513 dnnl_NCw16n16c = dnnl_ABc16a16b,
514 dnnl_NCdhw16n16c = dnnl_ABcde16a16b,
515 dnnl_NChw16n16c = dnnl_ABcd16a16b,
516 dnnl_NChw32n32c = dnnl_ABcd32a32b,
519 dnnl_IOw16o16i = dnnl_BAc16a16b,
520 dnnl_IOw16i16o = dnnl_BAc16b16a,
521 dnnl_OIw16i16o = dnnl_ABc16b16a,
522 dnnl_OIw16o16i = dnnl_ABc16a16b,
523 dnnl_Oiw16o = dnnl_Abc16a,
524 dnnl_OIw4i16o4i = dnnl_ABc4b16a4b,
525 dnnl_OIw2i8o4i = dnnl_ABc2b8a4b,
526 dnnl_OIw4i4o = dnnl_ABc4b4a,
527 dnnl_OIw4o4i = dnnl_ABc4a4b,
528 dnnl_Oiw4o = dnnl_Abc4a,
529 dnnl_OIw8i16o2i = dnnl_ABc8b16a2b,
530 dnnl_OIw8i8o = dnnl_ABc8b8a,
531 dnnl_OIw8o16i2o = dnnl_ABc8a16b2a,
532 dnnl_IOw8o16i2o = dnnl_BAc8a16b2a,
533 dnnl_OIw8o8i = dnnl_ABc8a8b,
534 dnnl_Owi16o = dnnl_Acb16a,
535 dnnl_OwI16o2i = dnnl_AcB16a2b,
536 dnnl_Owi4o = dnnl_Acb4a,
537 dnnl_Owi8o = dnnl_Acb8a,
540 dnnl_IOhw16i16o = dnnl_BAcd16b16a,
541 dnnl_IOhw16o16i = dnnl_BAcd16a16b,
542 dnnl_Ohwi16o = dnnl_Acdb16a,
543 dnnl_OhwI16o2i = dnnl_AcdB16a2b,
544 dnnl_Ohwi32o = dnnl_Acdb32a,
545 dnnl_Ohwi4o = dnnl_Acdb4a,
546 dnnl_Ohwi8o = dnnl_Acdb8a,
547 dnnl_OIhw16i16o = dnnl_ABcd16b16a,
548 dnnl_OIhw16o16i = dnnl_ABcd16a16b,
549 dnnl_Oihw16o = dnnl_Abcd16a,
550 dnnl_OIhw4i16o4i = dnnl_ABcd4b16a4b,
551 dnnl_OIhw4i4o = dnnl_ABcd4b4a,
552 dnnl_OIhw4o4i = dnnl_ABcd4a4b,
553 dnnl_Oihw4o = dnnl_Abcd4a,
554 dnnl_OIhw8i16o2i = dnnl_ABcd8b16a2b,
556 dnnl_OIhw8o16i2o = dnnl_ABcd8a16b2a,
557 dnnl_OIhw2i8o4i = dnnl_ABcd2b8a4b,
558 dnnl_IOhw8o16i2o = dnnl_BAcd8a16b2a,
559 dnnl_OIhw8o8i = dnnl_ABcd8a8b,
562 dnnl_Odhwi16o = dnnl_Acdeb16a,
563 dnnl_OdhwI16o2i = dnnl_AcdeB16a2b,
564 dnnl_Odhwi4o = dnnl_Acdeb4a,
565 dnnl_Odhwi8o = dnnl_Acdeb8a,
566 dnnl_OIdhw16i16o = dnnl_ABcde16b16a,
567 dnnl_OIdhw16o16i = dnnl_ABcde16a16b,
568 dnnl_Oidhw16o = dnnl_Abcde16a,
569 dnnl_OIdhw4i4o = dnnl_ABcde4b4a,
570 dnnl_OIdhw4o4i = dnnl_ABcde4a4b,
571 dnnl_Oidhw4o = dnnl_Abcde4a,
572 dnnl_OIdhw8i16o2i = dnnl_ABcde8b16a2b,
573 dnnl_OIdhw8i8o = dnnl_ABcde8b8a,
574 dnnl_OIdhw8o16i2o = dnnl_ABcde8a16b2a,
575 dnnl_IOdhw8o16i2o = dnnl_BAcde8a16b2a,
578 dnnl_OIdhw8o8i = dnnl_ABcde8a8b,
579 dnnl_IOdhw16i16o = dnnl_BAcde16b16a,
580 dnnl_IOdhw16o16i = dnnl_BAcde16a16b,
583 dnnl_Goiw16g = dnnl_Abcd16a,
584 dnnl_Goiw8g = dnnl_Abcd8a,
585 dnnl_gIOw16o16i = dnnl_aCBd16b16c,
586 dnnl_gIOw16i16o = dnnl_aCBd16c16b,
587 dnnl_gOIw16i16o = dnnl_aBCd16c16b,
588 dnnl_gOIw16o16i = dnnl_aBCd16b16c,
590 dnnl_gOIw4i16o4i = dnnl_aBCd4c16b4c,
591 dnnl_gOIw2i8o4i = dnnl_aBCd2c8b4c,
592 dnnl_gOIw4i4o = dnnl_aBCd4c4b,
593 dnnl_gOIw4o4i = dnnl_aBCd4b4c,
595 dnnl_gOIw8i16o2i = dnnl_aBCd8c16b2c,
596 dnnl_gOIw8i8o = dnnl_aBCd8c8b,
597 dnnl_gOIw8o16i2o = dnnl_aBCd8b16c2b,
598 dnnl_gIOw8o16i2o = dnnl_aCBd8b16c2b,
599 dnnl_gOIw8o8i = dnnl_aBCd8b8c,
600 dnnl_gOwi16o = dnnl_aBdc16b,
601 dnnl_gOwI16o2i = dnnl_aBdC16b2c,
602 dnnl_gOwi4o = dnnl_aBdc4b,
603 dnnl_gOwi8o = dnnl_aBdc8b,
604 dnnl_gOIw2i4o2i = dnnl_aBCd2c4b2c,
606 dnnl_gOIw4i8o2i = dnnl_aBCd4c8b2c,
607 dnnl_gOIw4o8i2o = dnnl_aBCd4b8c2b,
610 dnnl_gIOhw16i16o = dnnl_aCBde16c16b,
611 dnnl_gIOhw16o16i = dnnl_aCBde16b16c,
612 dnnl_gOhwi16o = dnnl_aBdec16b,
613 dnnl_gOhwI16o2i = dnnl_aBdeC16b2c,
614 dnnl_gOhwi32o = dnnl_aBdec32b,
615 dnnl_gOhwi4o = dnnl_aBdec4b,
616 dnnl_gOhwi8o = dnnl_aBdec8b,
617 dnnl_Goihw16g = dnnl_Abcde16a,
618 dnnl_gOIhw16i16o = dnnl_aBCde16c16b,
619 dnnl_gOIhw16o16i = dnnl_aBCde16b16c,
621 dnnl_gOIhw2i8o4i = dnnl_aBCde2c8b4c,
622 dnnl_gOIhw4i16o4i = dnnl_aBCde4c16b4c,
623 dnnl_gOIhw4i4o = dnnl_aBCde4c4b,
624 dnnl_gOIhw4o4i = dnnl_aBCde4b4c,
626 dnnl_Goihw8g = dnnl_Abcde8a,
627 dnnl_gOIhw8i16o2i = dnnl_aBCde8c16b2c,
628 dnnl_gOIhw8i8o = dnnl_aBCde8c8b,
629 dnnl_gOIhw8o16i2o = dnnl_aBCde8b16c2b,
630 dnnl_gIOhw8o16i2o = dnnl_aCBde8b16c2b,
631 dnnl_gOIhw8o8i = dnnl_aBCde8b8c,
633 dnnl_OIhw4o8i8o4i = dnnl_ABcd4a8b8a4b,
634 dnnl_OIhw2o8i8o2i = dnnl_ABcd2a8b8a2b,
635 dnnl_gOIhw4o8i8o4i = dnnl_aBCde4b8c8b4c,
636 dnnl_gOIhw2o8i8o2i = dnnl_aBCde2b8c8b2c,
637 dnnl_gOIhw2i4o2i = dnnl_aBCde2c4b2c,
639 dnnl_gOIhw4i8o2i = dnnl_aBCde4c8b2c,
640 dnnl_gOIhw4o8i2o = dnnl_aBCde4b8c2b,
643 dnnl_gIOdhw16i16o = dnnl_aCBdef16c16b,
644 dnnl_gIOdhw16o16i = dnnl_aCBdef16b16c,
645 dnnl_gOdhwi16o = dnnl_aBdefc16b,
646 dnnl_gOdhwI16o2i = dnnl_aBdefC16b2c,
647 dnnl_gOdhwi4o = dnnl_aBdefc4b,
648 dnnl_gOdhwi8o = dnnl_aBdefc8b,
649 dnnl_gOIdhw16i16o = dnnl_aBCdef16c16b,
650 dnnl_gOIdhw4i16o4i = dnnl_aBCdef4c16b4c,
652 dnnl_gOIdhw16o16i = dnnl_aBCdef16b16c,
654 dnnl_gOIdhw4i4o = dnnl_aBCdef4c4b,
655 dnnl_gOIdhw4o4i = dnnl_aBCdef4b4c,
657 dnnl_gOIdhw8i16o2i = dnnl_aBCdef8c16b2c,
658 dnnl_gOIdhw8i8o = dnnl_aBCdef8c8b,
659 dnnl_gOIdhw8o16i2o = dnnl_aBCdef8b16c2b,
660 dnnl_gIOdhw8o16i2o = dnnl_aCBdef8b16c2b,
661 dnnl_gOIdhw8o8i = dnnl_aBCdef8b8c,
662 dnnl_Goidhw16g = dnnl_Abcdef16a,
663 dnnl_gOIdhw2i4o2i = dnnl_aBCdef2c4b2c,
664 dnnl_gOIdhw4i8o2i = dnnl_aBCdef4c8b2c,
666 dnnl_gOIdhw4o8i2o = dnnl_aBCdef4b8c2b,
912 #define DNNL_MAX_NDIMS 12 916 #define DNNL_RUNTIME_DIM_VAL INT64_MIN 921 #define DNNL_RUNTIME_SIZE_VAL ((size_t)DNNL_RUNTIME_DIM_VAL) 928 } DNNL_RUNTIME_F32_VAL_REP = {0x7fc000d0};
933 #define DNNL_RUNTIME_F32_VAL (DNNL_RUNTIME_F32_VAL_REP.f) 936 static const int DNNL_RUNTIME_S32_VAL_REP = INT32_MIN;
941 #define DNNL_RUNTIME_S32_VAL DNNL_RUNTIME_S32_VAL_REP 995 dnnl_packed_format_undef = 0,
998 } dnnl_rnn_packed_memory_format_t;
1002 #define DNNL_RNN_MAX_N_PARTS 4 1006 dnnl_rnn_packed_memory_format_t format;
1013 size_t offset_compensation;
1020 dnnl_memory_extra_flag_none = 0x0U,
1029 dnnl_memory_extra_flag_scale_adjust = 0x2U,
1030 dnnl_memory_extra_flag_gpu_rnn_u8s8_compensation = 0x4U,
1109 #define DNNL_MEMORY_NONE (NULL) 1110 #define DNNL_MEMORY_ALLOCATE ((void *)(size_t)-1) 1663 typedef const struct dnnl_engine *const_dnnl_engine_t;
1779 #define DNNL_ARG_SRC_0 1 1780 #define DNNL_ARG_SRC DNNL_ARG_SRC_0 1783 #define DNNL_ARG_SRC_LAYER DNNL_ARG_SRC_0 1786 #define DNNL_ARG_FROM DNNL_ARG_SRC_0 1791 #define DNNL_ARG_SRC_1 2 1792 #define DNNL_ARG_SRC_ITER DNNL_ARG_SRC_1 1797 #define DNNL_ARG_SRC_2 3 1798 #define DNNL_ARG_SRC_ITER_C DNNL_ARG_SRC_2 1803 #define DNNL_ARG_DST_0 17 1804 #define DNNL_ARG_DST DNNL_ARG_DST_0 1807 #define DNNL_ARG_TO DNNL_ARG_DST_0 1810 #define DNNL_ARG_DST_LAYER DNNL_ARG_DST_0 1814 #define DNNL_ARG_DST_1 18 1815 #define DNNL_ARG_DST_ITER DNNL_ARG_DST_1 1820 #define DNNL_ARG_DST_2 19 1821 #define DNNL_ARG_DST_ITER_C DNNL_ARG_DST_2 1826 #define DNNL_ARG_WEIGHTS_0 33 1827 #define DNNL_ARG_WEIGHTS DNNL_ARG_WEIGHTS_0 1830 #define DNNL_ARG_SCALE_SHIFT DNNL_ARG_WEIGHTS_0 1833 #define DNNL_ARG_WEIGHTS_LAYER DNNL_ARG_WEIGHTS_0 1838 #define DNNL_ARG_WEIGHTS_1 34 1839 #define DNNL_ARG_WEIGHTS_ITER DNNL_ARG_WEIGHTS_1 1844 #define DNNL_ARG_WEIGHTS_2 35 1845 #define DNNL_ARG_WEIGHTS_PEEPHOLE DNNL_ARG_WEIGHTS_2 1850 #define DNNL_ARG_WEIGHTS_3 36 1851 #define DNNL_ARG_WEIGHTS_PROJECTION DNNL_ARG_WEIGHTS_3 1856 #define DNNL_ARG_BIAS 41 1859 #define DNNL_ARG_MEAN 49 1860 #define DNNL_ARG_VARIANCE 50 1865 #define DNNL_ARG_WORKSPACE 64 1866 #define DNNL_ARG_SCRATCHPAD 80 1870 #define DNNL_ARG_DIFF_SRC_0 129 1871 #define DNNL_ARG_DIFF_SRC DNNL_ARG_DIFF_SRC_0 1874 #define DNNL_ARG_DIFF_SRC_LAYER DNNL_ARG_DIFF_SRC_0 1879 #define DNNL_ARG_DIFF_SRC_1 130 1880 #define DNNL_ARG_DIFF_SRC_ITER DNNL_ARG_DIFF_SRC_1 1885 #define DNNL_ARG_DIFF_SRC_2 131 1886 #define DNNL_ARG_DIFF_SRC_ITER_C DNNL_ARG_DIFF_SRC_2 1891 #define DNNL_ARG_DIFF_DST_0 145 1892 #define DNNL_ARG_DIFF_DST DNNL_ARG_DIFF_DST_0 1895 #define DNNL_ARG_DIFF_DST_LAYER DNNL_ARG_DIFF_DST_0 1900 #define DNNL_ARG_DIFF_DST_1 146 1901 #define DNNL_ARG_DIFF_DST_ITER DNNL_ARG_DIFF_DST_1 1906 #define DNNL_ARG_DIFF_DST_2 147 1907 #define DNNL_ARG_DIFF_DST_ITER_C DNNL_ARG_DIFF_DST_2 1912 #define DNNL_ARG_DIFF_WEIGHTS_0 161 1913 #define DNNL_ARG_DIFF_WEIGHTS DNNL_ARG_DIFF_WEIGHTS_0 1916 #define DNNL_ARG_DIFF_SCALE_SHIFT DNNL_ARG_DIFF_WEIGHTS_0 1919 #define DNNL_ARG_DIFF_WEIGHTS_LAYER DNNL_ARG_DIFF_WEIGHTS_0 1924 #define DNNL_ARG_DIFF_WEIGHTS_1 162 1925 #define DNNL_ARG_DIFF_WEIGHTS_ITER DNNL_ARG_DIFF_WEIGHTS_1 1930 #define DNNL_ARG_DIFF_WEIGHTS_2 163 1931 #define DNNL_ARG_DIFF_WEIGHTS_PEEPHOLE DNNL_ARG_DIFF_WEIGHTS_2 1936 #define DNNL_ARG_DIFF_WEIGHTS_3 164 1937 #define DNNL_ARG_DIFF_WEIGHTS_PROJECTION DNNL_ARG_DIFF_WEIGHTS_3 1942 #define DNNL_ARG_DIFF_BIAS 169 1945 #define DNNL_ARG_ATTR_OUTPUT_SCALES 513 1949 #define DNNL_ARG_MULTIPLE_SRC 1024 1950 #define DNNL_ARG_MULTIPLE_DST 2048 1955 #define DNNL_ARG_ATTR_ZERO_POINTS 4096 1959 #define DNNL_ARG_ATTR_POST_OP_DW 8192 2089 struct dnnl_stream_attr;
2101 #define DNNL_RUNTIME_NONE 0u 2104 #define DNNL_RUNTIME_SEQ 1u 2107 #define DNNL_RUNTIME_OMP 2u 2110 #define DNNL_RUNTIME_TBB 4u 2113 #define DNNL_RUNTIME_THREADPOOL 8u 2116 #define DNNL_RUNTIME_OCL 256u 2130 #define DNNL_JIT_PROFILE_NONE 0u 2133 #define DNNL_JIT_PROFILE_VTUNE 1u 2136 #define DNNL_JIT_PROFILE_LINUX_PERFMAP 2u 2139 #define DNNL_JIT_PROFILE_LINUX_JITDUMP 4u 2143 #define DNNL_JIT_PROFILE_LINUX_JITDUMP_USE_TSC 8u 2146 #define DNNL_JIT_PROFILE_LINUX_PERF \ 2147 (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:1538
A layer normalization primitive.
Definition: dnnl_types.h:730
destination grad. memory desc
Definition: dnnl_types.h:2054
An element-wise primitive.
Definition: dnnl_types.h:720
dnnl_alg_kind_t activation_kind
Activation function used for vanilla_rnn cell kind.
Definition: dnnl_types.h:1556
dnnl_memory_desc_t weights_layer_desc
Weights layer memory descriptor.
Definition: dnnl_types.h:1505
dnnl_alg_kind_t alg_kind
The kind of pooling algorithm.
Definition: dnnl_types.h:1302
6D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:317
execution engine
Definition: dnnl_types.h:2005
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1443
dnnl_memory_desc_t diff_dst_iter_c_desc
Destination gradient iteration memory descriptor for cell state.
Definition: dnnl_types.h:1542
A batch normalization primitive.
Definition: dnnl_types.h:728
Eltwise: bounded_relu.
Definition: dnnl_types.h:775
Undefined memory format tag.
Definition: dnnl_types.h:169
3D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:212
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:470
CPU engine.
Definition: dnnl_types.h:1650
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1363
Eltwise: ReLU (dst for backward)
Definition: dnnl_types.h:800
destination memory desc
Definition: dnnl_types.h:2053
Direct deconvolution.
Definition: dnnl_types.h:757
struct dnnl_memory * dnnl_memory_t
A memory handle.
Definition: dnnl_types.h:1104
A descriptor for an RNN operation.
Definition: dnnl_types.h:1486
The user manages the scratchpad allocation by querying and providing the scratchpad memory to primiti...
Definition: dnnl_types.h:1722
layer normalization descriptor
Definition: dnnl_types.h:2038
memory consumption – extra
Definition: dnnl_types.h:2012
dnnl_primitive_kind_t
Kinds of primitives.
Definition: dnnl_types.h:704
permuted 3D tensor
Definition: dnnl_types.h:194
Eltwise: linear.
Definition: dnnl_types.h:773
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1447
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:1345
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:973
dnnl_memory_desc_t data_scaleshift_desc
Scale and shift data and gradient memory descriptors.
Definition: dnnl_types.h:1411
void * dnnl_op_desc_t
A pointer to any of the operation descriptors.
Definition: dnnl_types.h:1120
dnnl_alg_kind_t alg_kind
LRN algorithm.
Definition: dnnl_types.h:1338
A resampling primitive.
Definition: dnnl_types.h:744
dnnl_format_kind_t format_kind
Memory format kind.
Definition: dnnl_types.h:1084
An opaque structure to describe a primitive.
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1366
GRU cell with linear before reset.
Definition: dnnl_types.h:836
Any ISA (no restrictions)
Definition: dnnl_types.h:2152
dnnl_dims_t strides
Pooling kernel strides for spatial dimensions.
Definition: dnnl_types.h:1312
4D CNN weights tensor, an alias to dnnl_acdb
Definition: dnnl_types.h:416
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:1605
dnnl_dim_t group_size
Number of groups.
Definition: dnnl_types.h:1200
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1154
5D CNN weights tensor, an alias to dnnl_acdeb
Definition: dnnl_types.h:426
dnnl_convolution_desc_t dnnl_deconvolution_desc_t
A descriptor of a deconvolution operation.
Definition: dnnl_types.h:1179
4D CNN weights tensor (incl. groups), an alias to dnnl_abcd
Definition: dnnl_types.h:431
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1264
dnnl_alg_kind_t alg_kind
The kind of the convolution algorithm.
Definition: dnnl_types.h:1144
In-order execution.
Definition: dnnl_types.h:2073
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1170
Use no normalization flags.
Definition: dnnl_types.h:861
scratchpad memory desc
Definition: dnnl_types.h:2056
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1627
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1297
dnnl_memory_t memory
Input/output memory.
Definition: dnnl_types.h:1965
const void * const_dnnl_op_desc_t
A pointer to any of the operation descriptors (constant variant).
Definition: dnnl_types.h:1122
Intel Streaming SIMD Extensions 4.1 (Intel SSE4.1)
Definition: dnnl_types.h:2155
Eltwise: clip.
Definition: dnnl_types.h:794
An opaque structure for primitive descriptor attributes.
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1158
logsoftmax descriptor
Definition: dnnl_types.h:2043
permuted 4D tensor
Definition: dnnl_types.h:191
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1304
float lrn_alpha
LRN alpha parameter.
Definition: dnnl_types.h:1347
dnnl_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: dnnl_types.h:1445
dnnl_memory_desc_t dst_iter_c_desc
Destination iter memory descriptor for cell state.
Definition: dnnl_types.h:1515
Primitive iterator passed over last primitive descriptor.
Definition: dnnl_types.h:49
int minor
Minor version.
Definition: dnnl_types.h:2122
2D CNN weights tensor, an alias to dnnl_ab
Definition: dnnl_types.h:400
An opaque structure to describe a memory.
dnnl_memory_desc_t dst_layer_desc
Destination layer memory descriptor.
Definition: dnnl_types.h:1511
permuted 5D tensor
Definition: dnnl_types.h:192
dnnl_engine_kind_t
Kinds of engines.
Definition: dnnl_types.h:1646
struct dnnl_primitive_desc * dnnl_primitive_desc_t
A primitive descriptor handle.
Definition: dnnl_types.h:1689
Eltwise: square root (dst for backward)
Definition: dnnl_types.h:806
non-standard 16-bit (bfloat16 w/ 7 bit mantissa) floating point.
Definition: dnnl_types.h:68
Undefined primitive.
Definition: dnnl_types.h:706
dnnl_dims_t strides
Convolution strides in each spatial dimension.
Definition: dnnl_types.h:1162
int softmax_axis
The axis along which to perform the softmax.
Definition: dnnl_types.h:1273
Unidirectional execution of RNN primitive from left to right.
Definition: dnnl_types.h:1472
The library manages the scratchpad allocation according to the policy specified by the DNNL_ENABLE_CO...
Definition: dnnl_types.h:1717
5D CNN weights tensor (incl. groups), an alias to dnnl_acbde
Definition: dnnl_types.h:439
3D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:216
3D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBc8b ...
Definition: dnnl_types.h:512
dnnl_dims_t dims
Dimensions in the following order:
Definition: dnnl_types.h:1067
const struct dnnl_memory * const_dnnl_memory_t
A constant memory handle.
Definition: dnnl_types.h:1107
4D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcd16b ...
Definition: dnnl_types.h:497
binary descriptor
Definition: dnnl_types.h:2042
dnnl_memory_desc_t diff_weights_iter_desc
Weights gradient iter memory descriptor.
Definition: dnnl_types.h:1534
permuted 4D tensor
Definition: dnnl_types.h:186
Description of tensor of packed weights for rnn.
Definition: dnnl_types.h:1005
A descriptor of a pooling operation.
Definition: dnnl_types.h:1291
2D CNN activations tensor, an alias to dnnl_ab
Definition: dnnl_types.h:377
plain 2D tensor
Definition: dnnl_types.h:178
4D CNN activations tensor, an alias to dnnl_bcda
Definition: dnnl_types.h:393
4D RNN bias tensor in the format (num_layers, num_directions, num_gates, output_channels).
Definition: dnnl_types.h:480
permuted 5D tensor
Definition: dnnl_types.h:198
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:1603
Bidirectional execution of RNN primitive with summation of the results.
Definition: dnnl_types.h:1480
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:1530
int inner_nblks
The number of innermost blocks, e.g. 3 in case of OIhw_4i16o4i_
Definition: dnnl_types.h:959
Direct convolution.
Definition: dnnl_types.h:751
int major
Major version.
Definition: dnnl_types.h:2121
Just a sentinel, not real memory format tag.
Definition: dnnl_types.h:370
5D tensor blocked by 1st dimension with block size 8
Definition: dnnl_types.h:272
An opaque structure to describe a primitive descriptor iterator.
pooling descriptor
Definition: dnnl_types.h:2035
Convolution algorithm(either direct or Winograd) is chosen just in time.
Definition: dnnl_types.h:755
float lrn_beta
LRN beta parameter.
Definition: dnnl_types.h:1349
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1439
Unidirectional execution of RNN primitive from right to left.
Definition: dnnl_types.h:1474
A deconvolution primitive.
Definition: dnnl_types.h:718
dnnl_memory_desc_t src_iter_desc
Source iteration memory descriptor for hidden state.
Definition: dnnl_types.h:1501
5D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:293
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:1575
A descriptor of a matrix multiplication operation.
Definition: dnnl_types.h:1594
permuted 6D tensor
Definition: dnnl_types.h:204
3D RNN data tensor in the format (batch, seq_length, input channels).
Definition: dnnl_types.h:450
dnnl_alg_kind_t cell_kind
RNN cell kind.
Definition: dnnl_types.h:1495
const char * hash
Git hash of the sources (may be absent)
Definition: dnnl_types.h:2124
5D CNN weights tensor, an alias to dnnl_cdeba
Definition: dnnl_types.h:424
4D CNN activations tensor, an alias to dnnl_acdb
Definition: dnnl_types.h:391
dnnl_query_t
Primitive descriptor query specification.
Definition: dnnl_types.h:2002
Intel Advanced Vector Extensions (Intel AVX)
Definition: dnnl_types.h:2158
Intel AVX-512 subset for Intel Xeon Phi processors 7235, 7285, 7295 Series.
Definition: dnnl_types.h:2169
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1601
Backward data propagation.
Definition: dnnl_types.h:695
dnnl_memory_desc_t stat_desc
Statistics memory descriptor.
Definition: dnnl_types.h:1381
A descriptor of a binary operation.
Definition: dnnl_types.h:1568
source gradient memory desc
Definition: dnnl_types.h:2050
A binary primitive.
Definition: dnnl_types.h:738
Structure containing version information as per Semantic Versioning
Definition: dnnl_types.h:2120
int arg
An argument index, e.g. DNNL_ARG_SRC.
Definition: dnnl_types.h:1964
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1449
LSTM cell.
Definition: dnnl_types.h:826
Packed weights format used in RNN.
Definition: dnnl_types.h:93
4D CNN weights tensor, an alias to dnnl_bcda
Definition: dnnl_types.h:418
4D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:232
A reorder primitive.
Definition: dnnl_types.h:708
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1150
A descriptor of a convolution operation.
Definition: dnnl_types.h:1134
2D CNN activations tensor, an alias to dnnl_ba
Definition: dnnl_types.h:379
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1455
softmax descriptor
Definition: dnnl_types.h:2034
Intel AVX-512 subset for Intel Xeon Scalable processor family and Intel Core processor family...
Definition: dnnl_types.h:2173
no query
Definition: dnnl_types.h:2003
dnnl_scratchpad_mode_t
Scratchpad mode.
Definition: dnnl_types.h:1700
Fuse with ReLU.
Definition: dnnl_types.h:900
batch normalization descriptor
Definition: dnnl_types.h:2037
dnnl_dims_t padded_dims
Size of the data including padding in each dimension.
Definition: dnnl_types.h:1073
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:1081
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1619
5D CNN weights tensor, an alias to dnnl_abcde
Definition: dnnl_types.h:422
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:1077
Undefined memory format, used for empty memory descriptors.
Definition: dnnl_types.h:970
runtime estimation (seconds)
Definition: dnnl_types.h:2011
Backward propagation (with respect to all parameters).
Definition: dnnl_types.h:693
An unspecified engine.
Definition: dnnl_types.h:1648
5D tensor blocked by 1st dimension with block size 16
Definition: dnnl_types.h:270
Eltwise: ReLU.
Definition: dnnl_types.h:761
GPU engine.
Definition: dnnl_types.h:1652
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1579
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1571
4D RNN states tensor in the format (num_layers, num_directions, batch, state channels).
Definition: dnnl_types.h:453
5D RNN weights tensor in the format (num_layers, num_directions, input_channels, num_gates, output_channels).
Definition: dnnl_types.h:460
6D CNN weights tensor (incl. groups), an alias to dnnl_acbdef
Definition: dnnl_types.h:443
(scratch) memory, additional to all inputs and outputs memory (bytes)
Definition: dnnl_types.h:2017
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1492
Eltwise: pow.
Definition: dnnl_types.h:796
5D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:281
dnnl_memory_extra_flags_t
Flags for memory special features.
Definition: dnnl_types.h:1019
5D RNN weights tensor in the format (num_layers, num_directions, num_gates, output_channels, input_channels).
Definition: dnnl_types.h:467
permuted 4D tensor
Definition: dnnl_types.h:200
An opaque structure to describe an engine.
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1340
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1599
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1146
6D CNN weights tensor (incl. groups), an alias to dnnl_abcdef
Definition: dnnl_types.h:441
Forward data propagation (inference mode).
Definition: dnnl_types.h:687
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1401
Undefined RNN flags.
Definition: dnnl_types.h:1466
A sum primitive.
Definition: dnnl_types.h:714
unsigned cpu_runtime
CPU runtime.
Definition: dnnl_types.h:2125
5D CNN weights tensor (incl. groups), an alias to dnnl_decab
Definition: dnnl_types.h:437
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1215
Intel Advanced Vector Extensions 512 (Intel AVX-512) subset for Intel Xeon Phi processors x200 Series...
Definition: dnnl_types.h:2165
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1269
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1403
A descriptor of a element-wise operation.
Definition: dnnl_types.h:1209
dnnl_dims_t inner_blks
The size of the blocks, e.g. {4, 16, 4} in case of OIhw_4i16o4i
Definition: dnnl_types.h:961
A descriptor of a Softmax operation.
Definition: dnnl_types.h:1261
An opaque structure for a chain of post operations.
A descriptor of an inner product operation.
Definition: dnnl_types.h:1430
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:448
dnnl_memory_desc_t diff_weights_projection_desc
Weights gradient projection memory descriptor.
Definition: dnnl_types.h:1550
dnnl_rnn_direction_t
A direction of RNN primitive execution.
Definition: dnnl_types.h:1470
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:972
inner product descriptor
Definition: dnnl_types.h:2039
5D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:274
6D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:319
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:1308
Binary mul.
Definition: dnnl_types.h:840
dnnl_memory_desc_t dst_iter_desc
Destination iter memory descriptor for hidden state.
Definition: dnnl_types.h:1513
A softmax primitive.
Definition: dnnl_types.h:722
const struct dnnl_primitive_desc * const_dnnl_primitive_desc_t
A constant primitive descriptor handle.
Definition: dnnl_types.h:1692
int64_t dnnl_dim_t
A type to describe tensor dimension.
Definition: dnnl_types.h:944
Forward data propagation (alias for dnnl_forward_training).
Definition: dnnl_types.h:691
primitive kind
Definition: dnnl_types.h:2006
matrix multiplication (matmul) descriptor
Definition: dnnl_types.h:2044
Default stream configuration.
Definition: dnnl_types.h:2077
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1451
dnnl_memory_desc_t stat_desc
Mean and variance data memory descriptors.
Definition: dnnl_types.h:1418
const struct dnnl_primitive * const_dnnl_primitive_t
A constant primitive handle.
Definition: dnnl_types.h:1776
LRN within a single channel.
Definition: dnnl_types.h:822
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:952
plain 6D tensor
Definition: dnnl_types.h:182
Eltwise: exp (dst for backward)
Definition: dnnl_types.h:810
Winograd convolution.
Definition: dnnl_types.h:753
5D tensor blocked by 3rd dimension with block size 4
Definition: dnnl_types.h:307
dnnl_wino_desc_t wino_desc
Tensor of weights for integer 8bit winograd convolution.
Definition: dnnl_types.h:1090
dnnl_alg_kind_t alg_kind
The kind of eltwise algorithm.
Definition: dnnl_types.h:1228
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:473
Max pooling.
Definition: dnnl_types.h:812
Eltwise: natural logarithm.
Definition: dnnl_types.h:792
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1631
float batch_norm_epsilon
Batch normalization epsilon parameter.
Definition: dnnl_types.h:1383
dnnl_memory_desc_t weights_projection_desc
Weights projection memory descriptor.
Definition: dnnl_types.h:1523
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1399
Description of tensor of weights for winograd 2x3 convolution.
Definition: dnnl_types.h:980
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1267
4D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcd4b ...
Definition: dnnl_types.h:500
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1509
3D CNN weights tensor, an alias to dnnl_cba
Definition: dnnl_types.h:408
4D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:252
Out-of-order execution.
Definition: dnnl_types.h:2075
Binary min.
Definition: dnnl_types.h:844
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1332
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:268
5D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcde4b ...
Definition: dnnl_types.h:491
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1489
Average pooling (alias for dnnl_pooling_avg_exclude_padding)
Definition: dnnl_types.h:818
dnnl_memory_desc_t diff_src_layer_desc
Source gradient layer memory descriptor.
Definition: dnnl_types.h:1526
int axis
Axis for shuffling.
Definition: dnnl_types.h:1198
dnnl_rnn_packed_desc_t rnn_packed_desc
Tensor of packed weights for RNN.
Definition: dnnl_types.h:1092
3D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:223
Binary add.
Definition: dnnl_types.h:838
3D CNN activations tensor, an alias to dnnl_abc
Definition: dnnl_types.h:385
deconvolution descriptor
Definition: dnnl_types.h:2031
A pooling primitive.
Definition: dnnl_types.h:724
dnnl_dims_t strides
The strides between the outermost blocks.
Definition: dnnl_types.h:955
rnn descriptor
Definition: dnnl_types.h:2040
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1137
Eltwise: logistic.
Definition: dnnl_types.h:779
A descriptor of a shuffle operation.
Definition: dnnl_types.h:1187
const struct dnnl_primitive_desc_iterator * const_dnnl_primitive_desc_iterator_t
A constant primitive descriptor iterator handle.
Definition: dnnl_types.h:1681
dnnl_dims_t kernel
Pooling kernel spatial dimensions.
Definition: dnnl_types.h:1314
Eltwise: hyperbolic tangent non-linearity (tanh) (dst for backward)
Definition: dnnl_types.h:802
Winograd deconvolution.
Definition: dnnl_types.h:759
permuted 4D tensor
Definition: dnnl_types.h:201
number of outputs expected
Definition: dnnl_types.h:2009
#define DNNL_MAX_NDIMS
Maximum number of dimensions a tensor can have.
Definition: dnnl_types.h:912
5D CNN weights tensor (incl. groups), an alias to dnnl_abcde
Definition: dnnl_types.h:435
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1441
float lrn_k
LRN k parameter.
Definition: dnnl_types.h:1351
dnnl_rnn_direction_t direction
The direction of RNN primitive execution.
Definition: dnnl_types.h:1497
6D CNN weights tensor (incl. groups), an alias to dnnl_defcab
Definition: dnnl_types.h:445
GEMM descriptor (internal)
Definition: dnnl_types.h:2041
plain 1D tensor
Definition: dnnl_types.h:177
Bidirectional execution of RNN primitive with concatenation of the results.
Definition: dnnl_types.h:1477
permuted 2D tensor
Definition: dnnl_types.h:193
permuted 5D tensor
Definition: dnnl_types.h:203
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:1503
stub
Definition: dnnl_types.h:2028
dnnl_memory_desc_t diff_desc
Source and Destination of gradient memory descriptor.
Definition: dnnl_types.h:1271
3D CNN weights tensor, an alias to dnnl_bca
Definition: dnnl_types.h:410
5D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcde8b ...
Definition: dnnl_types.h:494
propagation kind
Definition: dnnl_types.h:2025
An inner product primitive.
Definition: dnnl_types.h:732
Use global statistics.
Definition: dnnl_types.h:874
GRU cell.
Definition: dnnl_types.h:828
3D CNN activations tensor, an alias to dnnl_acb
Definition: dnnl_types.h:387
The operation was successful.
Definition: dnnl_types.h:41
A descriptor of a Layer Normalization operation.
Definition: dnnl_types.h:1393
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1190
8-bit signed integer.
Definition: dnnl_types.h:74
convolution descriptor
Definition: dnnl_types.h:2030
dnnl_memory_desc_t weights_peephole_desc
Weights peephole memory descriptor.
Definition: dnnl_types.h:1519
RNN cell.
Definition: dnnl_types.h:824
Alias for dnnl_unidirectional_left2right.
Definition: dnnl_types.h:1482
A (out-of-place) concat primitive.
Definition: dnnl_types.h:712
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:974
dnnl_dims_t dilates
Convolution dilates in each spatial dimension.
Definition: dnnl_types.h:1164
const struct dnnl_stream * const_dnnl_stream_t
A constant execution stream handle.
Definition: dnnl_types.h:2086
2D RNN statistics tensor, an alias to dnnl_ba
Definition: dnnl_types.h:383
5D CNN activations tensor, an alias to dnnl_acdeb
Definition: dnnl_types.h:397
Intel AVX-512 and Intel Deep Learning Boost (Intel DL Boost) support for Intel Xeon Scalable processo...
Definition: dnnl_types.h:2178
Undefined memory format tag.
Definition: dnnl_types.h:166
permuted 5D tensor
Definition: dnnl_types.h:189
Eltwise: square root.
Definition: dnnl_types.h:771
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1368
int patch
Patch version.
Definition: dnnl_types.h:2123
permuted 3D tensor
Definition: dnnl_types.h:196
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1342
source memory desc
Definition: dnnl_types.h:2049
Eltwise: swish.
Definition: dnnl_types.h:790
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1335
#define DNNL_RNN_MAX_N_PARTS
Maximum number of parts of RNN weights tensor that require separate computation.
Definition: dnnl_types.h:1002
struct dnnl_stream_attr * dnnl_stream_attr_t
An execution stream attributes handle.
Definition: dnnl_types.h:2091
Memory descriptor.
Definition: dnnl_types.h:1050
dnnl_wino_memory_format_t
Winograd-specific formats.
Definition: dnnl_types.h:968
2D RNN statistics tensor, an alias to dnnl_ab
Definition: dnnl_types.h:381
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1396
dnnl_data_type_t data_type
Data type of the tensor elements.
Definition: dnnl_types.h:1070
A matrix multiplication primitive.
Definition: dnnl_types.h:742
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:1320
Eltwise: erf-based gelu.
Definition: dnnl_types.h:798
Indicates the weights have an additional buffer, that depends on the compensation_mask.
Definition: dnnl_types.h:1028
dnnl_blocking_desc_t blocking
Description of the data layout for memory formats that use blocking.
Definition: dnnl_types.h:1088
dnnl_dims_t inner_idxs
The logical indices of the blocks, e.g.
Definition: dnnl_types.h:964
The operation failed due to an out-of-memory condition.
Definition: dnnl_types.h:43
Backward weights propagation.
Definition: dnnl_types.h:697
3D CNN weights tensor, an alias to dnnl_acb
Definition: dnnl_types.h:406
dnnl_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: dnnl_types.h:1152
Default order execution.
Definition: dnnl_types.h:2071
dnnl_memory_desc_t data_scaleshift_desc
Scale and shift data and gradient memory descriptors.
Definition: dnnl_types.h:1376
workspace memory desc
Definition: dnnl_types.h:2055
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1597
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1160
eltwise descriptor
Definition: dnnl_types.h:2033
number of inputs expected
Definition: dnnl_types.h:2008
const struct dnnl_stream_attr * const_dnnl_stream_attr_t
A constant execution stream attributes handle.
Definition: dnnl_types.h:2093
shuffle descriptor
Definition: dnnl_types.h:2032
Average pooling include padding.
Definition: dnnl_types.h:814
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1370
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:1629
32-bit/single-precision floating point.
Definition: dnnl_types.h:70
permuted 5D tensor
Definition: dnnl_types.h:202
A structure that contains an index and a memory object, and is used to pass arguments to dnnl_primiti...
Definition: dnnl_types.h:1963
Intel AVX-512, Intel DL Boost and bfloat16 support for Intel Xeon Scalable processor family and Intel...
Definition: dnnl_types.h:2183
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1622
4D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcd8b ...
Definition: dnnl_types.h:503
struct dnnl_primitive_attr * dnnl_primitive_attr_t
A primitive descriptor attributes handle that controls primitive behavior.
Definition: dnnl_types.h:1734
lrn descriptor
Definition: dnnl_types.h:2036
dnnl_memory_desc_t src_layer_desc
Source layer memory descriptor.
Definition: dnnl_types.h:1499
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1633
4D tensor blocked by 1st and 2nd dimension with block size 8
Definition: dnnl_types.h:258
A shuffle primitive.
Definition: dnnl_types.h:710
for creating scratchpad memory
Definition: dnnl_types.h:2020
float layer_norm_epsilon
Layer normalization epsilon parameter.
Definition: dnnl_types.h:1420
dnnl_memory_desc_t diff_weights_peephole_desc
Weights gradient peephole memory descriptor.
Definition: dnnl_types.h:1546
struct dnnl_engine * dnnl_engine_t
An engine handle.
Definition: dnnl_types.h:1659
unsigned int flags
RNN cell flags.
Definition: dnnl_types.h:1553
permuted 4D tensor
Definition: dnnl_types.h:197
4D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:238
Binary max.
Definition: dnnl_types.h:842
Unspecified format kind.
Definition: dnnl_types.h:85
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1193
2D CNN weights tensor, an alias to dnnl_ba
Definition: dnnl_types.h:402
Average pooling exclude padding.
Definition: dnnl_types.h:816
3D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBc16b ...
Definition: dnnl_types.h:506
dnnl_alg_kind_t
Kinds of algorithms.
Definition: dnnl_types.h:748
4D CNN weights tensor, an alias to dnnl_cdba
Definition: dnnl_types.h:414
permuted 3D tensor
Definition: dnnl_types.h:199
dnnl_rnn_flags_t
Flags for RNN cell.
Definition: dnnl_types.h:1464
dnnl_memory_desc_t diff_dst_iter_desc
Destination gradient iteration memory descriptor for hidden state.
Definition: dnnl_types.h:1540
4D CNN weights tensor (incl. groups), an alias to dnnl_dcab
Definition: dnnl_types.h:433
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1437
An LRN primitive.
Definition: dnnl_types.h:726
A descriptor of a Local Response Normalization (LRN) operation.
Definition: dnnl_types.h:1329
dnnl_softmax_desc_t dnnl_logsoftmax_desc_t
A descriptor of a LogSoftmax operation.
Definition: dnnl_types.h:1283
int ndims
Number of dimensions.
Definition: dnnl_types.h:1052
dnnl_stream_flags_t
Stream flags.
Definition: dnnl_types.h:2068
dnnl_dim_t dnnl_dims_t[DNNL_MAX_NDIMS]
A type to describe tensor dimensions.
Definition: dnnl_types.h:947
Undefined propagation type.
Definition: dnnl_types.h:680
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1232
Primitive or engine failed on execution.
Definition: dnnl_types.h:51
op descriptor
Definition: dnnl_types.h:2029
6D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:314
dnnl_memory_desc_t weights_iter_desc
Weights iteration memory descriptor.
Definition: dnnl_types.h:1507
const struct dnnl_post_ops * const_dnnl_post_ops_t
A constant post operation chain handle.
Definition: dnnl_types.h:1763
Eltwise: exponent.
Definition: dnnl_types.h:781
1D tensor, an alias to dnnl_a
Definition: dnnl_types.h:375
Local response normalization (LRN) across multiple channels.
Definition: dnnl_types.h:820
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1294
resampling descriptor
Definition: dnnl_types.h:2045
const struct dnnl_primitive_attr * const_dnnl_primitive_attr_t
A constant primitive descriptor attributes handle.
Definition: dnnl_types.h:1737
A matrix multiplication primitive (internal).
Definition: dnnl_types.h:736
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1536
plain 3D tensor
Definition: dnnl_types.h:179
Use scale and shift parameters.
Definition: dnnl_types.h:887
A descriptor of a Batch Normalization operation.
Definition: dnnl_types.h:1360
5D CNN weights tensor, an alias to dnnl_bcdea
Definition: dnnl_types.h:428
struct dnnl_primitive * dnnl_primitive_t
A primitive handle.
Definition: dnnl_types.h:1774
Intel Advanced Vector Extensions 2 (Intel AVX2)
Definition: dnnl_types.h:2161
3D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBc4b ...
Definition: dnnl_types.h:509
struct dnnl_stream * dnnl_stream_t
An execution stream handle.
Definition: dnnl_types.h:2084
4D CNN weights tensor, an alias to dnnl_bacd
Definition: dnnl_types.h:420
Eltwise: exponential linear unit (elu) (dst for backward)
Definition: dnnl_types.h:804
Eltwise: exponential linear unit (elu)
Definition: dnnl_types.h:765
Forward data propagation (alias for dnnl_forward_inference).
Definition: dnnl_types.h:689
6D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:309
5D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcde16b ...
Definition: dnnl_types.h:488
An opaque structure to describe a primitive descriptor.
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1141
struct dnnl_primitive_desc_iterator * dnnl_primitive_desc_iterator_t
A primitive descriptor iterator handle.
Definition: dnnl_types.h:1678
Eltwise: abs.
Definition: dnnl_types.h:769
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1230
Internal weights format for 4x3 Winograd.
Definition: dnnl_types.h:976
Forward data propagation (training mode).
Definition: dnnl_types.h:683
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:1196
Eltwise: tanh-based gelu (alias for dnnl_eltwise_gelu_tanh)
Definition: dnnl_types.h:788
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1148
A rnn primitive.
Definition: dnnl_types.h:734
An opaque structure to describe an execution stream.
4D CNN activations tensor, an alias to dnnl_abcd
Definition: dnnl_types.h:389
A logsoftmax primitive.
Definition: dnnl_types.h:740
The operation failed because requested functionality is not implemented.
Definition: dnnl_types.h:47
Eltwise: gelu.
Definition: dnnl_types.h:786
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1607
dnnl_memory_desc_t diff_src_iter_desc
Source gradient iter memory descriptor for hidden state.
Definition: dnnl_types.h:1528
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1306
Eltwise: hyperbolic tangent non-linearity (tanh)
Definition: dnnl_types.h:763
struct dnnl_post_ops * dnnl_post_ops_t
A post operation chain handle.
Definition: dnnl_types.h:1760
A descriptor of resampling operation.
Definition: dnnl_types.h:1616
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1310
dnnl_prop_kind_t
Kinds of propagation.
Definition: dnnl_types.h:677
stub
Definition: dnnl_types.h:2048
Nearest Neighbor Resampling Method.
Definition: dnnl_types.h:846
permuted 4D tensor
Definition: dnnl_types.h:195
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1453
16-bit/half-precision floating point.
Definition: dnnl_types.h:66
source engine
Definition: dnnl_types.h:2022
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1156
dnnl_alg_kind_t alg_kind
The kind of the resampling algorithm.
Definition: dnnl_types.h:1625
dnnl_normalization_flags_t
Flags for normalization primitives.
Definition: dnnl_types.h:852
weights grad. memory desc
Definition: dnnl_types.h:2052
A convolution primitive.
Definition: dnnl_types.h:716
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1212
memory desc of an execute argument
Definition: dnnl_types.h:2057
Backward bias propagation.
Definition: dnnl_types.h:699
5D CNN activations tensor, an alias to dnnl_abcde
Definition: dnnl_types.h:395
4D CNN weights tensor, an alias to dnnl_abcd
Definition: dnnl_types.h:412
Eltwise: logistic (dst for backward)
Definition: dnnl_types.h:808
dnnl_memory_desc_t diff_weights_layer_desc
Weights gradient layer memory descriptor.
Definition: dnnl_types.h:1532
weights memory descriptor desc
Definition: dnnl_types.h:2051
unsigned gpu_runtime
GPU runtime.
Definition: dnnl_types.h:2126
Linear Resampling Method.
Definition: dnnl_types.h:848
3D CNN weights tensor, an alias to dnnl_abc
Definition: dnnl_types.h:404
dnnl_cpu_isa_t
CPU instruction set flags.
Definition: dnnl_types.h:2150
Eltwise: soft_relu.
Definition: dnnl_types.h:777
plain 5D tensor
Definition: dnnl_types.h:181
destination engine
Definition: dnnl_types.h:2023
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1433
Eltwise: square.
Definition: dnnl_types.h:767
float alpha
Algorithm specific parameter.
Definition: dnnl_types.h:1252