563 dnnl_NCw16n16c = dnnl_ABc16a16b,
564 dnnl_NCdhw16n16c = dnnl_ABcde16a16b,
565 dnnl_NChw16n16c = dnnl_ABcd16a16b,
566 dnnl_NCw32n32c = dnnl_ABc32a32b,
567 dnnl_NChw32n32c = dnnl_ABcd32a32b,
568 dnnl_NCdhw32n32c = dnnl_ABcde32a32b,
571 dnnl_IOw16o16i = dnnl_BAc16a16b,
572 dnnl_IOw16i16o = dnnl_BAc16b16a,
573 dnnl_OIw16i16o = dnnl_ABc16b16a,
574 dnnl_OIw16o16i = dnnl_ABc16a16b,
575 dnnl_Oiw16o = dnnl_Abc16a,
576 dnnl_OIw4i16o4i = dnnl_ABc4b16a4b,
577 dnnl_OIw2i8o4i = dnnl_ABc2b8a4b,
578 dnnl_OIw16i16o4i = dnnl_ABc16b16a4b,
579 dnnl_OIw16i16o2i = dnnl_ABc16b16a2b,
580 dnnl_OIw4i4o = dnnl_ABc4b4a,
581 dnnl_OIw4o4i = dnnl_ABc4a4b,
582 dnnl_Oiw4o = dnnl_Abc4a,
583 dnnl_OIw8i16o2i = dnnl_ABc8b16a2b,
584 dnnl_OIw8i8o = dnnl_ABc8b8a,
585 dnnl_OIw8o16i2o = dnnl_ABc8a16b2a,
586 dnnl_IOw8o16i2o = dnnl_BAc8a16b2a,
587 dnnl_OIw8o8i = dnnl_ABc8a8b,
588 dnnl_OIw8o4i = dnnl_ABc8a4b,
589 dnnl_Owi16o = dnnl_Acb16a,
590 dnnl_OwI16o2i = dnnl_AcB16a2b,
591 dnnl_OwI16o4i = dnnl_AcB16a4b,
592 dnnl_Owi4o = dnnl_Acb4a,
593 dnnl_Owi8o = dnnl_Acb8a,
596 dnnl_IOhw16i16o = dnnl_BAcd16b16a,
597 dnnl_IOhw16o16i = dnnl_BAcd16a16b,
598 dnnl_Ohwi16o = dnnl_Acdb16a,
599 dnnl_OhwI16o2i = dnnl_AcdB16a2b,
600 dnnl_OhwI16o4i = dnnl_AcdB16a4b,
601 dnnl_Ohwi32o = dnnl_Acdb32a,
602 dnnl_Ohwi4o = dnnl_Acdb4a,
603 dnnl_Ohwi8o = dnnl_Acdb8a,
604 dnnl_OIhw16i16o = dnnl_ABcd16b16a,
605 dnnl_OIhw16o16i = dnnl_ABcd16a16b,
606 dnnl_Oihw16o = dnnl_Abcd16a,
607 dnnl_OIhw4i16o4i = dnnl_ABcd4b16a4b,
608 dnnl_OIhw16i16o4i = dnnl_ABcd16b16a4b,
609 dnnl_OIhw16i16o2i = dnnl_ABcd16b16a2b,
610 dnnl_OIhw4i4o = dnnl_ABcd4b4a,
611 dnnl_OIhw4o4i = dnnl_ABcd4a4b,
612 dnnl_Oihw4o = dnnl_Abcd4a,
613 dnnl_OIhw8i16o2i = dnnl_ABcd8b16a2b,
615 dnnl_OIhw8o16i2o = dnnl_ABcd8a16b2a,
616 dnnl_OIhw2i8o4i = dnnl_ABcd2b8a4b,
617 dnnl_IOhw8o16i2o = dnnl_BAcd8a16b2a,
618 dnnl_OIhw8o8i = dnnl_ABcd8a8b,
619 dnnl_OIhw8o4i = dnnl_ABcd8a4b,
622 dnnl_Odhwi16o = dnnl_Acdeb16a,
623 dnnl_OdhwI16o2i = dnnl_AcdeB16a2b,
624 dnnl_Odhwi4o = dnnl_Acdeb4a,
625 dnnl_Odhwi8o = dnnl_Acdeb8a,
626 dnnl_OIdhw16i16o = dnnl_ABcde16b16a,
627 dnnl_OIdhw16o16i = dnnl_ABcde16a16b,
628 dnnl_Oidhw16o = dnnl_Abcde16a,
629 dnnl_OIdhw4i4o = dnnl_ABcde4b4a,
630 dnnl_OIdhw4o4i = dnnl_ABcde4a4b,
631 dnnl_Oidhw4o = dnnl_Abcde4a,
632 dnnl_OIdhw8i16o2i = dnnl_ABcde8b16a2b,
633 dnnl_OIdhw8i8o = dnnl_ABcde8b8a,
634 dnnl_OIdhw8o16i2o = dnnl_ABcde8a16b2a,
635 dnnl_IOdhw8o16i2o = dnnl_BAcde8a16b2a,
638 dnnl_OIdhw8o8i = dnnl_ABcde8a8b,
639 dnnl_OIdhw8o4i = dnnl_ABcde8a4b,
640 dnnl_IOdhw16i16o = dnnl_BAcde16b16a,
641 dnnl_OIdhw4o8i8o4i = dnnl_ABcde4a8b8a4b,
642 dnnl_IOdhw16o16i = dnnl_BAcde16a16b,
645 dnnl_Goiw16g = dnnl_Abcd16a,
646 dnnl_Goiw8g = dnnl_Abcd8a,
647 dnnl_gIOw16o16i = dnnl_aCBd16b16c,
648 dnnl_gIOw16i16o = dnnl_aCBd16c16b,
649 dnnl_gOIw16i16o = dnnl_aBCd16c16b,
650 dnnl_gOIw16o16i = dnnl_aBCd16b16c,
652 dnnl_gOIw4i16o4i = dnnl_aBCd4c16b4c,
653 dnnl_gOIw2i8o4i = dnnl_aBCd2c8b4c,
654 dnnl_gOIw16i16o4i = dnnl_aBCd16c16b4c,
655 dnnl_gOIw16i16o2i = dnnl_aBCd16c16b2c,
656 dnnl_gOIw4i4o = dnnl_aBCd4c4b,
657 dnnl_gOIw4o4i = dnnl_aBCd4b4c,
659 dnnl_gOIw8i16o2i = dnnl_aBCd8c16b2c,
660 dnnl_gOIw8i8o = dnnl_aBCd8c8b,
661 dnnl_gOIw8o16i2o = dnnl_aBCd8b16c2b,
662 dnnl_gIOw8o16i2o = dnnl_aCBd8b16c2b,
663 dnnl_gOIw8o8i = dnnl_aBCd8b8c,
664 dnnl_gOIw8o4i = dnnl_aBCd8b4c,
665 dnnl_gOwi16o = dnnl_aBdc16b,
666 dnnl_gOwI16o2i = dnnl_aBdC16b2c,
667 dnnl_gOwI16o4i = dnnl_aBdC16b4c,
668 dnnl_gOwi4o = dnnl_aBdc4b,
669 dnnl_gOwi8o = dnnl_aBdc8b,
670 dnnl_Goiw32g = dnnl_Abcd32a,
671 dnnl_gOIw2i4o2i = dnnl_aBCd2c4b2c,
673 dnnl_gOIw4i8o2i = dnnl_aBCd4c8b2c,
674 dnnl_gOIw4o8i2o = dnnl_aBCd4b8c2b,
677 dnnl_gIOhw16i16o = dnnl_aCBde16c16b,
678 dnnl_gIOhw16o16i = dnnl_aCBde16b16c,
679 dnnl_gOhwi16o = dnnl_aBdec16b,
680 dnnl_gOhwI16o2i = dnnl_aBdeC16b2c,
681 dnnl_gOhwI16o4i = dnnl_aBdeC16b4c,
682 dnnl_gOhwi32o = dnnl_aBdec32b,
683 dnnl_gOhwi4o = dnnl_aBdec4b,
684 dnnl_gOhwi8o = dnnl_aBdec8b,
685 dnnl_Goihw16g = dnnl_Abcde16a,
686 dnnl_gOIhw16i16o = dnnl_aBCde16c16b,
687 dnnl_gOIhw16o16i = dnnl_aBCde16b16c,
689 dnnl_gOIhw2i8o4i = dnnl_aBCde2c8b4c,
690 dnnl_gOIhw4i16o4i = dnnl_aBCde4c16b4c,
691 dnnl_gOIhw16i16o4i = dnnl_aBCde16c16b4c,
692 dnnl_gOIhw16i16o2i = dnnl_aBCde16c16b2c,
693 dnnl_gOIhw4i4o = dnnl_aBCde4c4b,
694 dnnl_gOIhw4o4i = dnnl_aBCde4b4c,
696 dnnl_Goihw8g = dnnl_Abcde8a,
697 dnnl_gOIhw8i16o2i = dnnl_aBCde8c16b2c,
698 dnnl_gOIhw8i8o = dnnl_aBCde8c8b,
699 dnnl_gOIhw8o16i2o = dnnl_aBCde8b16c2b,
700 dnnl_gIOhw8o16i2o = dnnl_aCBde8b16c2b,
701 dnnl_gOIhw8o8i = dnnl_aBCde8b8c,
702 dnnl_gOIhw8o4i = dnnl_aBCde8b4c,
703 dnnl_Goihw32g = dnnl_Abcde32a,
705 dnnl_OIw4o8i8o4i = dnnl_ABc4a8b8a4b,
706 dnnl_OIhw4o8i8o4i = dnnl_ABcd4a8b8a4b,
707 dnnl_IOw4i8o8i4o = dnnl_BAc4b8a8b4a,
708 dnnl_IOhw4i8o8i4o = dnnl_BAcd4b8a8b4a,
709 dnnl_IOdhw4i8o8i4o = dnnl_BAcde4b8a8b4a,
711 dnnl_OIhw2o8i8o2i = dnnl_ABcd2a8b8a2b,
712 dnnl_gOIw4o8i8o4i = dnnl_aBCd4b8c8b4c,
713 dnnl_gOIhw4o8i8o4i = dnnl_aBCde4b8c8b4c,
714 dnnl_gOIdhw4o8i8o4i = dnnl_aBCdef4b8c8b4c,
715 dnnl_gIOw4i8o8i4o = dnnl_aCBd4c8b8c4b,
716 dnnl_gIOhw4i8o8i4o = dnnl_aCBde4c8b8c4b,
717 dnnl_gIOdhw4i8o8i4o = dnnl_aCBdef4c8b8c4b,
718 dnnl_gOIhw2o8i8o2i = dnnl_aBCde2b8c8b2c,
719 dnnl_gOIhw2i4o2i = dnnl_aBCde2c4b2c,
721 dnnl_gOIhw4i8o2i = dnnl_aBCde4c8b2c,
722 dnnl_gOIhw4o8i2o = dnnl_aBCde4b8c2b,
725 dnnl_gIOdhw16i16o = dnnl_aCBdef16c16b,
726 dnnl_gIOdhw16o16i = dnnl_aCBdef16b16c,
727 dnnl_gOdhwi16o = dnnl_aBdefc16b,
728 dnnl_gOdhwI16o2i = dnnl_aBdefC16b2c,
729 dnnl_gOdhwi4o = dnnl_aBdefc4b,
730 dnnl_gOdhwi8o = dnnl_aBdefc8b,
731 dnnl_gOIdhw16i16o = dnnl_aBCdef16c16b,
732 dnnl_gOIdhw4i16o4i = dnnl_aBCdef4c16b4c,
734 dnnl_gOIdhw16o16i = dnnl_aBCdef16b16c,
736 dnnl_gOIdhw4i4o = dnnl_aBCdef4c4b,
737 dnnl_gOIdhw4o4i = dnnl_aBCdef4b4c,
739 dnnl_gOIdhw8i16o2i = dnnl_aBCdef8c16b2c,
740 dnnl_gOIdhw8i8o = dnnl_aBCdef8c8b,
741 dnnl_gOIdhw8o16i2o = dnnl_aBCdef8b16c2b,
742 dnnl_gIOdhw8o16i2o = dnnl_aCBdef8b16c2b,
743 dnnl_gOIdhw8o8i = dnnl_aBCdef8b8c,
744 dnnl_gOIdhw8o4i = dnnl_aBCdef8b4c,
745 dnnl_Goidhw16g = dnnl_Abcdef16a,
746 dnnl_Goidhw32g = dnnl_Abcdef32a,
747 dnnl_gOIdhw2i4o2i = dnnl_aBCdef2c4b2c,
748 dnnl_gOIdhw4i8o2i = dnnl_aBCdef4c8b2c,
750 dnnl_gOIdhw4o8i2o = dnnl_aBCdef4b8c2b,
1002 #define DNNL_MAX_NDIMS 12 1006 #define DNNL_RUNTIME_DIM_VAL INT64_MIN 1011 #define DNNL_RUNTIME_SIZE_VAL ((size_t)DNNL_RUNTIME_DIM_VAL) 1015 static const union {
1018 } DNNL_RUNTIME_F32_VAL_REP = {0x7fc000d0};
1023 #define DNNL_RUNTIME_F32_VAL (DNNL_RUNTIME_F32_VAL_REP.f) 1026 static const int DNNL_RUNTIME_S32_VAL_REP = INT32_MIN;
1031 #define DNNL_RUNTIME_S32_VAL DNNL_RUNTIME_S32_VAL_REP 1085 dnnl_packed_format_undef = 0,
1088 } dnnl_rnn_packed_memory_format_t;
1092 #define DNNL_RNN_MAX_N_PARTS 4 1096 dnnl_rnn_packed_memory_format_t format;
1103 size_t offset_compensation;
1110 dnnl_memory_extra_flag_none = 0x0U,
1119 dnnl_memory_extra_flag_scale_adjust = 0x2U,
1120 dnnl_memory_extra_flag_gpu_rnn_u8s8_compensation = 0x4U,
1199 #define DNNL_MEMORY_NONE (NULL) 1200 #define DNNL_MEMORY_ALLOCATE ((void *)(size_t)-1) 1754 typedef const struct dnnl_engine *const_dnnl_engine_t;
1870 #define DNNL_ARG_SRC_0 1 1871 #define DNNL_ARG_SRC DNNL_ARG_SRC_0 1874 #define DNNL_ARG_SRC_LAYER DNNL_ARG_SRC_0 1877 #define DNNL_ARG_FROM DNNL_ARG_SRC_0 1882 #define DNNL_ARG_SRC_1 2 1883 #define DNNL_ARG_SRC_ITER DNNL_ARG_SRC_1 1888 #define DNNL_ARG_SRC_2 3 1889 #define DNNL_ARG_SRC_ITER_C DNNL_ARG_SRC_2 1894 #define DNNL_ARG_DST_0 17 1895 #define DNNL_ARG_DST DNNL_ARG_DST_0 1898 #define DNNL_ARG_TO DNNL_ARG_DST_0 1901 #define DNNL_ARG_DST_LAYER DNNL_ARG_DST_0 1905 #define DNNL_ARG_DST_1 18 1906 #define DNNL_ARG_DST_ITER DNNL_ARG_DST_1 1911 #define DNNL_ARG_DST_2 19 1912 #define DNNL_ARG_DST_ITER_C DNNL_ARG_DST_2 1917 #define DNNL_ARG_WEIGHTS_0 33 1918 #define DNNL_ARG_WEIGHTS DNNL_ARG_WEIGHTS_0 1921 #define DNNL_ARG_SCALE_SHIFT DNNL_ARG_WEIGHTS_0 1924 #define DNNL_ARG_WEIGHTS_LAYER DNNL_ARG_WEIGHTS_0 1929 #define DNNL_ARG_WEIGHTS_1 34 1930 #define DNNL_ARG_WEIGHTS_ITER DNNL_ARG_WEIGHTS_1 1935 #define DNNL_ARG_WEIGHTS_2 35 1936 #define DNNL_ARG_WEIGHTS_PEEPHOLE DNNL_ARG_WEIGHTS_2 1941 #define DNNL_ARG_WEIGHTS_3 36 1942 #define DNNL_ARG_WEIGHTS_PROJECTION DNNL_ARG_WEIGHTS_3 1947 #define DNNL_ARG_BIAS 41 1950 #define DNNL_ARG_MEAN 49 1951 #define DNNL_ARG_VARIANCE 50 1956 #define DNNL_ARG_WORKSPACE 64 1957 #define DNNL_ARG_SCRATCHPAD 80 1961 #define DNNL_ARG_DIFF_SRC_0 129 1962 #define DNNL_ARG_DIFF_SRC DNNL_ARG_DIFF_SRC_0 1965 #define DNNL_ARG_DIFF_SRC_LAYER DNNL_ARG_DIFF_SRC_0 1970 #define DNNL_ARG_DIFF_SRC_1 130 1971 #define DNNL_ARG_DIFF_SRC_ITER DNNL_ARG_DIFF_SRC_1 1976 #define DNNL_ARG_DIFF_SRC_2 131 1977 #define DNNL_ARG_DIFF_SRC_ITER_C DNNL_ARG_DIFF_SRC_2 1982 #define DNNL_ARG_DIFF_DST_0 145 1983 #define DNNL_ARG_DIFF_DST DNNL_ARG_DIFF_DST_0 1986 #define DNNL_ARG_DIFF_DST_LAYER DNNL_ARG_DIFF_DST_0 1991 #define DNNL_ARG_DIFF_DST_1 146 1992 #define DNNL_ARG_DIFF_DST_ITER DNNL_ARG_DIFF_DST_1 1997 #define DNNL_ARG_DIFF_DST_2 147 1998 #define DNNL_ARG_DIFF_DST_ITER_C DNNL_ARG_DIFF_DST_2 2003 #define DNNL_ARG_DIFF_WEIGHTS_0 161 2004 #define DNNL_ARG_DIFF_WEIGHTS DNNL_ARG_DIFF_WEIGHTS_0 2007 #define DNNL_ARG_DIFF_SCALE_SHIFT DNNL_ARG_DIFF_WEIGHTS_0 2010 #define DNNL_ARG_DIFF_WEIGHTS_LAYER DNNL_ARG_DIFF_WEIGHTS_0 2015 #define DNNL_ARG_DIFF_WEIGHTS_1 162 2016 #define DNNL_ARG_DIFF_WEIGHTS_ITER DNNL_ARG_DIFF_WEIGHTS_1 2021 #define DNNL_ARG_DIFF_WEIGHTS_2 163 2022 #define DNNL_ARG_DIFF_WEIGHTS_PEEPHOLE DNNL_ARG_DIFF_WEIGHTS_2 2027 #define DNNL_ARG_DIFF_WEIGHTS_3 164 2028 #define DNNL_ARG_DIFF_WEIGHTS_PROJECTION DNNL_ARG_DIFF_WEIGHTS_3 2033 #define DNNL_ARG_DIFF_BIAS 169 2036 #define DNNL_ARG_ATTR_OUTPUT_SCALES 513 2040 #define DNNL_ARG_MULTIPLE_SRC 1024 2041 #define DNNL_ARG_MULTIPLE_DST 2048 2046 #define DNNL_ARG_ATTR_ZERO_POINTS 4096 2050 #define DNNL_ARG_ATTR_POST_OP_DW 8192 2151 dnnl_query_max = 0x7fff,
2183 struct dnnl_stream_attr;
2195 #define DNNL_RUNTIME_NONE 0u 2198 #define DNNL_RUNTIME_SEQ 1u 2201 #define DNNL_RUNTIME_OMP 2u 2204 #define DNNL_RUNTIME_TBB 4u 2207 #define DNNL_RUNTIME_THREADPOOL 8u 2210 #define DNNL_RUNTIME_OCL 256u 2224 #define DNNL_JIT_PROFILE_NONE 0u 2227 #define DNNL_JIT_PROFILE_VTUNE 1u 2230 #define DNNL_JIT_PROFILE_LINUX_PERFMAP 2u 2233 #define DNNL_JIT_PROFILE_LINUX_JITDUMP 4u 2237 #define DNNL_JIT_PROFILE_LINUX_JITDUMP_USE_TSC 8u 2240 #define DNNL_JIT_PROFILE_LINUX_PERF \ 2241 (DNNL_JIT_PROFILE_LINUX_JITDUMP | DNNL_JIT_PROFILE_LINUX_PERFMAP) dnnl_memory_desc_t diff_dst_layer_desc
Destination gradient layer memory descriptor.
Definition: dnnl_types.h:1629
A layer normalization primitive.
Definition: dnnl_types.h:814
destination grad. memory desc
Definition: dnnl_types.h:2145
An element-wise primitive.
Definition: dnnl_types.h:804
dnnl_alg_kind_t activation_kind
Activation function used for vanilla_rnn cell kind.
Definition: dnnl_types.h:1647
dnnl_memory_desc_t weights_layer_desc
Weights layer memory descriptor.
Definition: dnnl_types.h:1596
dnnl_alg_kind_t alg_kind
The kind of pooling algorithm.
Definition: dnnl_types.h:1393
6D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:347
execution engine
Definition: dnnl_types.h:2096
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1534
dnnl_memory_desc_t diff_dst_iter_c_desc
Destination gradient iteration memory descriptor for cell state.
Definition: dnnl_types.h:1633
A batch normalization primitive.
Definition: dnnl_types.h:812
Eltwise: bounded_relu.
Definition: dnnl_types.h:863
Undefined memory format tag.
Definition: dnnl_types.h:169
3D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:214
A tensor in a generic format described by the stride and blocking values in each dimension.
Definition: dnnl_types.h:89
4D LSTM projection tensor in the format (num_layers, num_directions, num_channels_in_hidden_state, num_channels_in_recurrent_projection).
Definition: dnnl_types.h:512
CPU engine.
Definition: dnnl_types.h:1741
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1454
Eltwise: ReLU (dst for backward)
Definition: dnnl_types.h:890
destination memory desc
Definition: dnnl_types.h:2144
Direct deconvolution.
Definition: dnnl_types.h:845
struct dnnl_memory * dnnl_memory_t
A memory handle.
Definition: dnnl_types.h:1194
A descriptor for an RNN operation.
Definition: dnnl_types.h:1577
The user manages the scratchpad allocation by querying and providing the scratchpad memory to primiti...
Definition: dnnl_types.h:1813
layer normalization descriptor
Definition: dnnl_types.h:2129
memory consumption – extra
Definition: dnnl_types.h:2103
dnnl_primitive_kind_t
Kinds of primitives.
Definition: dnnl_types.h:788
permuted 3D tensor
Definition: dnnl_types.h:194
Eltwise: linear.
Definition: dnnl_types.h:861
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1538
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:1436
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:1063
dnnl_memory_desc_t data_scaleshift_desc
Scale and shift data and gradient memory descriptors.
Definition: dnnl_types.h:1502
void * dnnl_op_desc_t
A pointer to any of the operation descriptors.
Definition: dnnl_types.h:1210
dnnl_alg_kind_t alg_kind
LRN algorithm.
Definition: dnnl_types.h:1429
A resampling primitive.
Definition: dnnl_types.h:828
dnnl_format_kind_t format_kind
Memory format kind.
Definition: dnnl_types.h:1174
An opaque structure to describe a primitive.
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1457
GRU cell with linear before reset.
Definition: dnnl_types.h:926
Any ISA (excepting those listed as initial support)
Definition: dnnl_types.h:2246
dnnl_dims_t strides
Pooling kernel strides for spatial dimensions.
Definition: dnnl_types.h:1403
4D CNN weights tensor, an alias to dnnl_acdb
Definition: dnnl_types.h:456
Undefined data type, used for empty memory descriptors.
Definition: dnnl_types.h:64
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1696
dnnl_dim_t group_size
Number of groups.
Definition: dnnl_types.h:1290
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1244
5D CNN weights tensor, an alias to dnnl_acdeb
Definition: dnnl_types.h:468
dnnl_convolution_desc_t dnnl_deconvolution_desc_t
A descriptor of a deconvolution operation.
Definition: dnnl_types.h:1269
4D CNN weights tensor (incl. groups), an alias to dnnl_abcd
Definition: dnnl_types.h:473
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1355
dnnl_alg_kind_t alg_kind
The kind of the convolution algorithm.
Definition: dnnl_types.h:1234
In-order execution.
Definition: dnnl_types.h:2167
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1260
Use no normalization flags.
Definition: dnnl_types.h:951
scratchpad memory desc
Definition: dnnl_types.h:2147
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1718
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1388
dnnl_memory_t memory
Input/output memory.
Definition: dnnl_types.h:2056
const void * const_dnnl_op_desc_t
A pointer to any of the operation descriptors (constant variant).
Definition: dnnl_types.h:1212
Intel Streaming SIMD Extensions 4.1 (Intel SSE4.1)
Definition: dnnl_types.h:2249
Eltwise: clip.
Definition: dnnl_types.h:882
Intel AVX-512, Intel DL Boost and bfloat16 support and Intel AMX with 8-bit integer and bfloat16 supp...
Definition: dnnl_types.h:2282
An opaque structure for primitive descriptor attributes.
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1248
logsoftmax descriptor
Definition: dnnl_types.h:2134
permuted 4D tensor
Definition: dnnl_types.h:191
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1395
float lrn_alpha
LRN alpha parameter.
Definition: dnnl_types.h:1438
dnnl_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: dnnl_types.h:1536
dnnl_memory_desc_t dst_iter_c_desc
Destination iter memory descriptor for cell state.
Definition: dnnl_types.h:1606
Primitive iterator passed over last primitive descriptor.
Definition: dnnl_types.h:49
int minor
Minor version.
Definition: dnnl_types.h:2216
2D CNN weights tensor, an alias to dnnl_ab
Definition: dnnl_types.h:440
An opaque structure to describe a memory.
dnnl_memory_desc_t dst_layer_desc
Destination layer memory descriptor.
Definition: dnnl_types.h:1602
permuted 5D tensor
Definition: dnnl_types.h:192
dnnl_engine_kind_t
Kinds of engines.
Definition: dnnl_types.h:1737
struct dnnl_primitive_desc * dnnl_primitive_desc_t
A primitive descriptor handle.
Definition: dnnl_types.h:1780
Eltwise: square root (dst for backward)
Definition: dnnl_types.h:896
non-standard 16-bit (bfloat16 w/ 7 bit mantissa) floating point.
Definition: dnnl_types.h:68
Parameter to allow internal only primitives without undefined behavior.
Definition: dnnl_types.h:832
Undefined primitive.
Definition: dnnl_types.h:790
dnnl_dims_t strides
Convolution strides in each spatial dimension.
Definition: dnnl_types.h:1252
int softmax_axis
The axis along which to perform the softmax.
Definition: dnnl_types.h:1364
Unidirectional execution of RNN primitive from left to right.
Definition: dnnl_types.h:1563
The library manages the scratchpad allocation according to the policy specified by the DNNL_ENABLE_CO...
Definition: dnnl_types.h:1808
5D CNN weights tensor (incl. groups), an alias to dnnl_acbde
Definition: dnnl_types.h:481
3D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:220
3D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBc8b ...
Definition: dnnl_types.h:562
dnnl_dims_t dims
Dimensions in the following order:
Definition: dnnl_types.h:1157
const struct dnnl_memory * const_dnnl_memory_t
A constant memory handle.
Definition: dnnl_types.h:1197
4D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcd16b ...
Definition: dnnl_types.h:544
binary descriptor
Definition: dnnl_types.h:2133
dnnl_memory_desc_t diff_weights_iter_desc
Weights gradient iter memory descriptor.
Definition: dnnl_types.h:1625
permuted 4D tensor
Definition: dnnl_types.h:186
Description of tensor of packed weights for rnn.
Definition: dnnl_types.h:1095
A descriptor of a pooling operation.
Definition: dnnl_types.h:1382
2D CNN activations tensor, an alias to dnnl_ab
Definition: dnnl_types.h:417
plain 2D tensor
Definition: dnnl_types.h:178
4D CNN activations tensor, an alias to dnnl_bcda
Definition: dnnl_types.h:433
4D RNN bias tensor in the format (num_layers, num_directions, num_gates, output_channels).
Definition: dnnl_types.h:522
permuted 5D tensor
Definition: dnnl_types.h:199
Undefined memory format kind, used for empty memory descriptors.
Definition: dnnl_types.h:82
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1694
Bidirectional execution of RNN primitive with summation of the results.
Definition: dnnl_types.h:1571
32-bit signed integer.
Definition: dnnl_types.h:72
dnnl_memory_desc_t diff_src_iter_c_desc
Source gradient iter memory descriptor for cell state.
Definition: dnnl_types.h:1621
int inner_nblks
The number of innermost blocks, e.g. 3 in case of OIhw_4i16o4i_
Definition: dnnl_types.h:1049
Direct convolution.
Definition: dnnl_types.h:839
int major
Major version.
Definition: dnnl_types.h:2215
Just a sentinel, not real memory format tag.
Definition: dnnl_types.h:410
5D tensor blocked by 1st dimension with block size 8
Definition: dnnl_types.h:289
An opaque structure to describe a primitive descriptor iterator.
pooling descriptor
Definition: dnnl_types.h:2126
Convolution algorithm(either direct or Winograd) is chosen just in time.
Definition: dnnl_types.h:843
float lrn_beta
LRN beta parameter.
Definition: dnnl_types.h:1440
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1530
Unidirectional execution of RNN primitive from right to left.
Definition: dnnl_types.h:1565
A deconvolution primitive.
Definition: dnnl_types.h:802
dnnl_memory_desc_t src_iter_desc
Source iteration memory descriptor for hidden state.
Definition: dnnl_types.h:1592
5D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:315
8-bit unsigned integer.
Definition: dnnl_types.h:76
dnnl_alg_kind_t alg_kind
The kind of the binary algorithm.
Definition: dnnl_types.h:1666
A descriptor of a matrix multiplication operation.
Definition: dnnl_types.h:1685
permuted 6D tensor
Definition: dnnl_types.h:205
3D RNN data tensor in the format (batch, seq_length, input channels).
Definition: dnnl_types.h:492
dnnl_alg_kind_t cell_kind
RNN cell kind.
Definition: dnnl_types.h:1586
const char * hash
Git hash of the sources (may be absent)
Definition: dnnl_types.h:2218
5D CNN weights tensor, an alias to dnnl_cdeba
Definition: dnnl_types.h:466
4D CNN activations tensor, an alias to dnnl_acdb
Definition: dnnl_types.h:431
dnnl_query_t
Primitive descriptor query specification.
Definition: dnnl_types.h:2093
Intel Advanced Vector Extensions (Intel AVX)
Definition: dnnl_types.h:2252
Intel AVX-512 subset for Intel Xeon Phi processors 7235, 7285, 7295 Series.
Definition: dnnl_types.h:2263
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1692
Backward data propagation.
Definition: dnnl_types.h:779
dnnl_memory_desc_t stat_desc
Statistics memory descriptor.
Definition: dnnl_types.h:1472
A descriptor of a binary operation.
Definition: dnnl_types.h:1659
source gradient memory desc
Definition: dnnl_types.h:2141
A binary primitive.
Definition: dnnl_types.h:822
Structure containing version information as per Semantic Versioning
Definition: dnnl_types.h:2214
4D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:246
int arg
An argument index, e.g. DNNL_ARG_SRC.
Definition: dnnl_types.h:2055
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1540
LSTM cell.
Definition: dnnl_types.h:916
Packed weights format used in RNN.
Definition: dnnl_types.h:93
4D CNN weights tensor, an alias to dnnl_bcda
Definition: dnnl_types.h:458
4D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:240
A reorder primitive.
Definition: dnnl_types.h:792
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1240
A descriptor of a convolution operation.
Definition: dnnl_types.h:1224
2D CNN activations tensor, an alias to dnnl_ba
Definition: dnnl_types.h:419
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1546
softmax descriptor
Definition: dnnl_types.h:2125
Intel AVX-512 subset for Intel Xeon Scalable processor family and Intel Core processor family...
Definition: dnnl_types.h:2267
no query
Definition: dnnl_types.h:2094
dnnl_scratchpad_mode_t
Scratchpad mode.
Definition: dnnl_types.h:1791
Fuse with ReLU.
Definition: dnnl_types.h:990
batch normalization descriptor
Definition: dnnl_types.h:2128
dnnl_dims_t padded_dims
Size of the data including padding in each dimension.
Definition: dnnl_types.h:1163
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:1171
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1710
5D CNN weights tensor, an alias to dnnl_abcde
Definition: dnnl_types.h:462
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:1167
Undefined memory format, used for empty memory descriptors.
Definition: dnnl_types.h:1060
runtime estimation (seconds)
Definition: dnnl_types.h:2102
Backward propagation (with respect to all parameters).
Definition: dnnl_types.h:777
An unspecified engine.
Definition: dnnl_types.h:1739
5D tensor blocked by 1st dimension with block size 16
Definition: dnnl_types.h:287
Eltwise: ReLU.
Definition: dnnl_types.h:849
GPU engine.
Definition: dnnl_types.h:1743
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1670
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1662
4D RNN states tensor in the format (num_layers, num_directions, batch, state channels).
Definition: dnnl_types.h:495
5D RNN weights tensor in the format (num_layers, num_directions, input_channels, num_gates, output_channels).
Definition: dnnl_types.h:502
6D CNN weights tensor (incl. groups), an alias to dnnl_acbdef
Definition: dnnl_types.h:485
3D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:218
(scratch) memory, additional to all inputs and outputs memory (bytes)
Definition: dnnl_types.h:2108
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1583
Eltwise: pow.
Definition: dnnl_types.h:884
5D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:300
dnnl_memory_extra_flags_t
Flags for memory special features.
Definition: dnnl_types.h:1109
5D RNN weights tensor in the format (num_layers, num_directions, num_gates, output_channels, input_channels).
Definition: dnnl_types.h:509
permuted 4D tensor
Definition: dnnl_types.h:201
An opaque structure to describe an engine.
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1431
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1690
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1236
6D CNN weights tensor (incl. groups), an alias to dnnl_abcdef
Definition: dnnl_types.h:483
Forward data propagation (inference mode).
Definition: dnnl_types.h:771
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1492
Undefined RNN flags.
Definition: dnnl_types.h:1557
A sum primitive.
Definition: dnnl_types.h:798
unsigned cpu_runtime
CPU runtime.
Definition: dnnl_types.h:2219
5D CNN weights tensor (incl. groups), an alias to dnnl_decab
Definition: dnnl_types.h:479
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1305
Intel Advanced Vector Extensions 512 (Intel AVX-512) subset for Intel Xeon Phi processors x200 Series...
Definition: dnnl_types.h:2259
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1360
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1494
A descriptor of a element-wise operation.
Definition: dnnl_types.h:1299
dnnl_dims_t inner_blks
The size of the blocks, e.g. {4, 16, 4} in case of OIhw_4i16o4i
Definition: dnnl_types.h:1051
A descriptor of a Softmax operation.
Definition: dnnl_types.h:1352
An opaque structure for a chain of post operations.
A descriptor of an inner product operation.
Definition: dnnl_types.h:1521
Eltwise: round.
Definition: dnnl_types.h:888
The operation failed because of incorrect function arguments.
Definition: dnnl_types.h:45
3D RNN data tensor in the format (seq_length, batch, input channels).
Definition: dnnl_types.h:490
dnnl_memory_desc_t diff_weights_projection_desc
Weights gradient projection memory descriptor.
Definition: dnnl_types.h:1641
dnnl_rnn_direction_t
A direction of RNN primitive execution.
Definition: dnnl_types.h:1561
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:1062
inner product descriptor
Definition: dnnl_types.h:2130
5D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:291
6D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:349
dnnl_status_t
Status values returned by the library functions.
Definition: dnnl_types.h:39
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1399
Binary mul.
Definition: dnnl_types.h:930
dnnl_memory_desc_t dst_iter_desc
Destination iter memory descriptor for hidden state.
Definition: dnnl_types.h:1604
A softmax primitive.
Definition: dnnl_types.h:806
const struct dnnl_primitive_desc * const_dnnl_primitive_desc_t
A constant primitive descriptor handle.
Definition: dnnl_types.h:1783
int64_t dnnl_dim_t
A type to describe tensor dimension.
Definition: dnnl_types.h:1034
Forward data propagation (alias for dnnl_forward_training).
Definition: dnnl_types.h:775
primitive kind
Definition: dnnl_types.h:2097
matrix multiplication (matmul) descriptor
Definition: dnnl_types.h:2135
Default stream configuration.
Definition: dnnl_types.h:2171
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1542
dnnl_memory_desc_t stat_desc
Mean and variance data memory descriptors.
Definition: dnnl_types.h:1509
const struct dnnl_primitive * const_dnnl_primitive_t
A constant primitive handle.
Definition: dnnl_types.h:1867
LRN within a single channel.
Definition: dnnl_types.h:912
dnnl_data_type_t
Data type specification.
Definition: dnnl_types.h:62
plain 4D tensor
Definition: dnnl_types.h:180
Generic description of blocked data layout for most memory formats.
Definition: dnnl_types.h:1042
plain 6D tensor
Definition: dnnl_types.h:182
Eltwise: exp (dst for backward)
Definition: dnnl_types.h:900
Winograd convolution.
Definition: dnnl_types.h:841
5D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:337
dnnl_wino_desc_t wino_desc
Tensor of weights for integer 8bit winograd convolution.
Definition: dnnl_types.h:1180
dnnl_alg_kind_t alg_kind
The kind of eltwise algorithm.
Definition: dnnl_types.h:1318
dnnl_format_tag_t
Memory format tag specification.
Definition: dnnl_types.h:164
4D LSTM projection tensor in the format (num_layers, num_directions, num_channels_in_recurrent_projec...
Definition: dnnl_types.h:515
Max pooling.
Definition: dnnl_types.h:902
Eltwise: natural logarithm.
Definition: dnnl_types.h:880
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1722
float batch_norm_epsilon
Batch normalization epsilon parameter.
Definition: dnnl_types.h:1474
dnnl_memory_desc_t weights_projection_desc
Weights projection memory descriptor.
Definition: dnnl_types.h:1614
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1490
Description of tensor of weights for winograd 2x3 convolution.
Definition: dnnl_types.h:1070
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1358
4D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcd4b ...
Definition: dnnl_types.h:547
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1600
3D CNN weights tensor, an alias to dnnl_cba
Definition: dnnl_types.h:448
4D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:267
Out-of-order execution.
Definition: dnnl_types.h:2169
Binary min.
Definition: dnnl_types.h:934
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1423
dnnl_format_kind_t
Memory format kind.
Definition: dnnl_types.h:80
permuted 3D tensor
Definition: dnnl_types.h:188
4D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:285
5D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcde4b ...
Definition: dnnl_types.h:535
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1580
Average pooling (alias for dnnl_pooling_avg_exclude_padding)
Definition: dnnl_types.h:908
dnnl_memory_desc_t diff_src_layer_desc
Source gradient layer memory descriptor.
Definition: dnnl_types.h:1617
int axis
Axis for shuffling.
Definition: dnnl_types.h:1288
dnnl_rnn_packed_desc_t rnn_packed_desc
Tensor of packed weights for RNN.
Definition: dnnl_types.h:1182
3D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:230
Binary add.
Definition: dnnl_types.h:928
3D CNN activations tensor, an alias to dnnl_abc
Definition: dnnl_types.h:425
deconvolution descriptor
Definition: dnnl_types.h:2122
A pooling primitive.
Definition: dnnl_types.h:808
dnnl_dims_t strides
The strides between the outermost blocks.
Definition: dnnl_types.h:1045
rnn descriptor
Definition: dnnl_types.h:2131
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1227
Eltwise: logistic.
Definition: dnnl_types.h:867
A descriptor of a shuffle operation.
Definition: dnnl_types.h:1277
const struct dnnl_primitive_desc_iterator * const_dnnl_primitive_desc_iterator_t
A constant primitive descriptor iterator handle.
Definition: dnnl_types.h:1772
dnnl_dims_t kernel
Pooling kernel spatial dimensions.
Definition: dnnl_types.h:1405
Eltwise: hyperbolic tangent non-linearity (tanh) (dst for backward)
Definition: dnnl_types.h:892
Winograd deconvolution.
Definition: dnnl_types.h:847
permuted 4D tensor
Definition: dnnl_types.h:202
number of outputs expected
Definition: dnnl_types.h:2100
#define DNNL_MAX_NDIMS
Maximum number of dimensions a tensor can have.
Definition: dnnl_types.h:1002
5D CNN weights tensor (incl. groups), an alias to dnnl_abcde
Definition: dnnl_types.h:477
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1532
float lrn_k
LRN k parameter.
Definition: dnnl_types.h:1442
dnnl_rnn_direction_t direction
The direction of RNN primitive execution.
Definition: dnnl_types.h:1588
6D CNN weights tensor (incl. groups), an alias to dnnl_defcab
Definition: dnnl_types.h:487
GEMM descriptor (internal)
Definition: dnnl_types.h:2132
plain 1D tensor
Definition: dnnl_types.h:177
Bidirectional execution of RNN primitive with concatenation of the results.
Definition: dnnl_types.h:1568
permuted 2D tensor
Definition: dnnl_types.h:193
permuted 5D tensor
Definition: dnnl_types.h:204
permuted 6D tensor
Definition: dnnl_types.h:190
dnnl_memory_desc_t src_iter_c_desc
Source iteration memory descriptor for cell state.
Definition: dnnl_types.h:1594
stub
Definition: dnnl_types.h:2119
dnnl_memory_desc_t diff_desc
Source and Destination of gradient memory descriptor.
Definition: dnnl_types.h:1362
3D CNN weights tensor, an alias to dnnl_bca
Definition: dnnl_types.h:450
5D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcde8b ...
Definition: dnnl_types.h:538
propagation kind
Definition: dnnl_types.h:2116
An inner product primitive.
Definition: dnnl_types.h:816
Use global statistics.
Definition: dnnl_types.h:964
5D CNN activations tensor blocked by channels with block size 32, an alias to dnnl_aBcde32b ...
Definition: dnnl_types.h:529
GRU cell.
Definition: dnnl_types.h:918
3D CNN activations tensor, an alias to dnnl_acb
Definition: dnnl_types.h:427
The operation was successful.
Definition: dnnl_types.h:41
A descriptor of a Layer Normalization operation.
Definition: dnnl_types.h:1484
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1280
8-bit signed integer.
Definition: dnnl_types.h:74
convolution descriptor
Definition: dnnl_types.h:2121
dnnl_memory_desc_t weights_peephole_desc
Weights peephole memory descriptor.
Definition: dnnl_types.h:1610
RNN cell.
Definition: dnnl_types.h:914
Alias for dnnl_unidirectional_left2right.
Definition: dnnl_types.h:1573
A (out-of-place) concat primitive.
Definition: dnnl_types.h:796
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:1064
dnnl_dims_t dilates
Convolution dilates in each spatial dimension.
Definition: dnnl_types.h:1254
const struct dnnl_stream * const_dnnl_stream_t
A constant execution stream handle.
Definition: dnnl_types.h:2180
2D RNN statistics tensor, an alias to dnnl_ba
Definition: dnnl_types.h:423
5D CNN activations tensor, an alias to dnnl_acdeb
Definition: dnnl_types.h:437
Intel AVX-512 and Intel Deep Learning Boost (Intel DL Boost) support for Intel Xeon Scalable processo...
Definition: dnnl_types.h:2272
Undefined memory format tag.
Definition: dnnl_types.h:166
permuted 5D tensor
Definition: dnnl_types.h:189
Eltwise: square root.
Definition: dnnl_types.h:859
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1459
int patch
Patch version.
Definition: dnnl_types.h:2217
4D CNN activations tensor blocked by channels with block size 32, an alias to dnnl_aBcd32b ...
Definition: dnnl_types.h:541
permuted 3D tensor
Definition: dnnl_types.h:197
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1433
source memory desc
Definition: dnnl_types.h:2140
Eltwise: swish.
Definition: dnnl_types.h:878
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1426
#define DNNL_RNN_MAX_N_PARTS
Maximum number of parts of RNN weights tensor that require separate computation.
Definition: dnnl_types.h:1092
struct dnnl_stream_attr * dnnl_stream_attr_t
An execution stream attributes handle.
Definition: dnnl_types.h:2185
Memory descriptor.
Definition: dnnl_types.h:1140
dnnl_wino_memory_format_t
Winograd-specific formats.
Definition: dnnl_types.h:1058
2D RNN statistics tensor, an alias to dnnl_ab
Definition: dnnl_types.h:421
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1487
dnnl_data_type_t data_type
Data type of the tensor elements.
Definition: dnnl_types.h:1160
A matrix multiplication primitive.
Definition: dnnl_types.h:826
Queried element is not required for given primitive.
Definition: dnnl_types.h:53
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1411
Eltwise: erf-based gelu.
Definition: dnnl_types.h:886
Indicates the weights have an additional buffer, that depends on the compensation_mask.
Definition: dnnl_types.h:1118
dnnl_blocking_desc_t blocking
Description of the data layout for memory formats that use blocking.
Definition: dnnl_types.h:1178
dnnl_dims_t inner_idxs
The logical indices of the blocks, e.g.
Definition: dnnl_types.h:1054
The operation failed due to an out-of-memory condition.
Definition: dnnl_types.h:43
Backward weights propagation.
Definition: dnnl_types.h:781
5D tensor blocked by 2nd dimension with block size 32
Definition: dnnl_types.h:298
3D CNN weights tensor, an alias to dnnl_acb
Definition: dnnl_types.h:446
dnnl_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: dnnl_types.h:1242
Default order execution.
Definition: dnnl_types.h:2165
dnnl_memory_desc_t data_scaleshift_desc
Scale and shift data and gradient memory descriptors.
Definition: dnnl_types.h:1467
workspace memory desc
Definition: dnnl_types.h:2146
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1688
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1250
eltwise descriptor
Definition: dnnl_types.h:2124
number of inputs expected
Definition: dnnl_types.h:2099
const struct dnnl_stream_attr * const_dnnl_stream_attr_t
A constant execution stream attributes handle.
Definition: dnnl_types.h:2187
shuffle descriptor
Definition: dnnl_types.h:2123
Average pooling include padding.
Definition: dnnl_types.h:904
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1461
Weights format used in 8bit Winograd convolution.
Definition: dnnl_types.h:91
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1720
32-bit/single-precision floating point.
Definition: dnnl_types.h:70
permuted 5D tensor
Definition: dnnl_types.h:203
A structure that contains an index and a memory object, and is used to pass arguments to dnnl_primiti...
Definition: dnnl_types.h:2054
Intel AVX-512, Intel DL Boost and bfloat16 support for Intel Xeon Scalable processor family and Intel...
Definition: dnnl_types.h:2277
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1713
4D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcd8b ...
Definition: dnnl_types.h:550
struct dnnl_primitive_attr * dnnl_primitive_attr_t
A primitive descriptor attributes handle that controls primitive behavior.
Definition: dnnl_types.h:1825
lrn descriptor
Definition: dnnl_types.h:2127
dnnl_memory_desc_t src_layer_desc
Source layer memory descriptor.
Definition: dnnl_types.h:1590
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1724
4D tensor blocked by 1st and 2nd dimension with block size 8
Definition: dnnl_types.h:273
A shuffle primitive.
Definition: dnnl_types.h:794
for creating scratchpad memory
Definition: dnnl_types.h:2111
float layer_norm_epsilon
Layer normalization epsilon parameter.
Definition: dnnl_types.h:1511
dnnl_memory_desc_t diff_weights_peephole_desc
Weights gradient peephole memory descriptor.
Definition: dnnl_types.h:1637
struct dnnl_engine * dnnl_engine_t
An engine handle.
Definition: dnnl_types.h:1750
unsigned int flags
RNN cell flags.
Definition: dnnl_types.h:1644
permuted 4D tensor
Definition: dnnl_types.h:198
4D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:248
Binary max.
Definition: dnnl_types.h:932
Unspecified format kind.
Definition: dnnl_types.h:85
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1283
2D CNN weights tensor, an alias to dnnl_ba
Definition: dnnl_types.h:442
Average pooling exclude padding.
Definition: dnnl_types.h:906
3D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBc16b ...
Definition: dnnl_types.h:556
dnnl_alg_kind_t
Kinds of algorithms.
Definition: dnnl_types.h:836
4D CNN weights tensor, an alias to dnnl_cdba
Definition: dnnl_types.h:454
5D CNN weights tensor, an alias to dnnl_bacde
Definition: dnnl_types.h:464
permuted 3D tensor
Definition: dnnl_types.h:200
dnnl_rnn_flags_t
Flags for RNN cell.
Definition: dnnl_types.h:1555
dnnl_memory_desc_t diff_dst_iter_desc
Destination gradient iteration memory descriptor for hidden state.
Definition: dnnl_types.h:1631
4D CNN weights tensor (incl. groups), an alias to dnnl_dcab
Definition: dnnl_types.h:475
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1528
An LRN primitive.
Definition: dnnl_types.h:810
A descriptor of a Local Response Normalization (LRN) operation.
Definition: dnnl_types.h:1420
dnnl_softmax_desc_t dnnl_logsoftmax_desc_t
A descriptor of a LogSoftmax operation.
Definition: dnnl_types.h:1374
int ndims
Number of dimensions.
Definition: dnnl_types.h:1142
dnnl_stream_flags_t
Stream flags.
Definition: dnnl_types.h:2162
dnnl_dim_t dnnl_dims_t[DNNL_MAX_NDIMS]
A type to describe tensor dimensions.
Definition: dnnl_types.h:1037
Undefined propagation type.
Definition: dnnl_types.h:764
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1322
Primitive or engine failed on execution.
Definition: dnnl_types.h:51
op descriptor
Definition: dnnl_types.h:2120
6D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:344
dnnl_memory_desc_t weights_iter_desc
Weights iteration memory descriptor.
Definition: dnnl_types.h:1598
const struct dnnl_post_ops * const_dnnl_post_ops_t
A constant post operation chain handle.
Definition: dnnl_types.h:1854
Eltwise: exponent.
Definition: dnnl_types.h:869
1D tensor, an alias to dnnl_a
Definition: dnnl_types.h:415
Local response normalization (LRN) across multiple channels.
Definition: dnnl_types.h:910
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1385
resampling descriptor
Definition: dnnl_types.h:2136
const struct dnnl_primitive_attr * const_dnnl_primitive_attr_t
A constant primitive descriptor attributes handle.
Definition: dnnl_types.h:1828
A matrix multiplication primitive (internal).
Definition: dnnl_types.h:820
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1627
plain 3D tensor
Definition: dnnl_types.h:179
Use scale and shift parameters.
Definition: dnnl_types.h:977
3D CNN activations tensor blocked by channels with block size 32, an alias to dnnl_aBc32b ...
Definition: dnnl_types.h:553
A descriptor of a Batch Normalization operation.
Definition: dnnl_types.h:1451
5D CNN weights tensor, an alias to dnnl_bcdea
Definition: dnnl_types.h:470
struct dnnl_primitive * dnnl_primitive_t
A primitive handle.
Definition: dnnl_types.h:1865
Intel Advanced Vector Extensions 2 (Intel AVX2)
Definition: dnnl_types.h:2255
3D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBc4b ...
Definition: dnnl_types.h:559
struct dnnl_stream * dnnl_stream_t
An execution stream handle.
Definition: dnnl_types.h:2178
4D CNN weights tensor, an alias to dnnl_bacd
Definition: dnnl_types.h:460
Eltwise: exponential linear unit (elu) (dst for backward)
Definition: dnnl_types.h:894
Eltwise: exponential linear unit (elu)
Definition: dnnl_types.h:853
Forward data propagation (alias for dnnl_forward_inference).
Definition: dnnl_types.h:773
6D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:339
5D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcde16b ...
Definition: dnnl_types.h:532
An opaque structure to describe a primitive descriptor.
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1231
struct dnnl_primitive_desc_iterator * dnnl_primitive_desc_iterator_t
A primitive descriptor iterator handle.
Definition: dnnl_types.h:1769
Eltwise: abs.
Definition: dnnl_types.h:857
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1320
Internal weights format for 4x3 Winograd.
Definition: dnnl_types.h:1066
Forward data propagation (training mode).
Definition: dnnl_types.h:767
permuted 5D tensor
Definition: dnnl_types.h:187
dnnl_memory_desc_t data_desc
Source and destination memory descriptor, and source and destination gradient memory descriptor...
Definition: dnnl_types.h:1286
Eltwise: tanh-based gelu (alias for dnnl_eltwise_gelu_tanh)
Definition: dnnl_types.h:876
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1238
A rnn primitive.
Definition: dnnl_types.h:818
An opaque structure to describe an execution stream.
4D CNN activations tensor, an alias to dnnl_abcd
Definition: dnnl_types.h:429
A logsoftmax primitive.
Definition: dnnl_types.h:824
permuted 5D tensor
Definition: dnnl_types.h:196
The operation failed because requested functionality is not implemented.
Definition: dnnl_types.h:47
Eltwise: gelu.
Definition: dnnl_types.h:874
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1698
dnnl_memory_desc_t diff_src_iter_desc
Source gradient iter memory descriptor for hidden state.
Definition: dnnl_types.h:1619
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1397
Eltwise: hyperbolic tangent non-linearity (tanh)
Definition: dnnl_types.h:851
struct dnnl_post_ops * dnnl_post_ops_t
A post operation chain handle.
Definition: dnnl_types.h:1851
A descriptor of resampling operation.
Definition: dnnl_types.h:1707
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1401
dnnl_prop_kind_t
Kinds of propagation.
Definition: dnnl_types.h:761
stub
Definition: dnnl_types.h:2139
Nearest Neighbor Resampling Method.
Definition: dnnl_types.h:936
permuted 4D tensor
Definition: dnnl_types.h:195
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1544
16-bit/half-precision floating point.
Definition: dnnl_types.h:66
source engine
Definition: dnnl_types.h:2113
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1246
dnnl_alg_kind_t alg_kind
The kind of the resampling algorithm.
Definition: dnnl_types.h:1716
dnnl_normalization_flags_t
Flags for normalization primitives.
Definition: dnnl_types.h:942
weights grad. memory desc
Definition: dnnl_types.h:2143
A convolution primitive.
Definition: dnnl_types.h:800
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1302
memory desc of an execute argument
Definition: dnnl_types.h:2148
Backward bias propagation.
Definition: dnnl_types.h:783
5D CNN activations tensor, an alias to dnnl_abcde
Definition: dnnl_types.h:435
4D CNN weights tensor, an alias to dnnl_abcd
Definition: dnnl_types.h:452
Eltwise: logistic (dst for backward)
Definition: dnnl_types.h:898
dnnl_memory_desc_t diff_weights_layer_desc
Weights gradient layer memory descriptor.
Definition: dnnl_types.h:1623
weights memory descriptor desc
Definition: dnnl_types.h:2142
unsigned gpu_runtime
GPU runtime.
Definition: dnnl_types.h:2220
Linear Resampling Method.
Definition: dnnl_types.h:938
3D CNN weights tensor, an alias to dnnl_abc
Definition: dnnl_types.h:444
dnnl_cpu_isa_t
CPU instruction set flags.
Definition: dnnl_types.h:2244
Eltwise: soft_relu.
Definition: dnnl_types.h:865
plain 5D tensor
Definition: dnnl_types.h:181
destination engine
Definition: dnnl_types.h:2114
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1524
Eltwise: square.
Definition: dnnl_types.h:855
float alpha
Algorithm specific parameter.
Definition: dnnl_types.h:1343