Performance library for Deep Learning
2.0.0
Go to the documentation of this file.
20 #ifndef ONEAPI_DNNL_DNNL_TYPES_H
21 #define ONEAPI_DNNL_DNNL_TYPES_H
580 dnnl_NCw16n16c = dnnl_ABc16a16b,
581 dnnl_NCdhw16n16c = dnnl_ABcde16a16b,
582 dnnl_NChw16n16c = dnnl_ABcd16a16b,
583 dnnl_NCw32n32c = dnnl_ABc32a32b,
584 dnnl_NChw32n32c = dnnl_ABcd32a32b,
585 dnnl_NCdhw32n32c = dnnl_ABcde32a32b,
588 dnnl_IOw16o16i = dnnl_BAc16a16b,
589 dnnl_IOw16i16o = dnnl_BAc16b16a,
590 dnnl_OIw16i16o = dnnl_ABc16b16a,
591 dnnl_OIw16o16i = dnnl_ABc16a16b,
592 dnnl_Oiw16o = dnnl_Abc16a,
593 dnnl_OIw4i16o4i = dnnl_ABc4b16a4b,
594 dnnl_OIw2i8o4i = dnnl_ABc2b8a4b,
595 dnnl_OIw16i16o4i = dnnl_ABc16b16a4b,
596 dnnl_OIw16i16o2i = dnnl_ABc16b16a2b,
597 dnnl_OIw4i4o = dnnl_ABc4b4a,
598 dnnl_OIw4o4i = dnnl_ABc4a4b,
599 dnnl_Oiw4o = dnnl_Abc4a,
600 dnnl_OIw8i16o2i = dnnl_ABc8b16a2b,
601 dnnl_OIw8i8o = dnnl_ABc8b8a,
602 dnnl_OIw8o16i2o = dnnl_ABc8a16b2a,
603 dnnl_IOw8o16i2o = dnnl_BAc8a16b2a,
604 dnnl_OIw8o8i = dnnl_ABc8a8b,
605 dnnl_OIw8o4i = dnnl_ABc8a4b,
606 dnnl_Owi16o = dnnl_Acb16a,
607 dnnl_OwI16o2i = dnnl_AcB16a2b,
608 dnnl_OwI16o4i = dnnl_AcB16a4b,
609 dnnl_Owi4o = dnnl_Acb4a,
610 dnnl_Owi8o = dnnl_Acb8a,
613 dnnl_IOhw16i16o = dnnl_BAcd16b16a,
614 dnnl_IOhw16o16i = dnnl_BAcd16a16b,
615 dnnl_Ohwi16o = dnnl_Acdb16a,
616 dnnl_OhwI16o2i = dnnl_AcdB16a2b,
617 dnnl_OhwI16o4i = dnnl_AcdB16a4b,
618 dnnl_Ohwi32o = dnnl_Acdb32a,
619 dnnl_Ohwi4o = dnnl_Acdb4a,
620 dnnl_Ohwi8o = dnnl_Acdb8a,
621 dnnl_OIhw16i16o = dnnl_ABcd16b16a,
622 dnnl_OIhw16o16i = dnnl_ABcd16a16b,
623 dnnl_Oihw16o = dnnl_Abcd16a,
624 dnnl_OIhw4i16o4i = dnnl_ABcd4b16a4b,
625 dnnl_OIhw16i16o4i = dnnl_ABcd16b16a4b,
626 dnnl_OIhw16i16o2i = dnnl_ABcd16b16a2b,
627 dnnl_OIhw4i4o = dnnl_ABcd4b4a,
628 dnnl_OIhw4o4i = dnnl_ABcd4a4b,
629 dnnl_Oihw4o = dnnl_Abcd4a,
630 dnnl_OIhw8i16o2i = dnnl_ABcd8b16a2b,
632 dnnl_OIhw8o16i2o = dnnl_ABcd8a16b2a,
633 dnnl_OIhw2i8o4i = dnnl_ABcd2b8a4b,
634 dnnl_IOhw8o16i2o = dnnl_BAcd8a16b2a,
635 dnnl_OIhw8o8i = dnnl_ABcd8a8b,
636 dnnl_OIhw8o4i = dnnl_ABcd8a4b,
637 dnnl_Owhi16o = dnnl_Adcb16a,
640 dnnl_Odhwi16o = dnnl_Acdeb16a,
641 dnnl_OdhwI16o2i = dnnl_AcdeB16a2b,
642 dnnl_Odhwi4o = dnnl_Acdeb4a,
643 dnnl_Odhwi8o = dnnl_Acdeb8a,
644 dnnl_OIdhw16i16o = dnnl_ABcde16b16a,
645 dnnl_OIdhw16o16i = dnnl_ABcde16a16b,
646 dnnl_Oidhw16o = dnnl_Abcde16a,
647 dnnl_OIdhw4i4o = dnnl_ABcde4b4a,
648 dnnl_OIdhw4o4i = dnnl_ABcde4a4b,
649 dnnl_Oidhw4o = dnnl_Abcde4a,
650 dnnl_OIdhw8i16o2i = dnnl_ABcde8b16a2b,
651 dnnl_OIdhw8i8o = dnnl_ABcde8b8a,
652 dnnl_OIdhw8o16i2o = dnnl_ABcde8a16b2a,
653 dnnl_IOdhw8o16i2o = dnnl_BAcde8a16b2a,
656 dnnl_OIdhw8o8i = dnnl_ABcde8a8b,
657 dnnl_OIdhw8o4i = dnnl_ABcde8a4b,
658 dnnl_IOdhw16i16o = dnnl_BAcde16b16a,
659 dnnl_OIdhw4o8i8o4i = dnnl_ABcde4a8b8a4b,
660 dnnl_IOdhw16o16i = dnnl_BAcde16a16b,
663 dnnl_Goiw16g = dnnl_Abcd16a,
664 dnnl_Goiw8g = dnnl_Abcd8a,
665 dnnl_Goiw4g = dnnl_Abcd4a,
666 dnnl_gIOw16o16i = dnnl_aCBd16b16c,
667 dnnl_gIOw16i16o = dnnl_aCBd16c16b,
668 dnnl_gOIw16i16o = dnnl_aBCd16c16b,
669 dnnl_gOIw16o16i = dnnl_aBCd16b16c,
671 dnnl_gOIw4i16o4i = dnnl_aBCd4c16b4c,
672 dnnl_gOIw2i8o4i = dnnl_aBCd2c8b4c,
673 dnnl_gOIw16i16o4i = dnnl_aBCd16c16b4c,
674 dnnl_gOIw16i16o2i = dnnl_aBCd16c16b2c,
675 dnnl_gOIw4i4o = dnnl_aBCd4c4b,
676 dnnl_gOIw4o4i = dnnl_aBCd4b4c,
678 dnnl_gOIw8i16o2i = dnnl_aBCd8c16b2c,
679 dnnl_gOIw8i8o = dnnl_aBCd8c8b,
680 dnnl_gOIw8o16i2o = dnnl_aBCd8b16c2b,
681 dnnl_gIOw8o16i2o = dnnl_aCBd8b16c2b,
682 dnnl_gOIw8o8i = dnnl_aBCd8b8c,
683 dnnl_gOIw8o4i = dnnl_aBCd8b4c,
684 dnnl_gOwi16o = dnnl_aBdc16b,
685 dnnl_gOwI16o2i = dnnl_aBdC16b2c,
686 dnnl_gOwI16o4i = dnnl_aBdC16b4c,
687 dnnl_gOwi4o = dnnl_aBdc4b,
688 dnnl_gOwi8o = dnnl_aBdc8b,
689 dnnl_Goiw32g = dnnl_Abcd32a,
690 dnnl_gOIw2i4o2i = dnnl_aBCd2c4b2c,
692 dnnl_gOIw4i8o2i = dnnl_aBCd4c8b2c,
693 dnnl_gOIw4o8i2o = dnnl_aBCd4b8c2b,
696 dnnl_gIOhw16i16o = dnnl_aCBde16c16b,
697 dnnl_gIOhw16o16i = dnnl_aCBde16b16c,
698 dnnl_gOhwi16o = dnnl_aBdec16b,
699 dnnl_gOhwI16o2i = dnnl_aBdeC16b2c,
700 dnnl_gOhwI16o4i = dnnl_aBdeC16b4c,
701 dnnl_gOhwi32o = dnnl_aBdec32b,
702 dnnl_gOhwi4o = dnnl_aBdec4b,
703 dnnl_gOhwi8o = dnnl_aBdec8b,
704 dnnl_Goihw16g = dnnl_Abcde16a,
705 dnnl_gOIhw16i16o = dnnl_aBCde16c16b,
706 dnnl_gOIhw16o16i = dnnl_aBCde16b16c,
708 dnnl_gOIhw2i8o4i = dnnl_aBCde2c8b4c,
709 dnnl_gOIhw4i16o4i = dnnl_aBCde4c16b4c,
710 dnnl_gOIhw16i16o4i = dnnl_aBCde16c16b4c,
711 dnnl_gOIhw16i16o2i = dnnl_aBCde16c16b2c,
712 dnnl_gOIhw4i4o = dnnl_aBCde4c4b,
713 dnnl_gOIhw4o4i = dnnl_aBCde4b4c,
715 dnnl_Goihw8g = dnnl_Abcde8a,
716 dnnl_Goihw4g = dnnl_Abcde4a,
717 dnnl_gOIhw8i16o2i = dnnl_aBCde8c16b2c,
718 dnnl_gOIhw8i8o = dnnl_aBCde8c8b,
719 dnnl_gOIhw8o16i2o = dnnl_aBCde8b16c2b,
720 dnnl_gIOhw8o16i2o = dnnl_aCBde8b16c2b,
721 dnnl_gOIhw8o8i = dnnl_aBCde8b8c,
722 dnnl_gOIhw8o4i = dnnl_aBCde8b4c,
723 dnnl_Goihw32g = dnnl_Abcde32a,
724 dnnl_gOwhi16o = dnnl_aBedc16b,
726 dnnl_OIw4o8i8o4i = dnnl_ABc4a8b8a4b,
727 dnnl_OIhw4o8i8o4i = dnnl_ABcd4a8b8a4b,
728 dnnl_IOw4i8o8i4o = dnnl_BAc4b8a8b4a,
729 dnnl_IOhw4i8o8i4o = dnnl_BAcd4b8a8b4a,
730 dnnl_IOdhw4i8o8i4o = dnnl_BAcde4b8a8b4a,
732 dnnl_OIhw2o8i8o2i = dnnl_ABcd2a8b8a2b,
733 dnnl_gOIw4o8i8o4i = dnnl_aBCd4b8c8b4c,
734 dnnl_gOIhw4o8i8o4i = dnnl_aBCde4b8c8b4c,
735 dnnl_gOIdhw4o8i8o4i = dnnl_aBCdef4b8c8b4c,
736 dnnl_gIOw4i8o8i4o = dnnl_aCBd4c8b8c4b,
737 dnnl_gIOhw4i8o8i4o = dnnl_aCBde4c8b8c4b,
738 dnnl_gIOdhw4i8o8i4o = dnnl_aCBdef4c8b8c4b,
739 dnnl_gOIhw2o8i8o2i = dnnl_aBCde2b8c8b2c,
740 dnnl_gOIhw2i4o2i = dnnl_aBCde2c4b2c,
742 dnnl_gOIhw4i8o2i = dnnl_aBCde4c8b2c,
743 dnnl_gOIhw4o8i2o = dnnl_aBCde4b8c2b,
746 dnnl_gIOdhw16i16o = dnnl_aCBdef16c16b,
747 dnnl_gIOdhw16o16i = dnnl_aCBdef16b16c,
748 dnnl_gOdhwi16o = dnnl_aBdefc16b,
749 dnnl_gOdhwI16o2i = dnnl_aBdefC16b2c,
750 dnnl_gOdhwi4o = dnnl_aBdefc4b,
751 dnnl_gOdhwi8o = dnnl_aBdefc8b,
752 dnnl_gOIdhw16i16o = dnnl_aBCdef16c16b,
753 dnnl_gOIdhw4i16o4i = dnnl_aBCdef4c16b4c,
755 dnnl_gOIdhw16o16i = dnnl_aBCdef16b16c,
757 dnnl_gOIdhw4i4o = dnnl_aBCdef4c4b,
758 dnnl_gOIdhw4o4i = dnnl_aBCdef4b4c,
760 dnnl_gOIdhw8i16o2i = dnnl_aBCdef8c16b2c,
761 dnnl_gOIdhw8i8o = dnnl_aBCdef8c8b,
762 dnnl_gOIdhw8o16i2o = dnnl_aBCdef8b16c2b,
763 dnnl_gIOdhw8o16i2o = dnnl_aCBdef8b16c2b,
764 dnnl_gOIdhw8o8i = dnnl_aBCdef8b8c,
765 dnnl_gOIdhw8o4i = dnnl_aBCdef8b4c,
766 dnnl_Goidhw16g = dnnl_Abcdef16a,
767 dnnl_Goidhw32g = dnnl_Abcdef32a,
768 dnnl_gOIdhw2i4o2i = dnnl_aBCdef2c4b2c,
769 dnnl_gOIdhw4i8o2i = dnnl_aBCdef4c8b2c,
771 dnnl_gOIdhw4o8i2o = dnnl_aBCdef4b8c2b,
1047 #define DNNL_MAX_NDIMS 12
1051 #define DNNL_RUNTIME_DIM_VAL INT64_MIN
1056 #define DNNL_RUNTIME_SIZE_VAL ((size_t)DNNL_RUNTIME_DIM_VAL)
1060 static const union {
1063 } DNNL_RUNTIME_F32_VAL_REP = {0x7fc000d0};
1068 #define DNNL_RUNTIME_F32_VAL (DNNL_RUNTIME_F32_VAL_REP.f)
1071 static const int DNNL_RUNTIME_S32_VAL_REP = INT32_MIN;
1076 #define DNNL_RUNTIME_S32_VAL DNNL_RUNTIME_S32_VAL_REP
1130 dnnl_packed_format_undef = 0,
1133 } dnnl_rnn_packed_memory_format_t;
1137 #define DNNL_RNN_MAX_N_PARTS 4
1141 dnnl_rnn_packed_memory_format_t format;
1148 size_t offset_compensation;
1155 dnnl_memory_extra_flag_none = 0x0U,
1164 dnnl_memory_extra_flag_scale_adjust = 0x2U,
1165 dnnl_memory_extra_flag_gpu_rnn_u8s8_compensation = 0x4U,
1166 dnnl_memory_extra_flag_compensation_conv_asymmetric_src = 0x8U,
1249 #define DNNL_MEMORY_NONE (NULL)
1253 #define DNNL_MEMORY_ALLOCATE ((void *)(size_t)-1)
1876 typedef const struct dnnl_engine *const_dnnl_engine_t;
1992 #define DNNL_ARG_SRC_0 1
1993 #define DNNL_ARG_SRC DNNL_ARG_SRC_0
1996 #define DNNL_ARG_SRC_LAYER DNNL_ARG_SRC_0
1999 #define DNNL_ARG_FROM DNNL_ARG_SRC_0
2004 #define DNNL_ARG_SRC_1 2
2005 #define DNNL_ARG_SRC_ITER DNNL_ARG_SRC_1
2010 #define DNNL_ARG_SRC_2 3
2011 #define DNNL_ARG_SRC_ITER_C DNNL_ARG_SRC_2
2016 #define DNNL_ARG_DST_0 17
2017 #define DNNL_ARG_DST DNNL_ARG_DST_0
2020 #define DNNL_ARG_TO DNNL_ARG_DST_0
2023 #define DNNL_ARG_DST_LAYER DNNL_ARG_DST_0
2027 #define DNNL_ARG_DST_1 18
2028 #define DNNL_ARG_DST_ITER DNNL_ARG_DST_1
2033 #define DNNL_ARG_DST_2 19
2034 #define DNNL_ARG_DST_ITER_C DNNL_ARG_DST_2
2039 #define DNNL_ARG_WEIGHTS_0 33
2040 #define DNNL_ARG_WEIGHTS DNNL_ARG_WEIGHTS_0
2043 #define DNNL_ARG_SCALE_SHIFT DNNL_ARG_WEIGHTS_0
2046 #define DNNL_ARG_WEIGHTS_LAYER DNNL_ARG_WEIGHTS_0
2051 #define DNNL_ARG_WEIGHTS_1 34
2052 #define DNNL_ARG_WEIGHTS_ITER DNNL_ARG_WEIGHTS_1
2057 #define DNNL_ARG_WEIGHTS_2 35
2058 #define DNNL_ARG_WEIGHTS_PEEPHOLE DNNL_ARG_WEIGHTS_2
2063 #define DNNL_ARG_WEIGHTS_3 36
2064 #define DNNL_ARG_WEIGHTS_PROJECTION DNNL_ARG_WEIGHTS_3
2069 #define DNNL_ARG_BIAS 41
2072 #define DNNL_ARG_MEAN 49
2073 #define DNNL_ARG_VARIANCE 50
2078 #define DNNL_ARG_WORKSPACE 64
2079 #define DNNL_ARG_SCRATCHPAD 80
2083 #define DNNL_ARG_DIFF_SRC_0 129
2084 #define DNNL_ARG_DIFF_SRC DNNL_ARG_DIFF_SRC_0
2087 #define DNNL_ARG_DIFF_SRC_LAYER DNNL_ARG_DIFF_SRC_0
2092 #define DNNL_ARG_DIFF_SRC_1 130
2093 #define DNNL_ARG_DIFF_SRC_ITER DNNL_ARG_DIFF_SRC_1
2098 #define DNNL_ARG_DIFF_SRC_2 131
2099 #define DNNL_ARG_DIFF_SRC_ITER_C DNNL_ARG_DIFF_SRC_2
2104 #define DNNL_ARG_DIFF_DST_0 145
2105 #define DNNL_ARG_DIFF_DST DNNL_ARG_DIFF_DST_0
2108 #define DNNL_ARG_DIFF_DST_LAYER DNNL_ARG_DIFF_DST_0
2113 #define DNNL_ARG_DIFF_DST_1 146
2114 #define DNNL_ARG_DIFF_DST_ITER DNNL_ARG_DIFF_DST_1
2119 #define DNNL_ARG_DIFF_DST_2 147
2120 #define DNNL_ARG_DIFF_DST_ITER_C DNNL_ARG_DIFF_DST_2
2125 #define DNNL_ARG_DIFF_WEIGHTS_0 161
2126 #define DNNL_ARG_DIFF_WEIGHTS DNNL_ARG_DIFF_WEIGHTS_0
2129 #define DNNL_ARG_DIFF_SCALE_SHIFT DNNL_ARG_DIFF_WEIGHTS_0
2132 #define DNNL_ARG_DIFF_WEIGHTS_LAYER DNNL_ARG_DIFF_WEIGHTS_0
2137 #define DNNL_ARG_DIFF_WEIGHTS_1 162
2138 #define DNNL_ARG_DIFF_WEIGHTS_ITER DNNL_ARG_DIFF_WEIGHTS_1
2143 #define DNNL_ARG_DIFF_WEIGHTS_2 163
2144 #define DNNL_ARG_DIFF_WEIGHTS_PEEPHOLE DNNL_ARG_DIFF_WEIGHTS_2
2149 #define DNNL_ARG_DIFF_WEIGHTS_3 164
2150 #define DNNL_ARG_DIFF_WEIGHTS_PROJECTION DNNL_ARG_DIFF_WEIGHTS_3
2155 #define DNNL_ARG_DIFF_BIAS 169
2158 #define DNNL_ARG_ATTR_OUTPUT_SCALES 513
2162 #define DNNL_ARG_MULTIPLE_SRC 1024
2163 #define DNNL_ARG_MULTIPLE_DST 2048
2168 #define DNNL_ARG_ATTR_ZERO_POINTS 4096
2172 #define DNNL_ARG_ATTR_POST_OP_DW 8192
2175 #define DNNL_ARG_ATTR_MULTIPLE_POST_OP_BASE 16384
2179 #define DNNL_ARG_ATTR_MULTIPLE_POST_OP(idx) \
2180 (DNNL_ARG_ATTR_MULTIPLE_POST_OP_BASE * ((idx) + 1))
2286 dnnl_query_max = 0x7fff,
2320 #define DNNL_RUNTIME_NONE 0u
2323 #define DNNL_RUNTIME_SEQ 1u
2326 #define DNNL_RUNTIME_OMP 2u
2329 #define DNNL_RUNTIME_TBB 4u
2332 #define DNNL_RUNTIME_THREADPOOL 8u
2335 #define DNNL_RUNTIME_OCL 256u
2338 #define DNNL_RUNTIME_SYCL 512u
2341 #define DNNL_RUNTIME_DPCPP DNNL_RUNTIME_SYCL
2355 #define DNNL_JIT_PROFILE_NONE 0u
2358 #define DNNL_JIT_PROFILE_VTUNE 1u
2361 #define DNNL_JIT_PROFILE_LINUX_PERFMAP 2u
2364 #define DNNL_JIT_PROFILE_LINUX_JITDUMP 4u
2368 #define DNNL_JIT_PROFILE_LINUX_JITDUMP_USE_TSC 8u
2371 #define DNNL_JIT_PROFILE_LINUX_PERF \
2372 (DNNL_JIT_PROFILE_LINUX_JITDUMP | DNNL_JIT_PROFILE_LINUX_PERFMAP)
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1514
@ dnnl_query_time_estimate_f64
runtime estimation (seconds)
Definition: dnnl_types.h:2235
@ dnnl_query_reorder_dst_engine
destination engine
Definition: dnnl_types.h:2247
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1438
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1688
@ dnnl_aBcdef4b
6D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:364
@ dnnl_dhwigo
6D CNN weights tensor (incl. groups), an alias to dnnl_defcab
Definition: dnnl_types.h:504
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1289
@ dnnl_scratchpad_mode_library
The library manages the scratchpad allocation according to the policy specified by the DNNL_ENABLE_CO...
Definition: dnnl_types.h:1930
@ dnnl_goidhw
6D CNN weights tensor (incl. groups), an alias to dnnl_abcdef
Definition: dnnl_types.h:500
@ dnnl_wino_wei_aaOIoi
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:1107
@ dnnl_io
2D CNN weights tensor, an alias to dnnl_ba
Definition: dnnl_types.h:459
dnnl_dims_t strides
Convolution strides in each spatial dimension.
Definition: dnnl_types.h:1305
@ dnnl_nc
2D CNN activations tensor, an alias to dnnl_ab
Definition: dnnl_types.h:434
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1373
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1798
@ dnnl_s32
32-bit signed integer.
Definition: dnnl_types.h:72
@ dnnl_x
1D tensor, an alias to dnnl_a
Definition: dnnl_types.h:432
@ dnnl_eltwise_round
Eltwise: round.
Definition: dnnl_types.h:913
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1547
Description of tensor of packed weights for rnn.
Definition: dnnl_types.h:1140
@ dnnl_eltwise_relu_use_dst_for_bwd
Eltwise: ReLU (dst for backward)
Definition: dnnl_types.h:915
float layer_norm_epsilon
Layer normalization epsilon parameter.
Definition: dnnl_types.h:1599
dnnl_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: dnnl_types.h:1624
@ dnnl_query_pooling_d
pooling descriptor
Definition: dnnl_types.h:2259
@ dnnl_ABcde2b8a4b
5D tensor blocked by 1st dimension with block size 8
Definition: dnnl_types.h:304
@ dnnl_wino_wei_aaOio
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:1108
dnnl_alg_kind_t alg_kind
The kind of the convolution algorithm.
Definition: dnnl_types.h:1287
@ dnnl_reduction_mul
Reduction using mul.
Definition: dnnl_types.h:973
dnnl_alg_kind_t alg_kind
The kind of pooling algorithm.
Definition: dnnl_types.h:1446
@ dnnl_aBCde2b4c2b
5D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:352
@ dnnl_query_memory_consumption_s64
memory consumption – extra
Definition: dnnl_types.h:2236
@ dnnl_s8
8-bit signed integer.
Definition: dnnl_types.h:74
dnnl_format_tag_t
Memory format tag specification.
Definition: dnnl_types.h:164
@ dnnl_f16
16-bit/half-precision floating point.
Definition: dnnl_types.h:66
@ dnnl_inner_product
An inner product primitive.
Definition: dnnl_types.h:837
@ dnnl_unimplemented
The operation failed because requested functionality is not implemented.
Definition: dnnl_types.h:47
An opaque structure to describe a memory.
@ dnnl_decab
permuted 5D tensor
Definition: dnnl_types.h:211
An opaque structure to describe a primitive descriptor iterator.
@ dnnl_batch_normalization
A batch normalization primitive.
Definition: dnnl_types.h:833
@ dnnl_query_logsoftmax_d
logsoftmax descriptor
Definition: dnnl_types.h:2267
struct dnnl_stream * dnnl_stream_t
An execution stream handle.
Definition: dnnl_types.h:2310
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1441
@ dnnl_abcdefghji
permuted 10D tensor
Definition: dnnl_types.h:218
dnnl_status_t
Status values returned by the library functions.
Definition: dnnl_types.h:39
@ dnnl_query_reorder_src_engine
source engine
Definition: dnnl_types.h:2246
@ dnnl_wino_undef
Undefined memory format, used for empty memory descriptors.
Definition: dnnl_types.h:1105
dnnl_rnn_direction_t direction
The direction of RNN primitive execution.
Definition: dnnl_types.h:1676
@ dnnl_memory_extra_flag_compensation_conv_s8s8
Indicates the weights have an additional buffer, that depends on the compensation_mask.
Definition: dnnl_types.h:1163
@ dnnl_softmax
A softmax primitive.
Definition: dnnl_types.h:827
@ dnnl_normalization_flags_none
Use no normalization flags.
Definition: dnnl_types.h:996
@ dnnl_query_rnn_d
rnn descriptor
Definition: dnnl_types.h:2264
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1630
unsigned int flags
RNN cell flags.
Definition: dnnl_types.h:1732
@ dnnl_cn
2D CNN activations tensor, an alias to dnnl_ba
Definition: dnnl_types.h:436
#define DNNL_MAX_NDIMS
Maximum number of dimensions a tensor can have.
Definition: dnnl_types.h:1047
@ dnnl_ldnc
4D RNN states tensor in the format (num_layers, num_directions, batch, state channels).
Definition: dnnl_types.h:512
@ dnnl_scratchpad_mode_user
The user manages the scratchpad allocation by querying and providing the scratchpad memory to primiti...
Definition: dnnl_types.h:1935
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1545
@ dnnl_defcab
permuted 6D tensor
Definition: dnnl_types.h:212
@ dnnl_abcdefghijlk
permuted 12D tensor
Definition: dnnl_types.h:220
@ dnnl_abcdefghijk
plain 11D tensor
Definition: dnnl_types.h:188
@ dnnl_aBcde16b
5D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:306
An opaque structure to describe an engine.
dnnl_memory_desc_t src_iter_c_desc
Source iteration memory descriptor for cell state.
Definition: dnnl_types.h:1682
dnnl_memory_desc_t stat_desc
Statistics memory descriptor.
Definition: dnnl_types.h:1560
@ dnnl_eltwise_relu
Eltwise: ReLU.
Definition: dnnl_types.h:874
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1485
@ dnnl_acb
permuted 3D tensor
Definition: dnnl_types.h:195
A descriptor of a matrix multiplication operation.
Definition: dnnl_types.h:1773
dnnl_memory_desc_t diff_weights_projection_desc
Weights gradient projection memory descriptor.
Definition: dnnl_types.h:1729
@ dnnl_eltwise_abs
Eltwise: abs.
Definition: dnnl_types.h:882
float p
Algorithm specific parameters.
Definition: dnnl_types.h:1848
dnnl_dim_t group_size
Number of groups.
Definition: dnnl_types.h:1343
@ dnnl_oihw
4D CNN weights tensor, an alias to dnnl_abcd
Definition: dnnl_types.h:469
dnnl_normalization_flags_t
Flags for normalization primitives.
Definition: dnnl_types.h:987
@ dnnl_eltwise_sqrt_use_dst_for_bwd
Eltwise: square root (dst for backward)
Definition: dnnl_types.h:921
@ dnnl_shuffle
A shuffle primitive.
Definition: dnnl_types.h:815
@ dnnl_query_shuffle_d
shuffle descriptor
Definition: dnnl_types.h:2256
A descriptor of a convolution operation.
Definition: dnnl_types.h:1277
dnnl_primitive_kind_t
Kinds of primitives.
Definition: dnnl_types.h:809
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1481
dnnl_rnn_flags_t
Flags for RNN cell.
Definition: dnnl_types.h:1643
@ dnnl_ldigo
5D RNN weights tensor in the format (num_layers, num_directions, input_channels, num_gates,...
Definition: dnnl_types.h:519
@ dnnl_pooling_max
Max pooling.
Definition: dnnl_types.h:927
A structure that contains an index and a memory object, and is used to pass arguments to dnnl_primiti...
Definition: dnnl_types.h:2187
dnnl_stream_flags_t
Stream flags.
Definition: dnnl_types.h:2297
dnnl_query_t
Primitive descriptor query specification.
Definition: dnnl_types.h:2226
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1408
float lrn_alpha
LRN alpha parameter.
Definition: dnnl_types.h:1526
@ dnnl_bf16
non-standard 16-bit (bfloat16 w/ 7 bit mantissa) floating point.
Definition: dnnl_types.h:68
@ dnnl_nhwc
4D CNN activations tensor, an alias to dnnl_acdb
Definition: dnnl_types.h:448
A descriptor for an RNN operation.
Definition: dnnl_types.h:1665
dnnl_rnn_direction_t
A direction of RNN primitive execution.
Definition: dnnl_types.h:1649
@ dnnl_bcdea
permuted 5D tensor
Definition: dnnl_types.h:206
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1291
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1293
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1301
@ dnnl_sum
A sum primitive.
Definition: dnnl_types.h:819
@ dnnl_oidhw
5D CNN weights tensor, an alias to dnnl_abcde
Definition: dnnl_types.h:479
dnnl_blocking_desc_t blocking
Description of the data layout for memory formats that use blocking.
Definition: dnnl_types.h:1226
@ dnnl_backward_weights
Backward weights propagation.
Definition: dnnl_types.h:802
@ dnnl_a
plain 1D tensor
Definition: dnnl_types.h:177
const struct dnnl_stream * const_dnnl_stream_t
A constant execution stream handle.
Definition: dnnl_types.h:2312
A descriptor of an inner product operation.
Definition: dnnl_types.h:1609
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1776
@ dnnl_gpu
GPU engine.
Definition: dnnl_types.h:1865
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1580
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1626
dnnl_memory_desc_t weights_projection_desc
Weights projection memory descriptor.
Definition: dnnl_types.h:1702
int softmax_axis
The axis along which to perform the softmax.
Definition: dnnl_types.h:1417
@ dnnl_query_diff_weights_md
weights grad. memory desc
Definition: dnnl_types.h:2278
@ dnnl_query_prop_kind
propagation kind
Definition: dnnl_types.h:2249
dnnl_dims_t strides
Pooling kernel strides for spatial dimensions.
Definition: dnnl_types.h:1489
@ dnnl_abced
permuted 5D tensor
Definition: dnnl_types.h:213
@ dnnl_eltwise_logistic
Eltwise: logistic.
Definition: dnnl_types.h:892
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1497
@ dnnl_eltwise
An element-wise primitive.
Definition: dnnl_types.h:825
@ dnnl_stream_in_order
In-order execution.
Definition: dnnl_types.h:2299
@ dnnl_aBc16b
3D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:229
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1582
@ dnnl_oiw
3D CNN weights tensor, an alias to dnnl_abc
Definition: dnnl_types.h:461
@ dnnl_convolution_auto
Convolution algorithm(either direct or Winograd) is chosen just in time.
Definition: dnnl_types.h:868
@ dnnl_eltwise_sqrt
Eltwise: square root.
Definition: dnnl_types.h:884
@ dnnl_cdba
permuted 4D tensor
Definition: dnnl_types.h:208
@ dnnl_cpu_isa_avx512_core
Intel AVX-512 subset for Intel Xeon Scalable processor family and Intel Core processor family.
Definition: dnnl_types.h:2398
@ dnnl_reduction_norm_lp_power_p_max
Reduction using lp norm without final pth-root.
Definition: dnnl_types.h:981
@ dnnl_eltwise_bounded_relu
Eltwise: bounded_relu.
Definition: dnnl_types.h:888
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1668
@ dnnl_hwio
4D CNN weights tensor, an alias to dnnl_cdba
Definition: dnnl_types.h:471
@ dnnl_forward_inference
Forward data propagation (inference mode).
Definition: dnnl_types.h:792
@ dnnl_query_impl_info_str
for creating scratchpad memory
Definition: dnnl_types.h:2244
@ dnnl_query_dst_md
destination memory desc
Definition: dnnl_types.h:2279
@ dnnl_query_resampling_d
resampling descriptor
Definition: dnnl_types.h:2269
@ dnnl_query_inner_product_d
inner product descriptor
Definition: dnnl_types.h:2263
@ dnnl_rnn_flags_undef
Undefined RNN flags.
Definition: dnnl_types.h:1645
@ dnnl_nCdhw16c
5D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcde16b
Definition: dnnl_types.h:549
@ dnnl_query_convolution_d
convolution descriptor
Definition: dnnl_types.h:2254
@ dnnl_cpu_isa_avx512_core_amx
Intel AVX-512, Intel DL Boost and bfloat16 support and Intel AMX with 8-bit integer and bfloat16 supp...
Definition: dnnl_types.h:2413
@ dnnl_aBCdef2c8b4c
6D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:359
@ dnnl_bcda
permuted 4D tensor
Definition: dnnl_types.h:205
int major
Major version.
Definition: dnnl_types.h:2346
@ dnnl_eltwise_gelu_tanh
Eltwise: gelu.
Definition: dnnl_types.h:899
@ dnnl_bidirectional_concat
Bidirectional execution of RNN primitive with concatenation of the results.
Definition: dnnl_types.h:1656
A descriptor of a pooling operation.
Definition: dnnl_types.h:1435
@ dnnl_aBcd32b
4D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:261
@ dnnl_ba
permuted 2D tensor
Definition: dnnl_types.h:200
dnnl_data_type_t
Data type specification.
Definition: dnnl_types.h:62
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1448
@ dnnl_lrn_within_channel
LRN within a single channel.
Definition: dnnl_types.h:937
struct dnnl_engine * dnnl_engine_t
An engine handle.
Definition: dnnl_types.h:1872
dnnl_memory_desc_t data_scaleshift_desc
Scale and shift data and gradient memory descriptors.
Definition: dnnl_types.h:1590
@ dnnl_reduction_norm_lp_sum
Reduction using lp norm.
Definition: dnnl_types.h:979
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1471
@ dnnl_binary_mul
Binary mul.
Definition: dnnl_types.h:955
@ dnnl_ihwo
4D CNN weights tensor, an alias to dnnl_bcda
Definition: dnnl_types.h:475
dnnl_memory_desc_t src_layer_desc
Source layer memory descriptor.
Definition: dnnl_types.h:1678
@ dnnl_format_tag_undef
Undefined memory format tag.
Definition: dnnl_types.h:166
@ dnnl_binary_min
Binary min.
Definition: dnnl_types.h:959
dnnl_memory_desc_t diff_weights_peephole_desc
Weights gradient peephole memory descriptor.
Definition: dnnl_types.h:1725
@ dnnl_format_kind_rnn_packed
Packed weights format used in RNN.
Definition: dnnl_types.h:93
@ dnnl_goiw
4D CNN weights tensor (incl. groups), an alias to dnnl_abcd
Definition: dnnl_types.h:490
const struct dnnl_primitive_desc_iterator * const_dnnl_primitive_desc_iterator_t
A constant primitive descriptor iterator handle.
Definition: dnnl_types.h:1894
@ dnnl_use_scaleshift
Use scale and shift parameters.
Definition: dnnl_types.h:1022
@ dnnl_eltwise_log
Eltwise: natural logarithm.
Definition: dnnl_types.h:905
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1834
@ dnnl_query_layer_normalization_d
layer normalization descriptor
Definition: dnnl_types.h:2262
@ dnnl_ldoi
4D LSTM projection tensor in the format (num_layers, num_directions, num_channels_in_recurrent_projec...
Definition: dnnl_types.h:532
int minor
Minor version.
Definition: dnnl_types.h:2347
dnnl_memory_desc_t stat_desc
Mean and variance data memory descriptors.
Definition: dnnl_types.h:1597
@ dnnl_ABcd8b8a
4D tensor blocked by 1st and 2nd dimension with block size 8
Definition: dnnl_types.h:288
@ dnnl_resampling_linear
Linear Resampling Method.
Definition: dnnl_types.h:965
dnnl_dims_t inner_blks
The size of the blocks, e.g. {4, 16, 4} in case of OIhw_4i16o4i
Definition: dnnl_types.h:1096
dnnl_memory_desc_t diff_dst_iter_desc
Destination gradient iteration memory descriptor for hidden state.
Definition: dnnl_types.h:1719
@ dnnl_acbd
plain 4D tensor
Definition: dnnl_types.h:181
@ dnnl_dhwio
5D CNN weights tensor, an alias to dnnl_cdeba
Definition: dnnl_types.h:483
@ dnnl_forward_training
Forward data propagation (training mode).
Definition: dnnl_types.h:788
@ dnnl_primitive_kind_max
Parameter to allow internal only primitives without undefined behavior.
Definition: dnnl_types.h:857
dnnl_dims_t kernel
Pooling kernel spatial dimensions.
Definition: dnnl_types.h:1491
@ dnnl_eltwise_square
Eltwise: square.
Definition: dnnl_types.h:880
@ dnnl_bac
permuted 3D tensor
Definition: dnnl_types.h:201
@ dnnl_fuse_norm_relu
Fuse with ReLU.
Definition: dnnl_types.h:1035
@ dnnl_bacde
permuted 5D tensor
Definition: dnnl_types.h:203
@ dnnl_cpu_isa_avx512_mic_4ops
Intel AVX-512 subset for Intel Xeon Phi processors 7235, 7285, 7295 Series.
Definition: dnnl_types.h:2394
@ dnnl_tn
2D RNN statistics tensor, an alias to dnnl_ab
Definition: dnnl_types.h:438
const struct dnnl_primitive_desc * const_dnnl_primitive_desc_t
A constant primitive descriptor handle.
Definition: dnnl_types.h:1905
dnnl_memory_desc_t weights_layer_desc
Weights layer memory descriptor.
Definition: dnnl_types.h:1684
dnnl_memory_desc_t weights_peephole_desc
Weights peephole memory descriptor.
Definition: dnnl_types.h:1698
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1483
@ dnnl_format_kind_wino
Weights format used in 8bit Winograd convolution.
Definition: dnnl_types.h:91
const struct dnnl_post_ops * const_dnnl_post_ops_t
A constant post operation chain handle.
Definition: dnnl_types.h:1976
dnnl_dims_t strides
The strides between the outermost blocks.
Definition: dnnl_types.h:1090
@ dnnl_convolution_winograd
Winograd convolution.
Definition: dnnl_types.h:866
@ dnnl_iodhw
5D CNN weights tensor, an alias to dnnl_bacde
Definition: dnnl_types.h:481
@ dnnl_ABcde4b16a4b
5D tensor blocked by 1st dimension with block size 16
Definition: dnnl_types.h:302
@ dnnl_nChw8c
4D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcd8b
Definition: dnnl_types.h:567
dnnl_engine_kind_t
Kinds of engines.
Definition: dnnl_types.h:1859
@ dnnl_binary
A binary primitive.
Definition: dnnl_types.h:843
@ dnnl_cdeba
permuted 5D tensor
Definition: dnnl_types.h:210
dnnl_memory_t memory
Input/output memory.
Definition: dnnl_types.h:2189
@ dnnl_eltwise_tanh
Eltwise: hyperbolic tangent non-linearity (tanh)
Definition: dnnl_types.h:876
dnnl_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: dnnl_types.h:1295
@ dnnl_aBc4b
3D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:235
@ dnnl_abcde
plain 5D tensor
Definition: dnnl_types.h:182
@ dnnl_nCw8c
3D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBc8b
Definition: dnnl_types.h:579
struct dnnl_post_ops * dnnl_post_ops_t
A post operation chain handle.
Definition: dnnl_types.h:1973
@ dnnl_query_gemm_d
GEMM descriptor (internal)
Definition: dnnl_types.h:2265
dnnl_dims_t dims
Dimensions in the following order:
Definition: dnnl_types.h:1205
@ dnnl_pooling
A pooling primitive.
Definition: dnnl_types.h:829
@ dnnl_acdb
permuted 4D tensor
Definition: dnnl_types.h:198
@ dnnl_query_lrn_d
lrn descriptor
Definition: dnnl_types.h:2260
@ dnnl_backward
Backward propagation (with respect to all parameters).
Definition: dnnl_types.h:798
@ dnnl_giohw
5D CNN weights tensor (incl. groups), an alias to dnnl_acbde
Definition: dnnl_types.h:498
A descriptor of a Softmax operation.
Definition: dnnl_types.h:1405
dnnl_dims_t dilates
Convolution dilates in each spatial dimension.
Definition: dnnl_types.h:1307
@ dnnl_cpu_isa_avx512_core_bf16
Intel AVX-512, Intel DL Boost and bfloat16 support for Intel Xeon Scalable processor family and Intel...
Definition: dnnl_types.h:2408
@ dnnl_iterator_ends
Primitive iterator passed over last primitive descriptor.
Definition: dnnl_types.h:49
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1810
@ dnnl_abcdefghi
plain 9D tensor
Definition: dnnl_types.h:186
int inner_nblks
The number of innermost blocks, e.g. 3 in case of OIhw_4i16o4i_
Definition: dnnl_types.h:1094
An opaque structure to describe a primitive descriptor.
@ dnnl_abcdefghijkl
plain 12D tensor
Definition: dnnl_types.h:189
@ dnnl_nCdhw8c
5D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcde8b
Definition: dnnl_types.h:555
@ dnnl_pooling_avg
Average pooling (alias for dnnl_pooling_avg_exclude_padding)
Definition: dnnl_types.h:933
@ dnnl_vanilla_rnn
RNN cell.
Definition: dnnl_types.h:939
@ dnnl_reduction_norm_lp_power_p_sum
Reduction using lp norm without final pth-root.
Definition: dnnl_types.h:983
@ dnnl_unidirectional
Alias for dnnl_unidirectional_left2right.
Definition: dnnl_types.h:1661
@ dnnl_abdc
permuted 4D tensor
Definition: dnnl_types.h:193
@ dnnl_eltwise_pow
Eltwise: pow.
Definition: dnnl_types.h:909
@ dnnl_reduction_max
Reduction using max.
Definition: dnnl_types.h:967
@ dnnl_ldio
4D LSTM projection tensor in the format (num_layers, num_directions, num_channels_in_hidden_state,...
Definition: dnnl_types.h:529
@ dnnl_aBcd4b
4D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:263
@ dnnl_reduction_mean
Reduction using mean.
Definition: dnnl_types.h:975
@ dnnl_query_matmul_d
matrix multiplication (matmul) descriptor
Definition: dnnl_types.h:2268
struct dnnl_primitive_desc * dnnl_primitive_desc_t
A primitive descriptor handle.
Definition: dnnl_types.h:1902
const char * hash
Git hash of the sources (may be absent)
Definition: dnnl_types.h:2349
@ dnnl_query_binary_d
binary descriptor
Definition: dnnl_types.h:2266
@ dnnl_lbr_gru
GRU cell with linear before reset.
Definition: dnnl_types.h:951
@ dnnl_forward
Forward data propagation (alias for dnnl_forward_training).
Definition: dnnl_types.h:796
@ dnnl_f32
32-bit/single-precision floating point.
Definition: dnnl_types.h:70
@ dnnl_acbdef
permuted 6D tensor
Definition: dnnl_types.h:197
@ dnnl_iwo
3D CNN weights tensor, an alias to dnnl_bca
Definition: dnnl_types.h:467
@ dnnl_use_global_stats
Use global statistics.
Definition: dnnl_types.h:1009
@ dnnl_lrn_across_channels
Local response normalization (LRN) across multiple channels.
Definition: dnnl_types.h:935
@ dnnl_concat
A (out-of-place) concat primitive.
Definition: dnnl_types.h:817
@ dnnl_ntc
3D RNN data tensor in the format (batch, seq_length, input channels).
Definition: dnnl_types.h:509
@ dnnl_query_diff_dst_md
destination grad. memory desc
Definition: dnnl_types.h:2280
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1784
@ dnnl_format_kind_undef
Undefined memory format kind, used for empty memory descriptors.
Definition: dnnl_types.h:82
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1575
unsigned cpu_runtime
CPU runtime.
Definition: dnnl_types.h:2350
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1521
@ dnnl_aBcdef16b
6D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:354
@ dnnl_layer_normalization
A layer normalization primitive.
Definition: dnnl_types.h:835
dnnl_data_type_t data_type
Data type of the tensor elements.
Definition: dnnl_types.h:1208
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1303
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1786
An opaque structure to describe a primitive.
@ dnnl_abcdefgh
plain 8D tensor
Definition: dnnl_types.h:185
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1358
@ dnnl_abcdefghij
plain 10D tensor
Definition: dnnl_types.h:187
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1452
@ dnnl_cpu_isa_all
Any ISA (excepting those listed as initial support)
Definition: dnnl_types.h:2377
dnnl_memory_desc_t diff_weights_layer_desc
Weights gradient layer memory descriptor.
Definition: dnnl_types.h:1711
@ dnnl_query_op_d
op descriptor
Definition: dnnl_types.h:2253
struct dnnl_primitive_desc_iterator * dnnl_primitive_desc_iterator_t
A primitive descriptor iterator handle.
Definition: dnnl_types.h:1891
@ dnnl_out_of_memory
The operation failed due to an out-of-memory condition.
Definition: dnnl_types.h:43
int64_t dnnl_dim_t
A type to describe tensor dimension.
Definition: dnnl_types.h:1079
int axis
Axis for shuffling.
Definition: dnnl_types.h:1341
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1411
float lrn_beta
LRN beta parameter.
Definition: dnnl_types.h:1528
@ dnnl_idhwo
5D CNN weights tensor, an alias to dnnl_bcdea
Definition: dnnl_types.h:487
@ dnnl_abcdegf
permuted 7D tensor
Definition: dnnl_types.h:215
@ dnnl_abcd
plain 4D tensor
Definition: dnnl_types.h:180
@ dnnl_u8
8-bit unsigned integer.
Definition: dnnl_types.h:76
@ dnnl_ncdhw
5D CNN activations tensor, an alias to dnnl_abcde
Definition: dnnl_types.h:452
@ dnnl_query_workspace_md
workspace memory desc
Definition: dnnl_types.h:2281
@ dnnl_format_tag_last
Just a sentinel, not real memory format tag.
Definition: dnnl_types.h:427
@ dnnl_query_deconvolution_d
deconvolution descriptor
Definition: dnnl_types.h:2255
struct dnnl_memory * dnnl_memory_t
A memory handle.
Definition: dnnl_types.h:1242
@ dnnl_logsoftmax
A logsoftmax primitive.
Definition: dnnl_types.h:845
@ dnnl_format_tag_any
Undefined memory format tag.
Definition: dnnl_types.h:169
@ dnnl_deconvolution_direct
Direct deconvolution.
Definition: dnnl_types.h:870
@ dnnl_reorder
A reorder primitive.
Definition: dnnl_types.h:813
A descriptor of a Local Response Normalization (LRN) operation.
Definition: dnnl_types.h:1508
@ dnnl_stream_default_flags
Default stream configuration.
Definition: dnnl_types.h:2303
A descriptor of a shuffle operation.
Definition: dnnl_types.h:1330
@ dnnl_owi
3D CNN weights tensor, an alias to dnnl_acb
Definition: dnnl_types.h:463
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1474
dnnl_alg_kind_t activation_kind
Activation function used for vanilla_rnn cell kind.
Definition: dnnl_types.h:1735
@ dnnl_query_reduction_d
reduction descriptor
Definition: dnnl_types.h:2271
@ dnnl_backward_data
Backward data propagation.
Definition: dnnl_types.h:800
@ dnnl_acdeb
permuted 5D tensor
Definition: dnnl_types.h:199
Structure containing version information as per Semantic Versioning
Definition: dnnl_types.h:2345
A descriptor of a Batch Normalization operation.
Definition: dnnl_types.h:1539
int arg
An argument index, e.g. DNNL_ARG_SRC.
Definition: dnnl_types.h:2188
@ dnnl_eltwise_exp_use_dst_for_bwd
Eltwise: exp (dst for backward)
Definition: dnnl_types.h:925
dnnl_memory_desc_t weights_iter_desc
Weights iteration memory descriptor.
Definition: dnnl_types.h:1686
dnnl_format_kind_t format_kind
Memory format kind.
Definition: dnnl_types.h:1222
@ dnnl_ldgo
4D RNN bias tensor in the format (num_layers, num_directions, num_gates, output_channels).
Definition: dnnl_types.h:539
dnnl_dim_t dnnl_dims_t[DNNL_MAX_NDIMS]
A type to describe tensor dimensions.
Definition: dnnl_types.h:1082
dnnl_alg_kind_t alg_kind
The kind of eltwise algorithm.
Definition: dnnl_types.h:1371
dnnl_memory_desc_t diff_dst_iter_c_desc
Destination gradient iteration memory descriptor for cell state.
Definition: dnnl_types.h:1721
A descriptor of a element-wise operation.
Definition: dnnl_types.h:1352
dnnl_memory_desc_t diff_src_iter_c_desc
Source gradient iter memory descriptor for cell state.
Definition: dnnl_types.h:1709
@ dnnl_aBcd16b
4D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:255
@ dnnl_resampling_nearest
Nearest Neighbor Resampling Method.
Definition: dnnl_types.h:963
@ dnnl_rnn
A rnn primitive.
Definition: dnnl_types.h:839
@ dnnl_aBc32b
3D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:233
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1715
@ dnnl_query_num_of_outputs_s32
number of outputs expected
Definition: dnnl_types.h:2233
@ dnnl_cpu_isa_sse41
Intel Streaming SIMD Extensions 4.1 (Intel SSE4.1)
Definition: dnnl_types.h:2380
@ dnnl_abcdfe
permuted 6D tensor
Definition: dnnl_types.h:214
dnnl_format_kind_t
Memory format kind.
Definition: dnnl_types.h:80
@ dnnl_aBCd2b4c2b
4D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:300
Generic description of blocked data layout for most memory formats.
Definition: dnnl_types.h:1087
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1413
const struct dnnl_primitive * const_dnnl_primitive_t
A constant primitive handle.
Definition: dnnl_types.h:1989
@ dnnl_abdec
permuted 5D tensor
Definition: dnnl_types.h:194
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1464
@ dnnl_reduction_sum
Reduction using sum.
Definition: dnnl_types.h:971
@ dnnl_cpu_isa_avx2
Intel Advanced Vector Extensions 2 (Intel AVX2)
Definition: dnnl_types.h:2386
@ dnnl_cpu_isa_avx512_core_vnni
Intel AVX-512 and Intel Deep Learning Boost (Intel DL Boost) support for Intel Xeon Scalable processo...
Definition: dnnl_types.h:2403
int ndims
Number of dimensions.
Definition: dnnl_types.h:1190
@ dnnl_aBc8b
3D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:245
A descriptor of a Layer Normalization operation.
Definition: dnnl_types.h:1572
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1782
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1299
@ dnnl_not_required
Queried element is not required for given primitive.
Definition: dnnl_types.h:53
@ dnnl_eltwise_clip
Eltwise: clip.
Definition: dnnl_types.h:907
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1618
@ dnnl_eltwise_logistic_use_dst_for_bwd
Eltwise: logistic (dst for backward)
Definition: dnnl_types.h:923
Description of tensor of weights for winograd 2x3 convolution.
Definition: dnnl_types.h:1115
dnnl_dims_t dilation
Pooling dilations for spatial dimensions.
Definition: dnnl_types.h:1499
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1549
dnnl_memory_desc_t src_iter_desc
Source iteration memory descriptor for hidden state.
Definition: dnnl_types.h:1680
@ dnnl_abcdefg
plain 7D tensor
Definition: dnnl_types.h:184
@ dnnl_pooling_avg_include_padding
Average pooling include padding.
Definition: dnnl_types.h:929
@ dnnl_hwigo
5D CNN weights tensor (incl. groups), an alias to dnnl_decab
Definition: dnnl_types.h:496
dnnl_memory_desc_t diff_src_iter_desc
Source gradient iter memory descriptor for hidden state.
Definition: dnnl_types.h:1707
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1616
@ dnnl_deconvolution
A deconvolution primitive.
Definition: dnnl_types.h:823
@ dnnl_aBcde4b
5D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:315
dnnl_memory_desc_t data_scaleshift_desc
Scale and shift data and gradient memory descriptors.
Definition: dnnl_types.h:1555
@ dnnl_stream_out_of_order
Out-of-order execution.
Definition: dnnl_types.h:2301
@ dnnl_gemm
A matrix multiplication primitive (internal).
Definition: dnnl_types.h:841
@ dnnl_convolution
A convolution primitive.
Definition: dnnl_types.h:821
struct dnnl_primitive * dnnl_primitive_t
A primitive handle.
Definition: dnnl_types.h:1987
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1519
const struct dnnl_primitive_attr * const_dnnl_primitive_attr_t
A constant primitive descriptor attributes handle.
Definition: dnnl_types.h:1950
An opaque structure for primitive descriptor attributes.
dnnl_memory_desc_t dst_layer_desc
Destination layer memory descriptor.
Definition: dnnl_types.h:1690
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1634
@ dnnl_lrn
An LRN primitive.
Definition: dnnl_types.h:831
@ dnnl_query_src_md
source memory desc
Definition: dnnl_types.h:2275
@ dnnl_query_pooling_v2_d
pooling version 2 descriptor
Definition: dnnl_types.h:2270
dnnl_softmax_desc_t dnnl_logsoftmax_desc_t
A descriptor of a LogSoftmax operation.
Definition: dnnl_types.h:1427
#define DNNL_RNN_MAX_N_PARTS
Maximum number of parts of RNN weights tensor that require separate computation.
Definition: dnnl_types.h:1137
dnnl_scratchpad_mode_t
Scratchpad mode.
Definition: dnnl_types.h:1913
dnnl_wino_desc_t wino_desc
Tensor of weights for integer 8bit winograd convolution.
Definition: dnnl_types.h:1228
@ dnnl_data_type_undef
Undefined data type, used for empty memory descriptors.
Definition: dnnl_types.h:64
@ dnnl_nCdhw32c
5D CNN activations tensor blocked by channels with block size 32, an alias to dnnl_aBcde32b
Definition: dnnl_types.h:546
@ dnnl_query_engine
execution engine
Definition: dnnl_types.h:2229
dnnl_wino_memory_format_t
Winograd-specific formats.
Definition: dnnl_types.h:1103
@ dnnl_query_softmax_d
softmax descriptor
Definition: dnnl_types.h:2258
A descriptor of resampling operation.
Definition: dnnl_types.h:1795
float batch_norm_epsilon
Batch normalization epsilon parameter.
Definition: dnnl_types.h:1562
@ dnnl_invalid_arguments
The operation failed because of incorrect function arguments.
Definition: dnnl_types.h:45
@ dnnl_eltwise_elu_use_dst_for_bwd
Eltwise: exponential linear unit (elu) (dst for backward)
Definition: dnnl_types.h:919
@ dnnl_cpu
CPU engine.
Definition: dnnl_types.h:1863
An opaque structure for a chain of post operations.
@ dnnl_query_undef
no query
Definition: dnnl_types.h:2227
@ dnnl_eltwise_swish
Eltwise: swish.
Definition: dnnl_types.h:903
@ dnnl_ndhwc
5D CNN activations tensor, an alias to dnnl_acdeb
Definition: dnnl_types.h:454
dnnl_memory_desc_t diff_dst_layer_desc
Destination gradient layer memory descriptor.
Definition: dnnl_types.h:1717
@ dnnl_abcdefhg
permuted 8D tensor
Definition: dnnl_types.h:216
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1280
dnnl_alg_kind_t alg_kind
The kind of reduction algorithm.
Definition: dnnl_types.h:1832
dnnl_dims_t kernel
Pooling kernel spatial dimensions.
Definition: dnnl_types.h:1458
@ dnnl_wino_wei_OBaaIBOIio
Internal weights format for 4x3 Winograd.
Definition: dnnl_types.h:1111
@ dnnl_binary_div
Binary div.
Definition: dnnl_types.h:961
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1622
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1333
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1808
@ dnnl_eltwise_gelu_erf
Eltwise: erf-based gelu.
Definition: dnnl_types.h:911
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1297
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1578
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1542
Memory descriptor.
Definition: dnnl_types.h:1188
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1758
@ dnnl_backward_bias
Backward bias propagation.
Definition: dnnl_types.h:804
void * dnnl_op_desc_t
A pointer to any of the operation descriptors.
Definition: dnnl_types.h:1263
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1620
@ dnnl_ncw
3D CNN activations tensor, an alias to dnnl_abc
Definition: dnnl_types.h:442
@ dnnl_matmul
A matrix multiplication primitive.
Definition: dnnl_types.h:847
int patch
Patch version.
Definition: dnnl_types.h:2348
dnnl_cpu_isa_t
CPU instruction set flags.
Definition: dnnl_types.h:2375
@ dnnl_query_some_md
stub
Definition: dnnl_types.h:2274
const struct dnnl_memory * const_dnnl_memory_t
A constant memory handle.
Definition: dnnl_types.h:1245
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1778
@ dnnl_nChw4c
4D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcd4b
Definition: dnnl_types.h:564
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1612
dnnl_memory_desc_t diff_desc
Source and Destination of gradient memory descriptor.
Definition: dnnl_types.h:1415
@ dnnl_oi
2D CNN weights tensor, an alias to dnnl_ab
Definition: dnnl_types.h:457
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1375
@ dnnl_ohwi
4D CNN weights tensor, an alias to dnnl_acdb
Definition: dnnl_types.h:473
@ dnnl_bacd
permuted 4D tensor
Definition: dnnl_types.h:202
@ dnnl_format_kind_any
Unspecified format kind.
Definition: dnnl_types.h:85
@ dnnl_tnc
3D RNN data tensor in the format (seq_length, batch, input channels).
Definition: dnnl_types.h:507
@ dnnl_nChw16c
4D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcd16b
Definition: dnnl_types.h:561
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1336
@ dnnl_query_eltwise_d
eltwise descriptor
Definition: dnnl_types.h:2257
struct dnnl_primitive_attr * dnnl_primitive_attr_t
A primitive descriptor attributes handle that controls primitive behavior.
Definition: dnnl_types.h:1947
@ dnnl_binary_max
Binary max.
Definition: dnnl_types.h:957
@ dnnl_cba
permuted 3D tensor
Definition: dnnl_types.h:207
A descriptor of reduction operation.
Definition: dnnl_types.h:1823
@ dnnl_query_num_of_inputs_s32
number of inputs expected
Definition: dnnl_types.h:2232
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1812
@ dnnl_acbde
permuted 5D tensor
Definition: dnnl_types.h:196
@ dnnl_dcab
permuted 4D tensor
Definition: dnnl_types.h:209
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1836
dnnl_alg_kind_t
Kinds of algorithms.
Definition: dnnl_types.h:861
@ dnnl_deconvolution_winograd
Winograd deconvolution.
Definition: dnnl_types.h:872
const void * const_dnnl_op_desc_t
A pointer to any of the operation descriptors (constant variant).
Definition: dnnl_types.h:1265
@ dnnl_cpu_isa_avx512_mic
Intel Advanced Vector Extensions 512 (Intel AVX-512) subset for Intel Xeon Phi processors x200 Series...
Definition: dnnl_types.h:2390
dnnl_dims_t padded_offsets
Per-dimension offset from the padding to actual data, the top-level tensor with offsets applied must ...
Definition: dnnl_types.h:1215
@ dnnl_ldgoi
5D RNN weights tensor in the format (num_layers, num_directions, num_gates, output_channels,...
Definition: dnnl_types.h:526
@ dnnl_success
The operation was successful.
Definition: dnnl_types.h:41
dnnl_dims_t padded_dims
Size of the data including padding in each dimension.
Definition: dnnl_types.h:1211
@ dnnl_eltwise_exp
Eltwise: exponent.
Definition: dnnl_types.h:894
@ dnnl_abcdef
plain 6D tensor
Definition: dnnl_types.h:183
@ dnnl_aBCdef2b4c2b
6D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:362
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1487
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1750
@ dnnl_goihw
5D CNN weights tensor (incl. groups), an alias to dnnl_abcde
Definition: dnnl_types.h:494
@ dnnl_bidirectional_sum
Bidirectional execution of RNN primitive with summation of the results.
Definition: dnnl_types.h:1659
float alpha
Algorithm specific parameter.
Definition: dnnl_types.h:1396
@ dnnl_eltwise_linear
Eltwise: linear.
Definition: dnnl_types.h:886
@ dnnl_nCw16c
3D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBc16b
Definition: dnnl_types.h:573
@ dnnl_vanilla_gru
GRU cell.
Definition: dnnl_types.h:943
dnnl_memory_desc_t dst_iter_c_desc
Destination iter memory descriptor for cell state.
Definition: dnnl_types.h:1694
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1284
dnnl_alg_kind_t alg_kind
The kind of the binary algorithm.
Definition: dnnl_types.h:1754
@ dnnl_abc
plain 3D tensor
Definition: dnnl_types.h:179
@ dnnl_nCw32c
3D CNN activations tensor blocked by channels with block size 32, an alias to dnnl_aBc32b
Definition: dnnl_types.h:570
An opaque structure to describe an execution stream.
dnnl_dims_t inner_idxs
The logical indices of the blocks, e.g.
Definition: dnnl_types.h:1099
@ dnnl_wigo
4D CNN weights tensor (incl. groups), an alias to dnnl_dcab
Definition: dnnl_types.h:492
A descriptor of a binary operation.
Definition: dnnl_types.h:1747
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1780
dnnl_memory_extra_flags_t
Flags for memory special features.
Definition: dnnl_types.h:1154
dnnl_alg_kind_t alg_kind
The kind of pooling algorithm.
Definition: dnnl_types.h:1479
@ dnnl_convolution_direct
Direct convolution.
Definition: dnnl_types.h:864
unsigned gpu_runtime
GPU runtime.
Definition: dnnl_types.h:2351
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1511
@ dnnl_reduction_min
Reduction using min.
Definition: dnnl_types.h:969
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1454
@ dnnl_query_diff_src_md
source gradient memory desc
Definition: dnnl_types.h:2276
@ dnnl_abcdefgih
permuted 9D tensor
Definition: dnnl_types.h:217
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1806
@ dnnl_wio
3D CNN weights tensor, an alias to dnnl_cba
Definition: dnnl_types.h:465
A descriptor of a pooling (version 2) operation.
Definition: dnnl_types.h:1468
@ dnnl_nChw32c
4D CNN activations tensor blocked by channels with block size 32, an alias to dnnl_aBcd32b
Definition: dnnl_types.h:558
dnnl_memory_desc_t diff_src_layer_desc
Source gradient layer memory descriptor.
Definition: dnnl_types.h:1705
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1632
@ dnnl_forward_scoring
Forward data propagation (alias for dnnl_forward_inference).
Definition: dnnl_types.h:794
@ dnnl_aBcde8b
5D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:330
@ dnnl_prop_kind_undef
Undefined propagation type.
Definition: dnnl_types.h:785
@ dnnl_blocked
A tensor in a generic format described by the stride and blocking values in each dimension.
Definition: dnnl_types.h:89
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1671
@ dnnl_query_primitive_kind
primitive kind
Definition: dnnl_types.h:2230
@ dnnl_unidirectional_left2right
Unidirectional execution of RNN primitive from left to right.
Definition: dnnl_types.h:1651
dnnl_memory_desc_t diff_weights_iter_desc
Weights gradient iter memory descriptor.
Definition: dnnl_types.h:1713
@ dnnl_iohw
4D CNN weights tensor, an alias to dnnl_bacd
Definition: dnnl_types.h:477
@ dnnl_eltwise_elu
Eltwise: exponential linear unit (elu)
Definition: dnnl_types.h:878
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1355
@ dnnl_odhwi
5D CNN weights tensor, an alias to dnnl_acdeb
Definition: dnnl_types.h:485
@ dnnl_reduction
A reduction primitive.
Definition: dnnl_types.h:853
@ dnnl_nwc
3D CNN activations tensor, an alias to dnnl_acb
Definition: dnnl_types.h:444
@ dnnl_nCw4c
3D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBc4b
Definition: dnnl_types.h:576
@ dnnl_aBcde32b
5D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:313
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1826
@ dnnl_vanilla_lstm
LSTM cell.
Definition: dnnl_types.h:941
@ dnnl_any_engine
An unspecified engine.
Definition: dnnl_types.h:1861
@ dnnl_nCdhw4c
5D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcde4b
Definition: dnnl_types.h:552
@ dnnl_resampling
A resampling primitive.
Definition: dnnl_types.h:849
@ dnnl_wino_wei_aaOBiOo
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:1109
@ dnnl_cpu_isa_avx
Intel Advanced Vector Extensions (Intel AVX)
Definition: dnnl_types.h:2383
@ dnnl_bca
permuted 3D tensor
Definition: dnnl_types.h:204
@ dnnl_reduction_norm_lp_max
Reduction using lp norm.
Definition: dnnl_types.h:977
dnnl_prop_kind_t
Kinds of propagation.
Definition: dnnl_types.h:782
@ dnnl_query_scratchpad_md
scratchpad memory desc
Definition: dnnl_types.h:2282
float lrn_k
LRN k parameter.
Definition: dnnl_types.h:1530
@ dnnl_nchw
4D CNN activations tensor, an alias to dnnl_abcd
Definition: dnnl_types.h:446
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1801
@ dnnl_eltwise_gelu
Eltwise: tanh-based gelu (alias for dnnl_eltwise_gelu_tanh)
Definition: dnnl_types.h:901
dnnl_alg_kind_t alg_kind
LRN algorithm.
Definition: dnnl_types.h:1517
dnnl_dim_t local_size
The number of channels to sum over (for cross-channel LRN) or the side length of the square region to...
Definition: dnnl_types.h:1524
@ dnnl_query_weights_md
weights memory descriptor desc
Definition: dnnl_types.h:2277
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1628
dnnl_alg_kind_t alg_kind
The kind of the resampling algorithm.
Definition: dnnl_types.h:1804
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1450
dnnl_memory_desc_t data_desc
Source and destination memory descriptor, and source and destination gradient memory descriptor.
Definition: dnnl_types.h:1339
@ dnnl_query_batch_normalization_d
batch normalization descriptor
Definition: dnnl_types.h:2261
@ dnnl_eltwise_tanh_use_dst_for_bwd
Eltwise: hyperbolic tangent non-linearity (tanh) (dst for backward)
Definition: dnnl_types.h:917
dnnl_dims_t strides
Pooling kernel strides for spatial dimensions.
Definition: dnnl_types.h:1456
dnnl_memory_desc_t dst_iter_desc
Destination iter memory descriptor for hidden state.
Definition: dnnl_types.h:1692
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1313
@ dnnl_chwn
4D CNN activations tensor, an alias to dnnl_bcda
Definition: dnnl_types.h:450
dnnl_alg_kind_t cell_kind
RNN cell kind.
Definition: dnnl_types.h:1674
@ dnnl_undefined_primitive
Undefined primitive.
Definition: dnnl_types.h:811
@ dnnl_eltwise_soft_relu
Eltwise: soft_relu.
Definition: dnnl_types.h:890
@ dnnl_abcdefghikj
permuted 11D tensor
Definition: dnnl_types.h:219
@ dnnl_nt
2D RNN statistics tensor, an alias to dnnl_ba
Definition: dnnl_types.h:440
dnnl_convolution_desc_t dnnl_deconvolution_desc_t
A descriptor of a deconvolution operation.
Definition: dnnl_types.h:1322
dnnl_dim_t offset0
Offset from memory origin to the current block, non-zero only in a description of a memory sub-block.
Definition: dnnl_types.h:1219
@ dnnl_unidirectional_right2left
Unidirectional execution of RNN primitive from right to left.
Definition: dnnl_types.h:1653
@ dnnl_aBcd8b
4D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:282
@ dnnl_ab
plain 2D tensor
Definition: dnnl_types.h:178
dnnl_rnn_packed_desc_t rnn_packed_desc
Tensor of packed weights for RNN.
Definition: dnnl_types.h:1230
@ dnnl_query_scratchpad_engine
(scratch) memory, additional to all inputs and outputs memory (bytes)
Definition: dnnl_types.h:2241
@ dnnl_pooling_v2
A pooling version 2 primitive (pooling with dilation support).
Definition: dnnl_types.h:851
@ dnnl_runtime_error
Primitive or engine failed on execution.
Definition: dnnl_types.h:51
@ dnnl_giodhw
6D CNN weights tensor (incl. groups), an alias to dnnl_acbdef
Definition: dnnl_types.h:502
@ dnnl_query_exec_arg_md
memory desc of an execute argument
Definition: dnnl_types.h:2283
@ dnnl_query_some_d
stub
Definition: dnnl_types.h:2252
@ dnnl_pooling_avg_exclude_padding
Average pooling exclude padding.
Definition: dnnl_types.h:931
@ dnnl_binary_add
Binary add.
Definition: dnnl_types.h:953