnl_aBCdef8b16c2b,
374  dnnl_aCBdef8b16c2b,
375  dnnl_aBCdef8c8b,
376  dnnl_aBdc16b,
377  dnnl_aBdC16b2c,
378  dnnl_aBdC16b4c,
379  dnnl_aBdc4b,
380  dnnl_aBdc8b,
381  dnnl_aBdec16b,
382  dnnl_aBdeC16b2c,
383  dnnl_aBdeC16b4c,
384  dnnl_aBdec32b,
385  dnnl_aBdec4b,
386  dnnl_aBdec8b,
387  dnnl_aBdefc16b,
388  dnnl_aBdefC16b2c,
389  dnnl_aCBdef16c16b,
390  dnnl_aBdefc4b,
391  dnnl_aBdefc8b,
392  dnnl_Abcdef16a,
393  dnnl_Abcdef32a,
394  dnnl_aBedc16b,
395  dnnl_Acb16a,
396  dnnl_AcB16a2b,
397  dnnl_AcB16a4b,
398  dnnl_Acb4a,
399  dnnl_Acb8a,
400  dnnl_aCBd16b16c,
401  dnnl_aCBd16c16b,
402  dnnl_aCBde16b16c,
403  dnnl_aCBde16c16b,
404  dnnl_Acdb16a,
405  dnnl_AcdB16a2b,
406  dnnl_AcdB16a4b,
407  dnnl_Acdb32a,
408  dnnl_Acdb4a,
409  dnnl_Acdb8a,
410  dnnl_Acdeb16a,
411  dnnl_AcdeB16a2b,
412  dnnl_Acdeb4a,
413  dnnl_Acdeb8a,
414  dnnl_Adcb16a,
415  dnnl_BAc16a16b,
416  dnnl_BAc16b16a,
417  dnnl_BAcd16a16b,
418  dnnl_BAcd16b16a,
419  dnnl_aCBd4c8b8c4b,
420  dnnl_aCBde4c8b8c4b,
421  dnnl_aCBdef4c8b8c4b,
422  dnnl_BAcde16a16b,
423  dnnl_aCBdef16b16c,
424 
428 
429  // Aliases
430 
455 
488 
505 
540 
541  // Opaque data types, are not to be used explicitly
542 
543  // data
580  dnnl_NCw16n16c = dnnl_ABc16a16b,
581  dnnl_NCdhw16n16c = dnnl_ABcde16a16b,
582  dnnl_NChw16n16c = dnnl_ABcd16a16b,
583  dnnl_NCw32n32c = dnnl_ABc32a32b,
584  dnnl_NChw32n32c = dnnl_ABcd32a32b,
585  dnnl_NCdhw32n32c = dnnl_ABcde32a32b,
586 
587  // weights, 3D
588  dnnl_IOw16o16i = dnnl_BAc16a16b,
589  dnnl_IOw16i16o = dnnl_BAc16b16a,
590  dnnl_OIw16i16o = dnnl_ABc16b16a,
591  dnnl_OIw16o16i = dnnl_ABc16a16b,
592  dnnl_Oiw16o = dnnl_Abc16a,
593  dnnl_OIw4i16o4i = dnnl_ABc4b16a4b,
594  dnnl_OIw2i8o4i = dnnl_ABc2b8a4b,
595  dnnl_OIw16i16o4i = dnnl_ABc16b16a4b,
596  dnnl_OIw16i16o2i = dnnl_ABc16b16a2b,
597  dnnl_OIw4i4o = dnnl_ABc4b4a,
598  dnnl_OIw4o4i = dnnl_ABc4a4b,
599  dnnl_Oiw4o = dnnl_Abc4a,
600  dnnl_OIw8i16o2i = dnnl_ABc8b16a2b,
601  dnnl_OIw8i8o = dnnl_ABc8b8a,
602  dnnl_OIw8o16i2o = dnnl_ABc8a16b2a,
603  dnnl_IOw8o16i2o = dnnl_BAc8a16b2a,
604  dnnl_OIw8o8i = dnnl_ABc8a8b,
605  dnnl_OIw8o4i = dnnl_ABc8a4b,
606  dnnl_Owi16o = dnnl_Acb16a,
607  dnnl_OwI16o2i = dnnl_AcB16a2b,
608  dnnl_OwI16o4i = dnnl_AcB16a4b,
609  dnnl_Owi4o = dnnl_Acb4a,
610  dnnl_Owi8o = dnnl_Acb8a,
611 
612  // weights, 4D
613  dnnl_IOhw16i16o = dnnl_BAcd16b16a,
614  dnnl_IOhw16o16i = dnnl_BAcd16a16b,
615  dnnl_Ohwi16o = dnnl_Acdb16a,
616  dnnl_OhwI16o2i = dnnl_AcdB16a2b,
617  dnnl_OhwI16o4i = dnnl_AcdB16a4b,
618  dnnl_Ohwi32o = dnnl_Acdb32a,
619  dnnl_Ohwi4o = dnnl_Acdb4a,
620  dnnl_Ohwi8o = dnnl_Acdb8a,
621  dnnl_OIhw16i16o = dnnl_ABcd16b16a,
622  dnnl_OIhw16o16i = dnnl_ABcd16a16b,
623  dnnl_Oihw16o = dnnl_Abcd16a,
624  dnnl_OIhw4i16o4i = dnnl_ABcd4b16a4b,
625  dnnl_OIhw16i16o4i = dnnl_ABcd16b16a4b,
626  dnnl_OIhw16i16o2i = dnnl_ABcd16b16a2b,
627  dnnl_OIhw4i4o = dnnl_ABcd4b4a,
628  dnnl_OIhw4o4i = dnnl_ABcd4a4b,
629  dnnl_Oihw4o = dnnl_Abcd4a,
630  dnnl_OIhw8i16o2i = dnnl_ABcd8b16a2b,
631  dnnl_OIhw8i8o = dnnl_ABcd8b8a,
632  dnnl_OIhw8o16i2o = dnnl_ABcd8a16b2a,
633  dnnl_OIhw2i8o4i = dnnl_ABcd2b8a4b,
634  dnnl_IOhw8o16i2o = dnnl_BAcd8a16b2a,
635  dnnl_OIhw8o8i = dnnl_ABcd8a8b,
636  dnnl_OIhw8o4i = dnnl_ABcd8a4b,
637  dnnl_Owhi16o = dnnl_Adcb16a,
638 
639  // weights, 5D
640  dnnl_Odhwi16o = dnnl_Acdeb16a,
641  dnnl_OdhwI16o2i = dnnl_AcdeB16a2b,
642  dnnl_Odhwi4o = dnnl_Acdeb4a,
643  dnnl_Odhwi8o = dnnl_Acdeb8a,
644  dnnl_OIdhw16i16o = dnnl_ABcde16b16a,
645  dnnl_OIdhw16o16i = dnnl_ABcde16a16b,
646  dnnl_Oidhw16o = dnnl_Abcde16a,
647  dnnl_OIdhw4i4o = dnnl_ABcde4b4a,
648  dnnl_OIdhw4o4i = dnnl_ABcde4a4b,
649  dnnl_Oidhw4o = dnnl_Abcde4a,
650  dnnl_OIdhw8i16o2i = dnnl_ABcde8b16a2b,
651  dnnl_OIdhw8i8o = dnnl_ABcde8b8a,
652  dnnl_OIdhw8o16i2o = dnnl_ABcde8a16b2a,
653  dnnl_IOdhw8o16i2o = dnnl_BAcde8a16b2a,
654  dnnl_OIdhw4i16o4i = dnnl_ABcde4b16a4b,
655  dnnl_OIdhw2i8o4i = dnnl_ABcde2b8a4b,
656  dnnl_OIdhw8o8i = dnnl_ABcde8a8b,
657  dnnl_OIdhw8o4i = dnnl_ABcde8a4b,
658  dnnl_IOdhw16i16o = dnnl_BAcde16b16a,
659  dnnl_OIdhw4o8i8o4i = dnnl_ABcde4a8b8a4b,
660  dnnl_IOdhw16o16i = dnnl_BAcde16a16b,
661 
662  // weights w/ groups, 3D
663  dnnl_Goiw16g = dnnl_Abcd16a,
664  dnnl_Goiw8g = dnnl_Abcd8a,
665  dnnl_Goiw4g = dnnl_Abcd4a,
666  dnnl_gIOw16o16i = dnnl_aCBd16b16c,
667  dnnl_gIOw16i16o = dnnl_aCBd16c16b,
668  dnnl_gOIw16i16o = dnnl_aBCd16c16b,
669  dnnl_gOIw16o16i = dnnl_aBCd16b16c,
670  dnnl_gOiw16o = dnnl_aBcd16b,
671  dnnl_gOIw4i16o4i = dnnl_aBCd4c16b4c,
672  dnnl_gOIw2i8o4i = dnnl_aBCd2c8b4c,
673  dnnl_gOIw16i16o4i = dnnl_aBCd16c16b4c,
674  dnnl_gOIw16i16o2i = dnnl_aBCd16c16b2c,
675  dnnl_gOIw4i4o = dnnl_aBCd4c4b,
676  dnnl_gOIw4o4i = dnnl_aBCd4b4c,
677  dnnl_gOiw4o = dnnl_aBcd4b,
678  dnnl_gOIw8i16o2i = dnnl_aBCd8c16b2c,
679  dnnl_gOIw8i8o = dnnl_aBCd8c8b,
680  dnnl_gOIw8o16i2o = dnnl_aBCd8b16c2b,
681  dnnl_gIOw8o16i2o = dnnl_aCBd8b16c2b,
682  dnnl_gOIw8o8i = dnnl_aBCd8b8c,
683  dnnl_gOIw8o4i = dnnl_aBCd8b4c,
684  dnnl_gOwi16o = dnnl_aBdc16b,
685  dnnl_gOwI16o2i = dnnl_aBdC16b2c,
686  dnnl_gOwI16o4i = dnnl_aBdC16b4c,
687  dnnl_gOwi4o = dnnl_aBdc4b,
688  dnnl_gOwi8o = dnnl_aBdc8b,
689  dnnl_Goiw32g = dnnl_Abcd32a,
690  dnnl_gOIw2i4o2i = dnnl_aBCd2c4b2c,
691  dnnl_gOIw2o4i2o = dnnl_aBCd2b4c2b,
692  dnnl_gOIw4i8o2i = dnnl_aBCd4c8b2c,
693  dnnl_gOIw4o8i2o = dnnl_aBCd4b8c2b,
694 
695  // weights w/ groups, 4D
696  dnnl_gIOhw16i16o = dnnl_aCBde16c16b,
697  dnnl_gIOhw16o16i = dnnl_aCBde16b16c,
698  dnnl_gOhwi16o = dnnl_aBdec16b,
699  dnnl_gOhwI16o2i = dnnl_aBdeC16b2c,
700  dnnl_gOhwI16o4i = dnnl_aBdeC16b4c,
701  dnnl_gOhwi32o = dnnl_aBdec32b,
702  dnnl_gOhwi4o = dnnl_aBdec4b,
703  dnnl_gOhwi8o = dnnl_aBdec8b,
704  dnnl_Goihw16g = dnnl_Abcde16a,
705  dnnl_gOIhw16i16o = dnnl_aBCde16c16b,
706  dnnl_gOIhw16o16i = dnnl_aBCde16b16c,
707  dnnl_gOihw16o = dnnl_aBcde16b,
708  dnnl_gOIhw2i8o4i = dnnl_aBCde2c8b4c,
709  dnnl_gOIhw4i16o4i = dnnl_aBCde4c16b4c,
710  dnnl_gOIhw16i16o4i = dnnl_aBCde16c16b4c,
711  dnnl_gOIhw16i16o2i = dnnl_aBCde16c16b2c,
712  dnnl_gOIhw4i4o = dnnl_aBCde4c4b,
713  dnnl_gOIhw4o4i = dnnl_aBCde4b4c,
714  dnnl_gOihw4o = dnnl_aBcde4b,
715  dnnl_Goihw8g = dnnl_Abcde8a,
716  dnnl_Goihw4g = dnnl_Abcde4a,
717  dnnl_gOIhw8i16o2i = dnnl_aBCde8c16b2c,
718  dnnl_gOIhw8i8o = dnnl_aBCde8c8b,
719  dnnl_gOIhw8o16i2o = dnnl_aBCde8b16c2b,
720  dnnl_gIOhw8o16i2o = dnnl_aCBde8b16c2b,
721  dnnl_gOIhw8o8i = dnnl_aBCde8b8c,
722  dnnl_gOIhw8o4i = dnnl_aBCde8b4c,
723  dnnl_Goihw32g = dnnl_Abcde32a,
724  dnnl_gOwhi16o = dnnl_aBedc16b,
725 
726  dnnl_OIw4o8i8o4i = dnnl_ABc4a8b8a4b,
727  dnnl_OIhw4o8i8o4i = dnnl_ABcd4a8b8a4b,
728  dnnl_IOw4i8o8i4o = dnnl_BAc4b8a8b4a,
729  dnnl_IOhw4i8o8i4o = dnnl_BAcd4b8a8b4a,
730  dnnl_IOdhw4i8o8i4o = dnnl_BAcde4b8a8b4a,
731 
732  dnnl_OIhw2o8i8o2i = dnnl_ABcd2a8b8a2b,
733  dnnl_gOIw4o8i8o4i = dnnl_aBCd4b8c8b4c,
734  dnnl_gOIhw4o8i8o4i = dnnl_aBCde4b8c8b4c,
735  dnnl_gOIdhw4o8i8o4i = dnnl_aBCdef4b8c8b4c,
736  dnnl_gIOw4i8o8i4o = dnnl_aCBd4c8b8c4b,
737  dnnl_gIOhw4i8o8i4o = dnnl_aCBde4c8b8c4b,
738  dnnl_gIOdhw4i8o8i4o = dnnl_aCBdef4c8b8c4b,
739  dnnl_gOIhw2o8i8o2i = dnnl_aBCde2b8c8b2c,
740  dnnl_gOIhw2i4o2i = dnnl_aBCde2c4b2c,
741  dnnl_gOIhw2o4i2o = dnnl_aBCde2b4c2b,
742  dnnl_gOIhw4i8o2i = dnnl_aBCde4c8b2c,
743  dnnl_gOIhw4o8i2o = dnnl_aBCde4b8c2b,
744 
745  // weights w/ groups, 6D
746  dnnl_gIOdhw16i16o = dnnl_aCBdef16c16b,
747  dnnl_gIOdhw16o16i = dnnl_aCBdef16b16c,
748  dnnl_gOdhwi16o = dnnl_aBdefc16b,
749  dnnl_gOdhwI16o2i = dnnl_aBdefC16b2c,
750  dnnl_gOdhwi4o = dnnl_aBdefc4b,
751  dnnl_gOdhwi8o = dnnl_aBdefc8b,
752  dnnl_gOIdhw16i16o = dnnl_aBCdef16c16b,
753  dnnl_gOIdhw4i16o4i = dnnl_aBCdef4c16b4c,
754  dnnl_gOIdhw2i8o4i = dnnl_aBCdef2c8b4c,
755  dnnl_gOIdhw16o16i = dnnl_aBCdef16b16c,
756  dnnl_gOidhw16o = dnnl_aBcdef16b,
757  dnnl_gOIdhw4i4o = dnnl_aBCdef4c4b,
758  dnnl_gOIdhw4o4i = dnnl_aBCdef4b4c,
759  dnnl_gOidhw4o = dnnl_aBcdef4b,
760  dnnl_gOIdhw8i16o2i = dnnl_aBCdef8c16b2c,
761  dnnl_gOIdhw8i8o = dnnl_aBCdef8c8b,
762  dnnl_gOIdhw8o16i2o = dnnl_aBCdef8b16c2b,
763  dnnl_gIOdhw8o16i2o = dnnl_aCBdef8b16c2b,
764  dnnl_gOIdhw8o8i = dnnl_aBCdef8b8c,
765  dnnl_gOIdhw8o4i = dnnl_aBCdef8b4c,
766  dnnl_Goidhw16g = dnnl_Abcdef16a,
767  dnnl_Goidhw32g = dnnl_Abcdef32a,
768  dnnl_gOIdhw2i4o2i = dnnl_aBCdef2c4b2c,
769  dnnl_gOIdhw4i8o2i = dnnl_aBCdef4c8b2c,
770  dnnl_gOIdhw2o4i2o = dnnl_aBCdef2b4c2b,
771  dnnl_gOIdhw4o8i2o = dnnl_aBCdef4b8c2b,
773 
775 
780 
782 typedef enum {
783  // TODO: suggest renames
806 
809 typedef enum {
854 
859 
861 typedef enum {
862  dnnl_alg_kind_undef,
951  dnnl_lbr_gru = 0x4fff,
953  dnnl_binary_add = 0x1fff0,
955  dnnl_binary_mul = 0x1fff1,
957  dnnl_binary_max = 0x1fff2,
959  dnnl_binary_min = 0x1fff3,
961  dnnl_binary_div = 0x1fff4,
985 
987 typedef enum {
997 
1010 
1023 
1037 
1040 
1043 
1047 #define DNNL_MAX_NDIMS 12
1051 #define DNNL_RUNTIME_DIM_VAL INT64_MIN
1056 #define DNNL_RUNTIME_SIZE_VAL ((size_t)DNNL_RUNTIME_DIM_VAL)
1060 static const union {
1061  unsigned u;
1062  float f;
1063 } DNNL_RUNTIME_F32_VAL_REP = {0x7fc000d0};
1065 
1068 #define DNNL_RUNTIME_F32_VAL (DNNL_RUNTIME_F32_VAL_REP.f)
1071 static const int DNNL_RUNTIME_S32_VAL_REP = INT32_MIN;
1073 
1076 #define DNNL_RUNTIME_S32_VAL DNNL_RUNTIME_S32_VAL_REP
1079 typedef int64_t dnnl_dim_t;
1080 
1083 
1087 typedef struct {
1091  // Innermost section
1092  // ASSUMPTION: the innermost blocks are always dense
1101 
1103 typedef enum {
1106  // Tensors of weights for 2x3 winograd convolutions.
1110  // Tensor of weights for 4x3 convolution.
1113 
1115 typedef struct {
1116  dnnl_wino_memory_format_t wino_format;
1117  int r;
1118  int alpha;
1119  int ic;
1120  int oc;
1121  int ic_block;
1122  int oc_block;
1123  int ic2_block;
1124  int oc2_block;
1125  float adj_scale;
1126  size_t size;
1128 
1129 typedef enum {
1130  dnnl_packed_format_undef = 0,
1131  dnnl_ldigo_p,
1132  dnnl_ldgoi_p
1133 } dnnl_rnn_packed_memory_format_t;
1134 
1137 #define DNNL_RNN_MAX_N_PARTS 4
1140 typedef struct {
1141  dnnl_rnn_packed_memory_format_t format;
1142  int n_parts;
1143  int n;
1144  int ldb;
1145  int parts[DNNL_RNN_MAX_N_PARTS];
1146  size_t part_pack_size[DNNL_RNN_MAX_N_PARTS];
1147  unsigned pack_part[DNNL_RNN_MAX_N_PARTS];
1148  size_t offset_compensation;
1149  size_t size;
1150  char reserved[200];
1152 
1154 typedef enum {
1155  dnnl_memory_extra_flag_none = 0x0U,
1164  dnnl_memory_extra_flag_scale_adjust = 0x2U,
1165  dnnl_memory_extra_flag_gpu_rnn_u8s8_compensation = 0x4U,
1166  dnnl_memory_extra_flag_compensation_conv_asymmetric_src = 0x8U,
1168 
1170 typedef struct {
1173  uint64_t flags;
1181  char reserved[60];
1183 
1188 typedef struct {
1190  int ndims;
1206 
1209 
1212 
1216 
1220 
1223  union {
1231  // ... other descriptions possible
1232  } format_desc;
1233 
1236 
1239 struct dnnl_memory;
1240 
1242 typedef struct dnnl_memory *dnnl_memory_t;
1243 
1245 typedef const struct dnnl_memory *const_dnnl_memory_t;
1246 
1249 #define DNNL_MEMORY_NONE (NULL)
1253 #define DNNL_MEMORY_ALLOCATE ((void *)(size_t)-1)
1256 
1261 
1263 typedef void *dnnl_op_desc_t;
1265 typedef const void *const_dnnl_op_desc_t;
1266 
1269 
1272 
1275 
1277 typedef struct {
1311  dnnl_dims_t padding[2];
1315 
1317 
1320 
1323 
1325 
1328 
1330 typedef struct {
1341  int axis;
1345 
1347 
1350 
1352 typedef struct {
1396  float alpha, beta;
1398 
1400 
1403 
1405 typedef struct {
1419 
1421 
1424 
1428 
1430 
1433 
1435 typedef struct {
1462  dnnl_dims_t padding[2];
1466 
1468 typedef struct {
1495  dnnl_dims_t padding[2];
1501 
1503 
1506 
1508 typedef struct {
1526  float lrn_alpha;
1528  float lrn_beta;
1530  float lrn_k;
1531 } dnnl_lrn_desc_t;
1532 
1534 
1537 
1539 typedef struct {
1556  dnnl_memory_desc_t diff_data_scaleshift_desc;
1563  unsigned flags;
1565 
1567 
1570 
1572 typedef struct {
1591  dnnl_memory_desc_t diff_data_scaleshift_desc;
1600  unsigned flags;
1602 
1604 
1607 
1609 typedef struct {
1636 
1638 
1641 
1643 typedef enum {
1645  dnnl_rnn_flags_undef = 0x0
1647 
1649 typedef enum {
1663 
1665 typedef struct {
1703 
1730 
1732  unsigned int flags;
1736  float alpha;
1737  float beta;
1738 
1739 } dnnl_rnn_desc_t;
1740 
1742 
1745 
1747 typedef struct {
1756  dnnl_memory_desc_t src_desc[2];
1760 
1762 
1765 
1773 typedef struct {
1788 
1790 
1793 
1795 typedef struct {
1814  float factors[DNNL_MAX_NDIMS];
1816 
1818 
1821 
1823 typedef struct {
1848  float p, eps;
1850 
1852 
1854 
1857 
1859 typedef enum {
1867 
1870 struct dnnl_engine;
1872 typedef struct dnnl_engine *dnnl_engine_t;
1873 #if 0
1874 // FIXME: looks like this never happens
1876 typedef const struct dnnl_engine *const_dnnl_engine_t;
1877 #endif
1878 
1880 
1885 
1889 
1892 
1894 typedef const struct dnnl_primitive_desc_iterator
1896 
1899 struct dnnl_primitive_desc;
1900 
1903 
1906 
1908 
1911 
1913 typedef enum {
1937 
1943 struct dnnl_primitive_attr;
1944 
1948 
1951 
1970 struct dnnl_post_ops;
1971 
1974 
1976 typedef const struct dnnl_post_ops *const_dnnl_post_ops_t;
1977 
1979 
1982 
1985 struct dnnl_primitive;
1990 
1992 #define DNNL_ARG_SRC_0 1
1993 #define DNNL_ARG_SRC DNNL_ARG_SRC_0
1996 #define DNNL_ARG_SRC_LAYER DNNL_ARG_SRC_0
1999 #define DNNL_ARG_FROM DNNL_ARG_SRC_0
2004 #define DNNL_ARG_SRC_1 2
2005 #define DNNL_ARG_SRC_ITER DNNL_ARG_SRC_1
2010 #define DNNL_ARG_SRC_2 3
2011 #define DNNL_ARG_SRC_ITER_C DNNL_ARG_SRC_2
2016 #define DNNL_ARG_DST_0 17
2017 #define DNNL_ARG_DST DNNL_ARG_DST_0
2020 #define DNNL_ARG_TO DNNL_ARG_DST_0
2023 #define DNNL_ARG_DST_LAYER DNNL_ARG_DST_0
2027 #define DNNL_ARG_DST_1 18
2028 #define DNNL_ARG_DST_ITER DNNL_ARG_DST_1
2033 #define DNNL_ARG_DST_2 19
2034 #define DNNL_ARG_DST_ITER_C DNNL_ARG_DST_2
2039 #define DNNL_ARG_WEIGHTS_0 33
2040 #define DNNL_ARG_WEIGHTS DNNL_ARG_WEIGHTS_0
2043 #define DNNL_ARG_SCALE_SHIFT DNNL_ARG_WEIGHTS_0
2046 #define DNNL_ARG_WEIGHTS_LAYER DNNL_ARG_WEIGHTS_0
2051 #define DNNL_ARG_WEIGHTS_1 34
2052 #define DNNL_ARG_WEIGHTS_ITER DNNL_ARG_WEIGHTS_1
2057 #define DNNL_ARG_WEIGHTS_2 35
2058 #define DNNL_ARG_WEIGHTS_PEEPHOLE DNNL_ARG_WEIGHTS_2
2063 #define DNNL_ARG_WEIGHTS_3 36
2064 #define DNNL_ARG_WEIGHTS_PROJECTION DNNL_ARG_WEIGHTS_3
2069 #define DNNL_ARG_BIAS 41
2072 #define DNNL_ARG_MEAN 49
2073 #define DNNL_ARG_VARIANCE 50
2078 #define DNNL_ARG_WORKSPACE 64
2079 #define DNNL_ARG_SCRATCHPAD 80
2083 #define DNNL_ARG_DIFF_SRC_0 129
2084 #define DNNL_ARG_DIFF_SRC DNNL_ARG_DIFF_SRC_0
2087 #define DNNL_ARG_DIFF_SRC_LAYER DNNL_ARG_DIFF_SRC_0
2092 #define DNNL_ARG_DIFF_SRC_1 130
2093 #define DNNL_ARG_DIFF_SRC_ITER DNNL_ARG_DIFF_SRC_1
2098 #define DNNL_ARG_DIFF_SRC_2 131
2099 #define DNNL_ARG_DIFF_SRC_ITER_C DNNL_ARG_DIFF_SRC_2
2104 #define DNNL_ARG_DIFF_DST_0 145
2105 #define DNNL_ARG_DIFF_DST DNNL_ARG_DIFF_DST_0
2108 #define DNNL_ARG_DIFF_DST_LAYER DNNL_ARG_DIFF_DST_0
2113 #define DNNL_ARG_DIFF_DST_1 146
2114 #define DNNL_ARG_DIFF_DST_ITER DNNL_ARG_DIFF_DST_1
2119 #define DNNL_ARG_DIFF_DST_2 147
2120 #define DNNL_ARG_DIFF_DST_ITER_C DNNL_ARG_DIFF_DST_2
2125 #define DNNL_ARG_DIFF_WEIGHTS_0 161
2126 #define DNNL_ARG_DIFF_WEIGHTS DNNL_ARG_DIFF_WEIGHTS_0
2129 #define DNNL_ARG_DIFF_SCALE_SHIFT DNNL_ARG_DIFF_WEIGHTS_0
2132 #define DNNL_ARG_DIFF_WEIGHTS_LAYER DNNL_ARG_DIFF_WEIGHTS_0
2137 #define DNNL_ARG_DIFF_WEIGHTS_1 162
2138 #define DNNL_ARG_DIFF_WEIGHTS_ITER DNNL_ARG_DIFF_WEIGHTS_1
2143 #define DNNL_ARG_DIFF_WEIGHTS_2 163
2144 #define DNNL_ARG_DIFF_WEIGHTS_PEEPHOLE DNNL_ARG_DIFF_WEIGHTS_2
2149 #define DNNL_ARG_DIFF_WEIGHTS_3 164
2150 #define DNNL_ARG_DIFF_WEIGHTS_PROJECTION DNNL_ARG_DIFF_WEIGHTS_3
2155 #define DNNL_ARG_DIFF_BIAS 169
2158 #define DNNL_ARG_ATTR_OUTPUT_SCALES 513
2162 #define DNNL_ARG_MULTIPLE_SRC 1024
2163 #define DNNL_ARG_MULTIPLE_DST 2048
2168 #define DNNL_ARG_ATTR_ZERO_POINTS 4096
2172 #define DNNL_ARG_ATTR_POST_OP_DW 8192
2175 #define DNNL_ARG_ATTR_MULTIPLE_POST_OP_BASE 16384
2179 #define DNNL_ARG_ATTR_MULTIPLE_POST_OP(idx) \
2180  (DNNL_ARG_ATTR_MULTIPLE_POST_OP_BASE * ((idx) + 1))
2181 
2182 // XXX: next define should have a (1 << 20) = 1048576 value to preserve 5 bits
2183 // for DNNL_ARG_ATTR_MULTIPLE_POST_OP argument.
2184 
2187 typedef struct {
2188  int arg;
2190 } dnnl_exec_arg_t;
2191 
2193 
2196 
2226 typedef enum {
2228 
2231 
2234 
2237 
2242 
2245 
2248 
2250 
2251  // memory and op descriptor section
2272 
2273  // memory descriptor section
2284 
2285  // Max value to prevent UB for internal use only dnnl_query_t
2286  dnnl_query_max = 0x7fff,
2287 } dnnl_query_t;
2288 
2290 
2292 
2295 
2297 typedef enum {
2305 
2308 struct dnnl_stream;
2310 typedef struct dnnl_stream *dnnl_stream_t;
2312 typedef const struct dnnl_stream *const_dnnl_stream_t;
2313 
2315 
2318 
2320 #define DNNL_RUNTIME_NONE 0u
2323 #define DNNL_RUNTIME_SEQ 1u
2326 #define DNNL_RUNTIME_OMP 2u
2329 #define DNNL_RUNTIME_TBB 4u
2332 #define DNNL_RUNTIME_THREADPOOL 8u
2335 #define DNNL_RUNTIME_OCL 256u
2338 #define DNNL_RUNTIME_SYCL 512u
2341 #define DNNL_RUNTIME_DPCPP DNNL_RUNTIME_SYCL
2345 typedef struct {
2346  int major;
2347  int minor;
2348  int patch;
2349  const char *hash;
2350  unsigned cpu_runtime;
2351  unsigned gpu_runtime;
2352 } dnnl_version_t;
2353 
2355 #define DNNL_JIT_PROFILE_NONE 0u
2358 #define DNNL_JIT_PROFILE_VTUNE 1u
2361 #define DNNL_JIT_PROFILE_LINUX_PERFMAP 2u
2364 #define DNNL_JIT_PROFILE_LINUX_JITDUMP 4u
2368 #define DNNL_JIT_PROFILE_LINUX_JITDUMP_USE_TSC 8u
2371 #define DNNL_JIT_PROFILE_LINUX_PERF \
2372  (DNNL_JIT_PROFILE_LINUX_JITDUMP | DNNL_JIT_PROFILE_LINUX_PERFMAP)
2373 
2375 typedef enum {
2378 
2381 
2384 
2387 
2391 
2395 
2399 
2404 
2409 
2414 } dnnl_cpu_isa_t;
2415 
2417 
2419 
2420 #ifdef __cplusplus
2421 }
2422 #endif
2423 
2424 #endif
dnnl_lrn_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1514
dnnl_query_time_estimate_f64
@ dnnl_query_time_estimate_f64
runtime estimation (seconds)
Definition: dnnl_types.h:2235
dnnl_query_reorder_dst_engine
@ dnnl_query_reorder_dst_engine
destination engine
Definition: dnnl_types.h:2247
dnnl_pooling_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1438
dnnl_rnn_desc_t::bias_desc
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1688
dnnl_aBcdef4b
@ dnnl_aBcdef4b
6D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:364
dnnl_dhwigo
@ dnnl_dhwigo
6D CNN weights tensor (incl. groups), an alias to dnnl_defcab
Definition: dnnl_types.h:504
dnnl_convolution_desc_t::src_desc
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1289
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:1930
dnnl_goidhw
@ dnnl_goidhw
6D CNN weights tensor (incl. groups), an alias to dnnl_abcdef
Definition: dnnl_types.h:500
dnnl_wino_wei_aaOIoi
@ dnnl_wino_wei_aaOIoi
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:1107
dnnl_io
@ dnnl_io
2D CNN weights tensor, an alias to dnnl_ba
Definition: dnnl_types.h:459
dnnl_convolution_desc_t::strides
dnnl_dims_t strides
Convolution strides in each spatial dimension.
Definition: dnnl_types.h:1305
dnnl_nc
@ dnnl_nc
2D CNN activations tensor, an alias to dnnl_ab
Definition: dnnl_types.h:434
dnnl_eltwise_desc_t::data_desc
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1373
dnnl_resampling_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1798
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:432
dnnl_eltwise_round
@ dnnl_eltwise_round
Eltwise: round.
Definition: dnnl_types.h:913
dnnl_batch_normalization_desc_t::data_desc
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1547
dnnl_rnn_packed_desc_t
Description of tensor of packed weights for rnn.
Definition: dnnl_types.h:1140
dnnl_eltwise_relu_use_dst_for_bwd
@ dnnl_eltwise_relu_use_dst_for_bwd
Eltwise: ReLU (dst for backward)
Definition: dnnl_types.h:915
dnnl_layer_normalization_desc_t::layer_norm_epsilon
float layer_norm_epsilon
Layer normalization epsilon parameter.
Definition: dnnl_types.h:1599
dnnl_inner_product_desc_t::diff_weights_desc
dnnl_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: dnnl_types.h:1624
dnnl_query_pooling_d
@ dnnl_query_pooling_d
pooling descriptor
Definition: dnnl_types.h:2259
dnnl_ABcde2b8a4b
@ dnnl_ABcde2b8a4b
5D tensor blocked by 1st dimension with block size 8
Definition: dnnl_types.h:304
dnnl_wino_wei_aaOio
@ dnnl_wino_wei_aaOio
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:1108
dnnl_convolution_desc_t::alg_kind
dnnl_alg_kind_t alg_kind
The kind of the convolution algorithm.
Definition: dnnl_types.h:1287
dnnl_reduction_mul
@ dnnl_reduction_mul
Reduction using mul.
Definition: dnnl_types.h:973
dnnl_pooling_desc_t::alg_kind
dnnl_alg_kind_t alg_kind
The kind of pooling algorithm.
Definition: dnnl_types.h:1446
dnnl_aBCde2b4c2b
@ dnnl_aBCde2b4c2b
5D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:352
dnnl_query_memory_consumption_s64
@ dnnl_query_memory_consumption_s64
memory consumption – extra
Definition: dnnl_types.h:2236
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:837
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:211
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:833
dnnl_query_logsoftmax_d
@ dnnl_query_logsoftmax_d
logsoftmax descriptor
Definition: dnnl_types.h:2267
dnnl_stream_t
struct dnnl_stream * dnnl_stream_t
An execution stream handle.
Definition: dnnl_types.h:2310
dnnl_pooling_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1441
dnnl_abcdefghji
@ dnnl_abcdefghji
permuted 10D tensor
Definition: dnnl_types.h:218
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:2246
dnnl_wino_undef
@ dnnl_wino_undef
Undefined memory format, used for empty memory descriptors.
Definition: dnnl_types.h:1105
dnnl_rnn_desc_t::direction
dnnl_rnn_direction_t direction
The direction of RNN primitive execution.
Definition: dnnl_types.h:1676
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:1163
dnnl_softmax
@ dnnl_softmax
A softmax primitive.
Definition: dnnl_types.h:827
dnnl_normalization_flags_none
@ dnnl_normalization_flags_none
Use no normalization flags.
Definition: dnnl_types.h:996
dnnl_query_rnn_d
@ dnnl_query_rnn_d
rnn descriptor
Definition: dnnl_types.h:2264
dnnl_inner_product_desc_t::dst_desc
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1630
dnnl_rnn_desc_t::flags
unsigned int flags
RNN cell flags.
Definition: dnnl_types.h:1732
dnnl_cn
@ dnnl_cn
2D CNN activations tensor, an alias to dnnl_ba
Definition: dnnl_types.h:436
DNNL_MAX_NDIMS
#define DNNL_MAX_NDIMS
Maximum number of dimensions a tensor can have.
Definition: dnnl_types.h:1047
dnnl_ldnc
@ dnnl_ldnc
4D RNN states tensor in the format (num_layers, num_directions, batch, state channels).
Definition: dnnl_types.h:512
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:1935
dnnl_batch_normalization_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1545
dnnl_defcab
@ dnnl_defcab
permuted 6D tensor
Definition: dnnl_types.h:212
dnnl_abcdefghijlk
@ dnnl_abcdefghijlk
permuted 12D tensor
Definition: dnnl_types.h:220
dnnl_abcdefghijk
@ dnnl_abcdefghijk
plain 11D tensor
Definition: dnnl_types.h:188
dnnl_aBcde16b
@ dnnl_aBcde16b
5D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:306
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:1682
dnnl_batch_normalization_desc_t::stat_desc
dnnl_memory_desc_t stat_desc
Statistics memory descriptor.
Definition: dnnl_types.h:1560
dnnl_eltwise_relu
@ dnnl_eltwise_relu
Eltwise: ReLU.
Definition: dnnl_types.h:874
dnnl_pooling_v2_desc_t::dst_desc
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1485
dnnl_acb
@ dnnl_acb
permuted 3D tensor
Definition: dnnl_types.h:195
dnnl_matmul_desc_t
A descriptor of a matrix multiplication operation.
Definition: dnnl_types.h:1773
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:1729
dnnl_eltwise_abs
@ dnnl_eltwise_abs
Eltwise: abs.
Definition: dnnl_types.h:882
dnnl_reduction_desc_t::p
float p
Algorithm specific parameters.
Definition: dnnl_types.h:1848
dnnl_shuffle_desc_t::group_size
dnnl_dim_t group_size
Number of groups.
Definition: dnnl_types.h:1343
dnnl_memory_extra_desc_t::scale_adjust
float scale_adjust
Scale applied to the data.
Definition: dnnl_types.h:1177
dnnl_oihw
@ dnnl_oihw
4D CNN weights tensor, an alias to dnnl_abcd
Definition: dnnl_types.h:469
dnnl_normalization_flags_t
dnnl_normalization_flags_t
Flags for normalization primitives.
Definition: dnnl_types.h:987
dnnl_eltwise_sqrt_use_dst_for_bwd
@ dnnl_eltwise_sqrt_use_dst_for_bwd
Eltwise: square root (dst for backward)
Definition: dnnl_types.h:921
dnnl_shuffle
@ dnnl_shuffle
A shuffle primitive.
Definition: dnnl_types.h:815
dnnl_query_shuffle_d
@ dnnl_query_shuffle_d
shuffle descriptor
Definition: dnnl_types.h:2256
dnnl_convolution_desc_t
A descriptor of a convolution operation.
Definition: dnnl_types.h:1277
dnnl_primitive_kind_t
dnnl_primitive_kind_t
Kinds of primitives.
Definition: dnnl_types.h:809
dnnl_pooling_v2_desc_t::src_desc
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1481
dnnl_rnn_flags_t
dnnl_rnn_flags_t
Flags for RNN cell.
Definition: dnnl_types.h:1643
dnnl_ldigo
@ dnnl_ldigo
5D RNN weights tensor in the format (num_layers, num_directions, input_channels, num_gates,...
Definition: dnnl_types.h:519
dnnl_pooling_max
@ dnnl_pooling_max
Max pooling.
Definition: dnnl_types.h:927
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:2187
dnnl_stream_flags_t
dnnl_stream_flags_t
Stream flags.
Definition: dnnl_types.h:2297
dnnl_query_t
dnnl_query_t
Primitive descriptor query specification.
Definition: dnnl_types.h:2226
dnnl_softmax_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1408
dnnl_lrn_desc_t::lrn_alpha
float lrn_alpha
LRN alpha parameter.
Definition: dnnl_types.h:1526
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:448
dnnl_rnn_desc_t
A descriptor for an RNN operation.
Definition: dnnl_types.h:1665
dnnl_rnn_direction_t
dnnl_rnn_direction_t
A direction of RNN primitive execution.
Definition: dnnl_types.h:1649
dnnl_bcdea
@ dnnl_bcdea
permuted 5D tensor
Definition: dnnl_types.h:206
dnnl_convolution_desc_t::diff_src_desc
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1291
dnnl_convolution_desc_t::weights_desc
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1293
dnnl_convolution_desc_t::dst_desc
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1301
dnnl_sum
@ dnnl_sum
A sum primitive.
Definition: dnnl_types.h:819
dnnl_oidhw
@ dnnl_oidhw
5D CNN weights tensor, an alias to dnnl_abcde
Definition: dnnl_types.h:479
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:1226
dnnl_backward_weights
@ dnnl_backward_weights
Backward weights propagation.
Definition: dnnl_types.h:802
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:2312
dnnl_inner_product_desc_t
A descriptor of an inner product operation.
Definition: dnnl_types.h:1609
dnnl_matmul_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1776
dnnl_gpu
@ dnnl_gpu
GPU engine.
Definition: dnnl_types.h:1865
dnnl_layer_normalization_desc_t::data_desc
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1580
dnnl_inner_product_desc_t::bias_desc
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1626
dnnl_rnn_desc_t::weights_projection_desc
dnnl_memory_desc_t weights_projection_desc
Weights projection memory descriptor.
Definition: dnnl_types.h:1702
dnnl_softmax_desc_t::softmax_axis
int softmax_axis
The axis along which to perform the softmax.
Definition: dnnl_types.h:1417
dnnl_query_diff_weights_md
@ dnnl_query_diff_weights_md
weights grad. memory desc
Definition: dnnl_types.h:2278
dnnl_query_prop_kind
@ dnnl_query_prop_kind
propagation kind
Definition: dnnl_types.h:2249
dnnl_pooling_v2_desc_t::strides
dnnl_dims_t strides
Pooling kernel strides for spatial dimensions.
Definition: dnnl_types.h:1489
dnnl_abced
@ dnnl_abced
permuted 5D tensor
Definition: dnnl_types.h:213
dnnl_eltwise_logistic
@ dnnl_eltwise_logistic
Eltwise: logistic.
Definition: dnnl_types.h:892
dnnl_pooling_v2_desc_t::accum_data_type
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1497
dnnl_eltwise
@ dnnl_eltwise
An element-wise primitive.
Definition: dnnl_types.h:825
dnnl_stream_in_order
@ dnnl_stream_in_order
In-order execution.
Definition: dnnl_types.h:2299
dnnl_aBc16b
@ dnnl_aBc16b
3D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:229
dnnl_memory_extra_desc_t::asymm_compensation_mask
int asymm_compensation_mask
Compensation mask for asymmetric quantization.
Definition: dnnl_types.h:1179
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:1582
dnnl_oiw
@ dnnl_oiw
3D CNN weights tensor, an alias to dnnl_abc
Definition: dnnl_types.h:461
dnnl_convolution_auto
@ dnnl_convolution_auto
Convolution algorithm(either direct or Winograd) is chosen just in time.
Definition: dnnl_types.h:868
dnnl_eltwise_sqrt
@ dnnl_eltwise_sqrt
Eltwise: square root.
Definition: dnnl_types.h:884
dnnl_cdba
@ dnnl_cdba
permuted 4D tensor
Definition: dnnl_types.h:208
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:2398
dnnl_reduction_norm_lp_power_p_max
@ dnnl_reduction_norm_lp_power_p_max
Reduction using lp norm without final pth-root.
Definition: dnnl_types.h:981
dnnl_eltwise_bounded_relu
@ dnnl_eltwise_bounded_relu
Eltwise: bounded_relu.
Definition: dnnl_types.h:888
dnnl_rnn_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1668
dnnl_hwio
@ dnnl_hwio
4D CNN weights tensor, an alias to dnnl_cdba
Definition: dnnl_types.h:471
dnnl_forward_inference
@ dnnl_forward_inference
Forward data propagation (inference mode).
Definition: dnnl_types.h:792
dnnl_query_impl_info_str
@ dnnl_query_impl_info_str
for creating scratchpad memory
Definition: dnnl_types.h:2244
dnnl_query_dst_md
@ dnnl_query_dst_md
destination memory desc
Definition: dnnl_types.h:2279
dnnl_query_resampling_d
@ dnnl_query_resampling_d
resampling descriptor
Definition: dnnl_types.h:2269
dnnl_query_inner_product_d
@ dnnl_query_inner_product_d
inner product descriptor
Definition: dnnl_types.h:2263
dnnl_rnn_flags_undef
@ dnnl_rnn_flags_undef
Undefined RNN flags.
Definition: dnnl_types.h:1645
dnnl_nCdhw16c
@ dnnl_nCdhw16c
5D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcde16b
Definition: dnnl_types.h:549
dnnl_query_convolution_d
@ dnnl_query_convolution_d
convolution descriptor
Definition: dnnl_types.h:2254
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:2413
dnnl_aBCdef2c8b4c
@ dnnl_aBCdef2c8b4c
6D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:359
dnnl_bcda
@ dnnl_bcda
permuted 4D tensor
Definition: dnnl_types.h:205
dnnl_version_t::major
int major
Major version.
Definition: dnnl_types.h:2346
dnnl_eltwise_gelu_tanh
@ dnnl_eltwise_gelu_tanh
Eltwise: gelu.
Definition: dnnl_types.h:899
dnnl_bidirectional_concat
@ dnnl_bidirectional_concat
Bidirectional execution of RNN primitive with concatenation of the results.
Definition: dnnl_types.h:1656
dnnl_pooling_desc_t
A descriptor of a pooling operation.
Definition: dnnl_types.h:1435
dnnl_aBcd32b
@ dnnl_aBcd32b
4D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:261
dnnl_ba
@ dnnl_ba
permuted 2D tensor
Definition: dnnl_types.h:200
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:1448
dnnl_lrn_within_channel
@ dnnl_lrn_within_channel
LRN within a single channel.
Definition: dnnl_types.h:937
dnnl_engine_t
struct dnnl_engine * dnnl_engine_t
An engine handle.
Definition: dnnl_types.h:1872
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:1590
dnnl_reduction_norm_lp_sum
@ dnnl_reduction_norm_lp_sum
Reduction using lp norm.
Definition: dnnl_types.h:979
dnnl_pooling_v2_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1471
dnnl_binary_mul
@ dnnl_binary_mul
Binary mul.
Definition: dnnl_types.h:955
dnnl_ihwo
@ dnnl_ihwo
4D CNN weights tensor, an alias to dnnl_bcda
Definition: dnnl_types.h:475
dnnl_rnn_desc_t::src_layer_desc
dnnl_memory_desc_t src_layer_desc
Source layer memory descriptor.
Definition: dnnl_types.h:1678
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:959
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:1725
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:490
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:1894
dnnl_use_scaleshift
@ dnnl_use_scaleshift
Use scale and shift parameters.
Definition: dnnl_types.h:1022
dnnl_eltwise_log
@ dnnl_eltwise_log
Eltwise: natural logarithm.
Definition: dnnl_types.h:905
dnnl_reduction_desc_t::src_desc
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1834
dnnl_query_layer_normalization_d
@ dnnl_query_layer_normalization_d
layer normalization descriptor
Definition: dnnl_types.h:2262
dnnl_ldoi
@ dnnl_ldoi
4D LSTM projection tensor in the format (num_layers, num_directions, num_channels_in_recurrent_projec...
Definition: dnnl_types.h:532
dnnl_version_t::minor
int minor
Minor version.
Definition: dnnl_types.h:2347
dnnl_layer_normalization_desc_t::stat_desc
dnnl_memory_desc_t stat_desc
Mean and variance data memory descriptors.
Definition: dnnl_types.h:1597
dnnl_ABcd8b8a
@ dnnl_ABcd8b8a
4D tensor blocked by 1st and 2nd dimension with block size 8
Definition: dnnl_types.h:288
dnnl_resampling_linear
@ dnnl_resampling_linear
Linear Resampling Method.
Definition: dnnl_types.h:965
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:1096
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:1719
dnnl_acbd
@ dnnl_acbd
plain 4D tensor
Definition: dnnl_types.h:181
dnnl_dhwio
@ dnnl_dhwio
5D CNN weights tensor, an alias to dnnl_cdeba
Definition: dnnl_types.h:483
dnnl_forward_training
@ dnnl_forward_training
Forward data propagation (training mode).
Definition: dnnl_types.h:788
dnnl_primitive_kind_max
@ dnnl_primitive_kind_max
Parameter to allow internal only primitives without undefined behavior.
Definition: dnnl_types.h:857
dnnl_pooling_v2_desc_t::kernel
dnnl_dims_t kernel
Pooling kernel spatial dimensions.
Definition: dnnl_types.h:1491
dnnl_eltwise_square
@ dnnl_eltwise_square
Eltwise: square.
Definition: dnnl_types.h:880
dnnl_bac
@ dnnl_bac
permuted 3D tensor
Definition: dnnl_types.h:201
dnnl_fuse_norm_relu
@ dnnl_fuse_norm_relu
Fuse with ReLU.
Definition: dnnl_types.h:1035
dnnl_bacde
@ dnnl_bacde
permuted 5D tensor
Definition: dnnl_types.h:203
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:2394
dnnl_tn
@ dnnl_tn
2D RNN statistics tensor, an alias to dnnl_ab
Definition: dnnl_types.h:438
const_dnnl_primitive_desc_t
const struct dnnl_primitive_desc * const_dnnl_primitive_desc_t
A constant primitive descriptor handle.
Definition: dnnl_types.h:1905
dnnl_rnn_desc_t::weights_layer_desc
dnnl_memory_desc_t weights_layer_desc
Weights layer memory descriptor.
Definition: dnnl_types.h:1684
dnnl_rnn_desc_t::weights_peephole_desc
dnnl_memory_desc_t weights_peephole_desc
Weights peephole memory descriptor.
Definition: dnnl_types.h:1698
dnnl_pooling_v2_desc_t::diff_src_desc
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1483
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:1976
dnnl_blocking_desc_t::strides
dnnl_dims_t strides
The strides between the outermost blocks.
Definition: dnnl_types.h:1090
dnnl_convolution_winograd
@ dnnl_convolution_winograd
Winograd convolution.
Definition: dnnl_types.h:866
dnnl_iodhw
@ dnnl_iodhw
5D CNN weights tensor, an alias to dnnl_bacde
Definition: dnnl_types.h:481
dnnl_ABcde4b16a4b
@ dnnl_ABcde4b16a4b
5D tensor blocked by 1st dimension with block size 16
Definition: dnnl_types.h:302
dnnl_nChw8c
@ dnnl_nChw8c
4D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcd8b
Definition: dnnl_types.h:567
dnnl_engine_kind_t
dnnl_engine_kind_t
Kinds of engines.
Definition: dnnl_types.h:1859
dnnl_binary
@ dnnl_binary
A binary primitive.
Definition: dnnl_types.h:843
dnnl_cdeba
@ dnnl_cdeba
permuted 5D tensor
Definition: dnnl_types.h:210
dnnl_exec_arg_t::memory
dnnl_memory_t memory
Input/output memory.
Definition: dnnl_types.h:2189
dnnl_eltwise_tanh
@ dnnl_eltwise_tanh
Eltwise: hyperbolic tangent non-linearity (tanh)
Definition: dnnl_types.h:876
dnnl_convolution_desc_t::diff_weights_desc
dnnl_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: dnnl_types.h:1295
dnnl_aBc4b
@ dnnl_aBc4b
3D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:235
dnnl_abcde
@ dnnl_abcde
plain 5D tensor
Definition: dnnl_types.h:182
dnnl_nCw8c
@ dnnl_nCw8c
3D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBc8b
Definition: dnnl_types.h:579
dnnl_post_ops_t
struct dnnl_post_ops * dnnl_post_ops_t
A post operation chain handle.
Definition: dnnl_types.h:1973
dnnl_query_gemm_d
@ dnnl_query_gemm_d
GEMM descriptor (internal)
Definition: dnnl_types.h:2265
dnnl_memory_desc_t::dims
dnnl_dims_t dims
Dimensions in the following order:
Definition: dnnl_types.h:1205
dnnl_pooling
@ dnnl_pooling
A pooling primitive.
Definition: dnnl_types.h:829
dnnl_acdb
@ dnnl_acdb
permuted 4D tensor
Definition: dnnl_types.h:198
dnnl_query_lrn_d
@ dnnl_query_lrn_d
lrn descriptor
Definition: dnnl_types.h:2260
dnnl_backward
@ dnnl_backward
Backward propagation (with respect to all parameters).
Definition: dnnl_types.h:798
dnnl_giohw
@ dnnl_giohw
5D CNN weights tensor (incl. groups), an alias to dnnl_acbde
Definition: dnnl_types.h:498
dnnl_softmax_desc_t
A descriptor of a Softmax operation.
Definition: dnnl_types.h:1405
dnnl_convolution_desc_t::dilates
dnnl_dims_t dilates
Convolution dilates in each spatial dimension.
Definition: dnnl_types.h:1307
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:2408
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:1810
dnnl_abcdefghi
@ dnnl_abcdefghi
plain 9D tensor
Definition: dnnl_types.h:186
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:1094
dnnl_primitive_desc
An opaque structure to describe a primitive descriptor.
dnnl_abcdefghijkl
@ dnnl_abcdefghijkl
plain 12D tensor
Definition: dnnl_types.h:189
dnnl_nCdhw8c
@ dnnl_nCdhw8c
5D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcde8b
Definition: dnnl_types.h:555
dnnl_pooling_avg
@ dnnl_pooling_avg
Average pooling (alias for dnnl_pooling_avg_exclude_padding)
Definition: dnnl_types.h:933
dnnl_vanilla_rnn
@ dnnl_vanilla_rnn
RNN cell.
Definition: dnnl_types.h:939
dnnl_reduction_norm_lp_power_p_sum
@ dnnl_reduction_norm_lp_power_p_sum
Reduction using lp norm without final pth-root.
Definition: dnnl_types.h:983
dnnl_unidirectional
@ dnnl_unidirectional
Alias for dnnl_unidirectional_left2right.
Definition: dnnl_types.h:1661
dnnl_abdc
@ dnnl_abdc
permuted 4D tensor
Definition: dnnl_types.h:193
dnnl_eltwise_pow
@ dnnl_eltwise_pow
Eltwise: pow.
Definition: dnnl_types.h:909
dnnl_reduction_max
@ dnnl_reduction_max
Reduction using max.
Definition: dnnl_types.h:967
dnnl_ldio
@ dnnl_ldio
4D LSTM projection tensor in the format (num_layers, num_directions, num_channels_in_hidden_state,...
Definition: dnnl_types.h:529
dnnl_aBcd4b
@ dnnl_aBcd4b
4D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:263
dnnl_reduction_mean
@ dnnl_reduction_mean
Reduction using mean.
Definition: dnnl_types.h:975
dnnl_query_matmul_d
@ dnnl_query_matmul_d
matrix multiplication (matmul) descriptor
Definition: dnnl_types.h:2268
dnnl_primitive_desc_t
struct dnnl_primitive_desc * dnnl_primitive_desc_t
A primitive descriptor handle.
Definition: dnnl_types.h:1902
dnnl_version_t::hash
const char * hash
Git hash of the sources (may be absent)
Definition: dnnl_types.h:2349
dnnl_query_binary_d
@ dnnl_query_binary_d
binary descriptor
Definition: dnnl_types.h:2266
dnnl_lbr_gru
@ dnnl_lbr_gru
GRU cell with linear before reset.
Definition: dnnl_types.h:951
dnnl_forward
@ dnnl_forward
Forward data propagation (alias for dnnl_forward_training).
Definition: dnnl_types.h:796
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:197
dnnl_iwo
@ dnnl_iwo
3D CNN weights tensor, an alias to dnnl_bca
Definition: dnnl_types.h:467
dnnl_use_global_stats
@ dnnl_use_global_stats
Use global statistics.
Definition: dnnl_types.h:1009
dnnl_lrn_across_channels
@ dnnl_lrn_across_channels
Local response normalization (LRN) across multiple channels.
Definition: dnnl_types.h:935
dnnl_concat
@ dnnl_concat
A (out-of-place) concat primitive.
Definition: dnnl_types.h:817
dnnl_ntc
@ dnnl_ntc
3D RNN data tensor in the format (batch, seq_length, input channels).
Definition: dnnl_types.h:509
dnnl_query_diff_dst_md
@ dnnl_query_diff_dst_md
destination grad. memory desc
Definition: dnnl_types.h:2280
dnnl_matmul_desc_t::dst_desc
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1784
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:1575
dnnl_version_t::cpu_runtime
unsigned cpu_runtime
CPU runtime.
Definition: dnnl_types.h:2350
dnnl_lrn_desc_t::diff_data_desc
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1521
dnnl_aBcdef16b
@ dnnl_aBcdef16b
6D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:354
dnnl_layer_normalization
@ dnnl_layer_normalization
A layer normalization primitive.
Definition: dnnl_types.h:835
dnnl_memory_desc_t::data_type
dnnl_data_type_t data_type
Data type of the tensor elements.
Definition: dnnl_types.h:1208
dnnl_convolution_desc_t::diff_dst_desc
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1303
dnnl_matmul_desc_t::accum_data_type
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1786
dnnl_primitive
dnnl_abcdefgh
@ dnnl_abcdefgh
plain 8D tensor
Definition: dnnl_types.h:185
dnnl_eltwise_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1358
dnnl_abcdefghij
@ dnnl_abcdefghij
plain 10D tensor
Definition: dnnl_types.h:187
dnnl_pooling_desc_t::dst_desc
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1452
dnnl_cpu_isa_all
@ dnnl_cpu_isa_all
Any ISA (excepting those listed as initial support)
Definition: dnnl_types.h:2377
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:1711
dnnl_query_op_d
@ dnnl_query_op_d
op descriptor
Definition: dnnl_types.h:2253
dnnl_primitive_desc_iterator_t
struct dnnl_primitive_desc_iterator * dnnl_primitive_desc_iterator_t
A primitive descriptor iterator handle.
Definition: dnnl_types.h:1891
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:1079
dnnl_shuffle_desc_t::axis
int axis
Axis for shuffling.
Definition: dnnl_types.h:1341
dnnl_softmax_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1411
dnnl_lrn_desc_t::lrn_beta
float lrn_beta
LRN beta parameter.
Definition: dnnl_types.h:1528
dnnl_idhwo
@ dnnl_idhwo
5D CNN weights tensor, an alias to dnnl_bcdea
Definition: dnnl_types.h:487
dnnl_abcdegf
@ dnnl_abcdegf
permuted 7D tensor
Definition: dnnl_types.h:215
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:452
dnnl_query_workspace_md
@ dnnl_query_workspace_md
workspace memory desc
Definition: dnnl_types.h:2281
dnnl_format_tag_last
@ dnnl_format_tag_last
Just a sentinel, not real memory format tag.
Definition: dnnl_types.h:427
dnnl_query_deconvolution_d
@ dnnl_query_deconvolution_d
deconvolution descriptor
Definition: dnnl_types.h:2255
dnnl_memory_t
struct dnnl_memory * dnnl_memory_t
A memory handle.
Definition: dnnl_types.h:1242
dnnl_logsoftmax
@ dnnl_logsoftmax
A logsoftmax primitive.
Definition: dnnl_types.h:845
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:870
dnnl_reorder
@ dnnl_reorder
A reorder primitive.
Definition: dnnl_types.h:813
dnnl_lrn_desc_t
A descriptor of a Local Response Normalization (LRN) operation.
Definition: dnnl_types.h:1508
dnnl_stream_default_flags
@ dnnl_stream_default_flags
Default stream configuration.
Definition: dnnl_types.h:2303
dnnl_shuffle_desc_t
A descriptor of a shuffle operation.
Definition: dnnl_types.h:1330
dnnl_owi
@ dnnl_owi
3D CNN weights tensor, an alias to dnnl_acb
Definition: dnnl_types.h:463
dnnl_pooling_v2_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1474
dnnl_rnn_desc_t::activation_kind
dnnl_alg_kind_t activation_kind
Activation function used for vanilla_rnn cell kind.
Definition: dnnl_types.h:1735
dnnl_query_reduction_d
@ dnnl_query_reduction_d
reduction descriptor
Definition: dnnl_types.h:2271
dnnl_backward_data
@ dnnl_backward_data
Backward data propagation.
Definition: dnnl_types.h:800
dnnl_acdeb
@ dnnl_acdeb
permuted 5D tensor
Definition: dnnl_types.h:199
dnnl_version_t
Structure containing version information as per Semantic Versioning
Definition: dnnl_types.h:2345
dnnl_batch_normalization_desc_t
A descriptor of a Batch Normalization operation.
Definition: dnnl_types.h:1539
dnnl_exec_arg_t::arg
int arg
An argument index, e.g. DNNL_ARG_SRC.
Definition: dnnl_types.h:2188
dnnl_eltwise_exp_use_dst_for_bwd
@ dnnl_eltwise_exp_use_dst_for_bwd
Eltwise: exp (dst for backward)
Definition: dnnl_types.h:925
dnnl_rnn_desc_t::weights_iter_desc
dnnl_memory_desc_t weights_iter_desc
Weights iteration memory descriptor.
Definition: dnnl_types.h:1686
dnnl_memory_desc_t::format_kind
dnnl_format_kind_t format_kind
Memory format kind.
Definition: dnnl_types.h:1222
dnnl_ldgo
@ dnnl_ldgo
4D RNN bias tensor in the format (num_layers, num_directions, num_gates, output_channels).
Definition: dnnl_types.h:539
dnnl_dims_t
dnnl_dim_t dnnl_dims_t[DNNL_MAX_NDIMS]
A type to describe tensor dimensions.
Definition: dnnl_types.h:1082
dnnl_eltwise_desc_t::alg_kind
dnnl_alg_kind_t alg_kind
The kind of eltwise algorithm.
Definition: dnnl_types.h:1371
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:1721
dnnl_eltwise_desc_t
A descriptor of a element-wise operation.
Definition: dnnl_types.h:1352
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:1709
dnnl_aBcd16b
@ dnnl_aBcd16b
4D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:255
dnnl_resampling_nearest
@ dnnl_resampling_nearest
Nearest Neighbor Resampling Method.
Definition: dnnl_types.h:963
dnnl_rnn
@ dnnl_rnn
A rnn primitive.
Definition: dnnl_types.h:839
dnnl_aBc32b
@ dnnl_aBc32b
3D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:233
dnnl_rnn_desc_t::diff_bias_desc
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1715
dnnl_query_num_of_outputs_s32
@ dnnl_query_num_of_outputs_s32
number of outputs expected
Definition: dnnl_types.h:2233
dnnl_cpu_isa_sse41
@ dnnl_cpu_isa_sse41
Intel Streaming SIMD Extensions 4.1 (Intel SSE4.1)
Definition: dnnl_types.h:2380
dnnl_abcdfe
@ dnnl_abcdfe
permuted 6D tensor
Definition: dnnl_types.h:214
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:300
dnnl_blocking_desc_t
Generic description of blocked data layout for most memory formats.
Definition: dnnl_types.h:1087
dnnl_softmax_desc_t::data_desc
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1413
const_dnnl_primitive_t
const struct dnnl_primitive * const_dnnl_primitive_t
A constant primitive handle.
Definition: dnnl_types.h:1989
dnnl_abdec
@ dnnl_abdec
permuted 5D tensor
Definition: dnnl_types.h:194
dnnl_pooling_desc_t::accum_data_type
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1464
dnnl_reduction_sum
@ dnnl_reduction_sum
Reduction using sum.
Definition: dnnl_types.h:971
dnnl_cpu_isa_avx2
@ dnnl_cpu_isa_avx2
Intel Advanced Vector Extensions 2 (Intel AVX2)
Definition: dnnl_types.h:2386
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:2403
dnnl_memory_desc_t::ndims
int ndims
Number of dimensions.
Definition: dnnl_types.h:1190
dnnl_aBc8b
@ dnnl_aBc8b
3D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:245
dnnl_layer_normalization_desc_t
A descriptor of a Layer Normalization operation.
Definition: dnnl_types.h:1572
dnnl_matmul_desc_t::bias_desc
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1782
dnnl_convolution_desc_t::diff_bias_desc
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1299
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:907
dnnl_inner_product_desc_t::src_desc
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1618
dnnl_eltwise_logistic_use_dst_for_bwd
@ dnnl_eltwise_logistic_use_dst_for_bwd
Eltwise: logistic (dst for backward)
Definition: dnnl_types.h:923
dnnl_wino_desc_t
Description of tensor of weights for winograd 2x3 convolution.
Definition: dnnl_types.h:1115
dnnl_pooling_v2_desc_t::dilation
dnnl_dims_t dilation
Pooling dilations for spatial dimensions.
Definition: dnnl_types.h:1499
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:1549
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:1680
dnnl_abcdefg
@ dnnl_abcdefg
plain 7D tensor
Definition: dnnl_types.h:184
dnnl_pooling_avg_include_padding
@ dnnl_pooling_avg_include_padding
Average pooling include padding.
Definition: dnnl_types.h:929
dnnl_hwigo
@ dnnl_hwigo
5D CNN weights tensor (incl. groups), an alias to dnnl_decab
Definition: dnnl_types.h:496
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:1707
dnnl_inner_product_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1616
dnnl_deconvolution
@ dnnl_deconvolution
A deconvolution primitive.
Definition: dnnl_types.h:823
dnnl_aBcde4b
@ dnnl_aBcde4b
5D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:315
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:1555
dnnl_stream_out_of_order
@ dnnl_stream_out_of_order
Out-of-order execution.
Definition: dnnl_types.h:2301
dnnl_gemm
@ dnnl_gemm
A matrix multiplication primitive (internal).
Definition: dnnl_types.h:841
dnnl_convolution
@ dnnl_convolution
A convolution primitive.
Definition: dnnl_types.h:821
dnnl_primitive_t
struct dnnl_primitive * dnnl_primitive_t
A primitive handle.
Definition: dnnl_types.h:1987
dnnl_lrn_desc_t::data_desc
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1519
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:1950
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:1690
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:1634
dnnl_lrn
@ dnnl_lrn
An LRN primitive.
Definition: dnnl_types.h:831
dnnl_query_src_md
@ dnnl_query_src_md
source memory desc
Definition: dnnl_types.h:2275
dnnl_query_pooling_v2_d
@ dnnl_query_pooling_v2_d
pooling version 2 descriptor
Definition: dnnl_types.h:2270
dnnl_logsoftmax_desc_t
dnnl_softmax_desc_t dnnl_logsoftmax_desc_t
A descriptor of a LogSoftmax operation.
Definition: dnnl_types.h:1427
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:1137
dnnl_scratchpad_mode_t
dnnl_scratchpad_mode_t
Scratchpad mode.
Definition: dnnl_types.h:1913
dnnl_memory_desc_t::wino_desc
dnnl_wino_desc_t wino_desc
Tensor of weights for integer 8bit winograd convolution.
Definition: dnnl_types.h:1228
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:546
dnnl_query_engine
@ dnnl_query_engine
execution engine
Definition: dnnl_types.h:2229
dnnl_wino_memory_format_t
dnnl_wino_memory_format_t
Winograd-specific formats.
Definition: dnnl_types.h:1103
dnnl_query_softmax_d
@ dnnl_query_softmax_d
softmax descriptor
Definition: dnnl_types.h:2258
dnnl_resampling_desc_t
A descriptor of resampling operation.
Definition: dnnl_types.h:1795
dnnl_batch_normalization_desc_t::batch_norm_epsilon
float batch_norm_epsilon
Batch normalization epsilon parameter.
Definition: dnnl_types.h:1562
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:919
dnnl_cpu
@ dnnl_cpu
CPU engine.
Definition: dnnl_types.h:1863
dnnl_post_ops
An opaque structure for a chain of post operations.
dnnl_query_undef
@ dnnl_query_undef
no query
Definition: dnnl_types.h:2227
dnnl_eltwise_swish
@ dnnl_eltwise_swish
Eltwise: swish.
Definition: dnnl_types.h:903
dnnl_ndhwc
@ dnnl_ndhwc
5D CNN activations tensor, an alias to dnnl_acdeb
Definition: dnnl_types.h:454
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:1717
dnnl_abcdefhg
@ dnnl_abcdefhg
permuted 8D tensor
Definition: dnnl_types.h:216
dnnl_convolution_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1280
dnnl_reduction_desc_t::alg_kind
dnnl_alg_kind_t alg_kind
The kind of reduction algorithm.
Definition: dnnl_types.h:1832
dnnl_pooling_desc_t::kernel
dnnl_dims_t kernel
Pooling kernel spatial dimensions.
Definition: dnnl_types.h:1458
dnnl_wino_wei_OBaaIBOIio
@ dnnl_wino_wei_OBaaIBOIio
Internal weights format for 4x3 Winograd.
Definition: dnnl_types.h:1111
dnnl_binary_div
@ dnnl_binary_div
Binary div.
Definition: dnnl_types.h:961
dnnl_inner_product_desc_t::weights_desc
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1622
dnnl_shuffle_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1333
dnnl_resampling_desc_t::diff_src_desc
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1808
dnnl_eltwise_gelu_erf
@ dnnl_eltwise_gelu_erf
Eltwise: erf-based gelu.
Definition: dnnl_types.h:911
dnnl_convolution_desc_t::bias_desc
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1297
dnnl_layer_normalization_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1578
dnnl_batch_normalization_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1542
dnnl_memory_desc_t
Memory descriptor.
Definition: dnnl_types.h:1188
dnnl_binary_desc_t::dst_desc
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1758
dnnl_backward_bias
@ dnnl_backward_bias
Backward bias propagation.
Definition: dnnl_types.h:804
dnnl_op_desc_t
void * dnnl_op_desc_t
A pointer to any of the operation descriptors.
Definition: dnnl_types.h:1263
dnnl_inner_product_desc_t::diff_src_desc
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1620
dnnl_ncw
@ dnnl_ncw
3D CNN activations tensor, an alias to dnnl_abc
Definition: dnnl_types.h:442
dnnl_matmul
@ dnnl_matmul
A matrix multiplication primitive.
Definition: dnnl_types.h:847
dnnl_version_t::patch
int patch
Patch version.
Definition: dnnl_types.h:2348
dnnl_cpu_isa_t
dnnl_cpu_isa_t
CPU instruction set flags.
Definition: dnnl_types.h:2375
dnnl_query_some_md
@ dnnl_query_some_md
stub
Definition: dnnl_types.h:2274
const_dnnl_memory_t
const struct dnnl_memory * const_dnnl_memory_t
A constant memory handle.
Definition: dnnl_types.h:1245
dnnl_matmul_desc_t::src_desc
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1778
dnnl_nChw4c
@ dnnl_nChw4c
4D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcd4b
Definition: dnnl_types.h:564
dnnl_memory_extra_desc_t::flags
uint64_t flags
The flags contain arbitrary extra information, such as compensation.
Definition: dnnl_types.h:1173
dnnl_inner_product_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1612
dnnl_softmax_desc_t::diff_desc
dnnl_memory_desc_t diff_desc
Source and Destination of gradient memory descriptor.
Definition: dnnl_types.h:1415
dnnl_oi
@ dnnl_oi
2D CNN weights tensor, an alias to dnnl_ab
Definition: dnnl_types.h:457
dnnl_eltwise_desc_t::diff_data_desc
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1375
dnnl_ohwi
@ dnnl_ohwi
4D CNN weights tensor, an alias to dnnl_acdb
Definition: dnnl_types.h:473
dnnl_bacd
@ dnnl_bacd
permuted 4D tensor
Definition: dnnl_types.h:202
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:507
dnnl_nChw16c
@ dnnl_nChw16c
4D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcd16b
Definition: dnnl_types.h:561
dnnl_shuffle_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1336
dnnl_query_eltwise_d
@ dnnl_query_eltwise_d
eltwise descriptor
Definition: dnnl_types.h:2257
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:1947
dnnl_binary_max
@ dnnl_binary_max
Binary max.
Definition: dnnl_types.h:957
dnnl_cba
@ dnnl_cba
permuted 3D tensor
Definition: dnnl_types.h:207
dnnl_reduction_desc_t
A descriptor of reduction operation.
Definition: dnnl_types.h:1823
dnnl_query_num_of_inputs_s32
@ dnnl_query_num_of_inputs_s32
number of inputs expected
Definition: dnnl_types.h:2232
dnnl_resampling_desc_t::diff_dst_desc
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1812
dnnl_acbde
@ dnnl_acbde
permuted 5D tensor
Definition: dnnl_types.h:196
dnnl_dcab
@ dnnl_dcab
permuted 4D tensor
Definition: dnnl_types.h:209
dnnl_reduction_desc_t::dst_desc
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1836
dnnl_alg_kind_t
dnnl_alg_kind_t
Kinds of algorithms.
Definition: dnnl_types.h:861
dnnl_deconvolution_winograd
@ dnnl_deconvolution_winograd
Winograd deconvolution.
Definition: dnnl_types.h:872
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:1265
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:2390
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:1215
dnnl_ldgoi
@ dnnl_ldgoi
5D RNN weights tensor in the format (num_layers, num_directions, num_gates, output_channels,...
Definition: dnnl_types.h:526
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:1211
dnnl_eltwise_exp
@ dnnl_eltwise_exp
Eltwise: exponent.
Definition: dnnl_types.h:894
dnnl_abcdef
@ dnnl_abcdef
plain 6D tensor
Definition: dnnl_types.h:183
dnnl_aBCdef2b4c2b
@ dnnl_aBCdef2b4c2b
6D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:362
dnnl_pooling_v2_desc_t::diff_dst_desc
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1487
dnnl_binary_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1750
dnnl_goihw
@ dnnl_goihw
5D CNN weights tensor (incl. groups), an alias to dnnl_abcde
Definition: dnnl_types.h:494
dnnl_bidirectional_sum
@ dnnl_bidirectional_sum
Bidirectional execution of RNN primitive with summation of the results.
Definition: dnnl_types.h:1659
dnnl_eltwise_desc_t::alpha
float alpha
Algorithm specific parameter.
Definition: dnnl_types.h:1396
dnnl_eltwise_linear
@ dnnl_eltwise_linear
Eltwise: linear.
Definition: dnnl_types.h:886
dnnl_nCw16c
@ dnnl_nCw16c
3D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBc16b
Definition: dnnl_types.h:573
dnnl_vanilla_gru
@ dnnl_vanilla_gru
GRU cell.
Definition: dnnl_types.h:943
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:1694
dnnl_convolution_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1284
dnnl_binary_desc_t::alg_kind
dnnl_alg_kind_t alg_kind
The kind of the binary algorithm.
Definition: dnnl_types.h:1754
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:570
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:1099
dnnl_wigo
@ dnnl_wigo
4D CNN weights tensor (incl. groups), an alias to dnnl_dcab
Definition: dnnl_types.h:492
dnnl_binary_desc_t
A descriptor of a binary operation.
Definition: dnnl_types.h:1747
dnnl_matmul_desc_t::weights_desc
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1780
dnnl_memory_extra_desc_t::compensation_mask
int compensation_mask
Compensation mask.
Definition: dnnl_types.h:1175
dnnl_memory_extra_flags_t
dnnl_memory_extra_flags_t
Flags for memory special features.
Definition: dnnl_types.h:1154
dnnl_pooling_v2_desc_t::alg_kind
dnnl_alg_kind_t alg_kind
The kind of pooling algorithm.
Definition: dnnl_types.h:1479
dnnl_convolution_direct
@ dnnl_convolution_direct
Direct convolution.
Definition: dnnl_types.h:864
dnnl_version_t::gpu_runtime
unsigned gpu_runtime
GPU runtime.
Definition: dnnl_types.h:2351
dnnl_lrn_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1511
dnnl_reduction_min
@ dnnl_reduction_min
Reduction using min.
Definition: dnnl_types.h:969
dnnl_pooling_desc_t::diff_dst_desc
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1454
dnnl_query_diff_src_md
@ dnnl_query_diff_src_md
source gradient memory desc
Definition: dnnl_types.h:2276
dnnl_abcdefgih
@ dnnl_abcdefgih
permuted 9D tensor
Definition: dnnl_types.h:217
dnnl_resampling_desc_t::src_desc
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1806
dnnl_wio
@ dnnl_wio
3D CNN weights tensor, an alias to dnnl_cba
Definition: dnnl_types.h:465
dnnl_pooling_v2_desc_t
A descriptor of a pooling (version 2) operation.
Definition: dnnl_types.h:1468
dnnl_nChw32c
@ dnnl_nChw32c
4D CNN activations tensor blocked by channels with block size 32, an alias to dnnl_aBcd32b
Definition: dnnl_types.h:558
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:1705
dnnl_inner_product_desc_t::diff_dst_desc
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1632
dnnl_forward_scoring
@ dnnl_forward_scoring
Forward data propagation (alias for dnnl_forward_inference).
Definition: dnnl_types.h:794
dnnl_aBcde8b
@ dnnl_aBcde8b
5D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:330
dnnl_prop_kind_undef
@ dnnl_prop_kind_undef
Undefined propagation type.
Definition: dnnl_types.h:785
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:1671
dnnl_query_primitive_kind
@ dnnl_query_primitive_kind
primitive kind
Definition: dnnl_types.h:2230
dnnl_unidirectional_left2right
@ dnnl_unidirectional_left2right
Unidirectional execution of RNN primitive from left to right.
Definition: dnnl_types.h:1651
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:1713
dnnl_iohw
@ dnnl_iohw
4D CNN weights tensor, an alias to dnnl_bacd
Definition: dnnl_types.h:477
dnnl_eltwise_elu
@ dnnl_eltwise_elu
Eltwise: exponential linear unit (elu)
Definition: dnnl_types.h:878
dnnl_eltwise_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1355
dnnl_odhwi
@ dnnl_odhwi
5D CNN weights tensor, an alias to dnnl_acdeb
Definition: dnnl_types.h:485
dnnl_reduction
@ dnnl_reduction
A reduction primitive.
Definition: dnnl_types.h:853
dnnl_nwc
@ dnnl_nwc
3D CNN activations tensor, an alias to dnnl_acb
Definition: dnnl_types.h:444
dnnl_nCw4c
@ dnnl_nCw4c
3D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBc4b
Definition: dnnl_types.h:576
dnnl_aBcde32b
@ dnnl_aBcde32b
5D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:313
dnnl_reduction_desc_t::primitive_kind
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1826
dnnl_vanilla_lstm
@ dnnl_vanilla_lstm
LSTM cell.
Definition: dnnl_types.h:941
dnnl_any_engine
@ dnnl_any_engine
An unspecified engine.
Definition: dnnl_types.h:1861
dnnl_nCdhw4c
@ dnnl_nCdhw4c
5D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcde4b
Definition: dnnl_types.h:552
dnnl_resampling
@ dnnl_resampling
A resampling primitive.
Definition: dnnl_types.h:849
dnnl_wino_wei_aaOBiOo
@ dnnl_wino_wei_aaOBiOo
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:1109
dnnl_cpu_isa_avx
@ dnnl_cpu_isa_avx
Intel Advanced Vector Extensions (Intel AVX)
Definition: dnnl_types.h:2383
dnnl_bca
@ dnnl_bca
permuted 3D tensor
Definition: dnnl_types.h:204
dnnl_reduction_norm_lp_max
@ dnnl_reduction_norm_lp_max
Reduction using lp norm.
Definition: dnnl_types.h:977
dnnl_prop_kind_t
dnnl_prop_kind_t
Kinds of propagation.
Definition: dnnl_types.h:782
dnnl_query_scratchpad_md
@ dnnl_query_scratchpad_md
scratchpad memory desc
Definition: dnnl_types.h:2282
dnnl_lrn_desc_t::lrn_k
float lrn_k
LRN k parameter.
Definition: dnnl_types.h:1530
dnnl_nchw
@ dnnl_nchw
4D CNN activations tensor, an alias to dnnl_abcd
Definition: dnnl_types.h:446
dnnl_resampling_desc_t::prop_kind
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1801
dnnl_eltwise_gelu
@ dnnl_eltwise_gelu
Eltwise: tanh-based gelu (alias for dnnl_eltwise_gelu_tanh)
Definition: dnnl_types.h:901
dnnl_lrn_desc_t::alg_kind
dnnl_alg_kind_t alg_kind
LRN algorithm.
Definition: dnnl_types.h:1517
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:1524
dnnl_query_weights_md
@ dnnl_query_weights_md
weights memory descriptor desc
Definition: dnnl_types.h:2277
dnnl_memory_extra_desc_t
Description of extra information stored in memory.
Definition: dnnl_types.h:1170
dnnl_inner_product_desc_t::diff_bias_desc
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1628
dnnl_resampling_desc_t::alg_kind
dnnl_alg_kind_t alg_kind
The kind of the resampling algorithm.
Definition: dnnl_types.h:1804
dnnl_pooling_desc_t::diff_src_desc
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1450
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:1339
dnnl_query_batch_normalization_d
@ dnnl_query_batch_normalization_d
batch normalization descriptor
Definition: dnnl_types.h:2261
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:917
dnnl_pooling_desc_t::strides
dnnl_dims_t strides
Pooling kernel strides for spatial dimensions.
Definition: dnnl_types.h:1456
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:1692
dnnl_convolution_desc_t::accum_data_type
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1313
dnnl_chwn
@ dnnl_chwn
4D CNN activations tensor, an alias to dnnl_bcda
Definition: dnnl_types.h:450
dnnl_rnn_desc_t::cell_kind
dnnl_alg_kind_t cell_kind
RNN cell kind.
Definition: dnnl_types.h:1674
dnnl_undefined_primitive
@ dnnl_undefined_primitive
Undefined primitive.
Definition: dnnl_types.h:811
dnnl_eltwise_soft_relu
@ dnnl_eltwise_soft_relu
Eltwise: soft_relu.
Definition: dnnl_types.h:890
dnnl_abcdefghikj
@ dnnl_abcdefghikj
permuted 11D tensor
Definition: dnnl_types.h:219
dnnl_nt
@ dnnl_nt
2D RNN statistics tensor, an alias to dnnl_ba
Definition: dnnl_types.h:440
dnnl_deconvolution_desc_t
dnnl_convolution_desc_t dnnl_deconvolution_desc_t
A descriptor of a deconvolution operation.
Definition: dnnl_types.h:1322
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:1219
dnnl_unidirectional_right2left
@ dnnl_unidirectional_right2left
Unidirectional execution of RNN primitive from right to left.
Definition: dnnl_types.h:1653
dnnl_aBcd8b
@ dnnl_aBcd8b
4D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:282
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:1230
dnnl_query_scratchpad_engine
@ dnnl_query_scratchpad_engine
(scratch) memory, additional to all inputs and outputs memory (bytes)
Definition: dnnl_types.h:2241
dnnl_pooling_v2
@ dnnl_pooling_v2
A pooling version 2 primitive (pooling with dilation support).
Definition: dnnl_types.h:851
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:502
dnnl_query_exec_arg_md
@ dnnl_query_exec_arg_md
memory desc of an execute argument
Definition: dnnl_types.h:2283
dnnl_query_some_d
@ dnnl_query_some_d
stub
Definition: dnnl_types.h:2252
dnnl_pooling_avg_exclude_padding
@ dnnl_pooling_avg_exclude_padding
Average pooling exclude padding.
Definition: dnnl_types.h:931
dnnl_binary_add
@ dnnl_binary_add
Binary add.
Definition: dnnl_types.h:953