Deep Neural Network Library (DNNL)
1.2.2
Performance library for Deep Learning
Go to the documentation of this file.
486 dnnl_NCw16n16c = dnnl_ABc16a16b,
487 dnnl_NCdhw16n16c = dnnl_ABcde16a16b,
488 dnnl_NChw16n16c = dnnl_ABcd16a16b,
489 dnnl_NChw32n32c = dnnl_ABcd32a32b,
492 dnnl_IOw16o16i = dnnl_BAc16a16b,
493 dnnl_IOw16i16o = dnnl_BAc16b16a,
494 dnnl_OIw16i16o = dnnl_ABc16b16a,
495 dnnl_OIw16o16i = dnnl_ABc16a16b,
496 dnnl_Oiw16o = dnnl_Abc16a,
497 dnnl_OIw4i16o4i = dnnl_ABc4b16a4b,
498 dnnl_OIw2i8o4i = dnnl_ABc2b8a4b,
499 dnnl_OIw4i4o = dnnl_ABc4b4a,
500 dnnl_OIw4o4i = dnnl_ABc4a4b,
501 dnnl_Oiw4o = dnnl_Abc4a,
502 dnnl_OIw8i16o2i = dnnl_ABc8b16a2b,
503 dnnl_OIw8i8o = dnnl_ABc8b8a,
504 dnnl_OIw8o16i2o = dnnl_ABc8a16b2a,
505 dnnl_IOw8o16i2o = dnnl_BAc8a16b2a,
506 dnnl_OIw8o8i = dnnl_ABc8a8b,
507 dnnl_Owi16o = dnnl_Acb16a,
508 dnnl_OwI16o2i = dnnl_AcB16a2b,
509 dnnl_Owi4o = dnnl_Acb4a,
510 dnnl_Owi8o = dnnl_Acb8a,
513 dnnl_IOhw16i16o = dnnl_BAcd16b16a,
514 dnnl_IOhw16o16i = dnnl_BAcd16a16b,
515 dnnl_Ohwi16o = dnnl_Acdb16a,
516 dnnl_OhwI16o2i = dnnl_AcdB16a2b,
517 dnnl_Ohwi32o = dnnl_Acdb32a,
518 dnnl_Ohwi4o = dnnl_Acdb4a,
519 dnnl_Ohwi8o = dnnl_Acdb8a,
520 dnnl_OIhw16i16o = dnnl_ABcd16b16a,
521 dnnl_OIhw16o16i = dnnl_ABcd16a16b,
522 dnnl_Oihw16o = dnnl_Abcd16a,
523 dnnl_OIhw4i16o4i = dnnl_ABcd4b16a4b,
524 dnnl_OIhw4i4o = dnnl_ABcd4b4a,
525 dnnl_OIhw4o4i = dnnl_ABcd4a4b,
526 dnnl_Oihw4o = dnnl_Abcd4a,
527 dnnl_OIhw8i16o2i = dnnl_ABcd8b16a2b,
529 dnnl_OIhw8o16i2o = dnnl_ABcd8a16b2a,
530 dnnl_OIhw2i8o4i = dnnl_ABcd2b8a4b,
531 dnnl_IOhw8o16i2o = dnnl_BAcd8a16b2a,
532 dnnl_OIhw8o8i = dnnl_ABcd8a8b,
535 dnnl_Odhwi16o = dnnl_Acdeb16a,
536 dnnl_OdhwI16o2i = dnnl_AcdeB16a2b,
537 dnnl_Odhwi4o = dnnl_Acdeb4a,
538 dnnl_Odhwi8o = dnnl_Acdeb8a,
539 dnnl_OIdhw16i16o = dnnl_ABcde16b16a,
540 dnnl_OIdhw16o16i = dnnl_ABcde16a16b,
541 dnnl_Oidhw16o = dnnl_Abcde16a,
542 dnnl_OIdhw4i4o = dnnl_ABcde4b4a,
543 dnnl_OIdhw4o4i = dnnl_ABcde4a4b,
544 dnnl_Oidhw4o = dnnl_Abcde4a,
545 dnnl_OIdhw8i16o2i = dnnl_ABcde8b16a2b,
546 dnnl_OIdhw8i8o = dnnl_ABcde8b8a,
547 dnnl_OIdhw8o16i2o = dnnl_ABcde8a16b2a,
548 dnnl_IOdhw8o16i2o = dnnl_BAcde8a16b2a,
551 dnnl_OIdhw8o8i = dnnl_ABcde8a8b,
552 dnnl_IOdhw16i16o = dnnl_BAcde16b16a,
555 dnnl_Goiw16g = dnnl_Abcd16a,
556 dnnl_Goiw8g = dnnl_Abcd8a,
557 dnnl_gIOw16o16i = dnnl_aCBd16b16c,
558 dnnl_gIOw16i16o = dnnl_aCBd16c16b,
559 dnnl_gOIw16i16o = dnnl_aBCd16c16b,
560 dnnl_gOIw16o16i = dnnl_aBCd16b16c,
562 dnnl_gOIw4i16o4i = dnnl_aBCd4c16b4c,
563 dnnl_gOIw2i8o4i = dnnl_aBCd2c8b4c,
564 dnnl_gOIw4i4o = dnnl_aBCd4c4b,
565 dnnl_gOIw4o4i = dnnl_aBCd4b4c,
567 dnnl_gOIw8i16o2i = dnnl_aBCd8c16b2c,
568 dnnl_gOIw8i8o = dnnl_aBCd8c8b,
569 dnnl_gOIw8o16i2o = dnnl_aBCd8b16c2b,
570 dnnl_gIOw8o16i2o = dnnl_aCBd8b16c2b,
571 dnnl_gOIw8o8i = dnnl_aBCd8b8c,
572 dnnl_gOwi16o = dnnl_aBdc16b,
573 dnnl_gOwI16o2i = dnnl_aBdC16b2c,
574 dnnl_gOwi4o = dnnl_aBdc4b,
575 dnnl_gOwi8o = dnnl_aBdc8b,
578 dnnl_gIOhw16i16o = dnnl_aCBde16c16b,
579 dnnl_gIOhw16o16i = dnnl_aCBde16b16c,
580 dnnl_gOhwi16o = dnnl_aBdec16b,
581 dnnl_gOhwI16o2i = dnnl_aBdeC16b2c,
582 dnnl_gOhwi32o = dnnl_aBdec32b,
583 dnnl_gOhwi4o = dnnl_aBdec4b,
584 dnnl_gOhwi8o = dnnl_aBdec8b,
585 dnnl_Goihw16g = dnnl_Abcde16a,
586 dnnl_gOIhw16i16o = dnnl_aBCde16c16b,
587 dnnl_gOIhw16o16i = dnnl_aBCde16b16c,
589 dnnl_gOIhw2i8o4i = dnnl_aBCde2c8b4c,
590 dnnl_gOIhw4i16o4i = dnnl_aBCde4c16b4c,
591 dnnl_gOIhw4i4o = dnnl_aBCde4c4b,
592 dnnl_gOIhw4o4i = dnnl_aBCde4b4c,
594 dnnl_Goihw8g = dnnl_Abcde8a,
595 dnnl_gOIhw8i16o2i = dnnl_aBCde8c16b2c,
596 dnnl_gOIhw8i8o = dnnl_aBCde8c8b,
597 dnnl_gOIhw8o16i2o = dnnl_aBCde8b16c2b,
598 dnnl_gIOhw8o16i2o = dnnl_aCBde8b16c2b,
599 dnnl_gOIhw8o8i = dnnl_aBCde8b8c,
601 dnnl_OIhw4o8i8o4i = dnnl_ABcd4a8b8a4b,
602 dnnl_OIhw2o8i8o2i = dnnl_ABcd2a8b8a2b,
603 dnnl_gOIhw4o8i8o4i = dnnl_aBCde4b8c8b4c,
604 dnnl_gOIhw2o8i8o2i = dnnl_aBCde2b8c8b2c,
607 dnnl_gIOdhw16i16o = dnnl_aCBdef16c16b,
608 dnnl_gOdhwi16o = dnnl_aBdefc16b,
609 dnnl_gOdhwI16o2i = dnnl_aBdefC16b2c,
610 dnnl_gOdhwi4o = dnnl_aBdefc4b,
611 dnnl_gOdhwi8o = dnnl_aBdefc8b,
612 dnnl_gOIdhw16i16o = dnnl_aBCdef16c16b,
613 dnnl_gOIdhw4i16o4i = dnnl_aBCdef4c16b4c,
615 dnnl_gOIdhw16o16i = dnnl_aBCdef16b16c,
617 dnnl_gOIdhw4i4o = dnnl_aBCdef4c4b,
618 dnnl_gOIdhw4o4i = dnnl_aBCdef4b4c,
620 dnnl_gOIdhw8i16o2i = dnnl_aBCdef8c16b2c,
621 dnnl_gOIdhw8i8o = dnnl_aBCdef8c8b,
622 dnnl_gOIdhw8o16i2o = dnnl_aBCdef8b16c2b,
623 dnnl_gIOdhw8o16i2o = dnnl_aCBdef8b16c2b,
624 dnnl_gOIdhw8o8i = dnnl_aBCdef8b8c,
625 dnnl_Goidhw16g = dnnl_Abcdef16a,
839 #define DNNL_MAX_NDIMS 12
843 #define DNNL_RUNTIME_DIM_VAL INT64_MIN
848 #define DNNL_RUNTIME_SIZE_VAL ((size_t)DNNL_RUNTIME_DIM_VAL)
855 } DNNL_RUNTIME_F32_VAL_REP = {0x7fc000d0};
860 #define DNNL_RUNTIME_F32_VAL (DNNL_RUNTIME_F32_VAL_REP.f)
863 static const int DNNL_RUNTIME_S32_VAL_REP = INT32_MIN;
868 #define DNNL_RUNTIME_S32_VAL DNNL_RUNTIME_S32_VAL_REP
922 dnnl_packed_format_undef = 0,
925 } dnnl_rnn_packed_memory_format_t;
929 #define DNNL_RNN_MAX_N_PARTS 4
933 dnnl_rnn_packed_memory_format_t format;
940 size_t offset_compensation;
947 dnnl_memory_extra_flag_none = 0x0U,
956 dnnl_memory_extra_flag_scale_adjust = 0x2U,
957 dnnl_memory_extra_flag_gpu_rnn_u8s8_compensation = 0x4U,
1036 #define DNNL_MEMORY_NONE (NULL)
1037 #define DNNL_MEMORY_ALLOCATE ((void *)(size_t)-1)
1571 typedef const struct dnnl_engine *const_dnnl_engine_t;
1687 #define DNNL_ARG_SRC_0 1
1688 #define DNNL_ARG_SRC DNNL_ARG_SRC_0
1691 #define DNNL_ARG_SRC_LAYER DNNL_ARG_SRC_0
1694 #define DNNL_ARG_FROM DNNL_ARG_SRC_0
1699 #define DNNL_ARG_SRC_1 2
1700 #define DNNL_ARG_SRC_ITER DNNL_ARG_SRC_1
1705 #define DNNL_ARG_SRC_2 3
1706 #define DNNL_ARG_SRC_ITER_C DNNL_ARG_SRC_2
1711 #define DNNL_ARG_DST_0 17
1712 #define DNNL_ARG_DST DNNL_ARG_DST_0
1715 #define DNNL_ARG_TO DNNL_ARG_DST_0
1718 #define DNNL_ARG_DST_LAYER DNNL_ARG_DST_0
1722 #define DNNL_ARG_DST_1 18
1723 #define DNNL_ARG_DST_ITER DNNL_ARG_DST_1
1728 #define DNNL_ARG_DST_2 19
1729 #define DNNL_ARG_DST_ITER_C DNNL_ARG_DST_2
1734 #define DNNL_ARG_WEIGHTS_0 33
1735 #define DNNL_ARG_WEIGHTS DNNL_ARG_WEIGHTS_0
1738 #define DNNL_ARG_SCALE_SHIFT DNNL_ARG_WEIGHTS_0
1741 #define DNNL_ARG_WEIGHTS_LAYER DNNL_ARG_WEIGHTS_0
1746 #define DNNL_ARG_WEIGHTS_1 34
1747 #define DNNL_ARG_WEIGHTS_ITER DNNL_ARG_WEIGHTS_1
1752 #define DNNL_ARG_BIAS 41
1755 #define DNNL_ARG_MEAN 49
1756 #define DNNL_ARG_VARIANCE 50
1761 #define DNNL_ARG_WORKSPACE 64
1762 #define DNNL_ARG_SCRATCHPAD 80
1766 #define DNNL_ARG_DIFF_SRC_0 129
1767 #define DNNL_ARG_DIFF_SRC DNNL_ARG_DIFF_SRC_0
1770 #define DNNL_ARG_DIFF_SRC_LAYER DNNL_ARG_DIFF_SRC_0
1775 #define DNNL_ARG_DIFF_SRC_1 130
1776 #define DNNL_ARG_DIFF_SRC_ITER DNNL_ARG_DIFF_SRC_1
1781 #define DNNL_ARG_DIFF_SRC_2 131
1782 #define DNNL_ARG_DIFF_SRC_ITER_C DNNL_ARG_DIFF_SRC_2
1787 #define DNNL_ARG_DIFF_DST_0 145
1788 #define DNNL_ARG_DIFF_DST DNNL_ARG_DIFF_DST_0
1791 #define DNNL_ARG_DIFF_DST_LAYER DNNL_ARG_DIFF_DST_0
1796 #define DNNL_ARG_DIFF_DST_1 146
1797 #define DNNL_ARG_DIFF_DST_ITER DNNL_ARG_DIFF_DST_1
1802 #define DNNL_ARG_DIFF_DST_2 147
1803 #define DNNL_ARG_DIFF_DST_ITER_C DNNL_ARG_DIFF_DST_2
1808 #define DNNL_ARG_DIFF_WEIGHTS_0 161
1809 #define DNNL_ARG_DIFF_WEIGHTS DNNL_ARG_DIFF_WEIGHTS_0
1812 #define DNNL_ARG_DIFF_SCALE_SHIFT DNNL_ARG_DIFF_WEIGHTS_0
1815 #define DNNL_ARG_DIFF_WEIGHTS_LAYER DNNL_ARG_DIFF_WEIGHTS_0
1820 #define DNNL_ARG_DIFF_WEIGHTS_1 162
1821 #define DNNL_ARG_DIFF_WEIGHTS_ITER DNNL_ARG_DIFF_WEIGHTS_1
1826 #define DNNL_ARG_DIFF_BIAS 169
1829 #define DNNL_ARG_ATTR_OUTPUT_SCALES 513
1833 #define DNNL_ARG_MULTIPLE_SRC 1024
1834 #define DNNL_ARG_MULTIPLE_DST 2048
1839 #define DNNL_ARG_ATTR_ZERO_POINTS 4096
1974 #define DNNL_RUNTIME_NONE 0u
1977 #define DNNL_RUNTIME_SEQ 1u
1980 #define DNNL_RUNTIME_OMP 2u
1983 #define DNNL_RUNTIME_TBB 4u
1986 #define DNNL_RUNTIME_OCL 256u
2000 #define DNNL_JIT_PROFILE_NONE 0u
2003 #define DNNL_JIT_PROFILE_VTUNE 1u
2006 #define DNNL_JIT_PROFILE_LINUX_PERFMAP 2u
2009 #define DNNL_JIT_PROFILE_LINUX_JITDUMP 4u
2013 #define DNNL_JIT_PROFILE_LINUX_JITDUMP_USE_TSC 8u
2016 #define DNNL_JIT_PROFILE_LINUX_PERF \
2017 (DNNL_JIT_PROFILE_LINUX_JITDUMP | DNNL_JIT_PROFILE_LINUX_PERFMAP)
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1254
@ dnnl_query_time_estimate_f64
runtime estimation (seconds)
Definition: dnnl_types.h:1891
@ dnnl_query_reorder_dst_engine
destination engine
Definition: dnnl_types.h:1903
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1213
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1428
@ dnnl_aBcdef4b
6D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:304
@ dnnl_dhwigo
6D CNN weights tensor (incl. groups), an alias to dnnl_defcab
Definition: dnnl_types.h:424
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1073
@ dnnl_scratchpad_mode_library
The library manages scratchpad (default) The allocation policy is controlled by the DNNL_ENABLE_CONCU...
Definition: dnnl_types.h:1626
@ dnnl_goidhw
6D CNN weights tensor (incl. groups), an alias to dnnl_abcdef
Definition: dnnl_types.h:420
@ dnnl_wino_wei_aaOIoi
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:899
@ dnnl_io
2D CNN weights tensor, an alias to dnnl_ba
Definition: dnnl_types.h:383
dnnl_dims_t strides
Convolution strides in each spatial dimension.
Definition: dnnl_types.h:1089
@ dnnl_nc
2D CNN activations tensor, an alias to dnnl_ab
Definition: dnnl_types.h:358
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1151
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1527
@ dnnl_s32
32-bit signed integer.
Definition: dnnl_types.h:72
@ dnnl_x
1D tensor, an alias to dnnl_a
Definition: dnnl_types.h:356
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1287
Description of tensor of packed weights for rnn.
Definition: dnnl_types.h:932
float layer_norm_epsilon
Layer normalization epsilon parameter.
Definition: dnnl_types.h:1339
dnnl_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: dnnl_types.h:1364
@ dnnl_query_pooling_d
pooling descriptor
Definition: dnnl_types.h:1915
@ dnnl_ABcde2b8a4b
5D tensor blocked by 1st dimension with block size 8
Definition: dnnl_types.h:265
@ dnnl_wino_wei_aaOio
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:900
dnnl_alg_kind_t alg_kind
The kind of the convolution algorithm.
Definition: dnnl_types.h:1071
dnnl_alg_kind_t alg_kind
The kind of pooling algorithm.
Definition: dnnl_types.h:1221
@ dnnl_query_memory_consumption_s64
memory consumption – extra
Definition: dnnl_types.h:1892
@ dnnl_s8
8-bit signed integer.
Definition: dnnl_types.h:74
dnnl_format_tag_t
Memory format tag specification.
Definition: dnnl_types.h:164
@ dnnl_f16
16-bit/half-precision floating point.
Definition: dnnl_types.h:66
@ dnnl_inner_product
An inner product primitive.
Definition: dnnl_types.h:691
@ dnnl_unimplemented
The operation failed because requested functionality is not implemented.
Definition: dnnl_types.h:47
@ dnnl_decab
permuted 5D tensor
Definition: dnnl_types.h:201
An opaque structure to describe a primitive descriptor iterator.
@ dnnl_batch_normalization
A batch normalization primitive.
Definition: dnnl_types.h:687
@ dnnl_query_logsoftmax_d
logsoftmax descriptor
Definition: dnnl_types.h:1923
struct dnnl_stream * dnnl_stream_t
An execution stream handle.
Definition: dnnl_types.h:1964
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1216
dnnl_status_t
Status values returned by the library functions.
Definition: dnnl_types.h:39
@ dnnl_query_reorder_src_engine
source engine
Definition: dnnl_types.h:1902
@ dnnl_wino_undef
Undefined memory format, used for empty memory descriptors.
Definition: dnnl_types.h:897
dnnl_rnn_direction_t direction
The direction of RNN primitive execution.
Definition: dnnl_types.h:1416
@ dnnl_memory_extra_flag_compensation_conv_s8s8
Indicates the weights have an additional buffer, that depends on the compensation_mask.
Definition: dnnl_types.h:955
@ dnnl_softmax
A softmax primitive.
Definition: dnnl_types.h:681
@ dnnl_query_rnn_d
rnn descriptor
Definition: dnnl_types.h:1920
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1370
unsigned int flags
RNN cell flags.
Definition: dnnl_types.h:1462
@ dnnl_cn
2D CNN activations tensor, an alias to dnnl_ba
Definition: dnnl_types.h:360
#define DNNL_MAX_NDIMS
Maximum number of dimensions a tensor can have.
Definition: dnnl_types.h:839
@ dnnl_ldnc
4D RNN states tensor in the format (num_layers, num_directions, batch, state channels).
Definition: dnnl_types.h:432
@ dnnl_scratchpad_mode_user
A user shall query and provide the scratchpad memory to primitives This mode is thread-safe as long a...
Definition: dnnl_types.h:1630
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1285
@ dnnl_defcab
permuted 6D tensor
Definition: dnnl_types.h:202
@ dnnl_aBcde16b
5D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:267
An opaque structure to describe an engine.
dnnl_memory_desc_t src_iter_c_desc
Source iteration memory descriptor for cell state.
Definition: dnnl_types.h:1422
dnnl_memory_desc_t stat_desc
Statistics memory descriptor.
Definition: dnnl_types.h:1300
@ dnnl_eltwise_relu
Eltwise: ReLU.
Definition: dnnl_types.h:720
@ dnnl_acb
permuted 3D tensor
Definition: dnnl_types.h:187
A descriptor of a matrix multiplication operation.
Definition: dnnl_types.h:1502
@ dnnl_eltwise_abs
Eltwise: abs.
Definition: dnnl_types.h:728
dnnl_dim_t group_size
Number of groups.
Definition: dnnl_types.h:1127
@ dnnl_oihw
4D CNN weights tensor, an alias to dnnl_abcd
Definition: dnnl_types.h:393
dnnl_normalization_flags_t
Flags for batch normalization primitive.
Definition: dnnl_types.h:789
@ dnnl_shuffle
A shuffle primitive.
Definition: dnnl_types.h:669
@ dnnl_query_shuffle_d
shuffle descriptor
Definition: dnnl_types.h:1912
A descriptor of a convolution operation.
Definition: dnnl_types.h:1061
dnnl_primitive_kind_t
Kinds of primitives.
Definition: dnnl_types.h:663
dnnl_rnn_flags_t
Flags for RNN cell.
Definition: dnnl_types.h:1383
@ dnnl_ldigo
5D RNN weights tensor in the format (num_layers, num_directions, input_channels, num_gates,...
Definition: dnnl_types.h:439
@ dnnl_pooling_max
Max pooling.
Definition: dnnl_types.h:753
A structure that contains an index and a memory object, and is used to pass arguments to dnnl_primiti...
Definition: dnnl_types.h:1843
dnnl_stream_flags_t
Stream flags.
Definition: dnnl_types.h:1948
dnnl_query_t
Primitive descriptor query specification.
Definition: dnnl_types.h:1882
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1183
float lrn_alpha
LRN alpha parameter.
Definition: dnnl_types.h:1266
@ dnnl_bf16
non-standard 16-bit (bfloat16 w/ 7 bit mantissa) floating point.
Definition: dnnl_types.h:68
@ dnnl_nhwc
4D CNN activations tensor, an alias to dnnl_acdb
Definition: dnnl_types.h:372
A descriptor for an RNN operation.
Definition: dnnl_types.h:1405
dnnl_rnn_direction_t
A direction of RNN primitive execution.
Definition: dnnl_types.h:1389
@ dnnl_bcdea
permuted 5D tensor
Definition: dnnl_types.h:197
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1075
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1077
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1085
@ dnnl_sum
A sum primitive.
Definition: dnnl_types.h:673
@ dnnl_oidhw
5D CNN weights tensor, an alias to dnnl_abcde
Definition: dnnl_types.h:403
dnnl_blocking_desc_t blocking
Description of the data layout for memory formats that use blocking.
Definition: dnnl_types.h:1015
@ dnnl_backward_weights
Backward weights propagation.
Definition: dnnl_types.h:656
@ dnnl_a
plain 1D tensor
Definition: dnnl_types.h:177
const struct dnnl_stream * const_dnnl_stream_t
A constant execution stream handle.
Definition: dnnl_types.h:1966
A descriptor of an inner product operation.
Definition: dnnl_types.h:1349
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1505
@ dnnl_gpu
GPU engine.
Definition: dnnl_types.h:1560
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1320
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1366
int softmax_axis
The axis along which to perform the softmax.
Definition: dnnl_types.h:1192
@ dnnl_query_diff_weights_md
weights grad. memory desc
Definition: dnnl_types.h:1932
@ dnnl_query_prop_kind
propagation kind
Definition: dnnl_types.h:1905
@ dnnl_eltwise_logistic
Eltwise: logistic.
Definition: dnnl_types.h:738
@ dnnl_eltwise
An element-wise primitive.
Definition: dnnl_types.h:679
@ dnnl_stream_in_order
In-order execution.
Definition: dnnl_types.h:1953
@ dnnl_aBc16b
3D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:210
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1322
@ dnnl_oiw
3D CNN weights tensor, an alias to dnnl_abc
Definition: dnnl_types.h:385
@ dnnl_convolution_auto
Convolution algorithm(either direct or Winograd) is chosen just in time.
Definition: dnnl_types.h:714
@ dnnl_eltwise_sqrt
Eltwise: square root.
Definition: dnnl_types.h:730
@ dnnl_cdba
permuted 4D tensor
Definition: dnnl_types.h:199
@ dnnl_cpu_isa_avx512_core
Intel(R) Advanced Vector Extensions 512 for Intel(R) Xeon(R) Processor Scalable Family and Intel(R) C...
Definition: dnnl_types.h:2043
@ dnnl_eltwise_bounded_relu
Eltwise: bounded_relu.
Definition: dnnl_types.h:734
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1408
@ dnnl_hwio
4D CNN weights tensor, an alias to dnnl_cdba
Definition: dnnl_types.h:395
@ dnnl_forward_inference
Forward data propagation (inference mode).
Definition: dnnl_types.h:646
@ dnnl_query_impl_info_str
for creating scratchpad memory
Definition: dnnl_types.h:1900
@ dnnl_query_dst_md
destination memory desc
Definition: dnnl_types.h:1933
@ dnnl_query_resampling_d
resampling descriptor
Definition: dnnl_types.h:1925
@ dnnl_query_inner_product_d
inner product descriptor
Definition: dnnl_types.h:1919
@ dnnl_rnn_flags_undef
Undefined RNN flags.
Definition: dnnl_types.h:1385
@ dnnl_nCdhw16c
5D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcde16b
Definition: dnnl_types.h:461
@ dnnl_query_convolution_d
convolution descriptor
Definition: dnnl_types.h:1910
@ dnnl_aBCdef2c8b4c
6D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:302
@ dnnl_bcda
permuted 4D tensor
Definition: dnnl_types.h:196
int major
Major version.
Definition: dnnl_types.h:1991
@ dnnl_bidirectional_concat
Bidirectional execution of RNN primitive with concatenation of the results.
Definition: dnnl_types.h:1396
A descriptor of a pooling operation.
Definition: dnnl_types.h:1210
@ dnnl_ba
permuted 2D tensor
Definition: dnnl_types.h:192
dnnl_data_type_t
Data type specification.
Definition: dnnl_types.h:62
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1223
@ dnnl_lrn_within_channel
LRN within a single channel.
Definition: dnnl_types.h:763
struct dnnl_engine * dnnl_engine_t
An engine handle.
Definition: dnnl_types.h:1567
dnnl_memory_desc_t data_scaleshift_desc
Scale and shift data and gradient memory descriptors.
Definition: dnnl_types.h:1330
@ dnnl_binary_mul
Binary mul.
Definition: dnnl_types.h:781
@ dnnl_ihwo
4D CNN weights tensor, an alias to dnnl_bcda
Definition: dnnl_types.h:399
dnnl_memory_desc_t src_layer_desc
Source layer memory descriptor.
Definition: dnnl_types.h:1418
@ dnnl_format_tag_undef
Undefined memory format tag.
Definition: dnnl_types.h:166
@ dnnl_format_kind_rnn_packed
Packed weights format used in RNN.
Definition: dnnl_types.h:93
@ dnnl_goiw
4D CNN weights tensor (incl. groups), an alias to dnnl_abcd
Definition: dnnl_types.h:412
const struct dnnl_primitive_desc_iterator * const_dnnl_primitive_desc_iterator_t
A constant primitive descriptor iterator handle.
Definition: dnnl_types.h:1589
@ dnnl_use_scaleshift
Use scale and shift parameters.
Definition: dnnl_types.h:814
@ dnnl_eltwise_log
Eltwise: natural logarithm.
Definition: dnnl_types.h:749
@ dnnl_query_layer_normalization_d
layer normalization descriptor
Definition: dnnl_types.h:1918
int minor
Minor version.
Definition: dnnl_types.h:1992
dnnl_memory_desc_t stat_desc
Mean and variance data memory descriptors.
Definition: dnnl_types.h:1337
@ dnnl_ABcd8b8a
4D tensor blocked by 1st and 2nd dimension with block size 8
Definition: dnnl_types.h:253
@ dnnl_resampling_linear
Linear Resampling Method.
Definition: dnnl_types.h:785
dnnl_dims_t inner_blks
The size of the blocks, e.g. {4, 16, 4} in case of OIhw_4i16o4i
Definition: dnnl_types.h:888
dnnl_memory_desc_t diff_dst_iter_desc
Destination gradient iteration memory descriptor for hidden state.
Definition: dnnl_types.h:1454
@ dnnl_dhwio
5D CNN weights tensor, an alias to dnnl_cdeba
Definition: dnnl_types.h:405
@ dnnl_forward_training
Forward data propagation (training mode).
Definition: dnnl_types.h:642
@ dnnl_eltwise_square
Eltwise: square.
Definition: dnnl_types.h:726
@ dnnl_bac
permuted 3D tensor
Definition: dnnl_types.h:193
@ dnnl_fuse_norm_relu
Fuse with ReLU.
Definition: dnnl_types.h:827
@ dnnl_cpu_isa_avx512_mic_4ops
Intel(R) Advanced Vector Extensions 512 subset for Intel(R) Xeon Phi(TM) Processors 7235,...
Definition: dnnl_types.h:2039
@ dnnl_tn
2D RNN statistics tensor, an alias to dnnl_ab
Definition: dnnl_types.h:362
const struct dnnl_primitive_desc * const_dnnl_primitive_desc_t
A constant primitive descriptor handle.
Definition: dnnl_types.h:1600
dnnl_memory_desc_t weights_layer_desc
Weights layer memory descriptor.
Definition: dnnl_types.h:1424
@ dnnl_format_kind_wino
Weights format used in 8bit Winograd convolution.
Definition: dnnl_types.h:91
const struct dnnl_post_ops * const_dnnl_post_ops_t
A constant post operation chain handle.
Definition: dnnl_types.h:1671
dnnl_dims_t strides
The strides between the outermost blocks.
Definition: dnnl_types.h:882
@ dnnl_convolution_winograd
Winograd convolution.
Definition: dnnl_types.h:712
@ dnnl_ABcde4b16a4b
5D tensor blocked by 1st dimension with block size 16
Definition: dnnl_types.h:263
@ dnnl_nChw8c
4D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcd8b
Definition: dnnl_types.h:476
dnnl_engine_kind_t
Kinds of engines.
Definition: dnnl_types.h:1554
@ dnnl_binary
A binary primitive.
Definition: dnnl_types.h:697
@ dnnl_cdeba
permuted 5D tensor
Definition: dnnl_types.h:200
dnnl_memory_t memory
Input/output memory.
Definition: dnnl_types.h:1845
@ dnnl_eltwise_tanh
Eltwise: hyperbolic tangent non-linearity (tanh)
Definition: dnnl_types.h:722
dnnl_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: dnnl_types.h:1079
@ dnnl_aBc4b
3D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:214
@ dnnl_abcde
plain 5D tensor
Definition: dnnl_types.h:181
@ dnnl_nCw8c
3D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBc8b
Definition: dnnl_types.h:485
struct dnnl_post_ops * dnnl_post_ops_t
A post operation chain handle.
Definition: dnnl_types.h:1668
@ dnnl_query_gemm_d
GEMM descriptor (internal)
Definition: dnnl_types.h:1921
dnnl_dims_t dims
Dimensions in the following order:
Definition: dnnl_types.h:994
@ dnnl_stream_default_order
Default order execution.
Definition: dnnl_types.h:1951
@ dnnl_pooling
A pooling primitive.
Definition: dnnl_types.h:683
@ dnnl_acdb
permuted 4D tensor
Definition: dnnl_types.h:190
dnnl_memory_desc_t diff_placeholder_desc
Placeholders.
Definition: dnnl_types.h:1458
@ dnnl_query_lrn_d
lrn descriptor
Definition: dnnl_types.h:1916
@ dnnl_backward
Backward propagation (with respect to all parameters).
Definition: dnnl_types.h:652
@ dnnl_giohw
5D CNN weights tensor (incl. groups), an alias to dnnl_acbde
Definition: dnnl_types.h:418
A descriptor of a Softmax operation.
Definition: dnnl_types.h:1180
dnnl_dims_t dilates
Convolution dilates in each spatial dimension.
Definition: dnnl_types.h:1091
@ dnnl_cpu_isa_avx512_core_bf16
Intel(R) Advanced Vector Extensions 512 with Intel(R) DL Boost and Bfloat16 Support for Intel(R) Xeon...
Definition: dnnl_types.h:2053
@ dnnl_iterator_ends
Primitive iterator passed over last primitive descriptor.
Definition: dnnl_types.h:49
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1539
int inner_nblks
The number of innermost blocks, e.g. 3 in case of OIhw_4i16o4i_
Definition: dnnl_types.h:886
An opaque structure to describe a primitive descriptor.
@ dnnl_nCdhw8c
5D CNN activations tensor blocked by channels with block size 8, an alias to dnnl_aBcde8b
Definition: dnnl_types.h:467
@ dnnl_pooling_avg
Average pooling (alias for dnnl_pooling_avg_exclude_padding)
Definition: dnnl_types.h:759
@ dnnl_vanilla_rnn
RNN cell.
Definition: dnnl_types.h:765
@ dnnl_unidirectional
Alias for dnnl_unidirectional_left2right.
Definition: dnnl_types.h:1401
@ dnnl_aBcd4b
4D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:236
@ dnnl_query_matmul_d
matrix multiplication (matmul) descriptor
Definition: dnnl_types.h:1924
struct dnnl_primitive_desc * dnnl_primitive_desc_t
A primitive descriptor handle.
Definition: dnnl_types.h:1597
const char * hash
Git hash of the sources (may be absent)
Definition: dnnl_types.h:1994
@ dnnl_query_binary_d
binary descriptor
Definition: dnnl_types.h:1922
@ dnnl_lbr_gru
GRU cell with linear before reset.
Definition: dnnl_types.h:777
@ dnnl_forward
Forward data propagation (alias for dnnl_forward_training).
Definition: dnnl_types.h:650
@ dnnl_f32
32-bit/single-precision floating point.
Definition: dnnl_types.h:70
@ dnnl_acbdef
permuted 6D tensor
Definition: dnnl_types.h:189
@ dnnl_iwo
3D CNN weights tensor, an alias to dnnl_bca
Definition: dnnl_types.h:391
@ dnnl_use_global_stats
Use global statistics.
Definition: dnnl_types.h:801
@ dnnl_lrn_across_channels
Local response normalization (LRN) across multiple channels.
Definition: dnnl_types.h:761
@ dnnl_concat
A (out-of-place) concat primitive.
Definition: dnnl_types.h:671
@ dnnl_ntc
3D RNN data tensor in the format (batch, seq_length, input channels).
Definition: dnnl_types.h:429
@ dnnl_query_diff_dst_md
destination grad. memory desc
Definition: dnnl_types.h:1934
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1513
@ dnnl_format_kind_undef
Undefined memory format kind, used for empty memory descriptors.
Definition: dnnl_types.h:82
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1315
unsigned cpu_runtime
CPU runtime.
Definition: dnnl_types.h:1995
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1261
@ dnnl_aBcdef16b
6D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:297
@ dnnl_layer_normalization
A layer normalization primitive.
Definition: dnnl_types.h:689
dnnl_data_type_t data_type
Data type of the tensor elements.
Definition: dnnl_types.h:997
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1087
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1515
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1142
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1227
@ dnnl_cpu_isa_all
Any ISA (no restrictions)
Definition: dnnl_types.h:2022
dnnl_memory_desc_t diff_weights_layer_desc
Weights gradient layer memory descriptor.
Definition: dnnl_types.h:1446
@ dnnl_query_op_d
op descriptor
Definition: dnnl_types.h:1909
struct dnnl_primitive_desc_iterator * dnnl_primitive_desc_iterator_t
A primitive descriptor iterator handle.
Definition: dnnl_types.h:1586
@ dnnl_out_of_memory
The operation failed due to an out-of-memory condition.
Definition: dnnl_types.h:43
int64_t dnnl_dim_t
A type to describe tensor dimension.
Definition: dnnl_types.h:871
int axis
Axis for shuffling.
Definition: dnnl_types.h:1125
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1186
float lrn_beta
LRN beta parameter.
Definition: dnnl_types.h:1268
@ dnnl_idhwo
5D CNN weights tensor, an alias to dnnl_bcdea
Definition: dnnl_types.h:409
@ dnnl_abcd
plain 4D tensor
Definition: dnnl_types.h:180
@ dnnl_u8
8-bit unsigned integer.
Definition: dnnl_types.h:76
@ dnnl_ncdhw
5D CNN activations tensor, an alias to dnnl_abcde
Definition: dnnl_types.h:376
@ dnnl_query_workspace_md
workspace memory desc
Definition: dnnl_types.h:1935
@ dnnl_format_tag_last
Just a sentinel, not real memory format tag.
Definition: dnnl_types.h:351
@ dnnl_query_deconvolution_d
deconvolution descriptor
Definition: dnnl_types.h:1911
struct dnnl_memory * dnnl_memory_t
A memory handle.
Definition: dnnl_types.h:1031
@ dnnl_logsoftmax
A logsoftmax primitive.
Definition: dnnl_types.h:699
@ dnnl_format_tag_any
Undefined memory format tag.
Definition: dnnl_types.h:169
@ dnnl_deconvolution_direct
Direct deconvolution.
Definition: dnnl_types.h:716
@ dnnl_reorder
A reorder primitive.
Definition: dnnl_types.h:667
A descriptor of a Local Response Normalization (LRN) operation.
Definition: dnnl_types.h:1248
@ dnnl_stream_default_flags
Default stream configuration.
Definition: dnnl_types.h:1957
A descriptor of a shuffle operation.
Definition: dnnl_types.h:1114
@ dnnl_owi
3D CNN weights tensor, an alias to dnnl_acb
Definition: dnnl_types.h:387
dnnl_alg_kind_t activation_kind
Activation function used for vanilla_rnn cell kind.
Definition: dnnl_types.h:1465
@ dnnl_backward_data
Backward data propagation.
Definition: dnnl_types.h:654
@ dnnl_acdeb
permuted 5D tensor
Definition: dnnl_types.h:191
Structure containing version information as per Semantic Versioning
Definition: dnnl_types.h:1990
A descriptor of a Batch Normalization operation.
Definition: dnnl_types.h:1279
int arg
An argument index, e.g. DNNL_ARG_SRC.
Definition: dnnl_types.h:1844
dnnl_memory_desc_t weights_iter_desc
Weights iteration memory descriptor.
Definition: dnnl_types.h:1426
dnnl_format_kind_t format_kind
Memory format kind.
Definition: dnnl_types.h:1011
@ dnnl_ldgo
4D RNN bias tensor in the format (num_layers, num_directions, num_gates, output_channels).
Definition: dnnl_types.h:453
dnnl_dim_t dnnl_dims_t[DNNL_MAX_NDIMS]
A type to describe tensor dimensions.
Definition: dnnl_types.h:874
dnnl_alg_kind_t alg_kind
The kind of eltwise algorithm.
Definition: dnnl_types.h:1149
dnnl_memory_desc_t diff_dst_iter_c_desc
Destination gradient iteration memory descriptor for cell state.
Definition: dnnl_types.h:1456
A descriptor of a element-wise operation.
Definition: dnnl_types.h:1136
dnnl_memory_desc_t diff_src_iter_c_desc
Source gradient iter memory descriptor for cell state.
Definition: dnnl_types.h:1444
@ dnnl_aBcd16b
4D tensor blocked by 2nd dimension with block size 16
Definition: dnnl_types.h:230
@ dnnl_resampling_nearest
Nearest Neighbor Resampling Method.
Definition: dnnl_types.h:783
@ dnnl_rnn
A rnn primitive.
Definition: dnnl_types.h:693
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1450
@ dnnl_query_num_of_outputs_s32
number of outputs expected
Definition: dnnl_types.h:1889
@ dnnl_cpu_isa_sse41
Intel(R) SSE4.1.
Definition: dnnl_types.h:2025
dnnl_format_kind_t
Memory format kind.
Definition: dnnl_types.h:80
Generic description of blocked data layout for most memory formats.
Definition: dnnl_types.h:879
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1188
const struct dnnl_primitive * const_dnnl_primitive_t
A constant primitive handle.
Definition: dnnl_types.h:1684
@ dnnl_abdec
permuted 5D tensor
Definition: dnnl_types.h:186
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1239
@ dnnl_cpu_isa_avx2
Intel(R) Advanced Vector Extensions 2.
Definition: dnnl_types.h:2031
@ dnnl_cpu_isa_avx512_core_vnni
Intel(R) Advanced Vector Extensions 512 with Intel(R) DL Boost Support for Intel(R) Xeon(R) Processor...
Definition: dnnl_types.h:2048
int ndims
Number of dimensions.
Definition: dnnl_types.h:979
@ dnnl_aBc8b
3D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:221
A descriptor of a Layer Normalization operation.
Definition: dnnl_types.h:1312
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1511
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1083
@ dnnl_not_required
Queried element is not required for given primitive.
Definition: dnnl_types.h:53
@ dnnl_eltwise_clip
Eltwise: clip.
Definition: dnnl_types.h:751
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1358
Description of tensor of weights for winograd 2x3 convolution.
Definition: dnnl_types.h:907
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1289
dnnl_memory_desc_t src_iter_desc
Source iteration memory descriptor for hidden state.
Definition: dnnl_types.h:1420
@ dnnl_pooling_avg_include_padding
Average pooling include padding.
Definition: dnnl_types.h:755
@ dnnl_hwigo
5D CNN weights tensor (incl. groups), an alias to dnnl_decab
Definition: dnnl_types.h:416
dnnl_memory_desc_t diff_src_iter_desc
Source gradient iter memory descriptor for hidden state.
Definition: dnnl_types.h:1442
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1356
@ dnnl_deconvolution
A deconvolution primitive.
Definition: dnnl_types.h:677
@ dnnl_aBcde4b
5D tensor blocked by 2nd dimension with block size 4
Definition: dnnl_types.h:274
dnnl_memory_desc_t data_scaleshift_desc
Scale and shift data and gradient memory descriptors.
Definition: dnnl_types.h:1295
@ dnnl_stream_out_of_order
Out-of-order execution.
Definition: dnnl_types.h:1955
@ dnnl_gemm
A matrix multiplication primitive (internal).
Definition: dnnl_types.h:695
@ dnnl_convolution
A convolution primitive.
Definition: dnnl_types.h:675
struct dnnl_primitive * dnnl_primitive_t
A primitive handle.
Definition: dnnl_types.h:1682
dnnl_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: dnnl_types.h:1259
const struct dnnl_primitive_attr * const_dnnl_primitive_attr_t
A constant primitive descriptor attributes handle.
Definition: dnnl_types.h:1645
An opaque structure for primitive descriptor attributes.
dnnl_memory_desc_t dst_layer_desc
Destination layer memory descriptor.
Definition: dnnl_types.h:1430
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1374
@ dnnl_lrn
An LRN primitive.
Definition: dnnl_types.h:685
@ dnnl_query_src_md
source memory desc
Definition: dnnl_types.h:1929
dnnl_softmax_desc_t dnnl_logsoftmax_desc_t
A descriptor of a LogSoftmax operation.
Definition: dnnl_types.h:1202
#define DNNL_RNN_MAX_N_PARTS
Maximum number of parts of RNN weights tensor that require separate computation.
Definition: dnnl_types.h:929
dnnl_scratchpad_mode_t
Scratchpad mode.
Definition: dnnl_types.h:1608
dnnl_wino_desc_t wino_desc
Tensor of weights for integer 8bit winograd convolution.
Definition: dnnl_types.h:1017
@ dnnl_data_type_undef
Undefined data type, used for empty memory descriptors.
Definition: dnnl_types.h:64
@ dnnl_query_engine
execution engine
Definition: dnnl_types.h:1885
dnnl_wino_memory_format_t
Winograd-specific formats.
Definition: dnnl_types.h:895
@ dnnl_query_softmax_d
softmax descriptor
Definition: dnnl_types.h:1914
A descriptor of resampling operation.
Definition: dnnl_types.h:1524
float batch_norm_epsilon
Batch normalization epsilon parameter.
Definition: dnnl_types.h:1302
@ dnnl_invalid_arguments
The operation failed because of incorrect function arguments.
Definition: dnnl_types.h:45
@ dnnl_cpu
CPU engine.
Definition: dnnl_types.h:1558
An opaque structure for a chain of post operations.
@ dnnl_query_undef
no query
Definition: dnnl_types.h:1883
@ dnnl_eltwise_swish
Eltwise: swish.
Definition: dnnl_types.h:747
@ dnnl_ndhwc
5D CNN activations tensor, an alias to dnnl_acdeb
Definition: dnnl_types.h:378
dnnl_memory_desc_t diff_dst_layer_desc
Destination gradient layer memory descriptor.
Definition: dnnl_types.h:1452
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1064
dnnl_dims_t kernel
Pooling kernel spatial dimensions.
Definition: dnnl_types.h:1233
@ dnnl_wino_wei_OBaaIBOIio
Internal weights format for 4x3 Winograd.
Definition: dnnl_types.h:903
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1362
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1117
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1537
dnnl_memory_desc_t bias_desc
Bias memory descriptor.
Definition: dnnl_types.h:1081
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1318
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1282
Memory descriptor.
Definition: dnnl_types.h:977
dnnl_memory_desc_t dst_desc
Destination memory descriptor.
Definition: dnnl_types.h:1487
@ dnnl_backward_bias
Backward bias propagation.
Definition: dnnl_types.h:658
void * dnnl_op_desc_t
A pointer to any of the operation descriptors.
Definition: dnnl_types.h:1047
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1360
@ dnnl_ncw
3D CNN activations tensor, an alias to dnnl_abc
Definition: dnnl_types.h:366
@ dnnl_matmul
A matrix multiplication primitive.
Definition: dnnl_types.h:701
int patch
Patch version.
Definition: dnnl_types.h:1993
dnnl_cpu_isa_t
CPU instruction set flags.
Definition: dnnl_types.h:2020
@ dnnl_query_some_md
stub
Definition: dnnl_types.h:1928
const struct dnnl_memory * const_dnnl_memory_t
A constant memory handle.
Definition: dnnl_types.h:1034
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1507
@ dnnl_nChw4c
4D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcd4b
Definition: dnnl_types.h:473
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1352
dnnl_memory_desc_t diff_desc
Source and Destination of gradient memory descriptor.
Definition: dnnl_types.h:1190
@ dnnl_oi
2D CNN weights tensor, an alias to dnnl_ab
Definition: dnnl_types.h:381
dnnl_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: dnnl_types.h:1153
@ dnnl_ohwi
4D CNN weights tensor, an alias to dnnl_acdb
Definition: dnnl_types.h:397
@ dnnl_bacd
permuted 4D tensor
Definition: dnnl_types.h:194
@ dnnl_format_kind_any
Unspecified format kind.
Definition: dnnl_types.h:85
@ dnnl_tnc
3D RNN data tensor in the format (seq_length, batch, input channels).
Definition: dnnl_types.h:427
@ dnnl_nChw16c
4D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBcd16b
Definition: dnnl_types.h:470
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1120
@ dnnl_query_eltwise_d
eltwise descriptor
Definition: dnnl_types.h:1913
struct dnnl_primitive_attr * dnnl_primitive_attr_t
A primitive descriptor attributes handle that controls primitive behavior.
Definition: dnnl_types.h:1642
@ dnnl_cba
permuted 3D tensor
Definition: dnnl_types.h:198
@ dnnl_query_num_of_inputs_s32
number of inputs expected
Definition: dnnl_types.h:1888
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1541
@ dnnl_acbde
permuted 5D tensor
Definition: dnnl_types.h:188
dnnl_alg_kind_t
Kinds of algorithms.
Definition: dnnl_types.h:707
@ dnnl_deconvolution_winograd
Winograd deconvolution.
Definition: dnnl_types.h:718
@ dnnl_cpu_isa_avx512_mic
Intel(R) Advanced Vector Extensions 512 subset for Intel(R) Xeon Phi(TM) Processors x200 Series.
Definition: dnnl_types.h:2035
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:1004
@ dnnl_ldgoi
5D RNN weights tensor in the format (num_layers, num_directions, num_gates, output_channels,...
Definition: dnnl_types.h:446
@ dnnl_success
The operation was successful.
Definition: dnnl_types.h:41
dnnl_dims_t padded_dims
Size of the data including padding in each dimension.
Definition: dnnl_types.h:1000
@ dnnl_eltwise_exp
Eltwise: exponent.
Definition: dnnl_types.h:740
@ dnnl_abcdef
plain 6D tensor
Definition: dnnl_types.h:182
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1480
@ dnnl_goihw
5D CNN weights tensor (incl. groups), an alias to dnnl_abcde
Definition: dnnl_types.h:414
@ dnnl_bidirectional_sum
Bidirectional execution of RNN primitive with summation of the results.
Definition: dnnl_types.h:1399
float alpha
Algorithm specific parameter.
Definition: dnnl_types.h:1171
@ dnnl_eltwise_linear
Eltwise: linear.
Definition: dnnl_types.h:732
@ dnnl_nCw16c
3D CNN activations tensor blocked by channels with block size 16, an alias to dnnl_aBc16b
Definition: dnnl_types.h:479
@ dnnl_vanilla_gru
GRU cell.
Definition: dnnl_types.h:769
dnnl_memory_desc_t dst_iter_c_desc
Destination iter memory descriptor for cell state.
Definition: dnnl_types.h:1434
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1068
dnnl_alg_kind_t alg_kind
The kind of the binary algorithm.
Definition: dnnl_types.h:1483
@ dnnl_abc
plain 3D tensor
Definition: dnnl_types.h:179
dnnl_dims_t inner_idxs
The logical indices of the blocks, e.g.
Definition: dnnl_types.h:891
A descriptor of a binary operation.
Definition: dnnl_types.h:1477
dnnl_memory_desc_t weights_desc
Weights memory descriptor.
Definition: dnnl_types.h:1509
dnnl_memory_extra_flags_t
Flags for memory special features.
Definition: dnnl_types.h:946
@ dnnl_convolution_direct
Direct convolution.
Definition: dnnl_types.h:710
unsigned gpu_runtime
GPU runtime.
Definition: dnnl_types.h:1996
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1251
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1229
@ dnnl_query_diff_src_md
source gradient memory desc
Definition: dnnl_types.h:1930
dnnl_memory_desc_t src_desc
Source memory descriptor.
Definition: dnnl_types.h:1535
@ dnnl_wio
3D CNN weights tensor, an alias to dnnl_cba
Definition: dnnl_types.h:389
dnnl_memory_desc_t diff_src_layer_desc
Source gradient layer memory descriptor.
Definition: dnnl_types.h:1440
dnnl_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: dnnl_types.h:1372
@ dnnl_forward_scoring
Forward data propagation (alias for dnnl_forward_inference).
Definition: dnnl_types.h:648
@ dnnl_aBcde8b
5D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:284
dnnl_memory_desc_t placeholder_desc
Placeholders.
Definition: dnnl_types.h:1436
@ dnnl_prop_kind_undef
Undefined propagation type.
Definition: dnnl_types.h:639
@ dnnl_blocked
A tensor in a generic format described by the stride and blocking values in each dimension.
Definition: dnnl_types.h:89
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1411
@ dnnl_query_primitive_kind
primitive kind
Definition: dnnl_types.h:1886
@ dnnl_unidirectional_left2right
Unidirectional execution of RNN primitive from left to right.
Definition: dnnl_types.h:1391
dnnl_memory_desc_t diff_weights_iter_desc
Weights gradient iter memory descriptor.
Definition: dnnl_types.h:1448
@ dnnl_iohw
4D CNN weights tensor, an alias to dnnl_bacd
Definition: dnnl_types.h:401
@ dnnl_eltwise_elu
Eltwise: parametric exponential linear unit (elu)
Definition: dnnl_types.h:724
dnnl_primitive_kind_t primitive_kind
The kind of primitive.
Definition: dnnl_types.h:1139
@ dnnl_odhwi
5D CNN weights tensor, an alias to dnnl_acdeb
Definition: dnnl_types.h:407
@ dnnl_nwc
3D CNN activations tensor, an alias to dnnl_acb
Definition: dnnl_types.h:368
@ dnnl_nCw4c
3D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBc4b
Definition: dnnl_types.h:482
@ dnnl_vanilla_lstm
LSTM cell.
Definition: dnnl_types.h:767
@ dnnl_any_engine
An unspecified engine.
Definition: dnnl_types.h:1556
@ dnnl_nCdhw4c
5D CNN activations tensor blocked by channels with block size 4, an alias to dnnl_aBcde4b
Definition: dnnl_types.h:464
@ dnnl_resampling
A resampling primitive.
Definition: dnnl_types.h:703
@ dnnl_wino_wei_aaOBiOo
Internal weights format for 2x3 Winograd.
Definition: dnnl_types.h:901
@ dnnl_cpu_isa_avx
Intel(R) Advanced Vector Extensions.
Definition: dnnl_types.h:2028
@ dnnl_bca
permuted 3D tensor
Definition: dnnl_types.h:195
dnnl_prop_kind_t
Kinds of propagation.
Definition: dnnl_types.h:636
@ dnnl_query_scratchpad_md
scratchpad memory desc
Definition: dnnl_types.h:1936
float lrn_k
LRN k parameter.
Definition: dnnl_types.h:1270
@ dnnl_nchw
4D CNN activations tensor, an alias to dnnl_abcd
Definition: dnnl_types.h:370
dnnl_prop_kind_t prop_kind
The kind of propagation.
Definition: dnnl_types.h:1530
@ dnnl_eltwise_gelu
Eltwise: gelu.
Definition: dnnl_types.h:745
dnnl_alg_kind_t alg_kind
LRN algorithm.
Definition: dnnl_types.h:1257
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:1264
@ dnnl_query_weights_md
weights memory descriptor desc
Definition: dnnl_types.h:1931
dnnl_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: dnnl_types.h:1368
dnnl_alg_kind_t alg_kind
The kind of the resampling algorithm.
Definition: dnnl_types.h:1533
dnnl_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: dnnl_types.h:1225
dnnl_memory_desc_t data_desc
Source and destination memory descriptor, and source and destination gradient memory descriptor.
Definition: dnnl_types.h:1123
@ dnnl_query_batch_normalization_d
batch normalization descriptor
Definition: dnnl_types.h:1917
dnnl_dims_t strides
Pooling kernel strides for spatial dimensions.
Definition: dnnl_types.h:1231
dnnl_memory_desc_t dst_iter_desc
Destination iter memory descriptor for hidden state.
Definition: dnnl_types.h:1432
dnnl_data_type_t accum_data_type
The accumulator data type. Initialized automatically.
Definition: dnnl_types.h:1097
@ dnnl_chwn
4D CNN activations tensor, an alias to dnnl_bcda
Definition: dnnl_types.h:374
dnnl_alg_kind_t cell_kind
RNN cell kind.
Definition: dnnl_types.h:1414
const typedef void * const_dnnl_op_desc_t
A pointer to any of the operation descriptors (constant variant).
Definition: dnnl_types.h:1049
@ dnnl_undefined_primitive
Undefined primitive.
Definition: dnnl_types.h:665
@ dnnl_eltwise_soft_relu
Eltwise: soft_relu.
Definition: dnnl_types.h:736
@ dnnl_nt
2D RNN statistics tensor, an alias to dnnl_ba
Definition: dnnl_types.h:364
dnnl_convolution_desc_t dnnl_deconvolution_desc_t
A descriptor of a deconvolution operation.
Definition: dnnl_types.h:1106
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:1008
@ dnnl_unidirectional_right2left
Unidirectional execution of RNN primitive from right to left.
Definition: dnnl_types.h:1393
@ dnnl_aBcd8b
4D tensor blocked by 2nd dimension with block size 8
Definition: dnnl_types.h:248
@ dnnl_ab
plain 2D tensor
Definition: dnnl_types.h:178
dnnl_rnn_packed_desc_t rnn_packed_desc
Tensor of packed weights for RNN.
Definition: dnnl_types.h:1019
@ dnnl_query_scratchpad_engine
(scratch) memory, additional to all inputs and outputs memory (bytes)
Definition: dnnl_types.h:1897
@ dnnl_runtime_error
Primitive or engine failed on execution.
Definition: dnnl_types.h:51
@ dnnl_giodhw
6D CNN weights tensor (incl. groups), an alias to dnnl_acbdef
Definition: dnnl_types.h:422
@ dnnl_query_exec_arg_md
memory desc of an execute argument
Definition: dnnl_types.h:1937
@ dnnl_query_some_d
stub
Definition: dnnl_types.h:1908
@ dnnl_pooling_avg_exclude_padding
Average pooling exclude padding.
Definition: dnnl_types.h:757
@ dnnl_binary_add
Binary add.
Definition: dnnl_types.h:779