20 #ifndef ONEAPI_DNNL_DNNL_TYPES_H 21 #define ONEAPI_DNNL_DNNL_TYPES_H 668 dnnl_ldOI32o4i = dnnl_abDC32d4c,
671 dnnl_ldgOI32o2i = dnnl_abdEC32e2c,
672 dnnl_ldgOI32o4i = dnnl_abdEC32e4c,
713 dnnl_NCw16n16c = dnnl_ABc16a16b,
714 dnnl_NCdhw16n16c = dnnl_ABcde16a16b,
715 dnnl_NChw16n16c = dnnl_ABcd16a16b,
716 dnnl_NCw32n32c = dnnl_ABc32a32b,
717 dnnl_NChw32n32c = dnnl_ABcd32a32b,
718 dnnl_NCdhw32n32c = dnnl_ABcde32a32b,
721 dnnl_OI16i16o = dnnl_AB16b16a,
722 dnnl_OI16i32o = dnnl_AB16b32a,
723 dnnl_OI16i64o = dnnl_AB16b64a,
724 dnnl_OI8i16o2i = dnnl_AB8b16a2b,
725 dnnl_OI8i32o2i = dnnl_AB8b32a2b,
726 dnnl_OI8i64o2i = dnnl_AB8b64a2b,
727 dnnl_OI4i16o4i = dnnl_AB4b16a4b,
728 dnnl_OI4i32o4i = dnnl_AB4b32a4b,
729 dnnl_OI4i64o4i = dnnl_AB4b64a4b,
730 dnnl_OI16i16o4i = dnnl_AB16b16a4b,
732 dnnl_IOw16o16i = dnnl_BAc16a16b,
733 dnnl_IOw16i16o = dnnl_BAc16b16a,
734 dnnl_OIw16i16o = dnnl_ABc16b16a,
735 dnnl_OIw16i32o = dnnl_ABc16b32a,
736 dnnl_OIw16i64o = dnnl_ABc16b64a,
737 dnnl_OIw16o16i = dnnl_ABc16a16b,
738 dnnl_Oiw16o = dnnl_Abc16a,
739 dnnl_OIw4i16o4i = dnnl_ABc4b16a4b,
740 dnnl_OIw4i32o4i = dnnl_ABc4b32a4b,
741 dnnl_OIw4i64o4i = dnnl_ABc4b64a4b,
742 dnnl_OIw2i8o4i = dnnl_ABc2b8a4b,
743 dnnl_OIw16i16o4i = dnnl_ABc16b16a4b,
744 dnnl_OIw16i16o2i = dnnl_ABc16b16a2b,
745 dnnl_OIw16o16i2o = dnnl_ABc16a16b2a,
746 dnnl_OIw4i4o = dnnl_ABc4b4a,
747 dnnl_OIw4o4i = dnnl_ABc4a4b,
748 dnnl_Oiw4o = dnnl_Abc4a,
749 dnnl_OIw8i16o2i = dnnl_ABc8b16a2b,
750 dnnl_OIw8i32o2i = dnnl_ABc8b32a2b,
751 dnnl_OIw8i64o2i = dnnl_ABc8b64a2b,
752 dnnl_OIw8i8o = dnnl_ABc8b8a,
753 dnnl_OIw8o16i2o = dnnl_ABc8a16b2a,
754 dnnl_IOw8o16i2o = dnnl_BAc8a16b2a,
755 dnnl_OIw8o8i = dnnl_ABc8a8b,
756 dnnl_OIw8o4i = dnnl_ABc8a4b,
757 dnnl_Owi16o = dnnl_Acb16a,
758 dnnl_OwI16o2i = dnnl_AcB16a2b,
759 dnnl_OwI16o4i = dnnl_AcB16a4b,
760 dnnl_Owi4o = dnnl_Acb4a,
761 dnnl_Owi8o = dnnl_Acb8a,
764 dnnl_IOhw16i16o = dnnl_BAcd16b16a,
765 dnnl_IOhw16o16i = dnnl_BAcd16a16b,
766 dnnl_Ohwi16o = dnnl_Acdb16a,
767 dnnl_OhwI16o2i = dnnl_AcdB16a2b,
768 dnnl_OhwI16o4i = dnnl_AcdB16a4b,
769 dnnl_Ohwi32o = dnnl_Acdb32a,
770 dnnl_Ohwi4o = dnnl_Acdb4a,
771 dnnl_Ohwi8o = dnnl_Acdb8a,
772 dnnl_OIhw16i16o = dnnl_ABcd16b16a,
773 dnnl_OIhw16i32o = dnnl_ABcd16b32a,
774 dnnl_OIhw16i64o = dnnl_ABcd16b64a,
775 dnnl_OIhw16o16i = dnnl_ABcd16a16b,
776 dnnl_Oihw16o = dnnl_Abcd16a,
777 dnnl_OIhw4i16o4i = dnnl_ABcd4b16a4b,
778 dnnl_OIhw4i32o4i = dnnl_ABcd4b32a4b,
779 dnnl_OIhw4i64o4i = dnnl_ABcd4b64a4b,
780 dnnl_OIhw16i16o4i = dnnl_ABcd16b16a4b,
781 dnnl_OIhw16i16o2i = dnnl_ABcd16b16a2b,
782 dnnl_OIhw16o16i2o = dnnl_ABcd16a16b2a,
783 dnnl_OIhw4i4o = dnnl_ABcd4b4a,
784 dnnl_OIhw4o4i = dnnl_ABcd4a4b,
785 dnnl_Oihw4o = dnnl_Abcd4a,
786 dnnl_OIhw8i16o2i = dnnl_ABcd8b16a2b,
787 dnnl_OIhw8i32o2i = dnnl_ABcd8b32a2b,
788 dnnl_OIhw8i64o2i = dnnl_ABcd8b64a2b,
790 dnnl_OIhw8o16i2o = dnnl_ABcd8a16b2a,
791 dnnl_OIhw2i8o4i = dnnl_ABcd2b8a4b,
792 dnnl_IOhw8o16i2o = dnnl_BAcd8a16b2a,
793 dnnl_OIhw8o8i = dnnl_ABcd8a8b,
794 dnnl_OIhw8o4i = dnnl_ABcd8a4b,
795 dnnl_Owhi16o = dnnl_Adcb16a,
798 dnnl_Odhwi16o = dnnl_Acdeb16a,
799 dnnl_OdhwI16o2i = dnnl_AcdeB16a2b,
800 dnnl_OdhwI16o4i = dnnl_AcdeB16a4b,
801 dnnl_Odhwi4o = dnnl_Acdeb4a,
802 dnnl_Odhwi8o = dnnl_Acdeb8a,
803 dnnl_OIdhw16i16o = dnnl_ABcde16b16a,
804 dnnl_OIdhw16i32o = dnnl_ABcde16b32a,
805 dnnl_OIdhw16i64o = dnnl_ABcde16b64a,
806 dnnl_OIdhw16o16i = dnnl_ABcde16a16b,
807 dnnl_Oidhw16o = dnnl_Abcde16a,
808 dnnl_OIdhw4i4o = dnnl_ABcde4b4a,
809 dnnl_OIdhw4o4i = dnnl_ABcde4a4b,
810 dnnl_Oidhw4o = dnnl_Abcde4a,
811 dnnl_OIdhw8i16o2i = dnnl_ABcde8b16a2b,
812 dnnl_OIdhw8i32o2i = dnnl_ABcde8b32a2b,
813 dnnl_OIdhw8i64o2i = dnnl_ABcde8b64a2b,
814 dnnl_OIdhw8i8o = dnnl_ABcde8b8a,
815 dnnl_OIdhw8o16i2o = dnnl_ABcde8a16b2a,
816 dnnl_IOdhw8o16i2o = dnnl_BAcde8a16b2a,
818 dnnl_OIdhw4i32o4i = dnnl_ABcde4b32a4b,
819 dnnl_OIdhw4i64o4i = dnnl_ABcde4b64a4b,
820 dnnl_OIdhw16i16o4i = dnnl_ABcde16b16a4b,
821 dnnl_OIdhw16i16o2i = dnnl_ABcde16b16a2b,
823 dnnl_OIdhw8o8i = dnnl_ABcde8a8b,
824 dnnl_OIdhw8o4i = dnnl_ABcde8a4b,
825 dnnl_IOdhw16i16o = dnnl_BAcde16b16a,
826 dnnl_OIdhw4o8i8o4i = dnnl_ABcde4a8b8a4b,
827 dnnl_IOdhw16o16i = dnnl_BAcde16a16b,
830 dnnl_Goiw16g = dnnl_Abcd16a,
831 dnnl_Goiw8g = dnnl_Abcd8a,
832 dnnl_Goiw4g = dnnl_Abcd4a,
833 dnnl_gIOw16o16i = dnnl_aCBd16b16c,
834 dnnl_gIOw16i16o = dnnl_aCBd16c16b,
835 dnnl_gOIw16i16o = dnnl_aBCd16c16b,
836 dnnl_gOIw16o16i = dnnl_aBCd16b16c,
838 dnnl_gOIw4i16o4i = dnnl_aBCd4c16b4c,
839 dnnl_gOIw2i8o4i = dnnl_aBCd2c8b4c,
840 dnnl_gOIw16i16o4i = dnnl_aBCd16c16b4c,
841 dnnl_gOIw16i16o2i = dnnl_aBCd16c16b2c,
842 dnnl_gOIw16o16i2o = dnnl_aBCd16b16c2b,
843 dnnl_gOIw4i4o = dnnl_aBCd4c4b,
844 dnnl_gOIw4o4i = dnnl_aBCd4b4c,
846 dnnl_gOIw8i16o2i = dnnl_aBCd8c16b2c,
847 dnnl_gOIw8i8o = dnnl_aBCd8c8b,
848 dnnl_gOIw8o16i2o = dnnl_aBCd8b16c2b,
849 dnnl_gIOw8o16i2o = dnnl_aCBd8b16c2b,
850 dnnl_gOIw8o8i = dnnl_aBCd8b8c,
851 dnnl_gOIw8o4i = dnnl_aBCd8b4c,
852 dnnl_gOwi16o = dnnl_aBdc16b,
853 dnnl_gOwI16o2i = dnnl_aBdC16b2c,
854 dnnl_gOwI16o4i = dnnl_aBdC16b4c,
855 dnnl_gOwi4o = dnnl_aBdc4b,
856 dnnl_gOwi8o = dnnl_aBdc8b,
857 dnnl_Goiw32g = dnnl_Abcd32a,
858 dnnl_gOIw2i4o2i = dnnl_aBCd2c4b2c,
860 dnnl_gOIw4i8o2i = dnnl_aBCd4c8b2c,
861 dnnl_gOIw4o8i2o = dnnl_aBCd4b8c2b,
864 dnnl_gIOhw16i16o = dnnl_aCBde16c16b,
865 dnnl_gIOhw16o16i = dnnl_aCBde16b16c,
866 dnnl_gOhwi16o = dnnl_aBdec16b,
867 dnnl_gOhwI16o2i = dnnl_aBdeC16b2c,
868 dnnl_gOhwI16o4i = dnnl_aBdeC16b4c,
869 dnnl_gOhwi32o = dnnl_aBdec32b,
870 dnnl_gOhwi4o = dnnl_aBdec4b,
871 dnnl_gOhwi8o = dnnl_aBdec8b,
872 dnnl_Goihw16g = dnnl_Abcde16a,
873 dnnl_gOIhw16i16o = dnnl_aBCde16c16b,
874 dnnl_gOIhw16o16i = dnnl_aBCde16b16c,
876 dnnl_gOIhw2i8o4i = dnnl_aBCde2c8b4c,
877 dnnl_gOIhw4i16o4i = dnnl_aBCde4c16b4c,
878 dnnl_gOIhw16i16o4i = dnnl_aBCde16c16b4c,
879 dnnl_gOIhw16i16o2i = dnnl_aBCde16c16b2c,
880 dnnl_gOIhw16o16i2o = dnnl_aBCde16b16c2b,
881 dnnl_gOIhw4i4o = dnnl_aBCde4c4b,
882 dnnl_gOIhw4o4i = dnnl_aBCde4b4c,
884 dnnl_Goihw8g = dnnl_Abcde8a,
885 dnnl_Goihw4g = dnnl_Abcde4a,
886 dnnl_gOIhw8i16o2i = dnnl_aBCde8c16b2c,
887 dnnl_gOIhw8i8o = dnnl_aBCde8c8b,
888 dnnl_gOIhw8o16i2o = dnnl_aBCde8b16c2b,
889 dnnl_gIOhw8o16i2o = dnnl_aCBde8b16c2b,
890 dnnl_gOIhw8o8i = dnnl_aBCde8b8c,
891 dnnl_gOIhw8o4i = dnnl_aBCde8b4c,
892 dnnl_Goihw32g = dnnl_Abcde32a,
893 dnnl_gOwhi16o = dnnl_aBedc16b,
895 dnnl_OIw4o8i8o4i = dnnl_ABc4a8b8a4b,
896 dnnl_OIhw4o8i8o4i = dnnl_ABcd4a8b8a4b,
897 dnnl_IOw4i8o8i4o = dnnl_BAc4b8a8b4a,
898 dnnl_IOhw4i8o8i4o = dnnl_BAcd4b8a8b4a,
899 dnnl_IOdhw4i8o8i4o = dnnl_BAcde4b8a8b4a,
901 dnnl_OIhw2o8i8o2i = dnnl_ABcd2a8b8a2b,
902 dnnl_gOIw4o8i8o4i = dnnl_aBCd4b8c8b4c,
903 dnnl_gOIhw4o8i8o4i = dnnl_aBCde4b8c8b4c,
904 dnnl_gOIdhw4o8i8o4i = dnnl_aBCdef4b8c8b4c,
905 dnnl_gIOw4i8o8i4o = dnnl_aCBd4c8b8c4b,
906 dnnl_gIOhw4i8o8i4o = dnnl_aCBde4c8b8c4b,
907 dnnl_gIOdhw4i8o8i4o = dnnl_aCBdef4c8b8c4b,
908 dnnl_gOIhw2o8i8o2i = dnnl_aBCde2b8c8b2c,
909 dnnl_gOIhw2i4o2i = dnnl_aBCde2c4b2c,
911 dnnl_gOIhw4i8o2i = dnnl_aBCde4c8b2c,
912 dnnl_gOIhw4o8i2o = dnnl_aBCde4b8c2b,
915 dnnl_gIOdhw16i16o = dnnl_aCBdef16c16b,
916 dnnl_gIOdhw16o16i = dnnl_aCBdef16b16c,
917 dnnl_gOdhwi16o = dnnl_aBdefc16b,
918 dnnl_gOdhwI16o2i = dnnl_aBdefC16b2c,
919 dnnl_gOdhwI16o4i = dnnl_aBdefC16b4c,
920 dnnl_gOdhwi4o = dnnl_aBdefc4b,
921 dnnl_gOdhwi8o = dnnl_aBdefc8b,
922 dnnl_gOIdhw16i16o = dnnl_aBCdef16c16b,
923 dnnl_gOIdhw4i16o4i = dnnl_aBCdef4c16b4c,
924 dnnl_gOIdhw16i16o4i = dnnl_aBCdef16c16b4c,
926 dnnl_gOIdhw16i16o2i = dnnl_aBCdef16c16b2c,
927 dnnl_gOIdhw16o16i = dnnl_aBCdef16b16c,
929 dnnl_gOIdhw4i4o = dnnl_aBCdef4c4b,
930 dnnl_gOIdhw4o4i = dnnl_aBCdef4b4c,
932 dnnl_gOIdhw8i16o2i = dnnl_aBCdef8c16b2c,
933 dnnl_gOIdhw8i8o = dnnl_aBCdef8c8b,
934 dnnl_gOIdhw8o16i2o = dnnl_aBCdef8b16c2b,
935 dnnl_gIOdhw8o16i2o = dnnl_aCBdef8b16c2b,
936 dnnl_gOIdhw8o8i = dnnl_aBCdef8b8c,
937 dnnl_gOIdhw8o4i = dnnl_aBCdef8b4c,
938 dnnl_Goidhw16g = dnnl_Abcdef16a,
939 dnnl_Goidhw32g = dnnl_Abcdef32a,
940 dnnl_gOIdhw2i4o2i = dnnl_aBCdef2c4b2c,
941 dnnl_gOIdhw4i8o2i = dnnl_aBCdef4c8b2c,
943 dnnl_gOIdhw4o8i2o = dnnl_aBCdef4b8c2b,
945 dnnl_Owi32o = dnnl_Acb32a,
946 dnnl_OwI32o2i = dnnl_AcB32a2b,
947 dnnl_OwI32o4i = dnnl_AcB32a4b,
948 dnnl_Owi48o = dnnl_Acb48a,
949 dnnl_OwI48o2i = dnnl_AcB48a2b,
950 dnnl_OwI48o4i = dnnl_AcB48a4b,
951 dnnl_Owi64o = dnnl_Acb64a,
952 dnnl_OwI64o2i = dnnl_AcB64a2b,
953 dnnl_OwI64o4i = dnnl_AcB64a4b,
954 dnnl_wIo2i = dnnl_cBa2b,
955 dnnl_wIo4i = dnnl_cBa4b,
956 dnnl_gOwi32o = dnnl_aBdc32b,
957 dnnl_gOwI32o2i = dnnl_aBdC32b2c,
958 dnnl_gOwI32o4i = dnnl_aBdC32b4c,
959 dnnl_gOwi48o = dnnl_aBdc48b,
960 dnnl_gOwI48o2i = dnnl_aBdC48b2c,
961 dnnl_gOwI48o4i = dnnl_aBdC48b4c,
962 dnnl_gOwi64o = dnnl_aBdc64b,
963 dnnl_gOwI64o2i = dnnl_aBdC64b2c,
964 dnnl_gOwI64o4i = dnnl_aBdC64b4c,
965 dnnl_gwio = dnnl_adcb,
966 dnnl_gwIo2i = dnnl_adCb2c,
967 dnnl_gwIo4i = dnnl_adCb4c,
969 dnnl_OhwI32o = dnnl_Acdb32a,
970 dnnl_OhwI32o2i = dnnl_AcdB32a2b,
971 dnnl_OhwI32o4i = dnnl_AcdB32a4b,
972 dnnl_Ohwi48o = dnnl_Acdb48a,
973 dnnl_OhwI48o2i = dnnl_AcdB48a2b,
974 dnnl_OhwI48o4i = dnnl_AcdB48a4b,
975 dnnl_Ohwi64o = dnnl_Acdb64a,
976 dnnl_OhwI64o2i = dnnl_AcdB64a2b,
977 dnnl_OhwI64o4i = dnnl_AcdB64a4b,
978 dnnl_hwIo2i = dnnl_cdBa2b,
979 dnnl_hwIo4i = dnnl_cdBa4b,
980 dnnl_gOhwI32o = dnnl_aBdec32b,
981 dnnl_gOhwI32o2i = dnnl_aBdeC32b2c,
982 dnnl_gOhwI32o4i = dnnl_aBdeC32b4c,
983 dnnl_gOhwi48o = dnnl_aBdec48b,
984 dnnl_gOhwI48o2i = dnnl_aBdeC48b2c,
985 dnnl_gOhwI48o4i = dnnl_aBdeC48b4c,
986 dnnl_gOhwi64o = dnnl_aBdec64b,
987 dnnl_gOhwI64o2i = dnnl_aBdeC64b2c,
988 dnnl_gOhwI64o4i = dnnl_aBdeC64b4c,
989 dnnl_ghwio = dnnl_adecb,
990 dnnl_ghwIo2i = dnnl_adeCb2c,
991 dnnl_ghwIo4i = dnnl_adeCb4c,
993 dnnl_Odhwi32o = dnnl_Acdeb32a,
994 dnnl_OdhwI32o2i = dnnl_AcdeB32a2b,
995 dnnl_OdhwI32o4i = dnnl_AcdeB32a4b,
996 dnnl_Odhwi48o = dnnl_Acdeb48a,
997 dnnl_OdhwI48o2i = dnnl_AcdeB48a2b,
998 dnnl_OdhwI48o4i = dnnl_AcdeB48a4b,
999 dnnl_Odhwi64o = dnnl_Acdeb64a,
1000 dnnl_OdhwI64o2i = dnnl_AcdeB64a2b,
1001 dnnl_OdhwI64o4i = dnnl_AcdeB64a4b,
1002 dnnl_dhwIo2i = dnnl_cdeBa2b,
1003 dnnl_dhwIo4i = dnnl_cdeBa4b,
1004 dnnl_gOdhwi32o = dnnl_aBdefc32b,
1005 dnnl_gOdhwI32o2i = dnnl_aBdefC32b2c,
1006 dnnl_gOdhwI32o4i = dnnl_aBdefC32b4c,
1007 dnnl_gOdhwi48o = dnnl_aBdefc48b,
1008 dnnl_gOdhwI48o2i = dnnl_aBdefC48b2c,
1009 dnnl_gOdhwI48o4i = dnnl_aBdefC48b4c,
1010 dnnl_gOdhwi64o = dnnl_aBdefc64b,
1011 dnnl_gOdhwI64o2i = dnnl_aBdefC64b2c,
1012 dnnl_gOdhwI64o4i = dnnl_aBdefC64b4c,
1013 dnnl_gdhwio = dnnl_adefcb,
1014 dnnl_gdhwIo2i = dnnl_adefCb2c,
1015 dnnl_gdhwIo4i = dnnl_adefCb4c,
1108 dnnl_alg_kind_undef,
1301 #define DNNL_MAX_NDIMS 12 1305 #define DNNL_RUNTIME_DIM_VAL INT64_MIN 1310 #define DNNL_RUNTIME_SIZE_VAL ((size_t)DNNL_RUNTIME_DIM_VAL) 1314 static const union {
1317 } DNNL_RUNTIME_F32_VAL_REP = {0x7fc000d0};
1322 #define DNNL_RUNTIME_F32_VAL (DNNL_RUNTIME_F32_VAL_REP.f) 1325 static const int DNNL_RUNTIME_S32_VAL_REP = INT32_MIN;
1330 #define DNNL_RUNTIME_S32_VAL DNNL_RUNTIME_S32_VAL_REP 1384 dnnl_packed_format_undef = 0,
1388 } dnnl_rnn_packed_memory_format_t;
1392 #define DNNL_RNN_MAX_N_PARTS 4 1396 dnnl_rnn_packed_memory_format_t format;
1403 size_t offset_compensation;
1410 dnnl_memory_extra_flag_none = 0x0U,
1419 dnnl_memory_extra_flag_scale_adjust = 0x2U,
1420 dnnl_memory_extra_flag_rnn_u8s8_compensation = 0x4U,
1421 dnnl_memory_extra_flag_gpu_rnn_u8s8_compensation
1422 = dnnl_memory_extra_flag_rnn_u8s8_compensation,
1423 dnnl_memory_extra_flag_compensation_conv_asymmetric_src = 0x8U,
1506 #define DNNL_MEMORY_NONE (NULL) 1510 #define DNNL_MEMORY_ALLOCATE ((void *)(size_t)-1) 1788 } dnnl_prelu_desc_t;
2164 typedef const struct dnnl_engine *const_dnnl_engine_t;
2280 #define DNNL_ARG_SRC_0 1 2281 #define DNNL_ARG_SRC DNNL_ARG_SRC_0 2284 #define DNNL_ARG_SRC_LAYER DNNL_ARG_SRC_0 2287 #define DNNL_ARG_FROM DNNL_ARG_SRC_0 2292 #define DNNL_ARG_SRC_1 2 2293 #define DNNL_ARG_SRC_ITER DNNL_ARG_SRC_1 2298 #define DNNL_ARG_SRC_2 3 2299 #define DNNL_ARG_SRC_ITER_C DNNL_ARG_SRC_2 2304 #define DNNL_ARG_DST_0 17 2305 #define DNNL_ARG_DST DNNL_ARG_DST_0 2308 #define DNNL_ARG_TO DNNL_ARG_DST_0 2311 #define DNNL_ARG_DST_LAYER DNNL_ARG_DST_0 2315 #define DNNL_ARG_DST_1 18 2316 #define DNNL_ARG_DST_ITER DNNL_ARG_DST_1 2321 #define DNNL_ARG_DST_2 19 2322 #define DNNL_ARG_DST_ITER_C DNNL_ARG_DST_2 2327 #define DNNL_ARG_WEIGHTS_0 33 2328 #define DNNL_ARG_WEIGHTS DNNL_ARG_WEIGHTS_0 2331 #define DNNL_ARG_SCALE_SHIFT DNNL_ARG_WEIGHTS_0 2334 #define DNNL_ARG_WEIGHTS_LAYER DNNL_ARG_WEIGHTS_0 2339 #define DNNL_ARG_WEIGHTS_1 34 2340 #define DNNL_ARG_WEIGHTS_ITER DNNL_ARG_WEIGHTS_1 2345 #define DNNL_ARG_WEIGHTS_2 35 2346 #define DNNL_ARG_WEIGHTS_PEEPHOLE DNNL_ARG_WEIGHTS_2 2351 #define DNNL_ARG_WEIGHTS_3 36 2352 #define DNNL_ARG_WEIGHTS_PROJECTION DNNL_ARG_WEIGHTS_3 2357 #define DNNL_ARG_BIAS 41 2360 #define DNNL_ARG_MEAN 49 2361 #define DNNL_ARG_VARIANCE 50 2366 #define DNNL_ARG_WORKSPACE 64 2367 #define DNNL_ARG_SCRATCHPAD 80 2371 #define DNNL_ARG_DIFF_SRC_0 129 2372 #define DNNL_ARG_DIFF_SRC DNNL_ARG_DIFF_SRC_0 2375 #define DNNL_ARG_DIFF_SRC_LAYER DNNL_ARG_DIFF_SRC_0 2380 #define DNNL_ARG_DIFF_SRC_1 130 2381 #define DNNL_ARG_DIFF_SRC_ITER DNNL_ARG_DIFF_SRC_1 2386 #define DNNL_ARG_DIFF_SRC_2 131 2387 #define DNNL_ARG_DIFF_SRC_ITER_C DNNL_ARG_DIFF_SRC_2 2392 #define DNNL_ARG_DIFF_DST_0 145 2393 #define DNNL_ARG_DIFF_DST DNNL_ARG_DIFF_DST_0 2396 #define DNNL_ARG_DIFF_DST_LAYER DNNL_ARG_DIFF_DST_0 2401 #define DNNL_ARG_DIFF_DST_1 146 2402 #define DNNL_ARG_DIFF_DST_ITER DNNL_ARG_DIFF_DST_1 2407 #define DNNL_ARG_DIFF_DST_2 147 2408 #define DNNL_ARG_DIFF_DST_ITER_C DNNL_ARG_DIFF_DST_2 2413 #define DNNL_ARG_DIFF_WEIGHTS_0 161 2414 #define DNNL_ARG_DIFF_WEIGHTS DNNL_ARG_DIFF_WEIGHTS_0 2417 #define DNNL_ARG_DIFF_SCALE_SHIFT DNNL_ARG_DIFF_WEIGHTS_0 2420 #define DNNL_ARG_DIFF_WEIGHTS_LAYER DNNL_ARG_DIFF_WEIGHTS_0 2425 #define DNNL_ARG_DIFF_WEIGHTS_1 162 2426 #define DNNL_ARG_DIFF_WEIGHTS_ITER DNNL_ARG_DIFF_WEIGHTS_1 2431 #define DNNL_ARG_DIFF_WEIGHTS_2 163 2432 #define DNNL_ARG_DIFF_WEIGHTS_PEEPHOLE DNNL_ARG_DIFF_WEIGHTS_2 2437 #define DNNL_ARG_DIFF_WEIGHTS_3 164 2438 #define DNNL_ARG_DIFF_WEIGHTS_PROJECTION DNNL_ARG_DIFF_WEIGHTS_3 2443 #define DNNL_ARG_DIFF_BIAS 169 2446 #define DNNL_ARG_ATTR_OUTPUT_SCALES 513 2450 #define DNNL_ARG_MULTIPLE_SRC 1024 2451 #define DNNL_ARG_MULTIPLE_DST 2048 2456 #define DNNL_ARG_ATTR_ZERO_POINTS 4096 2460 #define DNNL_ARG_ATTR_POST_OP_DW 8192 2463 #define DNNL_ARG_ATTR_MULTIPLE_POST_OP_BASE 16384 2467 #define DNNL_ARG_ATTR_MULTIPLE_POST_OP(idx) \ 2468 (DNNL_ARG_ATTR_MULTIPLE_POST_OP_BASE * ((idx) + 1)) 2575 dnnl_query_max = 0x7fff,
2588 dnnl_stream_in_order = 0x1U,
2609 #define DNNL_RUNTIME_NONE 0u 2612 #define DNNL_RUNTIME_SEQ 1u 2615 #define DNNL_RUNTIME_OMP 2u 2618 #define DNNL_RUNTIME_TBB 4u 2621 #define DNNL_RUNTIME_THREADPOOL 8u 2624 #define DNNL_RUNTIME_OCL 256u 2627 #define DNNL_RUNTIME_SYCL 512u 2630 #define DNNL_RUNTIME_DPCPP DNNL_RUNTIME_SYCL 2644 #define DNNL_JIT_PROFILE_NONE 0u 2647 #define DNNL_JIT_PROFILE_VTUNE 1u 2650 #define DNNL_JIT_PROFILE_LINUX_PERFMAP 2u 2653 #define DNNL_JIT_PROFILE_LINUX_JITDUMP 4u 2657 #define DNNL_JIT_PROFILE_LINUX_JITDUMP_USE_TSC 8u 2660 #define DNNL_JIT_PROFILE_LINUX_PERF \ 2661 (DNNL_JIT_PROFILE_LINUX_JITDUMP | DNNL_JIT_PROFILE_LINUX_PERFMAP) Reduction using sum.
Definition: dnnl_types.h:1225
dnnl_memory_desc_t diff_dst_layer_desc
Destination gradient layer memory descriptor.
Definition: dnnl_types.h:2005
dnnl_dims_t dilation
Pooling dilations for spatial dimensions.
Definition: dnnl_types.h:1765
A layer normalization primitive.
Definition: dnnl_types.h:1079
plain 7D tensor
Definition: dnnl_types.h:184
destination grad. memory desc
Definition: dnnl_types.h:2569
An element-wise primitive.
Definition: dnnl_types.h:1069
dnnl_alg_kind_t activation_kind
Activation function used for vanilla_rnn cell kind.
Definition: dnnl_types.h:2023
Reduction using lp norm without final pth-root.
Definition: dnnl_types.h:1235
dnnl_memory_desc_t weights_layer_desc
Weights layer memory descriptor.
Definition: dnnl_types.h:1972
prop_kind
Propagation kind.
Definition: dnnl.hpp:435
dnnl_alg_kind_t alg_kind
The kind of pooling algorithm.
Definition: dnnl_types.h:1707
6D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:362
execution engine
Definition: dnnl_types.h:2517
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1910
permuted 6D tensor
Definition: dnnl_types.h:424
dnnl_memory_desc_t diff_dst_iter_c_desc
Destination gradient iteration memory descriptor for cell state.
Definition: dnnl_types.h:2009
A batch normalization primitive.
Definition: dnnl_types.h:1077
Eltwise: bounded_relu.
Definition: dnnl_types.h:1134
Undefined memory format tag.
Definition: dnnl_types.h:169
3D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:229
A tensor in a generic format described by the stride and blocking values in each dimension.
Definition: dnnl_types.h:89
4D LSTM projection tensor in the format (num_layers, num_directions, num_channels_in_hidden_state, num_channels_in_recurrent_projection), an alias to dnnl_abcd.
Definition: dnnl_types.h:654
CPU engine.
Definition: dnnl_types.h:2151
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1830
Eltwise: ReLU (dst for backward)
Definition: dnnl_types.h:1165
destination memory desc
Definition: dnnl_types.h:2568
Direct deconvolution.
Definition: dnnl_types.h:1116
struct dnnl_memory * dnnl_memory_t
A memory handle.
Definition: dnnl_types.h:1499
A descriptor for an RNN operation.
Definition: dnnl_types.h:1953
The user manages the scratchpad allocation by querying and providing the scratchpad memory to primiti...
Definition: dnnl_types.h:2223
layer normalization descriptor
Definition: dnnl_types.h:2550
memory consumption – extra
Definition: dnnl_types.h:2524
dnnl_primitive_kind_t
Kinds of primitives.
Definition: dnnl_types.h:1053
permuted 3D tensor
Definition: dnnl_types.h:201
Eltwise: linear.
Definition: dnnl_types.h:1132
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1914
A PReLU primitive.
Definition: dnnl_types.h:1099
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:1812
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:1362
dnnl_memory_desc_t data_scaleshift_desc
Scale and shift data and gradient memory descriptors.
Definition: dnnl_types.h:1878
permuted 6D tensor
Definition: dnnl_types.h:425
permuted 12D tensor
Definition: dnnl_types.h:220
void * dnnl_op_desc_t
A pointer to any of the operation descriptors.
Definition: dnnl_types.h:1520
dnnl_alg_kind_t alg_kind
LRN algorithm.
Definition: dnnl_types.h:1805
A resampling primitive.
Definition: dnnl_types.h:1093
dnnl_format_kind_t format_kind
Memory format kind.
Definition: dnnl_types.h:1479
An opaque structure to describe a primitive.
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1833
GRU cell with linear before reset.
Definition: dnnl_types.h:1203
Any ISA (excepting those listed as initial support)
Definition: dnnl_types.h:2666
dnnl_dims_t strides
Pooling kernel strides for spatial dimensions.
Definition: dnnl_types.h:1717
4D CNN weights tensor, an alias to dnnl_acdb
Definition: dnnl_types.h:589
Undefined data type, used for empty memory descriptors.
Definition: dnnl_types.h:64
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:2072
dnnl_dim_t group_size
Number of groups.
Definition: dnnl_types.h:1600
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1554
5D CNN weights tensor, an alias to dnnl_acdeb
Definition: dnnl_types.h:601
5D LSTM projection tensor
Definition: dnnl_types.h:667
dnnl_convolution_desc_t dnnl_deconvolution_desc_t
A descriptor of a deconvolution operation.
Definition: dnnl_types.h:1579
4D CNN weights tensor (incl. groups), an alias to dnnl_abcd
Definition: dnnl_types.h:606
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1669
dnnl_alg_kind_t alg_kind
The kind of the convolution algorithm.
Definition: dnnl_types.h:1544
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1751
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1570
4D CNN weights tensor (incl. groups), an alias to dnnl_abdc
Definition: dnnl_types.h:608
Use no normalization flags.
Definition: dnnl_types.h:1250
scratchpad memory desc
Definition: dnnl_types.h:2571
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:2094
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1702
dnnl_memory_t memory
Input/output memory.
Definition: dnnl_types.h:2477
const void * const_dnnl_op_desc_t
A pointer to any of the operation descriptors (constant variant).
Definition: dnnl_types.h:1522
Intel Streaming SIMD Extensions 4.1 (Intel SSE4.1)
Definition: dnnl_types.h:2669
Eltwise: clip.
Definition: dnnl_types.h:1153
Intel AVX-512, Intel DL Boost and bfloat16 support and Intel AMX with 8-bit integer and bfloat16 supp...
Definition: dnnl_types.h:2702
prelu descriptor
Definition: dnnl_types.h:2560
An opaque structure for primitive descriptor attributes.
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1558
logsoftmax descriptor
Definition: dnnl_types.h:2555
permuted 4D tensor
Definition: dnnl_types.h:198
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1709
float lrn_alpha
LRN alpha parameter.
Definition: dnnl_types.h:1814
dnnl_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: dnnl_types.h:1912
dnnl_memory_desc_t dst_iter_c_desc
Destination iter memory descriptor for cell state.
Definition: dnnl_types.h:1982
Primitive iterator passed over last primitive descriptor.
Definition: dnnl_types.h:49
plain 8D tensor
Definition: dnnl_types.h:185
int minor
Minor version.
Definition: dnnl_types.h:2636
2D CNN weights tensor, an alias to dnnl_ab
Definition: dnnl_types.h:573
An opaque structure to describe a memory.
dnnl_memory_desc_t dst_layer_desc
Destination layer memory descriptor.
Definition: dnnl_types.h:1978
plain 11D tensor
Definition: dnnl_types.h:188
permuted 5D tensor
Definition: dnnl_types.h:199
dnnl_engine_kind_t
Kinds of engines.
Definition: dnnl_types.h:2147
struct dnnl_primitive_desc * dnnl_primitive_desc_t
A primitive descriptor handle.
Definition: dnnl_types.h:2190
Eltwise: square root (dst for backward)
Definition: dnnl_types.h:1171
non-standard 16-bit (bfloat16 w/ 7 bit mantissa) floating point.
Definition: dnnl_types.h:68
Parameter to allow internal only primitives without undefined behavior.
Definition: dnnl_types.h:1103
Undefined primitive.
Definition: dnnl_types.h:1055
dnnl_dims_t strides
Convolution strides in each spatial dimension.
Definition: dnnl_types.h:1562
int softmax_axis
The axis along which to perform the softmax.
Definition: dnnl_types.h:1678
Unidirectional execution of RNN primitive from left to right.
Definition: dnnl_types.h:1939
The library manages the scratchpad allocation according to the policy specified by the DNNL_ENABLE_CO...
Definition: dnnl_types.h:2218
5D CNN weights tensor (incl. groups), an alias to dnnl_acbde
Definition: dnnl_types.h:618
3D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:235
Eltwise: clip version 2.
Definition: dnnl_types.h:1155
3D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBc8b ...
Definition: dnnl_types.h:712
Intel AVX2 and Intel Deep Learning Boost (Intel DL Boost) support.
Definition: dnnl_types.h:2705
dnnl_dims_t dims
Dimensions in the following order:
Definition: dnnl_types.h:1462
const struct dnnl_memory * const_dnnl_memory_t
A constant memory handle.
Definition: dnnl_types.h:1502
4D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcd16b ...
Definition: dnnl_types.h:694
binary descriptor
Definition: dnnl_types.h:2554
dnnl_alg_kind_t alg_kind
The kind of pooling algorithm.
Definition: dnnl_types.h:1745
dnnl_memory_desc_t diff_weights_iter_desc
Weights gradient iter memory descriptor.
Definition: dnnl_types.h:2001
permuted 4D tensor
Definition: dnnl_types.h:193
Description of tensor of packed weights for rnn.
Definition: dnnl_types.h:1395
A descriptor of a pooling operation.
Definition: dnnl_types.h:1696
2D CNN activations tensor, an alias to dnnl_ab
Definition: dnnl_types.h:550
plain 2D tensor
Definition: dnnl_types.h:178
4D CNN activations tensor, an alias to dnnl_bcda
Definition: dnnl_types.h:566
4D RNN bias tensor in the format (num_layers, num_directions, num_gates, output_channels), an alias to dnnl_abcd.
Definition: dnnl_types.h:665
permuted 5D tensor
Definition: dnnl_types.h:206
pooling version 2 descriptor
Definition: dnnl_types.h:2558
Undefined memory format kind, used for empty memory descriptors.
Definition: dnnl_types.h:82
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:2070
Reduction using lp norm without final pth-root.
Definition: dnnl_types.h:1237
Bidirectional execution of RNN primitive with summation of the results.
Definition: dnnl_types.h:1947
32-bit signed integer.
Definition: dnnl_types.h:72
dnnl_memory_desc_t diff_src_iter_c_desc
Source gradient iter memory descriptor for cell state.
Definition: dnnl_types.h:1997
int inner_nblks
The number of innermost blocks, e.g. 3 in case of OIhw_4i16o4i_
Definition: dnnl_types.h:1348
Direct convolution.
Definition: dnnl_types.h:1110
int major
Major version.
Definition: dnnl_types.h:2635
Just a sentinel, not real memory format tag.
Definition: dnnl_types.h:543
5D tensor blocked by 1st dimension with block size 8
Definition: dnnl_types.h:304
An opaque structure to describe a primitive descriptor iterator.
pooling descriptor
Definition: dnnl_types.h:2547
Convolution algorithm(either direct or Winograd) is chosen just in time.
Definition: dnnl_types.h:1114
Reduction using mean.
Definition: dnnl_types.h:1229
float lrn_beta
LRN beta parameter.
Definition: dnnl_types.h:1816
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1906
Unidirectional execution of RNN primitive from right to left.
Definition: dnnl_types.h:1941
A deconvolution primitive.
Definition: dnnl_types.h:1067
dnnl_memory_desc_t src_iter_desc
Source iteration memory descriptor for hidden state.
Definition: dnnl_types.h:1968
5D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:330
8-bit unsigned integer.
Definition: dnnl_types.h:76
dnnl_alg_kind_t alg_kind
The kind of the binary algorithm.
Definition: dnnl_types.h:2042
A descriptor of a matrix multiplication operation.
Definition: dnnl_types.h:2061
permuted 6D tensor
Definition: dnnl_types.h:212
3D RNN data tensor in the format (batch, seq_length, input channels), an alias to dnnl_bac...
Definition: dnnl_types.h:633
dnnl_alg_kind_t cell_kind
RNN cell kind.
Definition: dnnl_types.h:1962
const char * hash
Git hash of the sources (may be absent)
Definition: dnnl_types.h:2638
5D CNN weights tensor, an alias to dnnl_cdeba
Definition: dnnl_types.h:599
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1737
4D CNN activations tensor, an alias to dnnl_acdb
Definition: dnnl_types.h:564
dnnl_query_t
Primitive descriptor query specification.
Definition: dnnl_types.h:2514
Intel Advanced Vector Extensions (Intel AVX)
Definition: dnnl_types.h:2672
Intel AVX-512 subset for Intel Xeon Phi processors 7235, 7285, 7295 Series.
Definition: dnnl_types.h:2683
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:2068
Backward data propagation.
Definition: dnnl_types.h:1044
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:2122
dnnl_memory_desc_t stat_desc
Statistics memory descriptor.
Definition: dnnl_types.h:1848
A descriptor of a binary operation.
Definition: dnnl_types.h:2035
source gradient memory desc
Definition: dnnl_types.h:2565
plain 10D tensor
Definition: dnnl_types.h:187
A binary primitive.
Definition: dnnl_types.h:1087
Structure containing version information as per Semantic Versioning
Definition: dnnl_types.h:2634
reduction descriptor
Definition: dnnl_types.h:2559
4D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:261
int arg
An argument index, e.g. DNNL_ARG_SRC.
Definition: dnnl_types.h:2476
5D CNN weights tensor (incl. groups), an alias to dnnl_abdec
Definition: dnnl_types.h:614
permuted 11D tensor
Definition: dnnl_types.h:219
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1916
LSTM cell.
Definition: dnnl_types.h:1193
Packed weights format used in RNN.
Definition: dnnl_types.h:93
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1740
4D CNN weights tensor, an alias to dnnl_bcda
Definition: dnnl_types.h:591
4D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:255
permuted 7D tensor
Definition: dnnl_types.h:215
A reorder primitive.
Definition: dnnl_types.h:1057
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1550
A descriptor of a convolution operation.
Definition: dnnl_types.h:1534
2D CNN activations tensor, an alias to dnnl_ba
Definition: dnnl_types.h:552
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1922
softmax descriptor
Definition: dnnl_types.h:2546
permuted 5D tensor
Definition: dnnl_types.h:213
dnnl_dims_t kernel
Pooling kernel spatial dimensions.
Definition: dnnl_types.h:1757
Intel AVX-512 subset for Intel Xeon Scalable processor family and Intel Core processor family...
Definition: dnnl_types.h:2687
Eltwise: logsigmoid.
Definition: dnnl_types.h:1163
no query
Definition: dnnl_types.h:2515
dnnl_scratchpad_mode_t
Scratchpad mode.
Definition: dnnl_types.h:2201
Fuse with ReLU.
Definition: dnnl_types.h:1289
batch normalization descriptor
Definition: dnnl_types.h:2549
dnnl_dims_t padded_dims
Size of the data including padding in each dimension.
Definition: dnnl_types.h:1468
A reduction primitive.
Definition: dnnl_types.h:1097
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:1476
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:2086
5D CNN weights tensor, an alias to dnnl_abcde
Definition: dnnl_types.h:595
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:1472
Undefined memory format, used for empty memory descriptors.
Definition: dnnl_types.h:1359
runtime estimation (seconds)
Definition: dnnl_types.h:2523
Backward propagation (with respect to all parameters).
Definition: dnnl_types.h:1042
An unspecified engine.
Definition: dnnl_types.h:2149
5D tensor blocked by 1st dimension with block size 16
Definition: dnnl_types.h:302
Eltwise: ReLU.
Definition: dnnl_types.h:1120
GPU engine.
Definition: dnnl_types.h:2153
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:2046
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:2038
4D RNN states tensor in the format (num_layers, num_directions, batch, state channels), an alias to dnnl_abcd.
Definition: dnnl_types.h:636
5D RNN weights tensor in the format (num_layers, num_directions, input_channels, num_gates, output_channels), an alias to dnnl_abcde.
Definition: dnnl_types.h:643
6D CNN weights tensor (incl. groups), an alias to dnnl_acbdef
Definition: dnnl_types.h:624
3D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:233
(scratch) memory, additional to all inputs and outputs memory (bytes)
Definition: dnnl_types.h:2529
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1959
Eltwise: pow.
Definition: dnnl_types.h:1157
5D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:315
dnnl_memory_extra_flags_t
Flags for memory special features.
Definition: dnnl_types.h:1409
5D RNN weights tensor in the format (num_layers, num_directions, num_gates, output_channels, input_channels), an alias to dnnl_abdec.
Definition: dnnl_types.h:650
permuted 4D tensor
Definition: dnnl_types.h:208
An opaque structure to describe an engine.
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1807
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:2066
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1546
6D CNN weights tensor (incl. groups), an alias to dnnl_abcdef
Definition: dnnl_types.h:620
Forward data propagation (inference mode).
Definition: dnnl_types.h:1036
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1868
Undefined RNN flags.
Definition: dnnl_types.h:1933
A sum primitive.
Definition: dnnl_types.h:1063
unsigned cpu_runtime
CPU runtime.
Definition: dnnl_types.h:2639
5D CNN weights tensor (incl. groups), an alias to dnnl_decab
Definition: dnnl_types.h:616
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1615
Intel Advanced Vector Extensions 512 (Intel AVX-512) subset for Intel Xeon Phi processors x200 Series...
Definition: dnnl_types.h:2679
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1674
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1870
A descriptor of a element-wise operation.
Definition: dnnl_types.h:1609
dnnl_dims_t inner_blks
The size of the blocks, e.g. {4, 16, 4} in case of OIhw_4i16o4i
Definition: dnnl_types.h:1350
A descriptor of a Softmax operation.
Definition: dnnl_types.h:1666
An opaque structure for a chain of post operations.
A descriptor of an inner product operation.
Definition: dnnl_types.h:1897
Eltwise: round.
Definition: dnnl_types.h:1161
The operation failed because of incorrect function arguments.
Definition: dnnl_types.h:45
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1763
3D RNN data tensor in the format (seq_length, batch, input channels), an alias to dnnl_abc...
Definition: dnnl_types.h:630
dnnl_memory_desc_t diff_weights_projection_desc
Weights gradient projection memory descriptor.
Definition: dnnl_types.h:2017
dnnl_rnn_direction_t
A direction of RNN primitive execution.
Definition: dnnl_types.h:1937
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:1361
inner product descriptor
Definition: dnnl_types.h:2551
5D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:306
A descriptor of reduction operation.
Definition: dnnl_types.h:2111
6D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:364
dnnl_status_t
Status values returned by the library functions.
Definition: dnnl_types.h:39
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1713
Reduction using lp norm.
Definition: dnnl_types.h:1233
Binary mul.
Definition: dnnl_types.h:1207
dnnl_memory_desc_t dst_iter_desc
Destination iter memory descriptor for hidden state.
Definition: dnnl_types.h:1980
A softmax primitive.
Definition: dnnl_types.h:1071
const struct dnnl_primitive_desc * const_dnnl_primitive_desc_t
A constant primitive descriptor handle.
Definition: dnnl_types.h:2193
No hints (use default features)
Definition: dnnl_types.h:2712
int64_t dnnl_dim_t
A type to describe tensor dimension.
Definition: dnnl_types.h:1333
Forward data propagation (alias for dnnl_forward_training).
Definition: dnnl_types.h:1040
primitive kind
Definition: dnnl_types.h:2518
matrix multiplication (matmul) descriptor
Definition: dnnl_types.h:2556
Default stream configuration.
Definition: dnnl_types.h:2592
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1918
dnnl_memory_desc_t stat_desc
Mean and variance data memory descriptors.
Definition: dnnl_types.h:1885
const struct dnnl_primitive * const_dnnl_primitive_t
A constant primitive handle.
Definition: dnnl_types.h:2277
LRN within a single channel.
Definition: dnnl_types.h:1189
dnnl_data_type_t
Data type specification.
Definition: dnnl_types.h:62
plain 4D tensor
Definition: dnnl_types.h:180
Generic description of blocked data layout for most memory formats.
Definition: dnnl_types.h:1341
plain 6D tensor
Definition: dnnl_types.h:183
Eltwise: exp (dst for backward)
Definition: dnnl_types.h:1175
Winograd convolution.
Definition: dnnl_types.h:1112
5D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:352
dnnl_wino_desc_t wino_desc
Tensor of weights for integer 8bit winograd convolution.
Definition: dnnl_types.h:1485
dnnl_alg_kind_t alg_kind
The kind of eltwise algorithm.
Definition: dnnl_types.h:1630
dnnl_format_tag_t
Memory format tag specification.
Definition: dnnl_types.h:164
4D LSTM projection tensor in the format (num_layers, num_directions, num_channels_in_recurrent_projec...
Definition: dnnl_types.h:658
Max pooling.
Definition: dnnl_types.h:1179
Eltwise: natural logarithm.
Definition: dnnl_types.h:1151
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:2098
float batch_norm_epsilon
Batch normalization epsilon parameter.
Definition: dnnl_types.h:1850
float p
Algorithm specific parameters.
Definition: dnnl_types.h:2136
dnnl_memory_desc_t weights_projection_desc
Weights projection memory descriptor.
Definition: dnnl_types.h:1990
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1866
plain 12D tensor
Definition: dnnl_types.h:189
Description of tensor of weights for winograd 2x3 convolution.
Definition: dnnl_types.h:1369
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1672
4D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcd4b ...
Definition: dnnl_types.h:697
Reduction using lp norm.
Definition: dnnl_types.h:1231
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1976
3D CNN weights tensor, an alias to dnnl_cba
Definition: dnnl_types.h:581
Binary div.
Definition: dnnl_types.h:1213
4D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:282
Out-of-order execution.
Definition: dnnl_types.h:2590
Binary min.
Definition: dnnl_types.h:1211
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:2124
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1799
dnnl_format_kind_t
Memory format kind.
Definition: dnnl_types.h:80
permuted 3D tensor
Definition: dnnl_types.h:195
4D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:300
5D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcde4b ...
Definition: dnnl_types.h:685
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1956
Average pooling (alias for dnnl_pooling_avg_exclude_padding)
Definition: dnnl_types.h:1185
dnnl_memory_desc_t diff_src_layer_desc
Source gradient layer memory descriptor.
Definition: dnnl_types.h:1993
int axis
Axis for shuffling.
Definition: dnnl_types.h:1598
Prefer to exclusively use Ymm registers for computations.
Definition: dnnl_types.h:2715
dnnl_rnn_packed_desc_t rnn_packed_desc
Tensor of packed weights for RNN.
Definition: dnnl_types.h:1487
3D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:245
Binary add.
Definition: dnnl_types.h:1205
3D CNN activations tensor, an alias to dnnl_abc
Definition: dnnl_types.h:558
deconvolution descriptor
Definition: dnnl_types.h:2543
A pooling primitive.
Definition: dnnl_types.h:1073
dnnl_dims_t strides
The strides between the outermost blocks.
Definition: dnnl_types.h:1344
rnn descriptor
Definition: dnnl_types.h:2552
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1537
Eltwise: logistic.
Definition: dnnl_types.h:1138
A descriptor of a shuffle operation.
Definition: dnnl_types.h:1587
const struct dnnl_primitive_desc_iterator * const_dnnl_primitive_desc_iterator_t
A constant primitive descriptor iterator handle.
Definition: dnnl_types.h:2182
dnnl_dims_t kernel
Pooling kernel spatial dimensions.
Definition: dnnl_types.h:1719
Eltwise: hyperbolic tangent non-linearity (tanh) (dst for backward)
Definition: dnnl_types.h:1167
Winograd deconvolution.
Definition: dnnl_types.h:1118
permuted 4D tensor
Definition: dnnl_types.h:209
number of outputs expected
Definition: dnnl_types.h:2521
#define DNNL_MAX_NDIMS
Maximum number of dimensions a tensor can have.
Definition: dnnl_types.h:1301
5D CNN weights tensor (incl. groups), an alias to dnnl_abcde
Definition: dnnl_types.h:612
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1908
float lrn_k
LRN k parameter.
Definition: dnnl_types.h:1818
dnnl_rnn_direction_t direction
The direction of RNN primitive execution.
Definition: dnnl_types.h:1964
6D CNN weights tensor (incl. groups), an alias to dnnl_defcab
Definition: dnnl_types.h:626
GEMM descriptor (internal)
Definition: dnnl_types.h:2553
plain 1D tensor
Definition: dnnl_types.h:177
Bidirectional execution of RNN primitive with concatenation of the results.
Definition: dnnl_types.h:1944
Reduction using min.
Definition: dnnl_types.h:1223
permuted 2D tensor
Definition: dnnl_types.h:200
permuted 5D tensor
Definition: dnnl_types.h:211
permuted 6D tensor
Definition: dnnl_types.h:197
dnnl_memory_desc_t src_iter_c_desc
Source iteration memory descriptor for cell state.
Definition: dnnl_types.h:1970
stub
Definition: dnnl_types.h:2540
dnnl_memory_desc_t diff_desc
Source and Destination of gradient memory descriptor.
Definition: dnnl_types.h:1676
3D CNN weights tensor, an alias to dnnl_bca
Definition: dnnl_types.h:583
5D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcde8b ...
Definition: dnnl_types.h:688
propagation kind
Definition: dnnl_types.h:2537
plain 9D tensor
Definition: dnnl_types.h:186
An inner product primitive.
Definition: dnnl_types.h:1081
Use global statistics.
Definition: dnnl_types.h:1263
6D RNN weights tensor
Definition: dnnl_types.h:670
5D CNN activations tensor blocked by channels with block size 32, an alias to dnnl_aBcde32b ...
Definition: dnnl_types.h:679
GRU cell.
Definition: dnnl_types.h:1195
3D CNN activations tensor, an alias to dnnl_acb
Definition: dnnl_types.h:560
The operation was successful.
Definition: dnnl_types.h:41
A descriptor of a Layer Normalization operation.
Definition: dnnl_types.h:1860
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1590
8-bit signed integer.
Definition: dnnl_types.h:74
convolution descriptor
Definition: dnnl_types.h:2542
dnnl_memory_desc_t weights_peephole_desc
Weights peephole memory descriptor.
Definition: dnnl_types.h:1986
RNN cell.
Definition: dnnl_types.h:1191
Alias for dnnl_unidirectional_left2right.
Definition: dnnl_types.h:1949
A (out-of-place) concat primitive.
Definition: dnnl_types.h:1061
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:1363
dnnl_dims_t dilates
Convolution dilates in each spatial dimension.
Definition: dnnl_types.h:1564
const struct dnnl_stream * const_dnnl_stream_t
A constant execution stream handle.
Definition: dnnl_types.h:2601
2D RNN statistics tensor, an alias to dnnl_ba
Definition: dnnl_types.h:556
5D CNN activations tensor, an alias to dnnl_acdeb
Definition: dnnl_types.h:570
Intel AVX-512 and Intel Deep Learning Boost (Intel DL Boost) support for Intel Xeon Scalable processo...
Definition: dnnl_types.h:2692
Undefined memory format tag.
Definition: dnnl_types.h:166
dnnl_cpu_isa_hints_t
CPU ISA hints flags.
Definition: dnnl_types.h:2710
Reduction using mul.
Definition: dnnl_types.h:1227
permuted 5D tensor
Definition: dnnl_types.h:196
Eltwise: square root.
Definition: dnnl_types.h:1130
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1835
int patch
Patch version.
Definition: dnnl_types.h:2637
dnnl_alg_kind_t alg_kind
The kind of reduction algorithm.
Definition: dnnl_types.h:2120
4D CNN activations tensor blocked by channels with block size 32, an alias to dnnl_aBcd32b ...
Definition: dnnl_types.h:691
permuted 3D tensor
Definition: dnnl_types.h:204
permuted 8D tensor
Definition: dnnl_types.h:216
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1809
source memory desc
Definition: dnnl_types.h:2564
Eltwise: swish.
Definition: dnnl_types.h:1149
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1802
#define DNNL_RNN_MAX_N_PARTS
Maximum number of parts of RNN weights tensor that require separate computation.
Definition: dnnl_types.h:1392
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:2114
Memory descriptor.
Definition: dnnl_types.h:1445
dnnl_wino_memory_format_t
Winograd-specific formats.
Definition: dnnl_types.h:1357
2D RNN statistics tensor, an alias to dnnl_ab
Definition: dnnl_types.h:554
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1863
A descriptor of a pooling operation.
Definition: dnnl_types.h:1734
dnnl_data_type_t data_type
Data type of the tensor elements.
Definition: dnnl_types.h:1465
A matrix multiplication primitive.
Definition: dnnl_types.h:1091
Queried element is not required for given primitive.
Definition: dnnl_types.h:53
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1725
Eltwise: erf-based gelu.
Definition: dnnl_types.h:1159
permuted 9D tensor
Definition: dnnl_types.h:217
Indicates the weights have an additional buffer, that depends on the compensation_mask.
Definition: dnnl_types.h:1418
dnnl_blocking_desc_t blocking
Description of the data layout for memory formats that use blocking.
Definition: dnnl_types.h:1483
dnnl_dims_t inner_idxs
The logical indices of the blocks, e.g.
Definition: dnnl_types.h:1353
The operation failed due to an out-of-memory condition.
Definition: dnnl_types.h:43
Backward weights propagation.
Definition: dnnl_types.h:1046
5D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:313
3D CNN weights tensor, an alias to dnnl_acb
Definition: dnnl_types.h:579
dnnl_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: dnnl_types.h:1552
dnnl_memory_desc_t data_scaleshift_desc
Scale and shift data and gradient memory descriptors.
Definition: dnnl_types.h:1843
workspace memory desc
Definition: dnnl_types.h:2570
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:2064
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1560
eltwise descriptor
Definition: dnnl_types.h:2545
number of inputs expected
Definition: dnnl_types.h:2520
shuffle descriptor
Definition: dnnl_types.h:2544
Average pooling include padding.
Definition: dnnl_types.h:1181
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1837
Weights format used in 8bit Winograd convolution.
Definition: dnnl_types.h:91
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:2096
32-bit/single-precision floating point.
Definition: dnnl_types.h:70
permuted 5D tensor
Definition: dnnl_types.h:210
A structure that contains an index and a memory object, and is used to pass arguments to dnnl_primiti...
Definition: dnnl_types.h:2475
Intel AVX-512, Intel DL Boost and bfloat16 support for Intel Xeon Scalable processor family and Intel...
Definition: dnnl_types.h:2697
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:2089
4D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcd8b ...
Definition: dnnl_types.h:700
struct dnnl_primitive_attr * dnnl_primitive_attr_t
A primitive descriptor attributes handle that controls primitive behavior.
Definition: dnnl_types.h:2235
lrn descriptor
Definition: dnnl_types.h:2548
dnnl_memory_desc_t src_layer_desc
Source layer memory descriptor.
Definition: dnnl_types.h:1966
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:2100
4D tensor blocked by 1st and 2nd dimension with block size 8
Definition: dnnl_types.h:288
A shuffle primitive.
Definition: dnnl_types.h:1059
for creating scratchpad memory
Definition: dnnl_types.h:2532
float layer_norm_epsilon
Layer normalization epsilon parameter.
Definition: dnnl_types.h:1887
dnnl_memory_desc_t diff_weights_peephole_desc
Weights gradient peephole memory descriptor.
Definition: dnnl_types.h:2013
struct dnnl_engine * dnnl_engine_t
An engine handle.
Definition: dnnl_types.h:2160
unsigned int flags
RNN cell flags.
Definition: dnnl_types.h:2020
permuted 4D tensor
Definition: dnnl_types.h:205
4D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:263
Binary max.
Definition: dnnl_types.h:1209
Unspecified format kind.
Definition: dnnl_types.h:85
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1593
2D CNN weights tensor, an alias to dnnl_ba
Definition: dnnl_types.h:575
Average pooling exclude padding.
Definition: dnnl_types.h:1183
3D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBc16b ...
Definition: dnnl_types.h:706
dnnl_alg_kind_t
Kinds of algorithms.
Definition: dnnl_types.h:1107
4D CNN weights tensor, an alias to dnnl_cdba
Definition: dnnl_types.h:587
6D CNN weights tensor (incl. groups), an alias to dnnl_abdefc
Definition: dnnl_types.h:622
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1753
Reduction using max.
Definition: dnnl_types.h:1221
5D CNN weights tensor, an alias to dnnl_bacde
Definition: dnnl_types.h:597
permuted 3D tensor
Definition: dnnl_types.h:207
dnnl_rnn_flags_t
Flags for RNN cell.
Definition: dnnl_types.h:1931
dnnl_memory_desc_t diff_dst_iter_desc
Destination gradient iteration memory descriptor for hidden state.
Definition: dnnl_types.h:2007
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1747
A pooling version 2 primitive (pooling with dilation support).
Definition: dnnl_types.h:1095
4D CNN weights tensor (incl. groups), an alias to dnnl_dcab
Definition: dnnl_types.h:610
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1904
An LRN primitive.
Definition: dnnl_types.h:1075
A descriptor of a Local Response Normalization (LRN) operation.
Definition: dnnl_types.h:1796
dnnl_softmax_desc_t dnnl_logsoftmax_desc_t
A descriptor of a LogSoftmax operation.
Definition: dnnl_types.h:1688
Eltwise: clip version 2 (dst for backward)
Definition: dnnl_types.h:1177
int ndims
Number of dimensions.
Definition: dnnl_types.h:1447
dnnl_stream_flags_t
Stream flags.
Definition: dnnl_types.h:2586
dnnl_dim_t dnnl_dims_t[DNNL_MAX_NDIMS]
A type to describe tensor dimensions.
Definition: dnnl_types.h:1336
Undefined propagation type.
Definition: dnnl_types.h:1029
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1634
Primitive or engine failed on execution.
Definition: dnnl_types.h:51
op descriptor
Definition: dnnl_types.h:2541
6D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:359
dnnl_memory_desc_t weights_iter_desc
Weights iteration memory descriptor.
Definition: dnnl_types.h:1974
const struct dnnl_post_ops * const_dnnl_post_ops_t
A constant post operation chain handle.
Definition: dnnl_types.h:2264
Eltwise: exponent.
Definition: dnnl_types.h:1140
1D tensor, an alias to dnnl_a
Definition: dnnl_types.h:548
Local response normalization (LRN) across multiple channels.
Definition: dnnl_types.h:1187
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1699
resampling descriptor
Definition: dnnl_types.h:2557
const struct dnnl_primitive_attr * const_dnnl_primitive_attr_t
A constant primitive descriptor attributes handle.
Definition: dnnl_types.h:2238
A matrix multiplication primitive (internal).
Definition: dnnl_types.h:1085
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:2003
plain 3D tensor
Definition: dnnl_types.h:179
Use scale and shift parameters.
Definition: dnnl_types.h:1276
3D CNN activations tensor blocked by channels with block size 32, an alias to dnnl_aBc32b ...
Definition: dnnl_types.h:703
A descriptor of a Batch Normalization operation.
Definition: dnnl_types.h:1827
5D CNN weights tensor, an alias to dnnl_bcdea
Definition: dnnl_types.h:603
struct dnnl_primitive * dnnl_primitive_t
A primitive handle.
Definition: dnnl_types.h:2275
Intel Advanced Vector Extensions 2 (Intel AVX2)
Definition: dnnl_types.h:2675
3D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBc4b ...
Definition: dnnl_types.h:709
struct dnnl_stream * dnnl_stream_t
An execution stream handle.
Definition: dnnl_types.h:2599
4D CNN weights tensor, an alias to dnnl_bacd
Definition: dnnl_types.h:593
Eltwise: exponential linear unit (elu) (dst for backward)
Definition: dnnl_types.h:1169
Eltwise: exponential linear unit (elu)
Definition: dnnl_types.h:1124
Forward data propagation (alias for dnnl_forward_inference).
Definition: dnnl_types.h:1038
6D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:354
Binary sub.
Definition: dnnl_types.h:1215
5D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcde16b ...
Definition: dnnl_types.h:682
An opaque structure to describe a primitive descriptor.
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1541
struct dnnl_primitive_desc_iterator * dnnl_primitive_desc_iterator_t
A primitive descriptor iterator handle.
Definition: dnnl_types.h:2179
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1749
Eltwise: abs.
Definition: dnnl_types.h:1128
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1632
Internal weights format for 4x3 Winograd.
Definition: dnnl_types.h:1365
Forward data propagation (training mode).
Definition: dnnl_types.h:1032
permuted 5D tensor
Definition: dnnl_types.h:194
dnnl_memory_desc_t data_desc
Source and destination memory descriptor, and source and destination gradient memory descriptor...
Definition: dnnl_types.h:1596
Eltwise: tanh-based gelu (alias for dnnl_eltwise_gelu_tanh)
Definition: dnnl_types.h:1147
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1548
A rnn primitive.
Definition: dnnl_types.h:1083
An opaque structure to describe an execution stream.
4D CNN activations tensor, an alias to dnnl_abcd
Definition: dnnl_types.h:562
A logsoftmax primitive.
Definition: dnnl_types.h:1089
permuted 5D tensor
Definition: dnnl_types.h:203
The operation failed because requested functionality is not implemented.
Definition: dnnl_types.h:47
Eltwise: gelu.
Definition: dnnl_types.h:1145
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:2074
dnnl_memory_desc_t diff_src_iter_desc
Source gradient iter memory descriptor for hidden state.
Definition: dnnl_types.h:1995
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1711
Eltwise: hyperbolic tangent non-linearity (tanh)
Definition: dnnl_types.h:1122
struct dnnl_post_ops * dnnl_post_ops_t
A post operation chain handle.
Definition: dnnl_types.h:2261
permuted 10D tensor
Definition: dnnl_types.h:218
A descriptor of resampling operation.
Definition: dnnl_types.h:2083
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1715
dnnl_prop_kind_t
Kinds of propagation.
Definition: dnnl_types.h:1026
permuted 6D tensor
Definition: dnnl_types.h:214
stub
Definition: dnnl_types.h:2563
Nearest Neighbor Resampling Method.
Definition: dnnl_types.h:1217
permuted 4D tensor
Definition: dnnl_types.h:202
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1920
plain 4D tensor
Definition: dnnl_types.h:181
16-bit/half-precision floating point.
Definition: dnnl_types.h:66
source engine
Definition: dnnl_types.h:2534
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1556
dnnl_alg_kind_t alg_kind
The kind of the resampling algorithm.
Definition: dnnl_types.h:2092
dnnl_normalization_flags_t
Flags for normalization primitives.
Definition: dnnl_types.h:1241
weights grad. memory desc
Definition: dnnl_types.h:2567
A convolution primitive.
Definition: dnnl_types.h:1065
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1612
memory desc of an execute argument
Definition: dnnl_types.h:2572
Backward bias propagation.
Definition: dnnl_types.h:1048
5D CNN activations tensor, an alias to dnnl_abcde
Definition: dnnl_types.h:568
4D CNN weights tensor, an alias to dnnl_abcd
Definition: dnnl_types.h:585
Eltwise: logistic (dst for backward)
Definition: dnnl_types.h:1173
dnnl_memory_desc_t diff_weights_layer_desc
Weights gradient layer memory descriptor.
Definition: dnnl_types.h:1999
weights memory descriptor desc
Definition: dnnl_types.h:2566
unsigned gpu_runtime
GPU runtime.
Definition: dnnl_types.h:2640
Linear Resampling Method.
Definition: dnnl_types.h:1219
3D CNN weights tensor, an alias to dnnl_abc
Definition: dnnl_types.h:577
dnnl_cpu_isa_t
CPU instruction set flags.
Definition: dnnl_types.h:2664
Eltwise: soft_relu.
Definition: dnnl_types.h:1136
plain 5D tensor
Definition: dnnl_types.h:182
dnnl_dims_t strides
Pooling kernel strides for spatial dimensions.
Definition: dnnl_types.h:1755
destination engine
Definition: dnnl_types.h:2535
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1900
Eltwise: square.
Definition: dnnl_types.h:1126
float alpha
Algorithm specific parameter.
Definition: dnnl_types.h:1657