17 #ifndef MKLDNN_TYPES_H    18 #define MKLDNN_TYPES_H    24 #ifndef DOXYGEN_SHOULD_SKIP_THIS   549 #define TENSOR_MAX_DIMS 12   564     mkldnn_strides_t strides[2];
   609 #define MKLDNN_RNN_MAX_N_PARTS 4   613     mkldnn_rnn_packed_memory_format_t 
format;
   709     mkldnn_dims_t padding[2];
   814     mkldnn_dims_t padding[2];
 mkldnn_data_type_t accum_data_type
The accumulator data type. 
Definition: mkldnn_types.h:905
LRN within a single channel. 
Definition: mkldnn_types.h:484
struct mkldnn_post_ops * mkldnn_post_ops_t
A post operation chain handle. 
Definition: mkldnn_types.h:1088
mkldnn_padding_kind_t padding_kind
The kind of padding to use. 
Definition: mkldnn_types.h:816
size_t size
Definition: mkldnn_types.h:598
A descriptor of a Local Response Normalization (LRN) operation. 
Definition: mkldnn_types.h:822
blocked weights format 
Definition: mkldnn_types.h:306
blocked weights format 
Definition: mkldnn_types.h:309
op descriptor 
Definition: mkldnn_types.h:1164
blocked weights format with additional buffer with size equal to the number of output channels multip...
Definition: mkldnn_types.h:333
blocked weights format 
Definition: mkldnn_types.h:293
blocked weights format 
Definition: mkldnn_types.h:355
A Softmax primitive. 
Definition: mkldnn_types.h:428
number of outputs expected 
Definition: mkldnn_types.h:1153
int alpha
Definition: mkldnn_types.h:590
mkldnn_memory_desc_t diff_bias_desc
Bias gradient memory descriptor. 
Definition: mkldnn_types.h:982
mkldnn_rnn_packed_memory_format_t format
Definition: mkldnn_types.h:613
mkldnn_dims_t dilates
Convolution dilates in each spatial dimension. 
Definition: mkldnn_types.h:705
mkldnn_status_t
Status values returned by Intel(R) MKL-DNN functions. 
Definition: mkldnn_types.h:39
A descriptor of a convolution operation. 
Definition: mkldnn_types.h:675
mkldnn_rnn_direction_t direction
The direction of RNN primitive execution. 
Definition: mkldnn_types.h:958
The operation failed and should be retried. 
Definition: mkldnn_types.h:45
blocked weights format 
Definition: mkldnn_types.h:265
mkldnn_memory_desc_t dst_layer_desc
Destination layer memory descriptor. 
Definition: mkldnn_types.h:970
int ic_block
Definition: mkldnn_types.h:593
4D RNN bias tensor in the format (num_layers, num_directions, num_gates, output_channels). 
Definition: mkldnn_types.h:245
4D data tensor with the physical layout chwn, used in Neon. 
Definition: mkldnn_types.h:163
The operation failed because of incorrect function arguments. 
Definition: mkldnn_types.h:47
Forward data propagation (alias for mkldnn_forward_inference) 
Definition: mkldnn_types.h:389
Definition: mkldnn_types.h:604
An opaque structure to describe an engine. 
Backward data propagation. 
Definition: mkldnn_types.h:395
blocked weights format 
Definition: mkldnn_types.h:289
Undefined memory format, used for empty memory descriptors. 
Definition: mkldnn_types.h:137
float alpha
alpha is a negative slope parameter (used only if (flags & mkldnn_rnn_cell_with_relu) != 0) ...
Definition: mkldnn_types.h:926
#define TENSOR_MAX_DIMS
Maximum number of dimensions a tensor can have. 
Definition: mkldnn_types.h:549
4D weights tensor with physical layout oihw, used in Caffe. 
Definition: mkldnn_types.h:184
A descriptor of a Softmax operation. 
Definition: mkldnn_types.h:772
blocked weights format 
Definition: mkldnn_types.h:358
mkldnn_padding_kind_t padding_kind
The kind of padding to use. 
Definition: mkldnn_types.h:711
blocked weights format 
Definition: mkldnn_types.h:359
int oc_block
Definition: mkldnn_types.h:594
blocked data format 
Definition: mkldnn_types.h:252
A descriptor of an inner product operation. 
Definition: mkldnn_types.h:880
3D RNN data tensor in the format (seq_length, batch, input channels). 
Definition: mkldnn_types.h:221
An opaque structure for a chain of post operations. 
An opaque structure to describe a primitive descriptor . 
batch normalization descriptor 
Definition: mkldnn_types.h:1173
mkldnn_rnn_direction_t
A direction of RNN primitive execution. 
Definition: mkldnn_types.h:933
mkldnn_memory_desc_t diff_data_scaleshift_desc
Definition: mkldnn_types.h:867
A convolution primitive. 
Definition: mkldnn_types.h:422
mkldnn_memory_desc_t diff_src_desc
Source gradient memory descriptor. 
Definition: mkldnn_types.h:891
size_t offset_compensation
Definition: mkldnn_types.h:618
int axis
axis for shuffling. 
Definition: mkldnn_types.h:731
struct mkldnn_stream * mkldnn_stream_t
An execution stream handle. 
Definition: mkldnn_types.h:1209
blocked data format 
Definition: mkldnn_types.h:253
mkldnn_prop_kind_t prop_kind
The kind of propagation. 
Definition: mkldnn_types.h:778
struct mkldnn_primitive_desc_iterator * mkldnn_primitive_desc_iterator_t
A primitive descriptor iterator handle. 
Definition: mkldnn_types.h:1023
mkldnn_primitive_kind_t primitive_kind
The kind of primitive. 
Definition: mkldnn_types.h:723
Undefined primitive (XXX: why do we have it?). 
Definition: mkldnn_types.h:406
An inner product primitive. 
Definition: mkldnn_types.h:436
Packed weights format used in RNN. 
Definition: mkldnn_types.h:363
Round down. 
Definition: mkldnn_types.h:82
4D grouped weights tensor with the physical layout goiw. 
Definition: mkldnn_types.h:202
mkldnn_memory_desc_t dst_desc
Destination memory descriptor. 
Definition: mkldnn_types.h:699
mkldnn_memory_desc_t diff_src_desc
Source gradient memory descriptor. 
Definition: mkldnn_types.h:802
Tensors of weights for 2x3 winograd convolutions. 
Definition: mkldnn_types.h:579
Definition: mkldnn_types.h:480
mkldnn_memory_desc_t diff_desc
Source and Destination of gradient memory descriptor. 
Definition: mkldnn_types.h:782
size_t output_index
Desired output index. 
Definition: mkldnn_types.h:1111
mkldnn_data_type_t data_type
Data type of the tensor elements. 
Definition: mkldnn_types.h:657
mkldnn_rnn_cell_flags_t
Flags for RNN cell. 
Definition: mkldnn_types.h:909
mkldnn_dims_t offset_padding_to_data
Per-dimension offset from the padding to actual data, the top-level tensor with offsets applied must ...
Definition: mkldnn_types.h:569
float lrn_beta
LRN beta parameter. 
Definition: mkldnn_types.h:843
32-bit signed integer. 
Definition: mkldnn_types.h:68
Max pooling. 
Definition: mkldnn_types.h:475
blocked weights format 
Definition: mkldnn_types.h:279
execution engine 
Definition: mkldnn_types.h:1149
void * mkldnn_op_desc_t
A pointer to any of the operation descriptors. 
Definition: mkldnn_types.h:626
mkldnn_data_type_t accum_data_type
The accumulator data type. 
Definition: mkldnn_types.h:713
blocked weights format 
Definition: mkldnn_types.h:286
mkldnn_prop_kind_t prop_kind
The kind of propagation. 
Definition: mkldnn_types.h:829
mkldnn_memory_desc_t diff_dst_desc
Destination gradient memory descriptor. 
Definition: mkldnn_types.h:806
Definition: mkldnn_types.h:911
mkldnn_memory_desc_t data_desc
Source and destination memory descriptor. 
Definition: mkldnn_types.h:752
float lrn_alpha
LRN alpha parameter. 
Definition: mkldnn_types.h:841
struct mkldnn_primitive * mkldnn_primitive_t
A primitive handle. 
Definition: mkldnn_types.h:1102
input memory primitive desc 
Definition: mkldnn_types.h:1179
blocked weights format 
Definition: mkldnn_types.h:300
ptrdiff_t mkldnn_strides_t[TENSOR_MAX_DIMS]
A type to describe strides within a tensor. 
Definition: mkldnn_types.h:554
5D grouped weights tensor with the physical layout goihw, used in Caffe. 
Definition: mkldnn_types.h:206
const_mkldnn_primitive_t primitive
Primitive to specify the output for. 
Definition: mkldnn_types.h:1109
mkldnn_prop_kind_t prop_kind
The kind of propagation. 
Definition: mkldnn_types.h:795
int local_size
The number of channels to sum over (for cross-channel LRN) or the side length of the square region to...
Definition: mkldnn_types.h:839
ptrdiff_t offset_padding
Offset from memory origin to the current block, non-zero only in a description of a memory sub-block...
Definition: mkldnn_types.h:572
A descriptor of a element-wise operation. 
Definition: mkldnn_types.h:737
rnn descriptor 
Definition: mkldnn_types.h:1175
An element-wise primitive. 
Definition: mkldnn_types.h:426
float beta
Definition: mkldnn_types.h:768
mkldnn_memory_desc_t src_desc
Source memory descriptor. 
Definition: mkldnn_types.h:889
destination grad. 
Definition: mkldnn_types.h:1186
mkldnn_alg_kind_t activation_kind
Activation function used. 
Definition: mkldnn_types.h:921
blocked weights format 
Definition: mkldnn_types.h:303
A descriptor for an rnn operation. 
Definition: mkldnn_types.h:948
eltwise descriptor 
Definition: mkldnn_types.h:1169
A memory primitive. 
Definition: mkldnn_types.h:408
float clipping
clipping parameter (used only if (flags & mkldnn_rnn_cell_with_clipping) != 0) 
Definition: mkldnn_types.h:929
blocked weights format 
Definition: mkldnn_types.h:288
mkldnn_memory_desc_t bias_desc
Bias memory descriptor. 
Definition: mkldnn_types.h:695
Eltwise: soft_relu. 
Definition: mkldnn_types.h:471
mkldnn_wino_memory_format_t
Definition: mkldnn_types.h:575
The operation failed due to an out-of-memory condition. 
Definition: mkldnn_types.h:43
RNN cell. 
Definition: mkldnn_types.h:486
blocked weights format 
Definition: mkldnn_types.h:315
Backward weights propagation. 
Definition: mkldnn_types.h:397
blocked weights format 
Definition: mkldnn_types.h:354
mkldnn_memory_desc_t weights_iter_desc
Weights iteration memory descriptor. 
Definition: mkldnn_types.h:966
stub 
Definition: mkldnn_types.h:1163
int ic2_block
Definition: mkldnn_types.h:595
32-bit/single-precision floating point. 
Definition: mkldnn_types.h:66
mkldnn_prop_kind_t prop_kind
The kind of propagation. 
Definition: mkldnn_types.h:744
const struct mkldnn_primitive_desc_iterator * const_mkldnn_primitive_desc_iterator_t
A constant primitive descriptor iterator handle. 
Definition: mkldnn_types.h:1027
blocked weights format 
Definition: mkldnn_types.h:262
blocked data format 
Definition: mkldnn_types.h:251
2D weights tensor with physical layout oi. 
Definition: mkldnn_types.h:172
Just a sentinel, not real memory format. 
Definition: mkldnn_types.h:367
Memory descriptor. 
Definition: mkldnn_types.h:634
mkldnn_dims_t kernel
Pooling kernel spatial dimensions. 
Definition: mkldnn_types.h:810
mkldnn_memory_desc_t data_desc
Source and destination memory descriptor. 
Definition: mkldnn_types.h:858
mkldnn_convolution_desc_t mkldnn_deconvolution_desc_t
A descriptor of a deconvolution operation. 
Definition: mkldnn_types.h:717
mkldnn_batch_normalization_flag_t
Flags for batch-normalization primititve. 
Definition: mkldnn_types.h:503
pooling descriptor 
Definition: mkldnn_types.h:1171
mkldnn_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor. 
Definition: mkldnn_types.h:836
mkldnn_alg_kind_t alg_kind
The kind of pooling algorithm. 
Definition: mkldnn_types.h:798
mkldnn_primitive_kind_t primitive_kind
The kind of primitive. 
Definition: mkldnn_types.h:678
blocked weights format 
Definition: mkldnn_types.h:261
mkldnn_memory_desc_t dst_desc
Destination memory descriptor. 
Definition: mkldnn_types.h:901
3D weights tensor with physical layout wio. 
Definition: mkldnn_types.h:181
mkldnn_memory_desc_t weights_layer_desc
Weights layer memory descriptor. 
Definition: mkldnn_types.h:964
mkldnn_memory_desc_t diff_bias_desc
Bias gradient memory descriptor. 
Definition: mkldnn_types.h:697
blocked weights format 
Definition: mkldnn_types.h:314
unsigned int flags
RNN cell flags. 
Definition: mkldnn_types.h:923
3D data tensor with the physical layout ncw. 
Definition: mkldnn_types.h:151
blocked weights format 
Definition: mkldnn_types.h:291
The operation was successful. 
Definition: mkldnn_types.h:41
mkldnn_memory_desc_t dst_iter_desc
Destination iter memory descriptor. 
Definition: mkldnn_types.h:972
blocked weights format with additional buffer with size equal to the number of groups and containing ...
Definition: mkldnn_types.h:348
blocked weights format 
Definition: mkldnn_types.h:326
mkldnn_primitive_kind_t primitive_kind
The kind of primitive. 
Definition: mkldnn_types.h:825
blocked weights format 
Definition: mkldnn_types.h:334
mkldnn_memory_desc_t src_iter_desc
Source iteration memory descriptor. 
Definition: mkldnn_types.h:962
blocked weights format 
Definition: mkldnn_types.h:352
Backward propagation (with respect to all parameters. 
Definition: mkldnn_types.h:393
5D data tensor with the physical layout ndhwc, used in TensorFlow. 
Definition: mkldnn_types.h:169
softmax descriptor 
Definition: mkldnn_types.h:1170
mkldnn_round_mode_t
Rounding mode. 
Definition: mkldnn_types.h:78
A deconvolution primitive. 
Definition: mkldnn_types.h:424
mkldnn_memory_desc_t data_scaleshift_desc
Scale and shift data and gradient memory descriptors. 
Definition: mkldnn_types.h:866
Use global statistics. 
Definition: mkldnn_types.h:516
blocked weights format 
Definition: mkldnn_types.h:292
no query 
Definition: mkldnn_types.h:1147
blocked weights format 
Definition: mkldnn_types.h:341
blocked weights format 
Definition: mkldnn_types.h:304
mkldnn_memory_desc_t mean_desc
Mean and variance data memory descriptors. 
Definition: mkldnn_types.h:872
mkldnn_primitive_kind_t primitive_kind
The kind of primitive. 
Definition: mkldnn_types.h:852
8-bit unsigned integer. 
Definition: mkldnn_types.h:74
mkldnn_alg_kind_t alg_kind
LRN algorithm. 
Definition: mkldnn_types.h:832
Average pooling include padding. 
Definition: mkldnn_types.h:477
Unspecified format. 
Definition: mkldnn_types.h:140
mkldnn_memory_desc_t diff_src_desc
Source gradient memory descriptor. 
Definition: mkldnn_types.h:689
destination memory primitive desc 
Definition: mkldnn_types.h:1185
5D RNN weights tensor in the format (num_layers, num_directions, input_channels, num_gates, output_channels). 
Definition: mkldnn_types.h:231
GRU cell with linear before reset. 
Definition: mkldnn_types.h:499
Local response normalization (LRN) across multiple channels. 
Definition: mkldnn_types.h:482
blocked weights format 
Definition: mkldnn_types.h:276
GRU cell. 
Definition: mkldnn_types.h:490
Eager stream. 
Definition: mkldnn_types.h:1200
implementation name 
Definition: mkldnn_types.h:1160
3D weights tensor with physical layout oiw. 
Definition: mkldnn_types.h:178
Eltwise: parametric exponential linear unit (elu) 
Definition: mkldnn_types.h:459
mkldnn_dims_t padding_dims
Size of the data including padding in each dimension. 
Definition: mkldnn_types.h:566
Eltwise: ReLU. 
Definition: mkldnn_types.h:455
1D data tensor. 
Definition: mkldnn_types.h:146
float lrn_k
LRN k parameter. 
Definition: mkldnn_types.h:845
4D weights tensor with physical layout ihwo. 
Definition: mkldnn_types.h:190
mkldnn_memory_format_t
Memory format specification. 
Definition: mkldnn_types.h:135
Eltwise: square. 
Definition: mkldnn_types.h:461
mkldnn_prop_kind_t prop_kind
The kind of propagation. 
Definition: mkldnn_types.h:887
mkldnn_wino_desc_t wino_desc
Tensor of weights for integer 8bit winograd convolution. 
Definition: mkldnn_types.h:665
mkldnn_data_type_t accum_data_type
The accumulator data type. 
Definition: mkldnn_types.h:818
int n
Definition: mkldnn_types.h:615
4D data tensor with the physical layout nhwc, used in TensorFlow. 
Definition: mkldnn_types.h:160
Description of tensor of packed weights for rnn. 
Definition: mkldnn_types.h:612
Backward bias propagation. 
Definition: mkldnn_types.h:399
blocked weights format 
Definition: mkldnn_types.h:349
Use scale and shift parameters. 
Definition: mkldnn_types.h:529
int group_size
number of groups in group convolution 
Definition: mkldnn_types.h:733
weights format with additional buffer size equal to the number of output channels multiplied by numbe...
Definition: mkldnn_types.h:325
mkldnn_memory_desc_t weights_desc
Weights memory descriptor. 
Definition: mkldnn_types.h:691
blocked weights format 
Definition: mkldnn_types.h:275
mkldnn_rnn_cell_desc_t cell_desc
The RNN cell desc. 
Definition: mkldnn_types.h:956
blocked weights format 
Definition: mkldnn_types.h:335
A descriptor of a shuffle operation. 
Definition: mkldnn_types.h:720
Definition: mkldnn_types.h:943
mkldnn_memory_desc_t data_desc
Source and destination memory descriptor. 
Definition: mkldnn_types.h:729
mkldnn_rnn_packed_memory_format_t
Definition: mkldnn_types.h:601
blocked weights format 
Definition: mkldnn_types.h:343
blocked weights format 
Definition: mkldnn_types.h:311
Undefined memory format, used for empty memory descriptors. 
Definition: mkldnn_types.h:577
int ndims
Number of dimensions. 
Definition: mkldnn_types.h:639
mkldnn_primitive_kind_t primitive_kind
The kind of primitive. 
Definition: mkldnn_types.h:637
5D grouped weights tensor with the physical layout giohw. 
Definition: mkldnn_types.h:213
An opaque structure to describe an execution stream. 
const struct mkldnn_primitive_attr * const_mkldnn_primitive_attr_t
A constant primitive descriptor attributes handle. 
Definition: mkldnn_types.h:1064
Undefined propagation type. 
Definition: mkldnn_types.h:380
mkldnn_blocking_desc_t blocking
Description of the data layout for memory formats that use blocking. 
Definition: mkldnn_types.h:663
5D data tensor with the physical layout ncdhw. 
Definition: mkldnn_types.h:166
5D RNN states tensor in the format (num_layers, num_directions, num_states, batch, state channels). 
Definition: mkldnn_types.h:224
mkldnn_dims_t dims
Dimensions in the following order: 
Definition: mkldnn_types.h:655
A rnn primitive. 
Definition: mkldnn_types.h:438
mkldnn_rnn_packed_desc_t rnn_packed_desc
Tensor of packed weights for RNN. 
Definition: mkldnn_types.h:667
mkldnn_dims_t strides
Convolution strides in each spatial dimension. 
Definition: mkldnn_types.h:703
blocked weights format 
Definition: mkldnn_types.h:299
mkldnn_prop_kind_t
Kinds of propagation. 
Definition: mkldnn_types.h:377
CPU engine. 
Definition: mkldnn_types.h:999
mkldnn_memory_desc_t bias_desc
Bias memory descriptor. 
Definition: mkldnn_types.h:968
Eltwise: square root. 
Definition: mkldnn_types.h:465
mkldnn_memory_desc_t data_desc
Source and destination memory descriptor. 
Definition: mkldnn_types.h:780
mkldnn_memory_format_t format
Memory format. 
Definition: mkldnn_types.h:659
blocked weights format 
Definition: mkldnn_types.h:263
mkldnn_stream_kind_t
Kinds of streams. 
Definition: mkldnn_types.h:1196
mkldnn_memory_desc_t src_desc
Source memory descriptor. 
Definition: mkldnn_types.h:687
4D weights tensor with physical layout hwio, used in TensorFlow. 
Definition: mkldnn_types.h:187
A wrapper structure to specify a particular output of a primitive. 
Definition: mkldnn_types.h:1107
Winograd convolution. 
Definition: mkldnn_types.h:447
Eltwise: linear. 
Definition: mkldnn_types.h:467
mkldnn_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor. 
Definition: mkldnn_types.h:860
Eltwise: logistic. 
Definition: mkldnn_types.h:473
Direct convolution. 
Definition: mkldnn_types.h:445
Primitive iterator passed over last primitive descriptor. 
Definition: mkldnn_types.h:54
const struct mkldnn_primitive * const_mkldnn_primitive_t
A constant primitive handle. 
Definition: mkldnn_types.h:1104
size_t size
Definition: mkldnn_types.h:619
source gradient memory primitive desc 
Definition: mkldnn_types.h:1182
mkldnn_alg_kind_t cell_kind
RNN cell kind. 
Definition: mkldnn_types.h:918
Definition: mkldnn_types.h:935
An opaque structure for primitive descriptor attributes. 
mkldnn_prop_kind_t prop_kind
The kind of propagation. 
Definition: mkldnn_types.h:954
int oc
Definition: mkldnn_types.h:592
blocked data format 
Definition: mkldnn_types.h:255
float batch_norm_epsilon
Batch normalization epsilon parameter. 
Definition: mkldnn_types.h:875
runtime estimation (seconds) 
Definition: mkldnn_types.h:1155
blocked weights format 
Definition: mkldnn_types.h:342
A (in-place) concat primitive. 
Definition: mkldnn_types.h:418
mkldnn_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor. 
Definition: mkldnn_types.h:754
blocked weights format 
Definition: mkldnn_types.h:277
LSTM cell. 
Definition: mkldnn_types.h:488
blocked weights format 
Definition: mkldnn_types.h:266
Definition: mkldnn_types.h:944
mkldnn_memory_desc_t diff_weights_layer_desc
Weights gradient layer memory descriptor. 
Definition: mkldnn_types.h:978
Definition: mkldnn_types.h:580
mkldnn_wino_memory_format_t wino_format
Definition: mkldnn_types.h:588
Undefined data type, used for empty memory descriptors. 
Definition: mkldnn_types.h:64
16-bit signed integer. 
Definition: mkldnn_types.h:70
A shuffle primitive. 
Definition: mkldnn_types.h:414
blocked weights format with additional buffer with size equal to the number of output channels and co...
Definition: mkldnn_types.h:284
mkldnn_prop_kind_t prop_kind
The kind of propagation. 
Definition: mkldnn_types.h:726
mkldnn_memory_desc_t src_layer_desc
Source layer memory descriptor. 
Definition: mkldnn_types.h:960
blocked weights format 
Definition: mkldnn_types.h:305
#define MKLDNN_RNN_MAX_N_PARTS
Definition: mkldnn_types.h:609
blocked weights format 
Definition: mkldnn_types.h:298
A (out-of-place) concat primitive. 
Definition: mkldnn_types.h:416
blocked weights format 
Definition: mkldnn_types.h:312
Fuse with ReLU. 
Definition: mkldnn_types.h:538
mkldnn_query_t
Primitive descriptor query specification. 
Definition: mkldnn_types.h:1146
A descriptor of a Batch Normalization operation. 
Definition: mkldnn_types.h:849
Definition: mkldnn_types.h:602
const struct mkldnn_stream * const_mkldnn_stream_t
A constant execution stream handle. 
Definition: mkldnn_types.h:1211
blocked data format 
Definition: mkldnn_types.h:254
A sum primitive. 
Definition: mkldnn_types.h:420
blocked weights format 
Definition: mkldnn_types.h:339
mkldnn_primitive_kind_t primitive_kind
The kind of primitive. 
Definition: mkldnn_types.h:775
unsigned flags
Definition: mkldnn_types.h:876
blocked weights format 
Definition: mkldnn_types.h:267
blocked weights format 
Definition: mkldnn_types.h:316
Convolution algorithm(either direct or Winograd) is chosen just in time. 
Definition: mkldnn_types.h:449
blocked weights format 
Definition: mkldnn_types.h:258
blocked weights format 
Definition: mkldnn_types.h:344
2D weights tensor with physical layout io. 
Definition: mkldnn_types.h:175
memory consumption – extra (scratch) memory, additional to all inputs and outputs memory (bytes) ...
Definition: mkldnn_types.h:1156
An batch normalization primitive. 
Definition: mkldnn_types.h:434
Definition: mkldnn_types.h:443
A descriptor of a pooling operation. 
Definition: mkldnn_types.h:788
mkldnn_dims_t strides
Pooling kernel strides for spatial dimensions. 
Definition: mkldnn_types.h:808
deconvolution descriptor 
Definition: mkldnn_types.h:1167
blocked weights format 
Definition: mkldnn_types.h:318
int softmax_axis
The axis along which to perform the softmax. 
Definition: mkldnn_types.h:784
mkldnn_memory_desc_t diff_dst_iter_desc
Destination gradient iteration memory descriptor. 
Definition: mkldnn_types.h:986
8-bit signed integer. 
Definition: mkldnn_types.h:72
The data in padding regions is zero. 
Definition: mkldnn_types.h:373
mkldnn_memory_desc_t variance_desc
Definition: mkldnn_types.h:873
source memory primitive desc 
Definition: mkldnn_types.h:1181
mkldnn_primitive_kind_t
Kinds of primitives. 
Definition: mkldnn_types.h:404
Winograd deconvolution. 
Definition: mkldnn_types.h:453
number of inputs expected 
Definition: mkldnn_types.h:1152
Definition: mkldnn_types.h:603
struct mkldnn_engine * mkldnn_engine_t
An engine handle. 
Definition: mkldnn_types.h:1006
mkldnn_memory_desc_t weights_desc
Weights memory descriptor. 
Definition: mkldnn_types.h:893
An unspecified engine. 
Definition: mkldnn_types.h:1198
A view primitive. 
Definition: mkldnn_types.h:410
Description of tensor of weights for winograd 2x3 convolution. 
Definition: mkldnn_types.h:587
blocked weights format 
Definition: mkldnn_types.h:290
Average pooling exclude padding. 
Definition: mkldnn_types.h:479
Definition: mkldnn_types.h:914
Forward data propagation (inference mode). 
Definition: mkldnn_types.h:387
6D grouped weights tensor with the physical layout goidhw, used in Caffe. 
Definition: mkldnn_types.h:217
5D weights tensor with physical layout iodhw, used in Caffe. 
Definition: mkldnn_types.h:196
Definition: mkldnn_types.h:581
Direct deconvolution. 
Definition: mkldnn_types.h:451
Eltwise: abs. 
Definition: mkldnn_types.h:463
blocked weights format 
Definition: mkldnn_types.h:328
mkldnn_memory_desc_t diff_dst_desc
Destination gradient memory descriptor. 
Definition: mkldnn_types.h:701
blocked weights format 
Definition: mkldnn_types.h:278
5D grouped weights tensor with the physical layout hwigo, used in TensorFlow. 
Definition: mkldnn_types.h:210
stub 
Definition: mkldnn_types.h:1178
int ic
Definition: mkldnn_types.h:591
blocked weights format 
Definition: mkldnn_types.h:336
The operation failed because requested functionality is not implemented. 
Definition: mkldnn_types.h:52
Eltwise: hyperbolic tangent non-linearity (tanh) 
Definition: mkldnn_types.h:457
mkldnn_memory_desc_t diff_dst_desc
Destination gradient memory descriptor. 
Definition: mkldnn_types.h:903
blocked weights format 
Definition: mkldnn_types.h:317
2D data tensor. 
Definition: mkldnn_types.h:148
float adj_scale
Definition: mkldnn_types.h:597
Primitive or engine failed on execution. 
Definition: mkldnn_types.h:56
memory descriptor for memory and view 
Definition: mkldnn_types.h:1165
const struct mkldnn_post_ops * const_mkldnn_post_ops_t
A constant post operation chain handle. 
Definition: mkldnn_types.h:1091
An LRN primitive. 
Definition: mkldnn_types.h:432
Definition: mkldnn_types.h:940
mkldnn_padding_kind_t
Kinds of padding. 
Definition: mkldnn_types.h:371
mkldnn_memory_desc_t dst_desc
Destination memory descriptor. 
Definition: mkldnn_types.h:804
Lazy stream. 
Definition: mkldnn_types.h:1202
blocked weights format 
Definition: mkldnn_types.h:340
blocked weights format 
Definition: mkldnn_types.h:260
mkldnn_memory_desc_t diff_src_iter_desc
Source gradient iter memory descriptor. 
Definition: mkldnn_types.h:976
5D RNN weights tensor in the format (num_layers, num_directions, num_gates, output_channels, input_channels). 
Definition: mkldnn_types.h:238
blocked weights format 
Definition: mkldnn_types.h:310
const struct mkldnn_primitive_desc * const_mkldnn_primitive_desc_t
A constant primitive descriptor handle. 
Definition: mkldnn_types.h:1043
shuffle descriptor 
Definition: mkldnn_types.h:1168
Forward data propagation (training mode). 
Definition: mkldnn_types.h:383
3D data tensor with the physical layout nwc. 
Definition: mkldnn_types.h:154
The operation failed because a primitive was not ready for execution. 
Definition: mkldnn_types.h:49
An opaque structure to describe a primitive. 
A tensor in a generic format described by the stride and blocking values in each dimension. 
Definition: mkldnn_types.h:144
mkldnn_data_type_t
Data type specification. 
Definition: mkldnn_types.h:62
convolution descriptor 
Definition: mkldnn_types.h:1166
mkldnn_primitive_kind_t primitive_kind
The kind of primitive. 
Definition: mkldnn_types.h:951
mkldnn_memory_desc_t src_desc
Source memory descriptor. 
Definition: mkldnn_types.h:800
mkldnn_prop_kind_t prop_kind
The kind of propagation. 
Definition: mkldnn_types.h:856
blocked weights format 
Definition: mkldnn_types.h:301
mkldnn_primitive_kind_t primitive_kind
The kind of primitive. 
Definition: mkldnn_types.h:740
mkldnn_alg_kind_t alg_kind
The kind of eltwise algorithm. 
Definition: mkldnn_types.h:750
blocked weights format 
Definition: mkldnn_types.h:294
mkldnn_memory_desc_t diff_src_layer_desc
Source gradient layer memory descriptor. 
Definition: mkldnn_types.h:974
Eltwise: bounded_relu. 
Definition: mkldnn_types.h:469
mkldnn_memory_desc_t diff_weights_desc
Weights gradient memory descriptor. 
Definition: mkldnn_types.h:895
Definition: mkldnn_types.h:937
mkldnn_prop_kind_t prop_kind
The kind of propagation. 
Definition: mkldnn_types.h:682
mkldnn_engine_kind_t
Kinds of engines. 
Definition: mkldnn_types.h:995
Definition: mkldnn_types.h:910
Queried element is not required for given primitive. 
Definition: mkldnn_types.h:58
blocked weights format 
Definition: mkldnn_types.h:357
Weights format used in 8bit Winograd convolution. 
Definition: mkldnn_types.h:361
Generic description of blocked data layout for most memory formats. 
Definition: mkldnn_types.h:559
Round nearest. 
Definition: mkldnn_types.h:80
blocked weights format 
Definition: mkldnn_types.h:356
const void * const_mkldnn_op_desc_t
A pointer to any of the operation descriptors (constant variant). 
Definition: mkldnn_types.h:628
blocked weights format 
Definition: mkldnn_types.h:259
blocked weights format 
Definition: mkldnn_types.h:353
int r
Definition: mkldnn_types.h:589
4D weights tensor with physical layout iohw. 
Definition: mkldnn_types.h:193
A reorder primitive. 
Definition: mkldnn_types.h:412
blocked weights format 
Definition: mkldnn_types.h:337
blocked weights format 
Definition: mkldnn_types.h:297
An unspecified engine. 
Definition: mkldnn_types.h:997
blocked weights format 
Definition: mkldnn_types.h:313
blocked weights format 
Definition: mkldnn_types.h:338
int oc2_block
Definition: mkldnn_types.h:596
blocked weights format 
Definition: mkldnn_types.h:327
mkldnn_alg_kind_t
Kinds of algorithms. 
Definition: mkldnn_types.h:442
int mkldnn_dims_t[TENSOR_MAX_DIMS]
A type to describe tensor dimensions. 
Definition: mkldnn_types.h:552
inner product descriptor 
Definition: mkldnn_types.h:1174
mkldnn_memory_desc_t bias_desc
Bias memory descriptor. 
Definition: mkldnn_types.h:897
A pooling primitive. 
Definition: mkldnn_types.h:430
weights memory primitive descriptor desc 
Definition: mkldnn_types.h:1183
output memory primitive desc 
Definition: mkldnn_types.h:1180
mkldnn_memory_desc_t data_desc
Source and destination memory descriptor. 
Definition: mkldnn_types.h:834
5D weights tensor with physical layout dhwio, used in TensorFlow. 
Definition: mkldnn_types.h:199
blocked weights format 
Definition: mkldnn_types.h:287
Forward data propagation (alias for mkldnn_forward_training) 
Definition: mkldnn_types.h:391
3D RNN data tensor in the format (batch, seq_length, input channels). 
Definition: mkldnn_types.h:219
lrn descriptor 
Definition: mkldnn_types.h:1172
struct mkldnn_primitive_desc * mkldnn_primitive_desc_t
A primitive descriptor handle. 
Definition: mkldnn_types.h:1040
workspace memory primitive desc 
Definition: mkldnn_types.h:1187
mkldnn_memory_desc_t diff_weights_desc
Weights gradient memory descriptor. 
Definition: mkldnn_types.h:693
blocked weights format 
Definition: mkldnn_types.h:264
mkldnn_alg_kind_t alg_kind
The kind of the convolution algorithm. 
Definition: mkldnn_types.h:685
blocked weights format 
Definition: mkldnn_types.h:302
weights format with additional buffer size equal to the number of output channels and containing the ...
Definition: mkldnn_types.h:274
int n_parts
Definition: mkldnn_types.h:614
weights grad. 
Definition: mkldnn_types.h:1184
mkldnn_memory_desc_t diff_dst_layer_desc
Destination gradient layer memory descriptor. 
Definition: mkldnn_types.h:984
4D data tensor with the physical layout nchw, used in Caffe. 
Definition: mkldnn_types.h:157
mkldnn_primitive_kind_t primitive_kind
The kind of primitive. 
Definition: mkldnn_types.h:791
mkldnn_memory_desc_t diff_weights_iter_desc
Weights gradient iter memory descriptor. 
Definition: mkldnn_types.h:980
mkldnn_primitive_kind_t primitive_kind
The kind of primitive. 
Definition: mkldnn_types.h:883
primitive kind 
Definition: mkldnn_types.h:1150
blocked data format 
Definition: mkldnn_types.h:250
mkldnn_memory_desc_t diff_bias_desc
Bias gradient memory descriptor. 
Definition: mkldnn_types.h:899
mkldnn_dims_t block_dims
Block size for each of the dimensions. 
Definition: mkldnn_types.h:561
blocked weights format 
Definition: mkldnn_types.h:285
struct mkldnn_primitive_attr * mkldnn_primitive_attr_t
A primitive descriptor attributes handle that controls primitive behavior. 
Definition: mkldnn_types.h:1061
An opaque structure to describe a primitive descriptor iterator . 
Tensor of weights for 4x3 convolution. 
Definition: mkldnn_types.h:583