oneAPI Deep Neural Network Library (oneDNN)
1.6.4
Performance library for Deep Learning
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577 dnnl_NCw16n16c = dnnl_ABc16a16b,
578 dnnl_NCdhw16n16c = dnnl_ABcde16a16b,
579 dnnl_NChw16n16c = dnnl_ABcd16a16b,
580 dnnl_NCw32n32c = dnnl_ABc32a32b,
581 dnnl_NChw32n32c = dnnl_ABcd32a32b,
582 dnnl_NCdhw32n32c = dnnl_ABcde32a32b,
585 dnnl_IOw16o16i = dnnl_BAc16a16b,
586 dnnl_IOw16i16o = dnnl_BAc16b16a,
587 dnnl_OIw16i16o = dnnl_ABc16b16a,
588 dnnl_OIw16o16i = dnnl_ABc16a16b,
589 dnnl_Oiw16o = dnnl_Abc16a,
590 dnnl_OIw4i16o4i = dnnl_ABc4b16a4b,
591 dnnl_OIw2i8o4i = dnnl_ABc2b8a4b,
592 dnnl_OIw16i16o4i = dnnl_ABc16b16a4b,
593 dnnl_OIw16i16o2i = dnnl_ABc16b16a2b,
594 dnnl_OIw4i4o = dnnl_ABc4b4a,
595 dnnl_OIw4o4i = dnnl_ABc4a4b,
596 dnnl_Oiw4o = dnnl_Abc4a,
597 dnnl_OIw8i16o2i = dnnl_ABc8b16a2b,
598 dnnl_OIw8i8o = dnnl_ABc8b8a,
599 dnnl_OIw8o16i2o = dnnl_ABc8a16b2a,
600 dnnl_IOw8o16i2o = dnnl_BAc8a16b2a,
601 dnnl_OIw8o8i = dnnl_ABc8a8b,
602 dnnl_OIw8o4i = dnnl_ABc8a4b,
603 dnnl_Owi16o = dnnl_Acb16a,
604 dnnl_OwI16o2i = dnnl_AcB16a2b,
605 dnnl_OwI16o4i = dnnl_AcB16a4b,
606 dnnl_Owi4o = dnnl_Acb4a,
607 dnnl_Owi8o = dnnl_Acb8a,
610 dnnl_IOhw16i16o = dnnl_BAcd16b16a,
611 dnnl_IOhw16o16i = dnnl_BAcd16a16b,
612 dnnl_Ohwi16o = dnnl_Acdb16a,
613 dnnl_OhwI16o2i = dnnl_AcdB16a2b,
614 dnnl_OhwI16o4i = dnnl_AcdB16a4b,
615 dnnl_Ohwi32o = dnnl_Acdb32a,
616 dnnl_Ohwi4o = dnnl_Acdb4a,
617 dnnl_Ohwi8o = dnnl_Acdb8a,
618 dnnl_OIhw16i16o = dnnl_ABcd16b16a,
619 dnnl_OIhw16o16i = dnnl_ABcd16a16b,
620 dnnl_Oihw16o = dnnl_Abcd16a,
621 dnnl_OIhw4i16o4i = dnnl_ABcd4b16a4b,
622 dnnl_OIhw16i16o4i = dnnl_ABcd16b16a4b,
623 dnnl_OIhw16i16o2i = dnnl_ABcd16b16a2b,
624 dnnl_OIhw4i4o = dnnl_ABcd4b4a,
625 dnnl_OIhw4o4i = dnnl_ABcd4a4b,
626 dnnl_Oihw4o = dnnl_Abcd4a,
627 dnnl_OIhw8i16o2i = dnnl_ABcd8b16a2b,
629 dnnl_OIhw8o16i2o = dnnl_ABcd8a16b2a,
630 dnnl_OIhw2i8o4i = dnnl_ABcd2b8a4b,
631 dnnl_IOhw8o16i2o = dnnl_BAcd8a16b2a,
632 dnnl_OIhw8o8i = dnnl_ABcd8a8b,
633 dnnl_OIhw8o4i = dnnl_ABcd8a4b,
636 dnnl_Odhwi16o = dnnl_Acdeb16a,
637 dnnl_OdhwI16o2i = dnnl_AcdeB16a2b,
638 dnnl_Odhwi4o = dnnl_Acdeb4a,
639 dnnl_Odhwi8o = dnnl_Acdeb8a,
640 dnnl_OIdhw16i16o = dnnl_ABcde16b16a,
641 dnnl_OIdhw16o16i = dnnl_ABcde16a16b,
642 dnnl_Oidhw16o = dnnl_Abcde16a,
643 dnnl_OIdhw4i4o = dnnl_ABcde4b4a,
644 dnnl_OIdhw4o4i = dnnl_ABcde4a4b,
645 dnnl_Oidhw4o = dnnl_Abcde4a,
646 dnnl_OIdhw8i16o2i = dnnl_ABcde8b16a2b,
647 dnnl_OIdhw8i8o = dnnl_ABcde8b8a,
648 dnnl_OIdhw8o16i2o = dnnl_ABcde8a16b2a,
649 dnnl_IOdhw8o16i2o = dnnl_BAcde8a16b2a,
652 dnnl_OIdhw8o8i = dnnl_ABcde8a8b,
653 dnnl_OIdhw8o4i = dnnl_ABcde8a4b,
654 dnnl_IOdhw16i16o = dnnl_BAcde16b16a,
655 dnnl_OIdhw4o8i8o4i = dnnl_ABcde4a8b8a4b,
656 dnnl_IOdhw16o16i = dnnl_BAcde16a16b,
659 dnnl_Goiw16g = dnnl_Abcd16a,
660 dnnl_Goiw8g = dnnl_Abcd8a,
661 dnnl_gIOw16o16i = dnnl_aCBd16b16c,
662 dnnl_gIOw16i16o = dnnl_aCBd16c16b,
663 dnnl_gOIw16i16o = dnnl_aBCd16c16b,
664 dnnl_gOIw16o16i = dnnl_aBCd16b16c,
666 dnnl_gOIw4i16o4i = dnnl_aBCd4c16b4c,
667 dnnl_gOIw2i8o4i = dnnl_aBCd2c8b4c,
668 dnnl_gOIw16i16o4i = dnnl_aBCd16c16b4c,
669 dnnl_gOIw16i16o2i = dnnl_aBCd16c16b2c,
670 dnnl_gOIw4i4o = dnnl_aBCd4c4b,
671 dnnl_gOIw4o4i = dnnl_aBCd4b4c,
673 dnnl_gOIw8i16o2i = dnnl_aBCd8c16b2c,
674 dnnl_gOIw8i8o = dnnl_aBCd8c8b,
675 dnnl_gOIw8o16i2o = dnnl_aBCd8b16c2b,
676 dnnl_gIOw8o16i2o = dnnl_aCBd8b16c2b,
677 dnnl_gOIw8o8i = dnnl_aBCd8b8c,
678 dnnl_gOIw8o4i = dnnl_aBCd8b4c,
679 dnnl_gOwi16o = dnnl_aBdc16b,
680 dnnl_gOwI16o2i = dnnl_aBdC16b2c,
681 dnnl_gOwI16o4i = dnnl_aBdC16b4c,
682 dnnl_gOwi4o = dnnl_aBdc4b,
683 dnnl_gOwi8o = dnnl_aBdc8b,
684 dnnl_Goiw32g = dnnl_Abcd32a,
685 dnnl_gOIw2i4o2i = dnnl_aBCd2c4b2c,
687 dnnl_gOIw4i8o2i = dnnl_aBCd4c8b2c,
688 dnnl_gOIw4o8i2o = dnnl_aBCd4b8c2b,
691 dnnl_gIOhw16i16o = dnnl_aCBde16c16b,
692 dnnl_gIOhw16o16i = dnnl_aCBde16b16c,
693 dnnl_gOhwi16o = dnnl_aBdec16b,
694 dnnl_gOhwI16o2i = dnnl_aBdeC16b2c,
695 dnnl_gOhwI16o4i = dnnl_aBdeC16b4c,
696 dnnl_gOhwi32o = dnnl_aBdec32b,
697 dnnl_gOhwi4o = dnnl_aBdec4b,
698 dnnl_gOhwi8o = dnnl_aBdec8b,
699 dnnl_Goihw16g = dnnl_Abcde16a,
700 dnnl_gOIhw16i16o = dnnl_aBCde16c16b,
701 dnnl_gOIhw16o16i = dnnl_aBCde16b16c,
703 dnnl_gOIhw2i8o4i = dnnl_aBCde2c8b4c,
704 dnnl_gOIhw4i16o4i = dnnl_aBCde4c16b4c,
705 dnnl_gOIhw16i16o4i = dnnl_aBCde16c16b4c,
706 dnnl_gOIhw16i16o2i = dnnl_aBCde16c16b2c,
707 dnnl_gOIhw4i4o = dnnl_aBCde4c4b,
708 dnnl_gOIhw4o4i = dnnl_aBCde4b4c,
710 dnnl_Goihw8g = dnnl_Abcde8a,
711 dnnl_gOIhw8i16o2i = dnnl_aBCde8c16b2c,
712 dnnl_gOIhw8i8o = dnnl_aBCde8c8b,
713 dnnl_gOIhw8o16i2o = dnnl_aBCde8b16c2b,
714 dnnl_gIOhw8o16i2o = dnnl_aCBde8b16c2b,
715 dnnl_gOIhw8o8i = dnnl_aBCde8b8c,
716 dnnl_gOIhw8o4i = dnnl_aBCde8b4c,
717 dnnl_Goihw32g = dnnl_Abcde32a,
719 dnnl_OIw4o8i8o4i = dnnl_ABc4a8b8a4b,
720 dnnl_OIhw4o8i8o4i = dnnl_ABcd4a8b8a4b,
721 dnnl_IOw4i8o8i4o = dnnl_BAc4b8a8b4a,
722 dnnl_IOhw4i8o8i4o = dnnl_BAcd4b8a8b4a,
723 dnnl_IOdhw4i8o8i4o = dnnl_BAcde4b8a8b4a,
725 dnnl_OIhw2o8i8o2i = dnnl_ABcd2a8b8a2b,
726 dnnl_gOIw4o8i8o4i = dnnl_aBCd4b8c8b4c,
727 dnnl_gOIhw4o8i8o4i = dnnl_aBCde4b8c8b4c,
728 dnnl_gOIdhw4o8i8o4i = dnnl_aBCdef4b8c8b4c,
729 dnnl_gIOw4i8o8i4o = dnnl_aCBd4c8b8c4b,
730 dnnl_gIOhw4i8o8i4o = dnnl_aCBde4c8b8c4b,
731 dnnl_gIOdhw4i8o8i4o = dnnl_aCBdef4c8b8c4b,
732 dnnl_gOIhw2o8i8o2i = dnnl_aBCde2b8c8b2c,
733 dnnl_gOIhw2i4o2i = dnnl_aBCde2c4b2c,
735 dnnl_gOIhw4i8o2i = dnnl_aBCde4c8b2c,
736 dnnl_gOIhw4o8i2o = dnnl_aBCde4b8c2b,
739 dnnl_gIOdhw16i16o = dnnl_aCBdef16c16b,
740 dnnl_gIOdhw16o16i = dnnl_aCBdef16b16c,
741 dnnl_gOdhwi16o = dnnl_aBdefc16b,
742 dnnl_gOdhwI16o2i = dnnl_aBdefC16b2c,
743 dnnl_gOdhwi4o = dnnl_aBdefc4b,
744 dnnl_gOdhwi8o = dnnl_aBdefc8b,
745 dnnl_gOIdhw16i16o = dnnl_aBCdef16c16b,
746 dnnl_gOIdhw4i16o4i = dnnl_aBCdef4c16b4c,
748 dnnl_gOIdhw16o16i = dnnl_aBCdef16b16c,
750 dnnl_gOIdhw4i4o = dnnl_aBCdef4c4b,
751 dnnl_gOIdhw4o4i = dnnl_aBCdef4b4c,
753 dnnl_gOIdhw8i16o2i = dnnl_aBCdef8c16b2c,
754 dnnl_gOIdhw8i8o = dnnl_aBCdef8c8b,
755 dnnl_gOIdhw8o16i2o = dnnl_aBCdef8b16c2b,
756 dnnl_gIOdhw8o16i2o = dnnl_aCBdef8b16c2b,
757 dnnl_gOIdhw8o8i = dnnl_aBCdef8b8c,
758 dnnl_gOIdhw8o4i = dnnl_aBCdef8b4c,
759 dnnl_Goidhw16g = dnnl_Abcdef16a,
760 dnnl_Goidhw32g = dnnl_Abcdef32a,
761 dnnl_gOIdhw2i4o2i = dnnl_aBCdef2c4b2c,
762 dnnl_gOIdhw4i8o2i = dnnl_aBCdef4c8b2c,
764 dnnl_gOIdhw4o8i2o = dnnl_aBCdef4b8c2b,
1016 #define DNNL_MAX_NDIMS 12
1020 #define DNNL_RUNTIME_DIM_VAL INT64_MIN
1025 #define DNNL_RUNTIME_SIZE_VAL ((size_t)DNNL_RUNTIME_DIM_VAL)
1029 static const union {
1032 } DNNL_RUNTIME_F32_VAL_REP = {0x7fc000d0};
1037 #define DNNL_RUNTIME_F32_VAL (DNNL_RUNTIME_F32_VAL_REP.f)
1040 static const int DNNL_RUNTIME_S32_VAL_REP = INT32_MIN;
1045 #define DNNL_RUNTIME_S32_VAL DNNL_RUNTIME_S32_VAL_REP
1099 dnnl_packed_format_undef = 0,
1102 } dnnl_rnn_packed_memory_format_t;
1106 #define DNNL_RNN_MAX_N_PARTS 4
1110 dnnl_rnn_packed_memory_format_t format;
1117 size_t offset_compensation;
1124 dnnl_memory_extra_flag_none = 0x0U,
1133 dnnl_memory_extra_flag_scale_adjust = 0x2U,
1134 dnnl_memory_extra_flag_gpu_rnn_u8s8_compensation = 0x4U,
1213 #define DNNL_MEMORY_NONE (NULL)
1214 #define DNNL_MEMORY_ALLOCATE ((void *)(size_t)-1)
1768 typedef const struct dnnl_engine *const_dnnl_engine_t;
1884 #define DNNL_ARG_SRC_0 1
1885 #define DNNL_ARG_SRC DNNL_ARG_SRC_0
1888 #define DNNL_ARG_SRC_LAYER DNNL_ARG_SRC_0
1891 #define DNNL_ARG_FROM DNNL_ARG_SRC_0
1896 #define DNNL_ARG_SRC_1 2
1897 #define DNNL_ARG_SRC_ITER DNNL_ARG_SRC_1
1902 #define DNNL_ARG_SRC_2 3
1903 #define DNNL_ARG_SRC_ITER_C DNNL_ARG_SRC_2
1908 #define DNNL_ARG_DST_0 17
1909 #define DNNL_ARG_DST DNNL_ARG_DST_0
1912 #define DNNL_ARG_TO DNNL_ARG_DST_0
1915 #define DNNL_ARG_DST_LAYER DNNL_ARG_DST_0
1919 #define DNNL_ARG_DST_1 18
1920 #define DNNL_ARG_DST_ITER DNNL_ARG_DST_1
1925 #define DNNL_ARG_DST_2 19
1926 #define DNNL_ARG_DST_ITER_C DNNL_ARG_DST_2
1931 #define DNNL_ARG_WEIGHTS_0 33
1932 #define DNNL_ARG_WEIGHTS DNNL_ARG_WEIGHTS_0
1935 #define DNNL_ARG_SCALE_SHIFT DNNL_ARG_WEIGHTS_0
1938 #define DNNL_ARG_WEIGHTS_LAYER DNNL_ARG_WEIGHTS_0
1943 #define DNNL_ARG_WEIGHTS_1 34
1944 #define DNNL_ARG_WEIGHTS_ITER DNNL_ARG_WEIGHTS_1
1949 #define DNNL_ARG_WEIGHTS_2 35
1950 #define DNNL_ARG_WEIGHTS_PEEPHOLE DNNL_ARG_WEIGHTS_2
1955 #define DNNL_ARG_WEIGHTS_3 36
1956 #define DNNL_ARG_WEIGHTS_PROJECTION DNNL_ARG_WEIGHTS_3
1961 #define DNNL_ARG_BIAS 41
1964 #define DNNL_ARG_MEAN 49
1965 #define DNNL_ARG_VARIANCE 50
1970 #define DNNL_ARG_WORKSPACE 64
1971 #define DNNL_ARG_SCRATCHPAD 80
1975 #define DNNL_ARG_DIFF_SRC_0 129
1976 #define DNNL_ARG_DIFF_SRC DNNL_ARG_DIFF_SRC_0
1979 #define DNNL_ARG_DIFF_SRC_LAYER DNNL_ARG_DIFF_SRC_0
1984 #define DNNL_ARG_DIFF_SRC_1 130
1985 #define DNNL_ARG_DIFF_SRC_ITER DNNL_ARG_DIFF_SRC_1
1990 #define DNNL_ARG_DIFF_SRC_2 131
1991 #define DNNL_ARG_DIFF_SRC_ITER_C DNNL_ARG_DIFF_SRC_2
1996 #define DNNL_ARG_DIFF_DST_0 145
1997 #define DNNL_ARG_DIFF_DST DNNL_ARG_DIFF_DST_0
2000 #define DNNL_ARG_DIFF_DST_LAYER DNNL_ARG_DIFF_DST_0
2005 #define DNNL_ARG_DIFF_DST_1 146
2006 #define DNNL_ARG_DIFF_DST_ITER DNNL_ARG_DIFF_DST_1
2011 #define DNNL_ARG_DIFF_DST_2 147
2012 #define DNNL_ARG_DIFF_DST_ITER_C DNNL_ARG_DIFF_DST_2
2017 #define DNNL_ARG_DIFF_WEIGHTS_0 161
2018 #define DNNL_ARG_DIFF_WEIGHTS DNNL_ARG_DIFF_WEIGHTS_0
2021 #define DNNL_ARG_DIFF_SCALE_SHIFT DNNL_ARG_DIFF_WEIGHTS_0
2024 #define DNNL_ARG_DIFF_WEIGHTS_LAYER DNNL_ARG_DIFF_WEIGHTS_0
2029 #define DNNL_ARG_DIFF_WEIGHTS_1 162
2030 #define DNNL_ARG_DIFF_WEIGHTS_ITER DNNL_ARG_DIFF_WEIGHTS_1
2035 #define DNNL_ARG_DIFF_WEIGHTS_2 163
2036 #define DNNL_ARG_DIFF_WEIGHTS_PEEPHOLE DNNL_ARG_DIFF_WEIGHTS_2
2041 #define DNNL_ARG_DIFF_WEIGHTS_3 164
2042 #define DNNL_ARG_DIFF_WEIGHTS_PROJECTION DNNL_ARG_DIFF_WEIGHTS_3
2047 #define DNNL_ARG_DIFF_BIAS 169
2050 #define DNNL_ARG_ATTR_OUTPUT_SCALES 513
2054 #define DNNL_ARG_MULTIPLE_SRC 1024
2055 #define DNNL_ARG_MULTIPLE_DST 2048
2060 #define DNNL_ARG_ATTR_ZERO_POINTS 4096
2064 #define DNNL_ARG_ATTR_POST_OP_DW 8192
2165 dnnl_query_max = 0x7fff,
2197 struct dnnl_stream_attr;
2209 #define DNNL_RUNTIME_NONE 0u
2212 #define DNNL_RUNTIME_SEQ 1u
2215 #define DNNL_RUNTIME_OMP 2u
2218 #define DNNL_RUNTIME_TBB 4u
2221 #define DNNL_RUNTIME_THREADPOOL 8u
2224 #define DNNL_RUNTIME_OCL 256u
2238 #define DNNL_JIT_PROFILE_NONE 0u
2241 #define DNNL_JIT_PROFILE_VTUNE 1u
2244 #define DNNL_JIT_PROFILE_LINUX_PERFMAP 2u
2247 #define DNNL_JIT_PROFILE_LINUX_JITDUMP 4u
2251 #define DNNL_JIT_PROFILE_LINUX_JITDUMP_USE_TSC 8u
2254 #define DNNL_JIT_PROFILE_LINUX_PERF \
2255 (DNNL_JIT_PROFILE_LINUX_JITDUMP | DNNL_JIT_PROFILE_LINUX_PERFMAP)
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1440
@ dnnl_query_time_estimate_f64
runtime estimation (seconds)
Definition: dnnl_types.h:2116
@ dnnl_query_reorder_dst_engine
destination engine
Definition: dnnl_types.h:2128
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1399
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1614
@ dnnl_aBcdef4b
6D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:363
@ dnnl_dhwigo
6D CNN weights tensor (incl. groups), an alias to dnnl_defcab
Definition: dnnl_types.h:501
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1250
@ dnnl_scratchpad_mode_library
The library manages the scratchpad allocation according to the policy specified by the DNNL_ENABLE_CO...
Definition: dnnl_types.h:1822
@ dnnl_goidhw
6D CNN weights tensor (incl. groups), an alias to dnnl_abcdef
Definition: dnnl_types.h:497
@ dnnl_wino_wei_aaOIoi
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:1076
struct dnnl_stream_attr * dnnl_stream_attr_t
An execution stream attributes handle.
Definition: dnnl_types.h:2199
@ dnnl_io
2D CNN weights tensor, an alias to dnnl_ba
Definition: dnnl_types.h:456
dnnl_dims_t strides
Convolution strides in each spatial dimension.
Definition: dnnl_types.h:1266
@ dnnl_nc
2D CNN activations tensor, an alias to dnnl_ab
Definition: dnnl_types.h:431
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1334
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1724
@ dnnl_s32
32-bit signed integer.
Definition: dnnl_types.h:72
@ dnnl_x
1D tensor, an alias to dnnl_a
Definition: dnnl_types.h:429
@ dnnl_eltwise_round
Eltwise: round.
Definition: dnnl_types.h:902
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1473
Description of tensor of packed weights for rnn.
Definition: dnnl_types.h:1109
@ dnnl_eltwise_relu_use_dst_for_bwd
Eltwise: ReLU (dst for backward)
Definition: dnnl_types.h:904
float layer_norm_epsilon
Layer normalization epsilon parameter.
Definition: dnnl_types.h:1525
dnnl_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: dnnl_types.h:1550
@ dnnl_query_pooling_d
pooling descriptor
Definition: dnnl_types.h:2140
@ dnnl_ABcde2b8a4b
5D tensor blocked by 1st dimension with block size 8
Definition: dnnl_types.h:303
@ dnnl_wino_wei_aaOio
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:1077
dnnl_alg_kind_t alg_kind
The kind of the convolution algorithm.
Definition: dnnl_types.h:1248
dnnl_alg_kind_t alg_kind
The kind of pooling algorithm.
Definition: dnnl_types.h:1407
@ dnnl_aBCde2b4c2b
5D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:351
@ dnnl_query_memory_consumption_s64
memory consumption – extra
Definition: dnnl_types.h:2117
@ 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:830
@ 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:210
An opaque structure to describe a primitive descriptor iterator.
@ dnnl_batch_normalization
A batch normalization primitive.
Definition: dnnl_types.h:826
@ dnnl_query_logsoftmax_d
logsoftmax descriptor
Definition: dnnl_types.h:2148
struct dnnl_stream * dnnl_stream_t
An execution stream handle.
Definition: dnnl_types.h:2192
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1402
@ dnnl_abcdefghji
permuted 10D tensor
Definition: dnnl_types.h:217
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:2127
@ dnnl_wino_undef
Undefined memory format, used for empty memory descriptors.
Definition: dnnl_types.h:1074
dnnl_rnn_direction_t direction
The direction of RNN primitive execution.
Definition: dnnl_types.h:1602
@ dnnl_memory_extra_flag_compensation_conv_s8s8
Indicates the weights have an additional buffer, that depends on the compensation_mask.
Definition: dnnl_types.h:1132
@ dnnl_softmax
A softmax primitive.
Definition: dnnl_types.h:820
@ dnnl_normalization_flags_none
Use no normalization flags.
Definition: dnnl_types.h:965
@ dnnl_query_rnn_d
rnn descriptor
Definition: dnnl_types.h:2145
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1556
unsigned int flags
RNN cell flags.
Definition: dnnl_types.h:1658
@ dnnl_cn
2D CNN activations tensor, an alias to dnnl_ba
Definition: dnnl_types.h:433
#define DNNL_MAX_NDIMS
Maximum number of dimensions a tensor can have.
Definition: dnnl_types.h:1016
@ dnnl_ldnc
4D RNN states tensor in the format (num_layers, num_directions, batch, state channels).
Definition: dnnl_types.h:509
@ dnnl_scratchpad_mode_user
The user manages the scratchpad allocation by querying and providing the scratchpad memory to primiti...
Definition: dnnl_types.h:1827
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1471
@ dnnl_defcab
permuted 6D tensor
Definition: dnnl_types.h:211
@ dnnl_abcdefghijlk
permuted 12D tensor
Definition: dnnl_types.h:219
@ dnnl_abcdefghijk
plain 11D tensor
Definition: dnnl_types.h:187
@ dnnl_aBcde16b
5D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:305
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:1608
dnnl_memory_desc_t stat_desc
Statistics memory descriptor.
Definition: dnnl_types.h:1486
@ dnnl_eltwise_relu
Eltwise: ReLU.
Definition: dnnl_types.h:863
@ dnnl_acb
permuted 3D tensor
Definition: dnnl_types.h:194
A descriptor of a matrix multiplication operation.
Definition: dnnl_types.h:1699
dnnl_memory_desc_t diff_weights_projection_desc
Weights gradient projection memory descriptor.
Definition: dnnl_types.h:1655
@ dnnl_eltwise_abs
Eltwise: abs.
Definition: dnnl_types.h:871
dnnl_dim_t group_size
Number of groups.
Definition: dnnl_types.h:1304
@ dnnl_oihw
4D CNN weights tensor, an alias to dnnl_abcd
Definition: dnnl_types.h:466
dnnl_normalization_flags_t
Flags for normalization primitives.
Definition: dnnl_types.h:956
@ dnnl_eltwise_sqrt_use_dst_for_bwd
Eltwise: square root (dst for backward)
Definition: dnnl_types.h:910
@ dnnl_shuffle
A shuffle primitive.
Definition: dnnl_types.h:808
@ dnnl_query_shuffle_d
shuffle descriptor
Definition: dnnl_types.h:2137
A descriptor of a convolution operation.
Definition: dnnl_types.h:1238
dnnl_primitive_kind_t
Kinds of primitives.
Definition: dnnl_types.h:802
dnnl_rnn_flags_t
Flags for RNN cell.
Definition: dnnl_types.h:1569
@ dnnl_ldigo
5D RNN weights tensor in the format (num_layers, num_directions, input_channels, num_gates,...
Definition: dnnl_types.h:516
@ dnnl_pooling_max
Max pooling.
Definition: dnnl_types.h:916
A structure that contains an index and a memory object, and is used to pass arguments to dnnl_primiti...
Definition: dnnl_types.h:2068
dnnl_stream_flags_t
Stream flags.
Definition: dnnl_types.h:2176
dnnl_query_t
Primitive descriptor query specification.
Definition: dnnl_types.h:2107
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1369
float lrn_alpha
LRN alpha parameter.
Definition: dnnl_types.h:1452
@ 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:445
A descriptor for an RNN operation.
Definition: dnnl_types.h:1591
dnnl_rnn_direction_t
A direction of RNN primitive execution.
Definition: dnnl_types.h:1575
@ dnnl_bcdea
permuted 5D tensor
Definition: dnnl_types.h:205
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1252
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1254
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1262
@ dnnl_sum
A sum primitive.
Definition: dnnl_types.h:812
@ dnnl_oidhw
5D CNN weights tensor, an alias to dnnl_abcde
Definition: dnnl_types.h:476
dnnl_blocking_desc_t blocking
Description of the data layout for memory formats that use blocking.
Definition: dnnl_types.h:1192
@ dnnl_backward_weights
Backward weights propagation.
Definition: dnnl_types.h:795
@ 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:2194
A descriptor of an inner product operation.
Definition: dnnl_types.h:1535
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1702
@ dnnl_gpu
GPU engine.
Definition: dnnl_types.h:1757
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1506
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1552
dnnl_memory_desc_t weights_projection_desc
Weights projection memory descriptor.
Definition: dnnl_types.h:1628
int softmax_axis
The axis along which to perform the softmax.
Definition: dnnl_types.h:1378
@ dnnl_query_diff_weights_md
weights grad. memory desc
Definition: dnnl_types.h:2157
@ dnnl_query_prop_kind
propagation kind
Definition: dnnl_types.h:2130
@ dnnl_abced
permuted 5D tensor
Definition: dnnl_types.h:212
@ dnnl_eltwise_logistic
Eltwise: logistic.
Definition: dnnl_types.h:881
@ dnnl_eltwise
An element-wise primitive.
Definition: dnnl_types.h:818
@ dnnl_stream_in_order
In-order execution.
Definition: dnnl_types.h:2181
@ dnnl_aBc16b
3D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:228
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1508
@ dnnl_oiw
3D CNN weights tensor, an alias to dnnl_abc
Definition: dnnl_types.h:458
@ dnnl_convolution_auto
Convolution algorithm(either direct or Winograd) is chosen just in time.
Definition: dnnl_types.h:857
@ dnnl_eltwise_sqrt
Eltwise: square root.
Definition: dnnl_types.h:873
@ dnnl_cdba
permuted 4D tensor
Definition: dnnl_types.h:207
@ dnnl_cpu_isa_avx512_core
Intel AVX-512 subset for Intel Xeon Scalable processor family and Intel Core processor family.
Definition: dnnl_types.h:2281
@ dnnl_eltwise_bounded_relu
Eltwise: bounded_relu.
Definition: dnnl_types.h:877
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1594
@ dnnl_hwio
4D CNN weights tensor, an alias to dnnl_cdba
Definition: dnnl_types.h:468
@ dnnl_forward_inference
Forward data propagation (inference mode).
Definition: dnnl_types.h:785
@ dnnl_query_impl_info_str
for creating scratchpad memory
Definition: dnnl_types.h:2125
@ dnnl_query_dst_md
destination memory desc
Definition: dnnl_types.h:2158
@ dnnl_query_resampling_d
resampling descriptor
Definition: dnnl_types.h:2150
@ dnnl_query_inner_product_d
inner product descriptor
Definition: dnnl_types.h:2144
@ dnnl_rnn_flags_undef
Undefined RNN flags.
Definition: dnnl_types.h:1571
@ dnnl_nCdhw16c
5D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcde16b
Definition: dnnl_types.h:546
@ dnnl_query_convolution_d
convolution descriptor
Definition: dnnl_types.h:2135
@ 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:2296
@ dnnl_aBCdef2c8b4c
6D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:358
@ dnnl_bcda
permuted 4D tensor
Definition: dnnl_types.h:204
int major
Major version.
Definition: dnnl_types.h:2229
@ dnnl_eltwise_gelu_tanh
Eltwise: gelu.
Definition: dnnl_types.h:888
@ dnnl_bidirectional_concat
Bidirectional execution of RNN primitive with concatenation of the results.
Definition: dnnl_types.h:1582
A descriptor of a pooling operation.
Definition: dnnl_types.h:1396
@ dnnl_aBcd32b
4D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:260
@ dnnl_ba
permuted 2D tensor
Definition: dnnl_types.h:199
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:1409
@ dnnl_lrn_within_channel
LRN within a single channel.
Definition: dnnl_types.h:926
struct dnnl_engine * dnnl_engine_t
An engine handle.
Definition: dnnl_types.h:1764
dnnl_memory_desc_t data_scaleshift_desc
Scale and shift data and gradient memory descriptors.
Definition: dnnl_types.h:1516
@ dnnl_binary_mul
Binary mul.
Definition: dnnl_types.h:944
@ dnnl_ihwo
4D CNN weights tensor, an alias to dnnl_bcda
Definition: dnnl_types.h:472
dnnl_memory_desc_t src_layer_desc
Source layer memory descriptor.
Definition: dnnl_types.h:1604
@ dnnl_format_tag_undef
Undefined memory format tag.
Definition: dnnl_types.h:166
@ dnnl_binary_min
Binary min.
Definition: dnnl_types.h:948
dnnl_memory_desc_t diff_weights_peephole_desc
Weights gradient peephole memory descriptor.
Definition: dnnl_types.h:1651
@ 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:487
const struct dnnl_primitive_desc_iterator * const_dnnl_primitive_desc_iterator_t
A constant primitive descriptor iterator handle.
Definition: dnnl_types.h:1786
@ dnnl_use_scaleshift
Use scale and shift parameters.
Definition: dnnl_types.h:991
@ dnnl_eltwise_log
Eltwise: natural logarithm.
Definition: dnnl_types.h:894
@ dnnl_query_layer_normalization_d
layer normalization descriptor
Definition: dnnl_types.h:2143
@ dnnl_ldoi
4D LSTM projection tensor in the format (num_layers, num_directions, num_channels_in_recurrent_projec...
Definition: dnnl_types.h:529
int minor
Minor version.
Definition: dnnl_types.h:2230
dnnl_memory_desc_t stat_desc
Mean and variance data memory descriptors.
Definition: dnnl_types.h:1523
@ dnnl_ABcd8b8a
4D tensor blocked by 1st and 2nd dimension with block size 8
Definition: dnnl_types.h:287
@ dnnl_resampling_linear
Linear Resampling Method.
Definition: dnnl_types.h:952
dnnl_dims_t inner_blks
The size of the blocks, e.g. {4, 16, 4} in case of OIhw_4i16o4i
Definition: dnnl_types.h:1065
dnnl_memory_desc_t diff_dst_iter_desc
Destination gradient iteration memory descriptor for hidden state.
Definition: dnnl_types.h:1645
@ dnnl_dhwio
5D CNN weights tensor, an alias to dnnl_cdeba
Definition: dnnl_types.h:480
@ dnnl_forward_training
Forward data propagation (training mode).
Definition: dnnl_types.h:781
@ dnnl_primitive_kind_max
Parameter to allow internal only primitives without undefined behavior.
Definition: dnnl_types.h:846
@ dnnl_eltwise_square
Eltwise: square.
Definition: dnnl_types.h:869
@ dnnl_bac
permuted 3D tensor
Definition: dnnl_types.h:200
@ dnnl_fuse_norm_relu
Fuse with ReLU.
Definition: dnnl_types.h:1004
@ dnnl_bacde
permuted 5D tensor
Definition: dnnl_types.h:202
@ dnnl_cpu_isa_avx512_mic_4ops
Intel AVX-512 subset for Intel Xeon Phi processors 7235, 7285, 7295 Series.
Definition: dnnl_types.h:2277
@ dnnl_tn
2D RNN statistics tensor, an alias to dnnl_ab
Definition: dnnl_types.h:435
const struct dnnl_primitive_desc * const_dnnl_primitive_desc_t
A constant primitive descriptor handle.
Definition: dnnl_types.h:1797
dnnl_memory_desc_t weights_layer_desc
Weights layer memory descriptor.
Definition: dnnl_types.h:1610
dnnl_memory_desc_t weights_peephole_desc
Weights peephole memory descriptor.
Definition: dnnl_types.h:1624
@ 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:1868
dnnl_dims_t strides
The strides between the outermost blocks.
Definition: dnnl_types.h:1059
@ dnnl_convolution_winograd
Winograd convolution.
Definition: dnnl_types.h:855
@ dnnl_iodhw
5D CNN weights tensor, an alias to dnnl_bacde
Definition: dnnl_types.h:478
@ dnnl_ABcde4b16a4b
5D tensor blocked by 1st dimension with block size 16
Definition: dnnl_types.h:301
@ dnnl_nChw8c
4D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcd8b
Definition: dnnl_types.h:564
dnnl_engine_kind_t
Kinds of engines.
Definition: dnnl_types.h:1751
@ dnnl_binary
A binary primitive.
Definition: dnnl_types.h:836
@ dnnl_cdeba
permuted 5D tensor
Definition: dnnl_types.h:209
dnnl_memory_t memory
Input/output memory.
Definition: dnnl_types.h:2070
@ dnnl_eltwise_tanh
Eltwise: hyperbolic tangent non-linearity (tanh)
Definition: dnnl_types.h:865
dnnl_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: dnnl_types.h:1256
@ dnnl_aBc4b
3D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:234
@ dnnl_abcde
plain 5D tensor
Definition: dnnl_types.h:181
@ dnnl_nCw8c
3D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBc8b
Definition: dnnl_types.h:576
struct dnnl_post_ops * dnnl_post_ops_t
A post operation chain handle.
Definition: dnnl_types.h:1865
@ dnnl_query_gemm_d
GEMM descriptor (internal)
Definition: dnnl_types.h:2146
dnnl_dims_t dims
Dimensions in the following order:
Definition: dnnl_types.h:1171
@ dnnl_stream_default_order
Default order execution.
Definition: dnnl_types.h:2179
@ dnnl_pooling
A pooling primitive.
Definition: dnnl_types.h:822
@ dnnl_acdb
permuted 4D tensor
Definition: dnnl_types.h:197
@ dnnl_query_lrn_d
lrn descriptor
Definition: dnnl_types.h:2141
@ dnnl_backward
Backward propagation (with respect to all parameters).
Definition: dnnl_types.h:791
@ dnnl_giohw
5D CNN weights tensor (incl. groups), an alias to dnnl_acbde
Definition: dnnl_types.h:495
A descriptor of a Softmax operation.
Definition: dnnl_types.h:1366
dnnl_dims_t dilates
Convolution dilates in each spatial dimension.
Definition: dnnl_types.h:1268
@ 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:2291
@ 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:1736
@ dnnl_abcdefghi
plain 9D tensor
Definition: dnnl_types.h:185
int inner_nblks
The number of innermost blocks, e.g. 3 in case of OIhw_4i16o4i_
Definition: dnnl_types.h:1063
An opaque structure to describe a primitive descriptor.
@ dnnl_abcdefghijkl
plain 12D tensor
Definition: dnnl_types.h:188
@ dnnl_nCdhw8c
5D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcde8b
Definition: dnnl_types.h:552
@ dnnl_pooling_avg
Average pooling (alias for dnnl_pooling_avg_exclude_padding)
Definition: dnnl_types.h:922
@ dnnl_vanilla_rnn
RNN cell.
Definition: dnnl_types.h:928
@ dnnl_unidirectional
Alias for dnnl_unidirectional_left2right.
Definition: dnnl_types.h:1587
@ dnnl_abdc
permuted 4D tensor
Definition: dnnl_types.h:192
@ dnnl_eltwise_pow
Eltwise: pow.
Definition: dnnl_types.h:898
@ dnnl_ldio
4D LSTM projection tensor in the format (num_layers, num_directions, num_channels_in_hidden_state,...
Definition: dnnl_types.h:526
@ dnnl_aBcd4b
4D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:262
@ dnnl_query_matmul_d
matrix multiplication (matmul) descriptor
Definition: dnnl_types.h:2149
struct dnnl_primitive_desc * dnnl_primitive_desc_t
A primitive descriptor handle.
Definition: dnnl_types.h:1794
const char * hash
Git hash of the sources (may be absent)
Definition: dnnl_types.h:2232
@ dnnl_query_binary_d
binary descriptor
Definition: dnnl_types.h:2147
@ dnnl_lbr_gru
GRU cell with linear before reset.
Definition: dnnl_types.h:940
@ dnnl_forward
Forward data propagation (alias for dnnl_forward_training).
Definition: dnnl_types.h:789
@ dnnl_f32
32-bit/single-precision floating point.
Definition: dnnl_types.h:70
@ dnnl_acbdef
permuted 6D tensor
Definition: dnnl_types.h:196
@ dnnl_iwo
3D CNN weights tensor, an alias to dnnl_bca
Definition: dnnl_types.h:464
@ dnnl_use_global_stats
Use global statistics.
Definition: dnnl_types.h:978
@ dnnl_lrn_across_channels
Local response normalization (LRN) across multiple channels.
Definition: dnnl_types.h:924
@ dnnl_concat
A (out-of-place) concat primitive.
Definition: dnnl_types.h:810
@ dnnl_ntc
3D RNN data tensor in the format (batch, seq_length, input channels).
Definition: dnnl_types.h:506
@ dnnl_query_diff_dst_md
destination grad. memory desc
Definition: dnnl_types.h:2159
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1710
@ 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:1501
unsigned cpu_runtime
CPU runtime.
Definition: dnnl_types.h:2233
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1447
@ dnnl_aBcdef16b
6D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:353
@ dnnl_layer_normalization
A layer normalization primitive.
Definition: dnnl_types.h:828
dnnl_data_type_t data_type
Data type of the tensor elements.
Definition: dnnl_types.h:1174
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1264
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1712
An opaque structure to describe a primitive.
@ dnnl_abcdefgh
plain 8D tensor
Definition: dnnl_types.h:184
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1319
@ dnnl_abcdefghij
plain 10D tensor
Definition: dnnl_types.h:186
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1413
@ dnnl_cpu_isa_all
Any ISA (excepting those listed as initial support)
Definition: dnnl_types.h:2260
dnnl_memory_desc_t diff_weights_layer_desc
Weights gradient layer memory descriptor.
Definition: dnnl_types.h:1637
@ dnnl_query_op_d
op descriptor
Definition: dnnl_types.h:2134
struct dnnl_primitive_desc_iterator * dnnl_primitive_desc_iterator_t
A primitive descriptor iterator handle.
Definition: dnnl_types.h:1783
@ 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:1048
int axis
Axis for shuffling.
Definition: dnnl_types.h:1302
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1372
float lrn_beta
LRN beta parameter.
Definition: dnnl_types.h:1454
@ dnnl_idhwo
5D CNN weights tensor, an alias to dnnl_bcdea
Definition: dnnl_types.h:484
@ dnnl_abcdegf
permuted 7D tensor
Definition: dnnl_types.h:214
@ 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:449
@ dnnl_query_workspace_md
workspace memory desc
Definition: dnnl_types.h:2160
@ dnnl_format_tag_last
Just a sentinel, not real memory format tag.
Definition: dnnl_types.h:424
@ dnnl_query_deconvolution_d
deconvolution descriptor
Definition: dnnl_types.h:2136
struct dnnl_memory * dnnl_memory_t
A memory handle.
Definition: dnnl_types.h:1208
@ dnnl_logsoftmax
A logsoftmax primitive.
Definition: dnnl_types.h:838
@ dnnl_format_tag_any
Undefined memory format tag.
Definition: dnnl_types.h:169
@ dnnl_deconvolution_direct
Direct deconvolution.
Definition: dnnl_types.h:859
@ dnnl_reorder
A reorder primitive.
Definition: dnnl_types.h:806
A descriptor of a Local Response Normalization (LRN) operation.
Definition: dnnl_types.h:1434
@ dnnl_stream_default_flags
Default stream configuration.
Definition: dnnl_types.h:2185
A descriptor of a shuffle operation.
Definition: dnnl_types.h:1291
@ dnnl_owi
3D CNN weights tensor, an alias to dnnl_acb
Definition: dnnl_types.h:460
dnnl_alg_kind_t activation_kind
Activation function used for vanilla_rnn cell kind.
Definition: dnnl_types.h:1661
@ dnnl_backward_data
Backward data propagation.
Definition: dnnl_types.h:793
@ dnnl_acdeb
permuted 5D tensor
Definition: dnnl_types.h:198
Structure containing version information as per Semantic Versioning
Definition: dnnl_types.h:2228
A descriptor of a Batch Normalization operation.
Definition: dnnl_types.h:1465
int arg
An argument index, e.g. DNNL_ARG_SRC.
Definition: dnnl_types.h:2069
@ dnnl_eltwise_exp_use_dst_for_bwd
Eltwise: exp (dst for backward)
Definition: dnnl_types.h:914
dnnl_memory_desc_t weights_iter_desc
Weights iteration memory descriptor.
Definition: dnnl_types.h:1612
dnnl_format_kind_t format_kind
Memory format kind.
Definition: dnnl_types.h:1188
@ dnnl_ldgo
4D RNN bias tensor in the format (num_layers, num_directions, num_gates, output_channels).
Definition: dnnl_types.h:536
dnnl_dim_t dnnl_dims_t[DNNL_MAX_NDIMS]
A type to describe tensor dimensions.
Definition: dnnl_types.h:1051
dnnl_alg_kind_t alg_kind
The kind of eltwise algorithm.
Definition: dnnl_types.h:1332
dnnl_memory_desc_t diff_dst_iter_c_desc
Destination gradient iteration memory descriptor for cell state.
Definition: dnnl_types.h:1647
A descriptor of a element-wise operation.
Definition: dnnl_types.h:1313
dnnl_memory_desc_t diff_src_iter_c_desc
Source gradient iter memory descriptor for cell state.
Definition: dnnl_types.h:1635
@ dnnl_aBcd16b
4D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:254
@ dnnl_resampling_nearest
Nearest Neighbor Resampling Method.
Definition: dnnl_types.h:950
@ dnnl_rnn
A rnn primitive.
Definition: dnnl_types.h:832
@ dnnl_aBc32b
3D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:232
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1641
@ dnnl_query_num_of_outputs_s32
number of outputs expected
Definition: dnnl_types.h:2114
@ dnnl_cpu_isa_sse41
Intel Streaming SIMD Extensions 4.1 (Intel SSE4.1)
Definition: dnnl_types.h:2263
@ dnnl_abcdfe
permuted 6D tensor
Definition: dnnl_types.h:213
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:299
Generic description of blocked data layout for most memory formats.
Definition: dnnl_types.h:1056
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1374
const struct dnnl_primitive * const_dnnl_primitive_t
A constant primitive handle.
Definition: dnnl_types.h:1881
@ dnnl_abdec
permuted 5D tensor
Definition: dnnl_types.h:193
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1425
@ dnnl_cpu_isa_avx2
Intel Advanced Vector Extensions 2 (Intel AVX2)
Definition: dnnl_types.h:2269
@ 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:2286
int ndims
Number of dimensions.
Definition: dnnl_types.h:1156
@ dnnl_aBc8b
3D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:244
A descriptor of a Layer Normalization operation.
Definition: dnnl_types.h:1498
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1708
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1260
@ 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:896
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1544
@ dnnl_eltwise_logistic_use_dst_for_bwd
Eltwise: logistic (dst for backward)
Definition: dnnl_types.h:912
Description of tensor of weights for winograd 2x3 convolution.
Definition: dnnl_types.h:1084
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1475
dnnl_memory_desc_t src_iter_desc
Source iteration memory descriptor for hidden state.
Definition: dnnl_types.h:1606
@ dnnl_abcdefg
plain 7D tensor
Definition: dnnl_types.h:183
@ dnnl_pooling_avg_include_padding
Average pooling include padding.
Definition: dnnl_types.h:918
@ dnnl_hwigo
5D CNN weights tensor (incl. groups), an alias to dnnl_decab
Definition: dnnl_types.h:493
dnnl_memory_desc_t diff_src_iter_desc
Source gradient iter memory descriptor for hidden state.
Definition: dnnl_types.h:1633
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1542
@ dnnl_deconvolution
A deconvolution primitive.
Definition: dnnl_types.h:816
@ dnnl_aBcde4b
5D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:314
dnnl_memory_desc_t data_scaleshift_desc
Scale and shift data and gradient memory descriptors.
Definition: dnnl_types.h:1481
@ dnnl_stream_out_of_order
Out-of-order execution.
Definition: dnnl_types.h:2183
@ dnnl_gemm
A matrix multiplication primitive (internal).
Definition: dnnl_types.h:834
@ dnnl_convolution
A convolution primitive.
Definition: dnnl_types.h:814
struct dnnl_primitive * dnnl_primitive_t
A primitive handle.
Definition: dnnl_types.h:1879
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1445
const struct dnnl_primitive_attr * const_dnnl_primitive_attr_t
A constant primitive descriptor attributes handle.
Definition: dnnl_types.h:1842
An opaque structure for primitive descriptor attributes.
dnnl_memory_desc_t dst_layer_desc
Destination layer memory descriptor.
Definition: dnnl_types.h:1616
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1560
@ dnnl_lrn
An LRN primitive.
Definition: dnnl_types.h:824
@ dnnl_query_src_md
source memory desc
Definition: dnnl_types.h:2154
dnnl_softmax_desc_t dnnl_logsoftmax_desc_t
A descriptor of a LogSoftmax operation.
Definition: dnnl_types.h:1388
#define DNNL_RNN_MAX_N_PARTS
Maximum number of parts of RNN weights tensor that require separate computation.
Definition: dnnl_types.h:1106
dnnl_scratchpad_mode_t
Scratchpad mode.
Definition: dnnl_types.h:1805
dnnl_wino_desc_t wino_desc
Tensor of weights for integer 8bit winograd convolution.
Definition: dnnl_types.h:1194
@ 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:543
@ dnnl_query_engine
execution engine
Definition: dnnl_types.h:2110
dnnl_wino_memory_format_t
Winograd-specific formats.
Definition: dnnl_types.h:1072
@ dnnl_query_softmax_d
softmax descriptor
Definition: dnnl_types.h:2139
A descriptor of resampling operation.
Definition: dnnl_types.h:1721
float batch_norm_epsilon
Batch normalization epsilon parameter.
Definition: dnnl_types.h:1488
@ 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:908
@ dnnl_cpu
CPU engine.
Definition: dnnl_types.h:1755
An opaque structure for a chain of post operations.
@ dnnl_query_undef
no query
Definition: dnnl_types.h:2108
@ dnnl_eltwise_swish
Eltwise: swish.
Definition: dnnl_types.h:892
@ dnnl_ndhwc
5D CNN activations tensor, an alias to dnnl_acdeb
Definition: dnnl_types.h:451
dnnl_memory_desc_t diff_dst_layer_desc
Destination gradient layer memory descriptor.
Definition: dnnl_types.h:1643
@ dnnl_abcdefhg
permuted 8D tensor
Definition: dnnl_types.h:215
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1241
dnnl_dims_t kernel
Pooling kernel spatial dimensions.
Definition: dnnl_types.h:1419
@ dnnl_wino_wei_OBaaIBOIio
Internal weights format for 4x3 Winograd.
Definition: dnnl_types.h:1080
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1548
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1294
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1734
@ dnnl_eltwise_gelu_erf
Eltwise: erf-based gelu.
Definition: dnnl_types.h:900
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1258
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1504
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1468
Memory descriptor.
Definition: dnnl_types.h:1154
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1684
@ dnnl_backward_bias
Backward bias propagation.
Definition: dnnl_types.h:797
void * dnnl_op_desc_t
A pointer to any of the operation descriptors.
Definition: dnnl_types.h:1224
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1546
@ dnnl_ncw
3D CNN activations tensor, an alias to dnnl_abc
Definition: dnnl_types.h:439
@ dnnl_matmul
A matrix multiplication primitive.
Definition: dnnl_types.h:840
int patch
Patch version.
Definition: dnnl_types.h:2231
dnnl_cpu_isa_t
CPU instruction set flags.
Definition: dnnl_types.h:2258
@ dnnl_query_some_md
stub
Definition: dnnl_types.h:2153
const struct dnnl_stream_attr * const_dnnl_stream_attr_t
A constant execution stream attributes handle.
Definition: dnnl_types.h:2201
const struct dnnl_memory * const_dnnl_memory_t
A constant memory handle.
Definition: dnnl_types.h:1211
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1704
@ dnnl_nChw4c
4D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcd4b
Definition: dnnl_types.h:561
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1538
dnnl_memory_desc_t diff_desc
Source and Destination of gradient memory descriptor.
Definition: dnnl_types.h:1376
@ dnnl_oi
2D CNN weights tensor, an alias to dnnl_ab
Definition: dnnl_types.h:454
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1336
@ dnnl_ohwi
4D CNN weights tensor, an alias to dnnl_acdb
Definition: dnnl_types.h:470
@ dnnl_bacd
permuted 4D tensor
Definition: dnnl_types.h:201
@ 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:504
@ dnnl_nChw16c
4D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcd16b
Definition: dnnl_types.h:558
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1297
@ dnnl_query_eltwise_d
eltwise descriptor
Definition: dnnl_types.h:2138
struct dnnl_primitive_attr * dnnl_primitive_attr_t
A primitive descriptor attributes handle that controls primitive behavior.
Definition: dnnl_types.h:1839
@ dnnl_binary_max
Binary max.
Definition: dnnl_types.h:946
@ dnnl_cba
permuted 3D tensor
Definition: dnnl_types.h:206
@ dnnl_query_num_of_inputs_s32
number of inputs expected
Definition: dnnl_types.h:2113
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1738
@ dnnl_acbde
permuted 5D tensor
Definition: dnnl_types.h:195
@ dnnl_dcab
permuted 4D tensor
Definition: dnnl_types.h:208
dnnl_alg_kind_t
Kinds of algorithms.
Definition: dnnl_types.h:850
@ dnnl_deconvolution_winograd
Winograd deconvolution.
Definition: dnnl_types.h:861
const void * const_dnnl_op_desc_t
A pointer to any of the operation descriptors (constant variant).
Definition: dnnl_types.h:1226
@ 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:2273
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:1181
@ dnnl_ldgoi
5D RNN weights tensor in the format (num_layers, num_directions, num_gates, output_channels,...
Definition: dnnl_types.h:523
@ 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:1177
@ dnnl_eltwise_exp
Eltwise: exponent.
Definition: dnnl_types.h:883
@ dnnl_abcdef
plain 6D tensor
Definition: dnnl_types.h:182
@ dnnl_aBCdef2b4c2b
6D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:361
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1676
@ dnnl_goihw
5D CNN weights tensor (incl. groups), an alias to dnnl_abcde
Definition: dnnl_types.h:491
@ dnnl_bidirectional_sum
Bidirectional execution of RNN primitive with summation of the results.
Definition: dnnl_types.h:1585
float alpha
Algorithm specific parameter.
Definition: dnnl_types.h:1357
@ dnnl_eltwise_linear
Eltwise: linear.
Definition: dnnl_types.h:875
@ dnnl_nCw16c
3D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBc16b
Definition: dnnl_types.h:570
@ dnnl_vanilla_gru
GRU cell.
Definition: dnnl_types.h:932
dnnl_memory_desc_t dst_iter_c_desc
Destination iter memory descriptor for cell state.
Definition: dnnl_types.h:1620
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1245
dnnl_alg_kind_t alg_kind
The kind of the binary algorithm.
Definition: dnnl_types.h:1680
@ 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:567
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:1068
@ dnnl_wigo
4D CNN weights tensor (incl. groups), an alias to dnnl_dcab
Definition: dnnl_types.h:489
A descriptor of a binary operation.
Definition: dnnl_types.h:1673
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1706
dnnl_memory_extra_flags_t
Flags for memory special features.
Definition: dnnl_types.h:1123
@ dnnl_convolution_direct
Direct convolution.
Definition: dnnl_types.h:853
unsigned gpu_runtime
GPU runtime.
Definition: dnnl_types.h:2234
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1437
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1415
@ dnnl_query_diff_src_md
source gradient memory desc
Definition: dnnl_types.h:2155
@ dnnl_abcdefgih
permuted 9D tensor
Definition: dnnl_types.h:216
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1732
@ dnnl_wio
3D CNN weights tensor, an alias to dnnl_cba
Definition: dnnl_types.h:462
@ dnnl_nChw32c
4D CNN activations tensor blocked by channels with block size 32, an alias to dnnl_aBcd32b
Definition: dnnl_types.h:555
dnnl_memory_desc_t diff_src_layer_desc
Source gradient layer memory descriptor.
Definition: dnnl_types.h:1631
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1558
@ dnnl_forward_scoring
Forward data propagation (alias for dnnl_forward_inference).
Definition: dnnl_types.h:787
@ dnnl_aBcde8b
5D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:329
@ dnnl_prop_kind_undef
Undefined propagation type.
Definition: dnnl_types.h:778
@ 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:1597
@ dnnl_query_primitive_kind
primitive kind
Definition: dnnl_types.h:2111
@ dnnl_unidirectional_left2right
Unidirectional execution of RNN primitive from left to right.
Definition: dnnl_types.h:1577
dnnl_memory_desc_t diff_weights_iter_desc
Weights gradient iter memory descriptor.
Definition: dnnl_types.h:1639
@ dnnl_iohw
4D CNN weights tensor, an alias to dnnl_bacd
Definition: dnnl_types.h:474
@ dnnl_eltwise_elu
Eltwise: exponential linear unit (elu)
Definition: dnnl_types.h:867
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1316
@ dnnl_odhwi
5D CNN weights tensor, an alias to dnnl_acdeb
Definition: dnnl_types.h:482
@ dnnl_nwc
3D CNN activations tensor, an alias to dnnl_acb
Definition: dnnl_types.h:441
@ dnnl_nCw4c
3D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBc4b
Definition: dnnl_types.h:573
@ dnnl_aBcde32b
5D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:312
@ dnnl_vanilla_lstm
LSTM cell.
Definition: dnnl_types.h:930
@ dnnl_any_engine
An unspecified engine.
Definition: dnnl_types.h:1753
@ dnnl_nCdhw4c
5D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcde4b
Definition: dnnl_types.h:549
@ dnnl_resampling
A resampling primitive.
Definition: dnnl_types.h:842
@ dnnl_wino_wei_aaOBiOo
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:1078
@ dnnl_cpu_isa_avx
Intel Advanced Vector Extensions (Intel AVX)
Definition: dnnl_types.h:2266
@ dnnl_bca
permuted 3D tensor
Definition: dnnl_types.h:203
dnnl_prop_kind_t
Kinds of propagation.
Definition: dnnl_types.h:775
@ dnnl_query_scratchpad_md
scratchpad memory desc
Definition: dnnl_types.h:2161
float lrn_k
LRN k parameter.
Definition: dnnl_types.h:1456
@ dnnl_nchw
4D CNN activations tensor, an alias to dnnl_abcd
Definition: dnnl_types.h:443
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1727
@ dnnl_eltwise_gelu
Eltwise: tanh-based gelu (alias for dnnl_eltwise_gelu_tanh)
Definition: dnnl_types.h:890
dnnl_alg_kind_t alg_kind
LRN algorithm.
Definition: dnnl_types.h:1443
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:1450
@ dnnl_query_weights_md
weights memory descriptor desc
Definition: dnnl_types.h:2156
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1554
dnnl_alg_kind_t alg_kind
The kind of the resampling algorithm.
Definition: dnnl_types.h:1730
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1411
dnnl_memory_desc_t data_desc
Source and destination memory descriptor, and source and destination gradient memory descriptor.
Definition: dnnl_types.h:1300
@ dnnl_query_batch_normalization_d
batch normalization descriptor
Definition: dnnl_types.h:2142
@ dnnl_eltwise_tanh_use_dst_for_bwd
Eltwise: hyperbolic tangent non-linearity (tanh) (dst for backward)
Definition: dnnl_types.h:906
dnnl_dims_t strides
Pooling kernel strides for spatial dimensions.
Definition: dnnl_types.h:1417
dnnl_memory_desc_t dst_iter_desc
Destination iter memory descriptor for hidden state.
Definition: dnnl_types.h:1618
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1274
@ dnnl_chwn
4D CNN activations tensor, an alias to dnnl_bcda
Definition: dnnl_types.h:447
dnnl_alg_kind_t cell_kind
RNN cell kind.
Definition: dnnl_types.h:1600
@ dnnl_undefined_primitive
Undefined primitive.
Definition: dnnl_types.h:804
@ dnnl_eltwise_soft_relu
Eltwise: soft_relu.
Definition: dnnl_types.h:879
@ dnnl_abcdefghikj
permuted 11D tensor
Definition: dnnl_types.h:218
@ dnnl_nt
2D RNN statistics tensor, an alias to dnnl_ba
Definition: dnnl_types.h:437
dnnl_convolution_desc_t dnnl_deconvolution_desc_t
A descriptor of a deconvolution operation.
Definition: dnnl_types.h:1283
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:1185
@ dnnl_unidirectional_right2left
Unidirectional execution of RNN primitive from right to left.
Definition: dnnl_types.h:1579
@ dnnl_aBcd8b
4D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:281
@ 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:1196
@ dnnl_query_scratchpad_engine
(scratch) memory, additional to all inputs and outputs memory (bytes)
Definition: dnnl_types.h:2122
@ 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:499
@ dnnl_query_exec_arg_md
memory desc of an execute argument
Definition: dnnl_types.h:2162
@ dnnl_query_some_d
stub
Definition: dnnl_types.h:2133
@ dnnl_pooling_avg_exclude_padding
Average pooling exclude padding.
Definition: dnnl_types.h:920
@ dnnl_binary_add
Binary add.
Definition: dnnl_types.h:942