20 #ifndef ONEAPI_DNNL_DNNL_TYPES_H 21 #define ONEAPI_DNNL_DNNL_TYPES_H 586 dnnl_ldOI32o4i = dnnl_abDC32d4c,
589 dnnl_ldgOI32o2i = dnnl_abdEC32e2c,
590 dnnl_ldgOI32o4i = dnnl_abdEC32e4c,
631 dnnl_NCw16n16c = dnnl_ABc16a16b,
632 dnnl_NCdhw16n16c = dnnl_ABcde16a16b,
633 dnnl_NChw16n16c = dnnl_ABcd16a16b,
634 dnnl_NCw32n32c = dnnl_ABc32a32b,
635 dnnl_NChw32n32c = dnnl_ABcd32a32b,
636 dnnl_NCdhw32n32c = dnnl_ABcde32a32b,
639 dnnl_OI16i16o = dnnl_AB16b16a,
640 dnnl_OI16i32o = dnnl_AB16b32a,
641 dnnl_OI16i64o = dnnl_AB16b64a,
642 dnnl_OI8i16o2i = dnnl_AB8b16a2b,
643 dnnl_OI8i32o2i = dnnl_AB8b32a2b,
644 dnnl_OI8i64o2i = dnnl_AB8b64a2b,
645 dnnl_OI4i16o4i = dnnl_AB4b16a4b,
646 dnnl_OI4i32o4i = dnnl_AB4b32a4b,
647 dnnl_OI4i64o4i = dnnl_AB4b64a4b,
649 dnnl_IOw16o16i = dnnl_BAc16a16b,
650 dnnl_IOw16i16o = dnnl_BAc16b16a,
651 dnnl_OIw16i16o = dnnl_ABc16b16a,
652 dnnl_OIw16i32o = dnnl_ABc16b32a,
653 dnnl_OIw16i64o = dnnl_ABc16b64a,
654 dnnl_OIw16o16i = dnnl_ABc16a16b,
655 dnnl_Oiw16o = dnnl_Abc16a,
656 dnnl_OIw4i16o4i = dnnl_ABc4b16a4b,
657 dnnl_OIw4i32o4i = dnnl_ABc4b32a4b,
658 dnnl_OIw4i64o4i = dnnl_ABc4b64a4b,
659 dnnl_OIw2i8o4i = dnnl_ABc2b8a4b,
660 dnnl_OIw16i16o4i = dnnl_ABc16b16a4b,
661 dnnl_OIw16i16o2i = dnnl_ABc16b16a2b,
662 dnnl_OIw4i4o = dnnl_ABc4b4a,
663 dnnl_OIw4o4i = dnnl_ABc4a4b,
664 dnnl_Oiw4o = dnnl_Abc4a,
665 dnnl_OIw8i16o2i = dnnl_ABc8b16a2b,
666 dnnl_OIw8i32o2i = dnnl_ABc8b32a2b,
667 dnnl_OIw8i64o2i = dnnl_ABc8b64a2b,
668 dnnl_OIw8i8o = dnnl_ABc8b8a,
669 dnnl_OIw8o16i2o = dnnl_ABc8a16b2a,
670 dnnl_IOw8o16i2o = dnnl_BAc8a16b2a,
671 dnnl_OIw8o8i = dnnl_ABc8a8b,
672 dnnl_OIw8o4i = dnnl_ABc8a4b,
673 dnnl_Owi16o = dnnl_Acb16a,
674 dnnl_OwI16o2i = dnnl_AcB16a2b,
675 dnnl_OwI16o4i = dnnl_AcB16a4b,
676 dnnl_Owi4o = dnnl_Acb4a,
677 dnnl_Owi8o = dnnl_Acb8a,
680 dnnl_IOhw16i16o = dnnl_BAcd16b16a,
681 dnnl_IOhw16o16i = dnnl_BAcd16a16b,
682 dnnl_Ohwi16o = dnnl_Acdb16a,
683 dnnl_OhwI16o2i = dnnl_AcdB16a2b,
684 dnnl_OhwI16o4i = dnnl_AcdB16a4b,
685 dnnl_Ohwi32o = dnnl_Acdb32a,
686 dnnl_Ohwi4o = dnnl_Acdb4a,
687 dnnl_Ohwi8o = dnnl_Acdb8a,
688 dnnl_OIhw16i16o = dnnl_ABcd16b16a,
689 dnnl_OIhw16i32o = dnnl_ABcd16b32a,
690 dnnl_OIhw16i64o = dnnl_ABcd16b64a,
691 dnnl_OIhw16o16i = dnnl_ABcd16a16b,
692 dnnl_Oihw16o = dnnl_Abcd16a,
693 dnnl_OIhw4i16o4i = dnnl_ABcd4b16a4b,
694 dnnl_OIhw4i32o4i = dnnl_ABcd4b32a4b,
695 dnnl_OIhw4i64o4i = dnnl_ABcd4b64a4b,
696 dnnl_OIhw16i16o4i = dnnl_ABcd16b16a4b,
697 dnnl_OIhw16i16o2i = dnnl_ABcd16b16a2b,
698 dnnl_OIhw4i4o = dnnl_ABcd4b4a,
699 dnnl_OIhw4o4i = dnnl_ABcd4a4b,
700 dnnl_Oihw4o = dnnl_Abcd4a,
701 dnnl_OIhw8i16o2i = dnnl_ABcd8b16a2b,
702 dnnl_OIhw8i32o2i = dnnl_ABcd8b32a2b,
703 dnnl_OIhw8i64o2i = dnnl_ABcd8b64a2b,
705 dnnl_OIhw8o16i2o = dnnl_ABcd8a16b2a,
706 dnnl_OIhw2i8o4i = dnnl_ABcd2b8a4b,
707 dnnl_IOhw8o16i2o = dnnl_BAcd8a16b2a,
708 dnnl_OIhw8o8i = dnnl_ABcd8a8b,
709 dnnl_OIhw8o4i = dnnl_ABcd8a4b,
710 dnnl_Owhi16o = dnnl_Adcb16a,
713 dnnl_Odhwi16o = dnnl_Acdeb16a,
714 dnnl_OdhwI16o2i = dnnl_AcdeB16a2b,
715 dnnl_Odhwi4o = dnnl_Acdeb4a,
716 dnnl_Odhwi8o = dnnl_Acdeb8a,
717 dnnl_OIdhw16i16o = dnnl_ABcde16b16a,
718 dnnl_OIdhw16i32o = dnnl_ABcde16b32a,
719 dnnl_OIdhw16i64o = dnnl_ABcde16b64a,
720 dnnl_OIdhw16o16i = dnnl_ABcde16a16b,
721 dnnl_Oidhw16o = dnnl_Abcde16a,
722 dnnl_OIdhw4i4o = dnnl_ABcde4b4a,
723 dnnl_OIdhw4o4i = dnnl_ABcde4a4b,
724 dnnl_Oidhw4o = dnnl_Abcde4a,
725 dnnl_OIdhw8i16o2i = dnnl_ABcde8b16a2b,
726 dnnl_OIdhw8i32o2i = dnnl_ABcde8b32a2b,
727 dnnl_OIdhw8i64o2i = dnnl_ABcde8b64a2b,
728 dnnl_OIdhw8i8o = dnnl_ABcde8b8a,
729 dnnl_OIdhw8o16i2o = dnnl_ABcde8a16b2a,
730 dnnl_IOdhw8o16i2o = dnnl_BAcde8a16b2a,
732 dnnl_OIdhw4i32o4i = dnnl_ABcde4b32a4b,
733 dnnl_OIdhw4i64o4i = dnnl_ABcde4b64a4b,
735 dnnl_OIdhw8o8i = dnnl_ABcde8a8b,
736 dnnl_OIdhw8o4i = dnnl_ABcde8a4b,
737 dnnl_IOdhw16i16o = dnnl_BAcde16b16a,
738 dnnl_OIdhw4o8i8o4i = dnnl_ABcde4a8b8a4b,
739 dnnl_IOdhw16o16i = dnnl_BAcde16a16b,
742 dnnl_Goiw16g = dnnl_Abcd16a,
743 dnnl_Goiw8g = dnnl_Abcd8a,
744 dnnl_Goiw4g = dnnl_Abcd4a,
745 dnnl_gIOw16o16i = dnnl_aCBd16b16c,
746 dnnl_gIOw16i16o = dnnl_aCBd16c16b,
747 dnnl_gOIw16i16o = dnnl_aBCd16c16b,
748 dnnl_gOIw16o16i = dnnl_aBCd16b16c,
750 dnnl_gOIw4i16o4i = dnnl_aBCd4c16b4c,
751 dnnl_gOIw2i8o4i = dnnl_aBCd2c8b4c,
752 dnnl_gOIw16i16o4i = dnnl_aBCd16c16b4c,
753 dnnl_gOIw16i16o2i = dnnl_aBCd16c16b2c,
754 dnnl_gOIw4i4o = dnnl_aBCd4c4b,
755 dnnl_gOIw4o4i = dnnl_aBCd4b4c,
757 dnnl_gOIw8i16o2i = dnnl_aBCd8c16b2c,
758 dnnl_gOIw8i8o = dnnl_aBCd8c8b,
759 dnnl_gOIw8o16i2o = dnnl_aBCd8b16c2b,
760 dnnl_gIOw8o16i2o = dnnl_aCBd8b16c2b,
761 dnnl_gOIw8o8i = dnnl_aBCd8b8c,
762 dnnl_gOIw8o4i = dnnl_aBCd8b4c,
763 dnnl_gOwi16o = dnnl_aBdc16b,
764 dnnl_gOwI16o2i = dnnl_aBdC16b2c,
765 dnnl_gOwI16o4i = dnnl_aBdC16b4c,
766 dnnl_gOwi4o = dnnl_aBdc4b,
767 dnnl_gOwi8o = dnnl_aBdc8b,
768 dnnl_Goiw32g = dnnl_Abcd32a,
769 dnnl_gOIw2i4o2i = dnnl_aBCd2c4b2c,
771 dnnl_gOIw4i8o2i = dnnl_aBCd4c8b2c,
772 dnnl_gOIw4o8i2o = dnnl_aBCd4b8c2b,
775 dnnl_gIOhw16i16o = dnnl_aCBde16c16b,
776 dnnl_gIOhw16o16i = dnnl_aCBde16b16c,
777 dnnl_gOhwi16o = dnnl_aBdec16b,
778 dnnl_gOhwI16o2i = dnnl_aBdeC16b2c,
779 dnnl_gOhwI16o4i = dnnl_aBdeC16b4c,
780 dnnl_gOhwi32o = dnnl_aBdec32b,
781 dnnl_gOhwi4o = dnnl_aBdec4b,
782 dnnl_gOhwi8o = dnnl_aBdec8b,
783 dnnl_Goihw16g = dnnl_Abcde16a,
784 dnnl_gOIhw16i16o = dnnl_aBCde16c16b,
785 dnnl_gOIhw16o16i = dnnl_aBCde16b16c,
787 dnnl_gOIhw2i8o4i = dnnl_aBCde2c8b4c,
788 dnnl_gOIhw4i16o4i = dnnl_aBCde4c16b4c,
789 dnnl_gOIhw16i16o4i = dnnl_aBCde16c16b4c,
790 dnnl_gOIhw16i16o2i = dnnl_aBCde16c16b2c,
791 dnnl_gOIhw4i4o = dnnl_aBCde4c4b,
792 dnnl_gOIhw4o4i = dnnl_aBCde4b4c,
794 dnnl_Goihw8g = dnnl_Abcde8a,
795 dnnl_Goihw4g = dnnl_Abcde4a,
796 dnnl_gOIhw8i16o2i = dnnl_aBCde8c16b2c,
797 dnnl_gOIhw8i8o = dnnl_aBCde8c8b,
798 dnnl_gOIhw8o16i2o = dnnl_aBCde8b16c2b,
799 dnnl_gIOhw8o16i2o = dnnl_aCBde8b16c2b,
800 dnnl_gOIhw8o8i = dnnl_aBCde8b8c,
801 dnnl_gOIhw8o4i = dnnl_aBCde8b4c,
802 dnnl_Goihw32g = dnnl_Abcde32a,
803 dnnl_gOwhi16o = dnnl_aBedc16b,
805 dnnl_OIw4o8i8o4i = dnnl_ABc4a8b8a4b,
806 dnnl_OIhw4o8i8o4i = dnnl_ABcd4a8b8a4b,
807 dnnl_IOw4i8o8i4o = dnnl_BAc4b8a8b4a,
808 dnnl_IOhw4i8o8i4o = dnnl_BAcd4b8a8b4a,
809 dnnl_IOdhw4i8o8i4o = dnnl_BAcde4b8a8b4a,
811 dnnl_OIhw2o8i8o2i = dnnl_ABcd2a8b8a2b,
812 dnnl_gOIw4o8i8o4i = dnnl_aBCd4b8c8b4c,
813 dnnl_gOIhw4o8i8o4i = dnnl_aBCde4b8c8b4c,
814 dnnl_gOIdhw4o8i8o4i = dnnl_aBCdef4b8c8b4c,
815 dnnl_gIOw4i8o8i4o = dnnl_aCBd4c8b8c4b,
816 dnnl_gIOhw4i8o8i4o = dnnl_aCBde4c8b8c4b,
817 dnnl_gIOdhw4i8o8i4o = dnnl_aCBdef4c8b8c4b,
818 dnnl_gOIhw2o8i8o2i = dnnl_aBCde2b8c8b2c,
819 dnnl_gOIhw2i4o2i = dnnl_aBCde2c4b2c,
821 dnnl_gOIhw4i8o2i = dnnl_aBCde4c8b2c,
822 dnnl_gOIhw4o8i2o = dnnl_aBCde4b8c2b,
825 dnnl_gIOdhw16i16o = dnnl_aCBdef16c16b,
826 dnnl_gIOdhw16o16i = dnnl_aCBdef16b16c,
827 dnnl_gOdhwi16o = dnnl_aBdefc16b,
828 dnnl_gOdhwI16o2i = dnnl_aBdefC16b2c,
829 dnnl_gOdhwi4o = dnnl_aBdefc4b,
830 dnnl_gOdhwi8o = dnnl_aBdefc8b,
831 dnnl_gOIdhw16i16o = dnnl_aBCdef16c16b,
832 dnnl_gOIdhw4i16o4i = dnnl_aBCdef4c16b4c,
834 dnnl_gOIdhw16o16i = dnnl_aBCdef16b16c,
836 dnnl_gOIdhw4i4o = dnnl_aBCdef4c4b,
837 dnnl_gOIdhw4o4i = dnnl_aBCdef4b4c,
839 dnnl_gOIdhw8i16o2i = dnnl_aBCdef8c16b2c,
840 dnnl_gOIdhw8i8o = dnnl_aBCdef8c8b,
841 dnnl_gOIdhw8o16i2o = dnnl_aBCdef8b16c2b,
842 dnnl_gIOdhw8o16i2o = dnnl_aCBdef8b16c2b,
843 dnnl_gOIdhw8o8i = dnnl_aBCdef8b8c,
844 dnnl_gOIdhw8o4i = dnnl_aBCdef8b4c,
845 dnnl_Goidhw16g = dnnl_Abcdef16a,
846 dnnl_Goidhw32g = dnnl_Abcdef32a,
847 dnnl_gOIdhw2i4o2i = dnnl_aBCdef2c4b2c,
848 dnnl_gOIdhw4i8o2i = dnnl_aBCdef4c8b2c,
850 dnnl_gOIdhw4o8i2o = dnnl_aBCdef4b8c2b,
1130 #define DNNL_MAX_NDIMS 12 1134 #define DNNL_RUNTIME_DIM_VAL INT64_MIN 1139 #define DNNL_RUNTIME_SIZE_VAL ((size_t)DNNL_RUNTIME_DIM_VAL) 1143 static const union {
1146 } DNNL_RUNTIME_F32_VAL_REP = {0x7fc000d0};
1151 #define DNNL_RUNTIME_F32_VAL (DNNL_RUNTIME_F32_VAL_REP.f) 1154 static const int DNNL_RUNTIME_S32_VAL_REP = INT32_MIN;
1159 #define DNNL_RUNTIME_S32_VAL DNNL_RUNTIME_S32_VAL_REP 1213 dnnl_packed_format_undef = 0,
1217 } dnnl_rnn_packed_memory_format_t;
1221 #define DNNL_RNN_MAX_N_PARTS 4 1225 dnnl_rnn_packed_memory_format_t format;
1232 size_t offset_compensation;
1239 dnnl_memory_extra_flag_none = 0x0U,
1248 dnnl_memory_extra_flag_scale_adjust = 0x2U,
1249 dnnl_memory_extra_flag_rnn_u8s8_compensation = 0x4U,
1250 dnnl_memory_extra_flag_gpu_rnn_u8s8_compensation
1251 = dnnl_memory_extra_flag_rnn_u8s8_compensation,
1252 dnnl_memory_extra_flag_compensation_conv_asymmetric_src = 0x8U,
1335 #define DNNL_MEMORY_NONE (NULL) 1339 #define DNNL_MEMORY_ALLOCATE ((void *)(size_t)-1) 1613 } dnnl_prelu_desc_t;
1989 typedef const struct dnnl_engine *const_dnnl_engine_t;
2105 #define DNNL_ARG_SRC_0 1 2106 #define DNNL_ARG_SRC DNNL_ARG_SRC_0 2109 #define DNNL_ARG_SRC_LAYER DNNL_ARG_SRC_0 2112 #define DNNL_ARG_FROM DNNL_ARG_SRC_0 2117 #define DNNL_ARG_SRC_1 2 2118 #define DNNL_ARG_SRC_ITER DNNL_ARG_SRC_1 2123 #define DNNL_ARG_SRC_2 3 2124 #define DNNL_ARG_SRC_ITER_C DNNL_ARG_SRC_2 2129 #define DNNL_ARG_DST_0 17 2130 #define DNNL_ARG_DST DNNL_ARG_DST_0 2133 #define DNNL_ARG_TO DNNL_ARG_DST_0 2136 #define DNNL_ARG_DST_LAYER DNNL_ARG_DST_0 2140 #define DNNL_ARG_DST_1 18 2141 #define DNNL_ARG_DST_ITER DNNL_ARG_DST_1 2146 #define DNNL_ARG_DST_2 19 2147 #define DNNL_ARG_DST_ITER_C DNNL_ARG_DST_2 2152 #define DNNL_ARG_WEIGHTS_0 33 2153 #define DNNL_ARG_WEIGHTS DNNL_ARG_WEIGHTS_0 2156 #define DNNL_ARG_SCALE_SHIFT DNNL_ARG_WEIGHTS_0 2159 #define DNNL_ARG_WEIGHTS_LAYER DNNL_ARG_WEIGHTS_0 2164 #define DNNL_ARG_WEIGHTS_1 34 2165 #define DNNL_ARG_WEIGHTS_ITER DNNL_ARG_WEIGHTS_1 2170 #define DNNL_ARG_WEIGHTS_2 35 2171 #define DNNL_ARG_WEIGHTS_PEEPHOLE DNNL_ARG_WEIGHTS_2 2176 #define DNNL_ARG_WEIGHTS_3 36 2177 #define DNNL_ARG_WEIGHTS_PROJECTION DNNL_ARG_WEIGHTS_3 2182 #define DNNL_ARG_BIAS 41 2185 #define DNNL_ARG_MEAN 49 2186 #define DNNL_ARG_VARIANCE 50 2191 #define DNNL_ARG_WORKSPACE 64 2192 #define DNNL_ARG_SCRATCHPAD 80 2196 #define DNNL_ARG_DIFF_SRC_0 129 2197 #define DNNL_ARG_DIFF_SRC DNNL_ARG_DIFF_SRC_0 2200 #define DNNL_ARG_DIFF_SRC_LAYER DNNL_ARG_DIFF_SRC_0 2205 #define DNNL_ARG_DIFF_SRC_1 130 2206 #define DNNL_ARG_DIFF_SRC_ITER DNNL_ARG_DIFF_SRC_1 2211 #define DNNL_ARG_DIFF_SRC_2 131 2212 #define DNNL_ARG_DIFF_SRC_ITER_C DNNL_ARG_DIFF_SRC_2 2217 #define DNNL_ARG_DIFF_DST_0 145 2218 #define DNNL_ARG_DIFF_DST DNNL_ARG_DIFF_DST_0 2221 #define DNNL_ARG_DIFF_DST_LAYER DNNL_ARG_DIFF_DST_0 2226 #define DNNL_ARG_DIFF_DST_1 146 2227 #define DNNL_ARG_DIFF_DST_ITER DNNL_ARG_DIFF_DST_1 2232 #define DNNL_ARG_DIFF_DST_2 147 2233 #define DNNL_ARG_DIFF_DST_ITER_C DNNL_ARG_DIFF_DST_2 2238 #define DNNL_ARG_DIFF_WEIGHTS_0 161 2239 #define DNNL_ARG_DIFF_WEIGHTS DNNL_ARG_DIFF_WEIGHTS_0 2242 #define DNNL_ARG_DIFF_SCALE_SHIFT DNNL_ARG_DIFF_WEIGHTS_0 2245 #define DNNL_ARG_DIFF_WEIGHTS_LAYER DNNL_ARG_DIFF_WEIGHTS_0 2250 #define DNNL_ARG_DIFF_WEIGHTS_1 162 2251 #define DNNL_ARG_DIFF_WEIGHTS_ITER DNNL_ARG_DIFF_WEIGHTS_1 2256 #define DNNL_ARG_DIFF_WEIGHTS_2 163 2257 #define DNNL_ARG_DIFF_WEIGHTS_PEEPHOLE DNNL_ARG_DIFF_WEIGHTS_2 2262 #define DNNL_ARG_DIFF_WEIGHTS_3 164 2263 #define DNNL_ARG_DIFF_WEIGHTS_PROJECTION DNNL_ARG_DIFF_WEIGHTS_3 2268 #define DNNL_ARG_DIFF_BIAS 169 2271 #define DNNL_ARG_ATTR_OUTPUT_SCALES 513 2275 #define DNNL_ARG_MULTIPLE_SRC 1024 2276 #define DNNL_ARG_MULTIPLE_DST 2048 2281 #define DNNL_ARG_ATTR_ZERO_POINTS 4096 2285 #define DNNL_ARG_ATTR_POST_OP_DW 8192 2288 #define DNNL_ARG_ATTR_MULTIPLE_POST_OP_BASE 16384 2292 #define DNNL_ARG_ATTR_MULTIPLE_POST_OP(idx) \ 2293 (DNNL_ARG_ATTR_MULTIPLE_POST_OP_BASE * ((idx) + 1)) 2400 dnnl_query_max = 0x7fff,
2413 dnnl_stream_in_order = 0x1U,
2429 struct dnnl_stream_attr;
2441 #define DNNL_RUNTIME_NONE 0u 2444 #define DNNL_RUNTIME_SEQ 1u 2447 #define DNNL_RUNTIME_OMP 2u 2450 #define DNNL_RUNTIME_TBB 4u 2453 #define DNNL_RUNTIME_THREADPOOL 8u 2456 #define DNNL_RUNTIME_OCL 256u 2459 #define DNNL_RUNTIME_SYCL 512u 2462 #define DNNL_RUNTIME_DPCPP DNNL_RUNTIME_SYCL 2476 #define DNNL_JIT_PROFILE_NONE 0u 2479 #define DNNL_JIT_PROFILE_VTUNE 1u 2482 #define DNNL_JIT_PROFILE_LINUX_PERFMAP 2u 2485 #define DNNL_JIT_PROFILE_LINUX_JITDUMP 4u 2489 #define DNNL_JIT_PROFILE_LINUX_JITDUMP_USE_TSC 8u 2492 #define DNNL_JIT_PROFILE_LINUX_PERF \ 2493 (DNNL_JIT_PROFILE_LINUX_JITDUMP | DNNL_JIT_PROFILE_LINUX_PERFMAP) Reduction using sum.
Definition: dnnl_types.h:1054
dnnl_memory_desc_t diff_dst_layer_desc
Destination gradient layer memory descriptor.
Definition: dnnl_types.h:1830
dnnl_dims_t dilation
Pooling dilations for spatial dimensions.
Definition: dnnl_types.h:1590
A layer normalization primitive.
Definition: dnnl_types.h:914
plain 7D tensor
Definition: dnnl_types.h:184
destination grad. memory desc
Definition: dnnl_types.h:2394
An element-wise primitive.
Definition: dnnl_types.h:904
dnnl_alg_kind_t activation_kind
Activation function used for vanilla_rnn cell kind.
Definition: dnnl_types.h:1848
Reduction using lp norm without final pth-root.
Definition: dnnl_types.h:1064
dnnl_memory_desc_t weights_layer_desc
Weights layer memory descriptor.
Definition: dnnl_types.h:1797
prop_kind
Propagation kind.
Definition: dnnl.hpp:435
dnnl_alg_kind_t alg_kind
The kind of pooling algorithm.
Definition: dnnl_types.h:1532
6D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:391
execution engine
Definition: dnnl_types.h:2342
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1735
permuted 6D tensor
Definition: dnnl_types.h:195
dnnl_memory_desc_t diff_dst_iter_c_desc
Destination gradient iteration memory descriptor for cell state.
Definition: dnnl_types.h:1834
A batch normalization primitive.
Definition: dnnl_types.h:912
Eltwise: bounded_relu.
Definition: dnnl_types.h:969
Undefined memory format tag.
Definition: dnnl_types.h:169
3D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:231
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).
Definition: dnnl_types.h:573
CPU engine.
Definition: dnnl_types.h:1976
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1655
Eltwise: ReLU (dst for backward)
Definition: dnnl_types.h:996
destination memory desc
Definition: dnnl_types.h:2393
Direct deconvolution.
Definition: dnnl_types.h:951
struct dnnl_memory * dnnl_memory_t
A memory handle.
Definition: dnnl_types.h:1328
A descriptor for an RNN operation.
Definition: dnnl_types.h:1778
The user manages the scratchpad allocation by querying and providing the scratchpad memory to primiti...
Definition: dnnl_types.h:2048
layer normalization descriptor
Definition: dnnl_types.h:2376
memory consumption – extra
Definition: dnnl_types.h:2349
dnnl_primitive_kind_t
Kinds of primitives.
Definition: dnnl_types.h:888
permuted 3D tensor
Definition: dnnl_types.h:203
Eltwise: linear.
Definition: dnnl_types.h:967
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1739
A PReLU primitive.
Definition: dnnl_types.h:934
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:1637
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:1191
dnnl_memory_desc_t data_scaleshift_desc
Scale and shift data and gradient memory descriptors.
Definition: dnnl_types.h:1703
permuted 6D tensor
Definition: dnnl_types.h:199
permuted 12D tensor
Definition: dnnl_types.h:222
void * dnnl_op_desc_t
A pointer to any of the operation descriptors.
Definition: dnnl_types.h:1349
dnnl_alg_kind_t alg_kind
LRN algorithm.
Definition: dnnl_types.h:1630
A resampling primitive.
Definition: dnnl_types.h:928
dnnl_format_kind_t format_kind
Memory format kind.
Definition: dnnl_types.h:1308
An opaque structure to describe a primitive.
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1658
GRU cell with linear before reset.
Definition: dnnl_types.h:1032
Any ISA (excepting those listed as initial support)
Definition: dnnl_types.h:2498
dnnl_dims_t strides
Pooling kernel strides for spatial dimensions.
Definition: dnnl_types.h:1542
4D CNN weights tensor, an alias to dnnl_acdb
Definition: dnnl_types.h:511
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:1897
dnnl_dim_t group_size
Number of groups.
Definition: dnnl_types.h:1429
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1383
5D CNN weights tensor, an alias to dnnl_acdeb
Definition: dnnl_types.h:523
5D LSTM projection tensor
Definition: dnnl_types.h:585
dnnl_convolution_desc_t dnnl_deconvolution_desc_t
A descriptor of a deconvolution operation.
Definition: dnnl_types.h:1408
4D CNN weights tensor (incl. groups), an alias to dnnl_abcd
Definition: dnnl_types.h:528
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1494
dnnl_alg_kind_t alg_kind
The kind of the convolution algorithm.
Definition: dnnl_types.h:1373
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1576
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1399
4D CNN weights tensor (incl. groups), an alias to dnnl_abdc
Definition: dnnl_types.h:530
Use no normalization flags.
Definition: dnnl_types.h:1079
scratchpad memory desc
Definition: dnnl_types.h:2396
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1919
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1527
dnnl_memory_t memory
Input/output memory.
Definition: dnnl_types.h:2302
const void * const_dnnl_op_desc_t
A pointer to any of the operation descriptors (constant variant).
Definition: dnnl_types.h:1351
Intel Streaming SIMD Extensions 4.1 (Intel SSE4.1)
Definition: dnnl_types.h:2501
Eltwise: clip.
Definition: dnnl_types.h:988
Intel AVX-512, Intel DL Boost and bfloat16 support and Intel AMX with 8-bit integer and bfloat16 supp...
Definition: dnnl_types.h:2534
prelu descriptor
Definition: dnnl_types.h:2373
An opaque structure for primitive descriptor attributes.
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1387
logsoftmax descriptor
Definition: dnnl_types.h:2381
permuted 4D tensor
Definition: dnnl_types.h:200
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1534
float lrn_alpha
LRN alpha parameter.
Definition: dnnl_types.h:1639
dnnl_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: dnnl_types.h:1737
dnnl_memory_desc_t dst_iter_c_desc
Destination iter memory descriptor for cell state.
Definition: dnnl_types.h:1807
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:2468
2D CNN weights tensor, an alias to dnnl_ab
Definition: dnnl_types.h:495
An opaque structure to describe a memory.
dnnl_memory_desc_t dst_layer_desc
Destination layer memory descriptor.
Definition: dnnl_types.h:1803
plain 11D tensor
Definition: dnnl_types.h:188
permuted 5D tensor
Definition: dnnl_types.h:201
dnnl_engine_kind_t
Kinds of engines.
Definition: dnnl_types.h:1972
struct dnnl_primitive_desc * dnnl_primitive_desc_t
A primitive descriptor handle.
Definition: dnnl_types.h:2015
Eltwise: square root (dst for backward)
Definition: dnnl_types.h:1002
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:938
Undefined primitive.
Definition: dnnl_types.h:890
dnnl_dims_t strides
Convolution strides in each spatial dimension.
Definition: dnnl_types.h:1391
int softmax_axis
The axis along which to perform the softmax.
Definition: dnnl_types.h:1503
Unidirectional execution of RNN primitive from left to right.
Definition: dnnl_types.h:1764
The library manages the scratchpad allocation according to the policy specified by the DNNL_ENABLE_CO...
Definition: dnnl_types.h:2043
5D CNN weights tensor (incl. groups), an alias to dnnl_acbde
Definition: dnnl_types.h:540
3D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:239
3D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBc8b ...
Definition: dnnl_types.h:630
Intel AVX2 and Intel Deep Learning Boost (Intel DL Boost) support.
Definition: dnnl_types.h:2537
dnnl_dims_t dims
Dimensions in the following order:
Definition: dnnl_types.h:1291
const struct dnnl_memory * const_dnnl_memory_t
A constant memory handle.
Definition: dnnl_types.h:1331
4D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcd16b ...
Definition: dnnl_types.h:612
binary descriptor
Definition: dnnl_types.h:2380
dnnl_alg_kind_t alg_kind
The kind of pooling algorithm.
Definition: dnnl_types.h:1570
dnnl_memory_desc_t diff_weights_iter_desc
Weights gradient iter memory descriptor.
Definition: dnnl_types.h:1826
permuted 4D tensor
Definition: dnnl_types.h:193
Description of tensor of packed weights for rnn.
Definition: dnnl_types.h:1224
A descriptor of a pooling operation.
Definition: dnnl_types.h:1521
2D CNN activations tensor, an alias to dnnl_ab
Definition: dnnl_types.h:472
plain 2D tensor
Definition: dnnl_types.h:178
4D CNN activations tensor, an alias to dnnl_bcda
Definition: dnnl_types.h:488
4D RNN bias tensor in the format (num_layers, num_directions, num_gates, output_channels).
Definition: dnnl_types.h:583
permuted 5D tensor
Definition: dnnl_types.h:208
pooling version 2 descriptor
Definition: dnnl_types.h:2384
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:1895
Reduction using lp norm without final pth-root.
Definition: dnnl_types.h:1066
Bidirectional execution of RNN primitive with summation of the results.
Definition: dnnl_types.h:1772
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:1822
int inner_nblks
The number of innermost blocks, e.g. 3 in case of OIhw_4i16o4i_
Definition: dnnl_types.h:1177
Direct convolution.
Definition: dnnl_types.h:945
int major
Major version.
Definition: dnnl_types.h:2467
Just a sentinel, not real memory format tag.
Definition: dnnl_types.h:465
5D tensor blocked by 1st dimension with block size 8
Definition: dnnl_types.h:329
An opaque structure to describe a primitive descriptor iterator.
pooling descriptor
Definition: dnnl_types.h:2372
Convolution algorithm(either direct or Winograd) is chosen just in time.
Definition: dnnl_types.h:949
Reduction using mean.
Definition: dnnl_types.h:1058
float lrn_beta
LRN beta parameter.
Definition: dnnl_types.h:1641
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1731
Unidirectional execution of RNN primitive from right to left.
Definition: dnnl_types.h:1766
A deconvolution primitive.
Definition: dnnl_types.h:902
dnnl_memory_desc_t src_iter_desc
Source iteration memory descriptor for hidden state.
Definition: dnnl_types.h:1793
5D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:357
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:1867
A descriptor of a matrix multiplication operation.
Definition: dnnl_types.h:1886
permuted 6D tensor
Definition: dnnl_types.h:214
3D RNN data tensor in the format (batch, seq_length, input channels).
Definition: dnnl_types.h:553
dnnl_alg_kind_t cell_kind
RNN cell kind.
Definition: dnnl_types.h:1787
const char * hash
Git hash of the sources (may be absent)
Definition: dnnl_types.h:2470
5D CNN weights tensor, an alias to dnnl_cdeba
Definition: dnnl_types.h:521
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1562
4D CNN activations tensor, an alias to dnnl_acdb
Definition: dnnl_types.h:486
dnnl_query_t
Primitive descriptor query specification.
Definition: dnnl_types.h:2339
Intel Advanced Vector Extensions (Intel AVX)
Definition: dnnl_types.h:2504
Intel AVX-512 subset for Intel Xeon Phi processors 7235, 7285, 7295 Series.
Definition: dnnl_types.h:2515
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1893
Backward data propagation.
Definition: dnnl_types.h:879
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1947
dnnl_memory_desc_t stat_desc
Statistics memory descriptor.
Definition: dnnl_types.h:1673
A descriptor of a binary operation.
Definition: dnnl_types.h:1860
source gradient memory desc
Definition: dnnl_types.h:2390
plain 10D tensor
Definition: dnnl_types.h:187
A binary primitive.
Definition: dnnl_types.h:922
Structure containing version information as per Semantic Versioning
Definition: dnnl_types.h:2466
reduction descriptor
Definition: dnnl_types.h:2385
4D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:280
int arg
An argument index, e.g. DNNL_ARG_SRC.
Definition: dnnl_types.h:2301
5D CNN weights tensor (incl. groups), an alias to dnnl_abdec
Definition: dnnl_types.h:536
permuted 11D tensor
Definition: dnnl_types.h:221
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1741
LSTM cell.
Definition: dnnl_types.h:1022
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:1565
4D CNN weights tensor, an alias to dnnl_bcda
Definition: dnnl_types.h:513
4D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:272
permuted 7D tensor
Definition: dnnl_types.h:217
A reorder primitive.
Definition: dnnl_types.h:892
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1379
A descriptor of a convolution operation.
Definition: dnnl_types.h:1363
2D CNN activations tensor, an alias to dnnl_ba
Definition: dnnl_types.h:474
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1747
softmax descriptor
Definition: dnnl_types.h:2371
permuted 5D tensor
Definition: dnnl_types.h:215
dnnl_dims_t kernel
Pooling kernel spatial dimensions.
Definition: dnnl_types.h:1582
Intel AVX-512 subset for Intel Xeon Scalable processor family and Intel Core processor family...
Definition: dnnl_types.h:2519
no query
Definition: dnnl_types.h:2340
dnnl_scratchpad_mode_t
Scratchpad mode.
Definition: dnnl_types.h:2026
Fuse with ReLU.
Definition: dnnl_types.h:1118
batch normalization descriptor
Definition: dnnl_types.h:2375
dnnl_dims_t padded_dims
Size of the data including padding in each dimension.
Definition: dnnl_types.h:1297
A reduction primitive.
Definition: dnnl_types.h:932
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:1305
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1911
5D CNN weights tensor, an alias to dnnl_abcde
Definition: dnnl_types.h:517
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:1301
Undefined memory format, used for empty memory descriptors.
Definition: dnnl_types.h:1188
runtime estimation (seconds)
Definition: dnnl_types.h:2348
Backward propagation (with respect to all parameters).
Definition: dnnl_types.h:877
An unspecified engine.
Definition: dnnl_types.h:1974
5D tensor blocked by 1st dimension with block size 16
Definition: dnnl_types.h:325
Eltwise: ReLU.
Definition: dnnl_types.h:955
GPU engine.
Definition: dnnl_types.h:1978
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1871
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1863
4D RNN states tensor in the format (num_layers, num_directions, batch, state channels).
Definition: dnnl_types.h:556
5D RNN weights tensor in the format (num_layers, num_directions, input_channels, num_gates, output_channels).
Definition: dnnl_types.h:563
6D CNN weights tensor (incl. groups), an alias to dnnl_acbdef
Definition: dnnl_types.h:546
3D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:237
(scratch) memory, additional to all inputs and outputs memory (bytes)
Definition: dnnl_types.h:2354
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1784
Eltwise: pow.
Definition: dnnl_types.h:990
5D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:342
dnnl_memory_extra_flags_t
Flags for memory special features.
Definition: dnnl_types.h:1238
5D RNN weights tensor in the format (num_layers, num_directions, num_gates, output_channels, input_channels).
Definition: dnnl_types.h:570
permuted 4D tensor
Definition: dnnl_types.h:210
An opaque structure to describe an engine.
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1632
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1891
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1375
6D CNN weights tensor (incl. groups), an alias to dnnl_abcdef
Definition: dnnl_types.h:542
Forward data propagation (inference mode).
Definition: dnnl_types.h:871
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1693
Undefined RNN flags.
Definition: dnnl_types.h:1758
A sum primitive.
Definition: dnnl_types.h:898
unsigned cpu_runtime
CPU runtime.
Definition: dnnl_types.h:2471
5D CNN weights tensor (incl. groups), an alias to dnnl_decab
Definition: dnnl_types.h:538
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1444
Intel Advanced Vector Extensions 512 (Intel AVX-512) subset for Intel Xeon Phi processors x200 Series...
Definition: dnnl_types.h:2511
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1499
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1695
A descriptor of a element-wise operation.
Definition: dnnl_types.h:1438
dnnl_dims_t inner_blks
The size of the blocks, e.g. {4, 16, 4} in case of OIhw_4i16o4i
Definition: dnnl_types.h:1179
A descriptor of a Softmax operation.
Definition: dnnl_types.h:1491
An opaque structure for a chain of post operations.
A descriptor of an inner product operation.
Definition: dnnl_types.h:1722
Eltwise: round.
Definition: dnnl_types.h:994
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:1588
3D RNN data tensor in the format (seq_length, batch, input channels).
Definition: dnnl_types.h:551
dnnl_memory_desc_t diff_weights_projection_desc
Weights gradient projection memory descriptor.
Definition: dnnl_types.h:1842
dnnl_rnn_direction_t
A direction of RNN primitive execution.
Definition: dnnl_types.h:1762
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:1190
inner product descriptor
Definition: dnnl_types.h:2377
5D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:331
A descriptor of reduction operation.
Definition: dnnl_types.h:1936
6D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:393
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:1538
Reduction using lp norm.
Definition: dnnl_types.h:1062
Binary mul.
Definition: dnnl_types.h:1036
dnnl_memory_desc_t dst_iter_desc
Destination iter memory descriptor for hidden state.
Definition: dnnl_types.h:1805
A softmax primitive.
Definition: dnnl_types.h:906
const struct dnnl_primitive_desc * const_dnnl_primitive_desc_t
A constant primitive descriptor handle.
Definition: dnnl_types.h:2018
int64_t dnnl_dim_t
A type to describe tensor dimension.
Definition: dnnl_types.h:1162
Forward data propagation (alias for dnnl_forward_training).
Definition: dnnl_types.h:875
primitive kind
Definition: dnnl_types.h:2343
matrix multiplication (matmul) descriptor
Definition: dnnl_types.h:2382
Default stream configuration.
Definition: dnnl_types.h:2417
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1743
dnnl_memory_desc_t stat_desc
Mean and variance data memory descriptors.
Definition: dnnl_types.h:1710
const struct dnnl_primitive * const_dnnl_primitive_t
A constant primitive handle.
Definition: dnnl_types.h:2102
LRN within a single channel.
Definition: dnnl_types.h:1018
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:1170
plain 6D tensor
Definition: dnnl_types.h:183
Eltwise: exp (dst for backward)
Definition: dnnl_types.h:1006
Winograd convolution.
Definition: dnnl_types.h:947
5D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:381
dnnl_wino_desc_t wino_desc
Tensor of weights for integer 8bit winograd convolution.
Definition: dnnl_types.h:1314
dnnl_alg_kind_t alg_kind
The kind of eltwise algorithm.
Definition: dnnl_types.h:1457
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:576
Max pooling.
Definition: dnnl_types.h:1008
Eltwise: natural logarithm.
Definition: dnnl_types.h:986
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1923
float batch_norm_epsilon
Batch normalization epsilon parameter.
Definition: dnnl_types.h:1675
float p
Algorithm specific parameters.
Definition: dnnl_types.h:1961
dnnl_memory_desc_t weights_projection_desc
Weights projection memory descriptor.
Definition: dnnl_types.h:1815
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1691
plain 12D tensor
Definition: dnnl_types.h:189
Description of tensor of weights for winograd 2x3 convolution.
Definition: dnnl_types.h:1198
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1497
4D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcd4b ...
Definition: dnnl_types.h:615
Reduction using lp norm.
Definition: dnnl_types.h:1060
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1801
3D CNN weights tensor, an alias to dnnl_cba
Definition: dnnl_types.h:503
Binary div.
Definition: dnnl_types.h:1042
4D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:303
Out-of-order execution.
Definition: dnnl_types.h:2415
Binary min.
Definition: dnnl_types.h:1040
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1949
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1624
dnnl_format_kind_t
Memory format kind.
Definition: dnnl_types.h:80
permuted 3D tensor
Definition: dnnl_types.h:196
4D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:323
5D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcde4b ...
Definition: dnnl_types.h:603
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1781
Average pooling (alias for dnnl_pooling_avg_exclude_padding)
Definition: dnnl_types.h:1014
dnnl_memory_desc_t diff_src_layer_desc
Source gradient layer memory descriptor.
Definition: dnnl_types.h:1818
int axis
Axis for shuffling.
Definition: dnnl_types.h:1427
dnnl_rnn_packed_desc_t rnn_packed_desc
Tensor of packed weights for RNN.
Definition: dnnl_types.h:1316
3D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:262
Binary add.
Definition: dnnl_types.h:1034
3D CNN activations tensor, an alias to dnnl_abc
Definition: dnnl_types.h:480
deconvolution descriptor
Definition: dnnl_types.h:2368
A pooling primitive.
Definition: dnnl_types.h:908
dnnl_dims_t strides
The strides between the outermost blocks.
Definition: dnnl_types.h:1173
rnn descriptor
Definition: dnnl_types.h:2378
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1366
Eltwise: logistic.
Definition: dnnl_types.h:973
A descriptor of a shuffle operation.
Definition: dnnl_types.h:1416
const struct dnnl_primitive_desc_iterator * const_dnnl_primitive_desc_iterator_t
A constant primitive descriptor iterator handle.
Definition: dnnl_types.h:2007
dnnl_dims_t kernel
Pooling kernel spatial dimensions.
Definition: dnnl_types.h:1544
Eltwise: hyperbolic tangent non-linearity (tanh) (dst for backward)
Definition: dnnl_types.h:998
Winograd deconvolution.
Definition: dnnl_types.h:953
permuted 4D tensor
Definition: dnnl_types.h:211
number of outputs expected
Definition: dnnl_types.h:2346
#define DNNL_MAX_NDIMS
Maximum number of dimensions a tensor can have.
Definition: dnnl_types.h:1130
5D CNN weights tensor (incl. groups), an alias to dnnl_abcde
Definition: dnnl_types.h:534
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1733
float lrn_k
LRN k parameter.
Definition: dnnl_types.h:1643
dnnl_rnn_direction_t direction
The direction of RNN primitive execution.
Definition: dnnl_types.h:1789
6D CNN weights tensor (incl. groups), an alias to dnnl_defcab
Definition: dnnl_types.h:548
GEMM descriptor (internal)
Definition: dnnl_types.h:2379
plain 1D tensor
Definition: dnnl_types.h:177
Bidirectional execution of RNN primitive with concatenation of the results.
Definition: dnnl_types.h:1769
Reduction using min.
Definition: dnnl_types.h:1052
permuted 2D tensor
Definition: dnnl_types.h:202
permuted 5D tensor
Definition: dnnl_types.h:213
permuted 6D tensor
Definition: dnnl_types.h:198
dnnl_memory_desc_t src_iter_c_desc
Source iteration memory descriptor for cell state.
Definition: dnnl_types.h:1795
stub
Definition: dnnl_types.h:2365
dnnl_memory_desc_t diff_desc
Source and Destination of gradient memory descriptor.
Definition: dnnl_types.h:1501
3D CNN weights tensor, an alias to dnnl_bca
Definition: dnnl_types.h:505
5D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcde8b ...
Definition: dnnl_types.h:606
propagation kind
Definition: dnnl_types.h:2362
plain 9D tensor
Definition: dnnl_types.h:186
An inner product primitive.
Definition: dnnl_types.h:916
Use global statistics.
Definition: dnnl_types.h:1092
6D RNN weights tensor
Definition: dnnl_types.h:588
5D CNN activations tensor blocked by channels with block size 32, an alias to dnnl_aBcde32b ...
Definition: dnnl_types.h:597
GRU cell.
Definition: dnnl_types.h:1024
3D CNN activations tensor, an alias to dnnl_acb
Definition: dnnl_types.h:482
The operation was successful.
Definition: dnnl_types.h:41
A descriptor of a Layer Normalization operation.
Definition: dnnl_types.h:1685
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1419
8-bit signed integer.
Definition: dnnl_types.h:74
convolution descriptor
Definition: dnnl_types.h:2367
dnnl_memory_desc_t weights_peephole_desc
Weights peephole memory descriptor.
Definition: dnnl_types.h:1811
RNN cell.
Definition: dnnl_types.h:1020
Alias for dnnl_unidirectional_left2right.
Definition: dnnl_types.h:1774
A (out-of-place) concat primitive.
Definition: dnnl_types.h:896
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:1192
dnnl_dims_t dilates
Convolution dilates in each spatial dimension.
Definition: dnnl_types.h:1393
const struct dnnl_stream * const_dnnl_stream_t
A constant execution stream handle.
Definition: dnnl_types.h:2426
2D RNN statistics tensor, an alias to dnnl_ba
Definition: dnnl_types.h:478
5D CNN activations tensor, an alias to dnnl_acdeb
Definition: dnnl_types.h:492
Intel AVX-512 and Intel Deep Learning Boost (Intel DL Boost) support for Intel Xeon Scalable processo...
Definition: dnnl_types.h:2524
Undefined memory format tag.
Definition: dnnl_types.h:166
Reduction using mul.
Definition: dnnl_types.h:1056
permuted 5D tensor
Definition: dnnl_types.h:197
Eltwise: square root.
Definition: dnnl_types.h:965
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1660
int patch
Patch version.
Definition: dnnl_types.h:2469
dnnl_alg_kind_t alg_kind
The kind of reduction algorithm.
Definition: dnnl_types.h:1945
4D CNN activations tensor blocked by channels with block size 32, an alias to dnnl_aBcd32b ...
Definition: dnnl_types.h:609
permuted 3D tensor
Definition: dnnl_types.h:206
permuted 8D tensor
Definition: dnnl_types.h:218
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1634
source memory desc
Definition: dnnl_types.h:2389
Eltwise: swish.
Definition: dnnl_types.h:984
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1627
#define DNNL_RNN_MAX_N_PARTS
Maximum number of parts of RNN weights tensor that require separate computation.
Definition: dnnl_types.h:1221
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1939
struct dnnl_stream_attr * dnnl_stream_attr_t
An execution stream attributes handle.
Definition: dnnl_types.h:2431
Memory descriptor.
Definition: dnnl_types.h:1274
dnnl_wino_memory_format_t
Winograd-specific formats.
Definition: dnnl_types.h:1186
2D RNN statistics tensor, an alias to dnnl_ab
Definition: dnnl_types.h:476
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1688
A descriptor of a pooling operation.
Definition: dnnl_types.h:1559
dnnl_data_type_t data_type
Data type of the tensor elements.
Definition: dnnl_types.h:1294
A matrix multiplication primitive.
Definition: dnnl_types.h:926
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:1550
Eltwise: erf-based gelu.
Definition: dnnl_types.h:992
permuted 9D tensor
Definition: dnnl_types.h:219
Indicates the weights have an additional buffer, that depends on the compensation_mask.
Definition: dnnl_types.h:1247
dnnl_blocking_desc_t blocking
Description of the data layout for memory formats that use blocking.
Definition: dnnl_types.h:1312
dnnl_dims_t inner_idxs
The logical indices of the blocks, e.g.
Definition: dnnl_types.h:1182
The operation failed due to an out-of-memory condition.
Definition: dnnl_types.h:43
Backward weights propagation.
Definition: dnnl_types.h:881
5D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:340
3D CNN weights tensor, an alias to dnnl_acb
Definition: dnnl_types.h:501
dnnl_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: dnnl_types.h:1381
dnnl_memory_desc_t data_scaleshift_desc
Scale and shift data and gradient memory descriptors.
Definition: dnnl_types.h:1668
workspace memory desc
Definition: dnnl_types.h:2395
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1889
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1389
eltwise descriptor
Definition: dnnl_types.h:2370
number of inputs expected
Definition: dnnl_types.h:2345
const struct dnnl_stream_attr * const_dnnl_stream_attr_t
A constant execution stream attributes handle.
Definition: dnnl_types.h:2433
shuffle descriptor
Definition: dnnl_types.h:2369
Average pooling include padding.
Definition: dnnl_types.h:1010
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1662
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:1921
32-bit/single-precision floating point.
Definition: dnnl_types.h:70
permuted 5D tensor
Definition: dnnl_types.h:212
A structure that contains an index and a memory object, and is used to pass arguments to dnnl_primiti...
Definition: dnnl_types.h:2300
Intel AVX-512, Intel DL Boost and bfloat16 support for Intel Xeon Scalable processor family and Intel...
Definition: dnnl_types.h:2529
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1914
4D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcd8b ...
Definition: dnnl_types.h:618
struct dnnl_primitive_attr * dnnl_primitive_attr_t
A primitive descriptor attributes handle that controls primitive behavior.
Definition: dnnl_types.h:2060
lrn descriptor
Definition: dnnl_types.h:2374
dnnl_memory_desc_t src_layer_desc
Source layer memory descriptor.
Definition: dnnl_types.h:1791
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1925
4D tensor blocked by 1st and 2nd dimension with block size 8
Definition: dnnl_types.h:311
A shuffle primitive.
Definition: dnnl_types.h:894
for creating scratchpad memory
Definition: dnnl_types.h:2357
float layer_norm_epsilon
Layer normalization epsilon parameter.
Definition: dnnl_types.h:1712
dnnl_memory_desc_t diff_weights_peephole_desc
Weights gradient peephole memory descriptor.
Definition: dnnl_types.h:1838
struct dnnl_engine * dnnl_engine_t
An engine handle.
Definition: dnnl_types.h:1985
unsigned int flags
RNN cell flags.
Definition: dnnl_types.h:1845
permuted 4D tensor
Definition: dnnl_types.h:207
4D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:282
Binary max.
Definition: dnnl_types.h:1038
Unspecified format kind.
Definition: dnnl_types.h:85
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1422
2D CNN weights tensor, an alias to dnnl_ba
Definition: dnnl_types.h:497
Average pooling exclude padding.
Definition: dnnl_types.h:1012
3D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBc16b ...
Definition: dnnl_types.h:624
dnnl_alg_kind_t
Kinds of algorithms.
Definition: dnnl_types.h:942
4D CNN weights tensor, an alias to dnnl_cdba
Definition: dnnl_types.h:509
6D CNN weights tensor (incl. groups), an alias to dnnl_abdefc
Definition: dnnl_types.h:544
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1578
Reduction using max.
Definition: dnnl_types.h:1050
5D CNN weights tensor, an alias to dnnl_bacde
Definition: dnnl_types.h:519
permuted 3D tensor
Definition: dnnl_types.h:209
dnnl_rnn_flags_t
Flags for RNN cell.
Definition: dnnl_types.h:1756
dnnl_memory_desc_t diff_dst_iter_desc
Destination gradient iteration memory descriptor for hidden state.
Definition: dnnl_types.h:1832
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1572
A pooling version 2 primitive (pooling with dilation support).
Definition: dnnl_types.h:930
4D CNN weights tensor (incl. groups), an alias to dnnl_dcab
Definition: dnnl_types.h:532
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1729
An LRN primitive.
Definition: dnnl_types.h:910
A descriptor of a Local Response Normalization (LRN) operation.
Definition: dnnl_types.h:1621
dnnl_softmax_desc_t dnnl_logsoftmax_desc_t
A descriptor of a LogSoftmax operation.
Definition: dnnl_types.h:1513
int ndims
Number of dimensions.
Definition: dnnl_types.h:1276
dnnl_stream_flags_t
Stream flags.
Definition: dnnl_types.h:2411
dnnl_dim_t dnnl_dims_t[DNNL_MAX_NDIMS]
A type to describe tensor dimensions.
Definition: dnnl_types.h:1165
Undefined propagation type.
Definition: dnnl_types.h:864
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1461
Primitive or engine failed on execution.
Definition: dnnl_types.h:51
op descriptor
Definition: dnnl_types.h:2366
6D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:388
dnnl_memory_desc_t weights_iter_desc
Weights iteration memory descriptor.
Definition: dnnl_types.h:1799
const struct dnnl_post_ops * const_dnnl_post_ops_t
A constant post operation chain handle.
Definition: dnnl_types.h:2089
Eltwise: exponent.
Definition: dnnl_types.h:975
1D tensor, an alias to dnnl_a
Definition: dnnl_types.h:470
Local response normalization (LRN) across multiple channels.
Definition: dnnl_types.h:1016
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1524
resampling descriptor
Definition: dnnl_types.h:2383
const struct dnnl_primitive_attr * const_dnnl_primitive_attr_t
A constant primitive descriptor attributes handle.
Definition: dnnl_types.h:2063
A matrix multiplication primitive (internal).
Definition: dnnl_types.h:920
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1828
plain 3D tensor
Definition: dnnl_types.h:179
Use scale and shift parameters.
Definition: dnnl_types.h:1105
3D CNN activations tensor blocked by channels with block size 32, an alias to dnnl_aBc32b ...
Definition: dnnl_types.h:621
A descriptor of a Batch Normalization operation.
Definition: dnnl_types.h:1652
5D CNN weights tensor, an alias to dnnl_bcdea
Definition: dnnl_types.h:525
struct dnnl_primitive * dnnl_primitive_t
A primitive handle.
Definition: dnnl_types.h:2100
Intel Advanced Vector Extensions 2 (Intel AVX2)
Definition: dnnl_types.h:2507
3D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBc4b ...
Definition: dnnl_types.h:627
struct dnnl_stream * dnnl_stream_t
An execution stream handle.
Definition: dnnl_types.h:2424
4D CNN weights tensor, an alias to dnnl_bacd
Definition: dnnl_types.h:515
Eltwise: exponential linear unit (elu) (dst for backward)
Definition: dnnl_types.h:1000
Eltwise: exponential linear unit (elu)
Definition: dnnl_types.h:959
Forward data propagation (alias for dnnl_forward_inference).
Definition: dnnl_types.h:873
6D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:383
Binary sub.
Definition: dnnl_types.h:1044
5D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcde16b ...
Definition: dnnl_types.h:600
An opaque structure to describe a primitive descriptor.
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1370
struct dnnl_primitive_desc_iterator * dnnl_primitive_desc_iterator_t
A primitive descriptor iterator handle.
Definition: dnnl_types.h:2004
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1574
Eltwise: abs.
Definition: dnnl_types.h:963
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1459
Internal weights format for 4x3 Winograd.
Definition: dnnl_types.h:1194
Forward data propagation (training mode).
Definition: dnnl_types.h:867
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:1425
Eltwise: tanh-based gelu (alias for dnnl_eltwise_gelu_tanh)
Definition: dnnl_types.h:982
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1377
A rnn primitive.
Definition: dnnl_types.h:918
An opaque structure to describe an execution stream.
4D CNN activations tensor, an alias to dnnl_abcd
Definition: dnnl_types.h:484
A logsoftmax primitive.
Definition: dnnl_types.h:924
permuted 5D tensor
Definition: dnnl_types.h:205
The operation failed because requested functionality is not implemented.
Definition: dnnl_types.h:47
Eltwise: gelu.
Definition: dnnl_types.h:980
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1899
dnnl_memory_desc_t diff_src_iter_desc
Source gradient iter memory descriptor for hidden state.
Definition: dnnl_types.h:1820
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1536
Eltwise: hyperbolic tangent non-linearity (tanh)
Definition: dnnl_types.h:957
struct dnnl_post_ops * dnnl_post_ops_t
A post operation chain handle.
Definition: dnnl_types.h:2086
permuted 10D tensor
Definition: dnnl_types.h:220
A descriptor of resampling operation.
Definition: dnnl_types.h:1908
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1540
dnnl_prop_kind_t
Kinds of propagation.
Definition: dnnl_types.h:861
permuted 6D tensor
Definition: dnnl_types.h:216
stub
Definition: dnnl_types.h:2388
Nearest Neighbor Resampling Method.
Definition: dnnl_types.h:1046
permuted 4D tensor
Definition: dnnl_types.h:204
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1745
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:2359
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1385
dnnl_alg_kind_t alg_kind
The kind of the resampling algorithm.
Definition: dnnl_types.h:1917
dnnl_normalization_flags_t
Flags for normalization primitives.
Definition: dnnl_types.h:1070
weights grad. memory desc
Definition: dnnl_types.h:2392
A convolution primitive.
Definition: dnnl_types.h:900
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1441
memory desc of an execute argument
Definition: dnnl_types.h:2397
Backward bias propagation.
Definition: dnnl_types.h:883
5D CNN activations tensor, an alias to dnnl_abcde
Definition: dnnl_types.h:490
4D CNN weights tensor, an alias to dnnl_abcd
Definition: dnnl_types.h:507
Eltwise: logistic (dst for backward)
Definition: dnnl_types.h:1004
dnnl_memory_desc_t diff_weights_layer_desc
Weights gradient layer memory descriptor.
Definition: dnnl_types.h:1824
weights memory descriptor desc
Definition: dnnl_types.h:2391
unsigned gpu_runtime
GPU runtime.
Definition: dnnl_types.h:2472
Linear Resampling Method.
Definition: dnnl_types.h:1048
3D CNN weights tensor, an alias to dnnl_abc
Definition: dnnl_types.h:499
dnnl_cpu_isa_t
CPU instruction set flags.
Definition: dnnl_types.h:2496
Eltwise: soft_relu.
Definition: dnnl_types.h:971
plain 5D tensor
Definition: dnnl_types.h:182
dnnl_dims_t strides
Pooling kernel strides for spatial dimensions.
Definition: dnnl_types.h:1580
destination engine
Definition: dnnl_types.h:2360
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1725
Eltwise: square.
Definition: dnnl_types.h:961
float alpha
Algorithm specific parameter.
Definition: dnnl_types.h:1482