17 #ifndef MKLDNN_TYPES_H
18 #define MKLDNN_TYPES_H
24 #ifndef DOXYGEN_SHOULD_SKIP_THIS
607 #define TENSOR_MAX_DIMS 12
622 mkldnn_strides_t strides[2];
667 #define MKLDNN_RNN_MAX_N_PARTS 4
767 mkldnn_dims_t padding[2];
872 mkldnn_dims_t padding[2];
mkldnn_data_type_t accum_data_type
The accumulator data type.
Definition: mkldnn_types.h:963
LRN within a single channel.
Definition: mkldnn_types.h:542
struct mkldnn_post_ops * mkldnn_post_ops_t
A post operation chain handle.
Definition: mkldnn_types.h:1146
mkldnn_padding_kind_t padding_kind
The kind of padding to use.
Definition: mkldnn_types.h:874
size_t size
Definition: mkldnn_types.h:656
A descriptor of a Local Response Normalization (LRN) operation.
Definition: mkldnn_types.h:880
blocked weights format
Definition: mkldnn_types.h:332
blocked weights format
Definition: mkldnn_types.h:337
op descriptor
Definition: mkldnn_types.h:1222
blocked weights format with additional buffer with size equal to the number of output channels multip...
Definition: mkldnn_types.h:374
blocked weights format
Definition: mkldnn_types.h:316
blocked weights format
Definition: mkldnn_types.h:412
A Softmax primitive.
Definition: mkldnn_types.h:486
number of outputs expected
Definition: mkldnn_types.h:1211
blocked weights format
Definition: mkldnn_types.h:415
int alpha
Definition: mkldnn_types.h:648
mkldnn_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: mkldnn_types.h:1040
int minor
Definition: mkldnn_types.h:41
mkldnn_rnn_packed_memory_format_t format
Definition: mkldnn_types.h:671
mkldnn_dims_t dilates
Convolution dilates in each spatial dimension.
Definition: mkldnn_types.h:763
mkldnn_status_t
Status values returned by Intel(R) MKL-DNN functions.
Definition: mkldnn_types.h:47
A descriptor of a convolution operation.
Definition: mkldnn_types.h:733
mkldnn_rnn_direction_t direction
The direction of RNN primitive execution.
Definition: mkldnn_types.h:1016
The operation failed and should be retried.
Definition: mkldnn_types.h:53
blocked weights format
Definition: mkldnn_types.h:279
mkldnn_memory_desc_t dst_layer_desc
Destination layer memory descriptor.
Definition: mkldnn_types.h:1028
int ic_block
Definition: mkldnn_types.h:651
4D RNN bias tensor in the format (num_layers, num_directions, num_gates, output_channels).
Definition: mkldnn_types.h:253
4D data tensor with the physical layout chwn, used in Neon.
Definition: mkldnn_types.h:171
The operation failed because of incorrect function arguments.
Definition: mkldnn_types.h:55
Forward data propagation (alias for mkldnn_forward_inference)
Definition: mkldnn_types.h:447
Definition: mkldnn_types.h:662
An opaque structure to describe an engine.
Backward data propagation.
Definition: mkldnn_types.h:453
blocked weights format
Definition: mkldnn_types.h:310
blocked weights format
Definition: mkldnn_types.h:383
Undefined memory format, used for empty memory descriptors.
Definition: mkldnn_types.h:145
float alpha
alpha is a negative slope parameter (used only if (flags & mkldnn_rnn_cell_with_relu) != 0) ...
Definition: mkldnn_types.h:984
#define TENSOR_MAX_DIMS
Maximum number of dimensions a tensor can have.
Definition: mkldnn_types.h:607
4D weights tensor with physical layout oihw, used in Caffe.
Definition: mkldnn_types.h:192
A descriptor of a Softmax operation.
Definition: mkldnn_types.h:830
blocked weights format
Definition: mkldnn_types.h:416
mkldnn_padding_kind_t padding_kind
The kind of padding to use.
Definition: mkldnn_types.h:769
blocked weights format
Definition: mkldnn_types.h:417
int oc_block
Definition: mkldnn_types.h:652
blocked data format
Definition: mkldnn_types.h:262
A descriptor of an inner product operation.
Definition: mkldnn_types.h:938
3D RNN data tensor in the format (seq_length, batch, input channels).
Definition: mkldnn_types.h:229
An opaque structure for a chain of post operations.
An opaque structure to describe a primitive descriptor.
batch normalization descriptor
Definition: mkldnn_types.h:1231
mkldnn_rnn_direction_t
A direction of RNN primitive execution.
Definition: mkldnn_types.h:991
mkldnn_memory_desc_t diff_data_scaleshift_desc
Definition: mkldnn_types.h:925
A convolution primitive.
Definition: mkldnn_types.h:480
mkldnn_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: mkldnn_types.h:949
size_t offset_compensation
Definition: mkldnn_types.h:676
int axis
axis for shuffling.
Definition: mkldnn_types.h:789
struct mkldnn_stream * mkldnn_stream_t
An execution stream handle.
Definition: mkldnn_types.h:1267
blocked weights format with additional buffer with size equal to the number of output channels and co...
Definition: mkldnn_types.h:287
blocked data format
Definition: mkldnn_types.h:263
mkldnn_prop_kind_t prop_kind
The kind of propagation.
Definition: mkldnn_types.h:836
blocked weights format
Definition: mkldnn_types.h:408
struct mkldnn_primitive_desc_iterator * mkldnn_primitive_desc_iterator_t
A primitive descriptor iterator handle.
Definition: mkldnn_types.h:1081
blocked weights format
Definition: mkldnn_types.h:323
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:781
Undefined primitive (XXX: why do we have it?).
Definition: mkldnn_types.h:464
An inner product primitive.
Definition: mkldnn_types.h:494
Packed weights format used in RNN.
Definition: mkldnn_types.h:421
Round down.
Definition: mkldnn_types.h:90
4D grouped weights tensor with the physical layout goiw.
Definition: mkldnn_types.h:210
mkldnn_memory_desc_t dst_desc
Destination memory descriptor.
Definition: mkldnn_types.h:757
mkldnn_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: mkldnn_types.h:860
Tensors of weights for 2x3 winograd convolutions.
Definition: mkldnn_types.h:637
Definition: mkldnn_types.h:538
mkldnn_memory_desc_t diff_desc
Source and Destination of gradient memory descriptor.
Definition: mkldnn_types.h:840
size_t output_index
Desired output index.
Definition: mkldnn_types.h:1169
mkldnn_data_type_t data_type
Data type of the tensor elements.
Definition: mkldnn_types.h:715
mkldnn_rnn_cell_flags_t
Flags for RNN cell.
Definition: mkldnn_types.h:967
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:627
float lrn_beta
LRN beta parameter.
Definition: mkldnn_types.h:901
32-bit signed integer.
Definition: mkldnn_types.h:76
Max pooling.
Definition: mkldnn_types.h:533
int patch
Definition: mkldnn_types.h:42
blocked weights format
Definition: mkldnn_types.h:300
blocked weights format
Definition: mkldnn_types.h:322
execution engine
Definition: mkldnn_types.h:1207
void * mkldnn_op_desc_t
A pointer to any of the operation descriptors.
Definition: mkldnn_types.h:684
mkldnn_data_type_t accum_data_type
The accumulator data type.
Definition: mkldnn_types.h:771
blocked weights format
Definition: mkldnn_types.h:307
mkldnn_prop_kind_t prop_kind
The kind of propagation.
Definition: mkldnn_types.h:887
mkldnn_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: mkldnn_types.h:864
Definition: mkldnn_types.h:969
mkldnn_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: mkldnn_types.h:810
float lrn_alpha
LRN alpha parameter.
Definition: mkldnn_types.h:899
struct mkldnn_primitive * mkldnn_primitive_t
A primitive handle.
Definition: mkldnn_types.h:1160
input memory primitive desc
Definition: mkldnn_types.h:1237
blocked weights format
Definition: mkldnn_types.h:325
ptrdiff_t mkldnn_strides_t[TENSOR_MAX_DIMS]
A type to describe strides within a tensor.
Definition: mkldnn_types.h:612
5D grouped weights tensor with the physical layout goihw, used in Caffe.
Definition: mkldnn_types.h:214
const_mkldnn_primitive_t primitive
Primitive to specify the output for.
Definition: mkldnn_types.h:1167
mkldnn_prop_kind_t prop_kind
The kind of propagation.
Definition: mkldnn_types.h:853
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:897
blocked weights format
Definition: mkldnn_types.h:336
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:630
A descriptor of a element-wise operation.
Definition: mkldnn_types.h:795
rnn descriptor
Definition: mkldnn_types.h:1233
An element-wise primitive.
Definition: mkldnn_types.h:484
float beta
Definition: mkldnn_types.h:826
mkldnn_memory_desc_t src_desc
Source memory descriptor.
Definition: mkldnn_types.h:947
blocked weights format
Definition: mkldnn_types.h:315
destination grad.
Definition: mkldnn_types.h:1244
mkldnn_alg_kind_t activation_kind
Activation function used.
Definition: mkldnn_types.h:979
blocked weights format
Definition: mkldnn_types.h:328
A descriptor for an RNN operation.
Definition: mkldnn_types.h:1006
eltwise descriptor
Definition: mkldnn_types.h:1227
A memory primitive.
Definition: mkldnn_types.h:466
float clipping
clipping parameter (used only if (flags & mkldnn_rnn_cell_with_clipping) != 0)
Definition: mkldnn_types.h:987
blocked weights format
Definition: mkldnn_types.h:297
blocked weights format
Definition: mkldnn_types.h:309
struct mkldnn_primitive_desc * const_mkldnn_primitive_desc_t
A constant primitive descriptor handle.
Definition: mkldnn_types.h:1101
mkldnn_memory_desc_t bias_desc
Bias memory descriptor.
Definition: mkldnn_types.h:753
Eltwise: soft_relu.
Definition: mkldnn_types.h:529
mkldnn_wino_memory_format_t
Definition: mkldnn_types.h:633
The operation failed due to an out-of-memory condition.
Definition: mkldnn_types.h:51
RNN cell.
Definition: mkldnn_types.h:544
blocked weights format
Definition: mkldnn_types.h:344
Backward weights propagation.
Definition: mkldnn_types.h:455
blocked weights format
Definition: mkldnn_types.h:411
mkldnn_memory_desc_t weights_iter_desc
Weights iteration memory descriptor.
Definition: mkldnn_types.h:1024
stub
Definition: mkldnn_types.h:1221
int ic2_block
Definition: mkldnn_types.h:653
32-bit/single-precision floating point.
Definition: mkldnn_types.h:74
mkldnn_prop_kind_t prop_kind
The kind of propagation.
Definition: mkldnn_types.h:802
blocked weights format
Definition: mkldnn_types.h:275
blocked data format
Definition: mkldnn_types.h:260
struct mkldnn_primitive_attr * const_mkldnn_primitive_attr_t
A constant primitive descriptor attributes handle.
Definition: mkldnn_types.h:1122
struct mkldnn_stream * const_mkldnn_stream_t
A constant execution stream handle.
Definition: mkldnn_types.h:1269
2D weights tensor with physical layout oi.
Definition: mkldnn_types.h:180
Just a sentinel, not real memory format.
Definition: mkldnn_types.h:425
Memory descriptor.
Definition: mkldnn_types.h:692
mkldnn_dims_t kernel
Pooling kernel spatial dimensions.
Definition: mkldnn_types.h:868
mkldnn_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: mkldnn_types.h:916
mkldnn_convolution_desc_t mkldnn_deconvolution_desc_t
A descriptor of a deconvolution operation.
Definition: mkldnn_types.h:775
mkldnn_batch_normalization_flag_t
Flags for batch-normalization primititve.
Definition: mkldnn_types.h:561
pooling descriptor
Definition: mkldnn_types.h:1229
mkldnn_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: mkldnn_types.h:894
mkldnn_alg_kind_t alg_kind
The kind of pooling algorithm.
Definition: mkldnn_types.h:856
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:736
blocked weights format
Definition: mkldnn_types.h:274
blocked data format
Definition: mkldnn_types.h:264
mkldnn_memory_desc_t dst_desc
Destination memory descriptor.
Definition: mkldnn_types.h:959
3D weights tensor with physical layout wio.
Definition: mkldnn_types.h:189
mkldnn_memory_desc_t weights_layer_desc
Weights layer memory descriptor.
Definition: mkldnn_types.h:1022
blocked weights format
Definition: mkldnn_types.h:393
mkldnn_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: mkldnn_types.h:755
blocked weights format
Definition: mkldnn_types.h:343
unsigned int flags
RNN cell flags.
Definition: mkldnn_types.h:981
3D data tensor with the physical layout ncw.
Definition: mkldnn_types.h:159
blocked weights format
Definition: mkldnn_types.h:313
The operation was successful.
Definition: mkldnn_types.h:49
mkldnn_memory_desc_t dst_iter_desc
Destination iter memory descriptor.
Definition: mkldnn_types.h:1030
blocked weights format with additional buffer with size equal to the number of groups and containing ...
Definition: mkldnn_types.h:403
blocked weights format
Definition: mkldnn_types.h:367
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:883
blocked weights format
Definition: mkldnn_types.h:381
mkldnn_memory_desc_t src_iter_desc
Source iteration memory descriptor.
Definition: mkldnn_types.h:1020
blocked weights format
Definition: mkldnn_types.h:409
Backward propagation (with respect to all parameters.
Definition: mkldnn_types.h:451
5D data tensor with the physical layout ndhwc, used in TensorFlow.
Definition: mkldnn_types.h:177
softmax descriptor
Definition: mkldnn_types.h:1228
mkldnn_round_mode_t
Rounding mode.
Definition: mkldnn_types.h:86
A deconvolution primitive.
Definition: mkldnn_types.h:482
mkldnn_memory_desc_t data_scaleshift_desc
Scale and shift data and gradient memory descriptors.
Definition: mkldnn_types.h:924
Use global statistics.
Definition: mkldnn_types.h:574
blocked weights format
Definition: mkldnn_types.h:314
no query
Definition: mkldnn_types.h:1205
blocked weights format
Definition: mkldnn_types.h:395
blocked weights format
Definition: mkldnn_types.h:330
mkldnn_memory_desc_t mean_desc
Mean and variance data memory descriptors.
Definition: mkldnn_types.h:930
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:910
8-bit unsigned integer.
Definition: mkldnn_types.h:82
blocked weights format
Definition: mkldnn_types.h:407
mkldnn_alg_kind_t alg_kind
LRN algorithm.
Definition: mkldnn_types.h:890
Average pooling include padding.
Definition: mkldnn_types.h:535
Unspecified format.
Definition: mkldnn_types.h:148
mkldnn_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: mkldnn_types.h:747
destination memory primitive desc
Definition: mkldnn_types.h:1243
5D RNN weights tensor in the format (num_layers, num_directions, input_channels, num_gates, output_channels).
Definition: mkldnn_types.h:239
GRU cell with linear before reset.
Definition: mkldnn_types.h:557
Local response normalization (LRN) across multiple channels.
Definition: mkldnn_types.h:540
blocked weights format
Definition: mkldnn_types.h:296
GRU cell.
Definition: mkldnn_types.h:548
Eager stream.
Definition: mkldnn_types.h:1258
implementation name
Definition: mkldnn_types.h:1218
3D weights tensor with physical layout oiw.
Definition: mkldnn_types.h:186
Eltwise: parametric exponential linear unit (elu)
Definition: mkldnn_types.h:517
mkldnn_dims_t padding_dims
Size of the data including padding in each dimension.
Definition: mkldnn_types.h:624
Eltwise: ReLU.
Definition: mkldnn_types.h:513
1D data tensor.
Definition: mkldnn_types.h:154
float lrn_k
LRN k parameter.
Definition: mkldnn_types.h:903
struct mkldnn_primitive_desc_iterator * const_mkldnn_primitive_desc_iterator_t
A constant primitive descriptor iterator handle.
Definition: mkldnn_types.h:1085
4D weights tensor with physical layout ihwo.
Definition: mkldnn_types.h:198
mkldnn_memory_format_t
Memory format specification.
Definition: mkldnn_types.h:143
Eltwise: square.
Definition: mkldnn_types.h:519
mkldnn_prop_kind_t prop_kind
The kind of propagation.
Definition: mkldnn_types.h:945
mkldnn_wino_desc_t wino_desc
Tensor of weights for integer 8bit winograd convolution.
Definition: mkldnn_types.h:723
mkldnn_data_type_t accum_data_type
The accumulator data type.
Definition: mkldnn_types.h:876
int n
Definition: mkldnn_types.h:673
4D data tensor with the physical layout nhwc, used in TensorFlow.
Definition: mkldnn_types.h:168
Description of tensor of packed weights for rnn.
Definition: mkldnn_types.h:670
Backward bias propagation.
Definition: mkldnn_types.h:457
blocked weights format
Definition: mkldnn_types.h:404
Use scale and shift parameters.
Definition: mkldnn_types.h:587
int group_size
number of groups in group convolution
Definition: mkldnn_types.h:791
weights format with additional buffer size equal to the number of output channels multiplied by numbe...
Definition: mkldnn_types.h:365
mkldnn_memory_desc_t weights_desc
Weights memory descriptor.
Definition: mkldnn_types.h:749
blocked weights format
Definition: mkldnn_types.h:295
mkldnn_rnn_cell_desc_t cell_desc
The RNN cell desc.
Definition: mkldnn_types.h:1014
blocked weights format
Definition: mkldnn_types.h:382
A descriptor of a shuffle operation.
Definition: mkldnn_types.h:778
Definition: mkldnn_types.h:1001
struct mkldnn_primitive * const_mkldnn_primitive_t
A constant primitive handle.
Definition: mkldnn_types.h:1162
mkldnn_memory_desc_t data_desc
Source and destination memory descriptor, and source and destination gradient memory descriptor...
Definition: mkldnn_types.h:787
mkldnn_rnn_packed_memory_format_t
Definition: mkldnn_types.h:659
blocked weights format
Definition: mkldnn_types.h:398
blocked weights format
Definition: mkldnn_types.h:339
Undefined memory format, used for empty memory descriptors.
Definition: mkldnn_types.h:635
int ndims
Number of dimensions.
Definition: mkldnn_types.h:697
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:695
blocked weights format with additional buffer with size equal to the number of groups and containing ...
Definition: mkldnn_types.h:358
5D grouped weights tensor with the physical layout giohw.
Definition: mkldnn_types.h:221
An opaque structure to describe an execution stream.
Undefined propagation type.
Definition: mkldnn_types.h:438
mkldnn_blocking_desc_t blocking
Description of the data layout for memory formats that use blocking.
Definition: mkldnn_types.h:721
5D data tensor with the physical layout ncdhw.
Definition: mkldnn_types.h:174
5D RNN states tensor in the format (num_layers, num_directions, num_states, batch, state channels).
Definition: mkldnn_types.h:232
mkldnn_dims_t dims
Dimensions in the following order:
Definition: mkldnn_types.h:713
A rnn primitive.
Definition: mkldnn_types.h:496
mkldnn_rnn_packed_desc_t rnn_packed_desc
Tensor of packed weights for RNN.
Definition: mkldnn_types.h:725
mkldnn_dims_t strides
Convolution strides in each spatial dimension.
Definition: mkldnn_types.h:761
blocked weights format
Definition: mkldnn_types.h:324
blocked weights format
Definition: mkldnn_types.h:270
mkldnn_prop_kind_t
Kinds of propagation.
Definition: mkldnn_types.h:435
CPU engine.
Definition: mkldnn_types.h:1057
mkldnn_memory_desc_t bias_desc
Bias memory descriptor.
Definition: mkldnn_types.h:1026
Eltwise: square root.
Definition: mkldnn_types.h:523
mkldnn_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: mkldnn_types.h:838
mkldnn_memory_format_t format
Memory format.
Definition: mkldnn_types.h:717
blocked weights format
Definition: mkldnn_types.h:277
mkldnn_stream_kind_t
Kinds of streams.
Definition: mkldnn_types.h:1254
int major
Definition: mkldnn_types.h:40
mkldnn_memory_desc_t src_desc
Source memory descriptor.
Definition: mkldnn_types.h:745
4D weights tensor with physical layout hwio, used in TensorFlow.
Definition: mkldnn_types.h:195
A wrapper structure to specify a particular output of a primitive.
Definition: mkldnn_types.h:1165
Winograd convolution.
Definition: mkldnn_types.h:505
Eltwise: linear.
Definition: mkldnn_types.h:525
mkldnn_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: mkldnn_types.h:918
Eltwise: logistic.
Definition: mkldnn_types.h:531
Direct convolution.
Definition: mkldnn_types.h:503
Primitive iterator passed over last primitive descriptor.
Definition: mkldnn_types.h:62
size_t size
Definition: mkldnn_types.h:677
source gradient memory primitive desc
Definition: mkldnn_types.h:1240
mkldnn_alg_kind_t cell_kind
RNN cell kind.
Definition: mkldnn_types.h:976
Definition: mkldnn_types.h:993
An opaque structure for primitive descriptor attributes.
mkldnn_prop_kind_t prop_kind
The kind of propagation.
Definition: mkldnn_types.h:1012
int oc
Definition: mkldnn_types.h:650
blocked data format
Definition: mkldnn_types.h:266
blocked weights format
Definition: mkldnn_types.h:329
float batch_norm_epsilon
Batch normalization epsilon parameter.
Definition: mkldnn_types.h:933
runtime estimation (seconds)
Definition: mkldnn_types.h:1213
blocked weights format
Definition: mkldnn_types.h:397
A (in-place) concat primitive.
Definition: mkldnn_types.h:476
mkldnn_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: mkldnn_types.h:812
blocked weights format
Definition: mkldnn_types.h:298
LSTM cell.
Definition: mkldnn_types.h:546
blocked weights format
Definition: mkldnn_types.h:280
Definition: mkldnn_types.h:1002
mkldnn_memory_desc_t diff_weights_layer_desc
Weights gradient layer memory descriptor.
Definition: mkldnn_types.h:1036
Definition: mkldnn_types.h:638
mkldnn_wino_memory_format_t wino_format
Definition: mkldnn_types.h:646
Undefined data type, used for empty memory descriptors.
Definition: mkldnn_types.h:72
blocked weights format with additional buffer with size equal to the number of output channels multip...
Definition: mkldnn_types.h:353
16-bit signed integer.
Definition: mkldnn_types.h:78
A shuffle primitive.
Definition: mkldnn_types.h:472
blocked weights format with additional buffer with size equal to the number of output channels and co...
Definition: mkldnn_types.h:305
mkldnn_prop_kind_t prop_kind
The kind of propagation.
Definition: mkldnn_types.h:784
mkldnn_memory_desc_t src_layer_desc
Source layer memory descriptor.
Definition: mkldnn_types.h:1018
blocked weights format
Definition: mkldnn_types.h:312
blocked data format
Definition: mkldnn_types.h:258
blocked weights format
Definition: mkldnn_types.h:331
#define MKLDNN_RNN_MAX_N_PARTS
Definition: mkldnn_types.h:667
blocked weights format
Definition: mkldnn_types.h:321
A (out-of-place) concat primitive.
Definition: mkldnn_types.h:474
blocked weights format
Definition: mkldnn_types.h:340
Fuse with ReLU.
Definition: mkldnn_types.h:596
mkldnn_query_t
Primitive descriptor query specification.
Definition: mkldnn_types.h:1204
A descriptor of a Batch Normalization operation.
Definition: mkldnn_types.h:907
Definition: mkldnn_types.h:660
blocked weights format
Definition: mkldnn_types.h:354
blocked data format
Definition: mkldnn_types.h:265
blocked weights format
Definition: mkldnn_types.h:276
A sum primitive.
Definition: mkldnn_types.h:478
blocked weights format
Definition: mkldnn_types.h:342
blocked weights format
Definition: mkldnn_types.h:392
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:833
blocked weights format
Definition: mkldnn_types.h:282
unsigned flags
Definition: mkldnn_types.h:934
blocked weights format
Definition: mkldnn_types.h:281
blocked weights format
Definition: mkldnn_types.h:345
Convolution algorithm(either direct or Winograd) is chosen just in time.
Definition: mkldnn_types.h:507
blocked weights format
Definition: mkldnn_types.h:271
blocked weights format
Definition: mkldnn_types.h:399
2D weights tensor with physical layout io.
Definition: mkldnn_types.h:183
memory consumption – extra (scratch) memory, additional to all inputs and outputs memory (bytes) ...
Definition: mkldnn_types.h:1214
blocked weights format
Definition: mkldnn_types.h:335
An batch normalization primitive.
Definition: mkldnn_types.h:492
Definition: mkldnn_types.h:501
A descriptor of a pooling operation.
Definition: mkldnn_types.h:846
mkldnn_dims_t strides
Pooling kernel strides for spatial dimensions.
Definition: mkldnn_types.h:866
deconvolution descriptor
Definition: mkldnn_types.h:1225
blocked weights format
Definition: mkldnn_types.h:347
int softmax_axis
The axis along which to perform the softmax.
Definition: mkldnn_types.h:842
mkldnn_memory_desc_t diff_dst_iter_desc
Destination gradient iteration memory descriptor.
Definition: mkldnn_types.h:1044
8-bit signed integer.
Definition: mkldnn_types.h:80
The data in padding regions is zero.
Definition: mkldnn_types.h:431
mkldnn_memory_desc_t variance_desc
Definition: mkldnn_types.h:931
source memory primitive desc
Definition: mkldnn_types.h:1239
mkldnn_primitive_kind_t
Kinds of primitives.
Definition: mkldnn_types.h:462
Winograd deconvolution.
Definition: mkldnn_types.h:511
number of inputs expected
Definition: mkldnn_types.h:1210
Definition: mkldnn_types.h:661
struct mkldnn_engine * mkldnn_engine_t
An engine handle.
Definition: mkldnn_types.h:1064
mkldnn_memory_desc_t weights_desc
Weights memory descriptor.
Definition: mkldnn_types.h:951
An unspecified engine.
Definition: mkldnn_types.h:1256
A view primitive.
Definition: mkldnn_types.h:468
Description of tensor of weights for winograd 2x3 convolution.
Definition: mkldnn_types.h:645
blocked weights format
Definition: mkldnn_types.h:311
blocked data format
Definition: mkldnn_types.h:261
Average pooling exclude padding.
Definition: mkldnn_types.h:537
const char * hash
Definition: mkldnn_types.h:43
Definition: mkldnn_types.h:972
Forward data propagation (inference mode).
Definition: mkldnn_types.h:445
6D grouped weights tensor with the physical layout goidhw, used in Caffe.
Definition: mkldnn_types.h:225
5D weights tensor with physical layout iodhw, used in Caffe.
Definition: mkldnn_types.h:204
Definition: mkldnn_types.h:639
Direct deconvolution.
Definition: mkldnn_types.h:509
Eltwise: abs.
Definition: mkldnn_types.h:521
blocked weights format
Definition: mkldnn_types.h:369
mkldnn_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: mkldnn_types.h:759
blocked weights format
Definition: mkldnn_types.h:299
5D grouped weights tensor with the physical layout hwigo, used in TensorFlow.
Definition: mkldnn_types.h:218
stub
Definition: mkldnn_types.h:1236
int ic
Definition: mkldnn_types.h:649
blocked weights format
Definition: mkldnn_types.h:389
The operation failed because requested functionality is not implemented.
Definition: mkldnn_types.h:60
Eltwise: hyperbolic tangent non-linearity (tanh)
Definition: mkldnn_types.h:515
blocked weights format with additional buffer with size equal to the number of output channels and co...
Definition: mkldnn_types.h:388
mkldnn_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: mkldnn_types.h:961
blocked weights format
Definition: mkldnn_types.h:348
blocked weights format
Definition: mkldnn_types.h:346
2D data tensor.
Definition: mkldnn_types.h:156
float adj_scale
Definition: mkldnn_types.h:655
Primitive or engine failed on execution.
Definition: mkldnn_types.h:64
memory descriptor for memory and view
Definition: mkldnn_types.h:1223
An LRN primitive.
Definition: mkldnn_types.h:490
Definition: mkldnn_types.h:998
mkldnn_padding_kind_t
Kinds of padding.
Definition: mkldnn_types.h:429
mkldnn_memory_desc_t dst_desc
Destination memory descriptor.
Definition: mkldnn_types.h:862
Lazy stream.
Definition: mkldnn_types.h:1260
blocked weights format
Definition: mkldnn_types.h:394
blocked weights format
Definition: mkldnn_types.h:273
mkldnn_memory_desc_t diff_src_iter_desc
Source gradient iter memory descriptor.
Definition: mkldnn_types.h:1034
struct mkldnn_post_ops * const_mkldnn_post_ops_t
A constant post operation chain handle.
Definition: mkldnn_types.h:1149
5D RNN weights tensor in the format (num_layers, num_directions, num_gates, output_channels, input_channels).
Definition: mkldnn_types.h:246
blocked weights format
Definition: mkldnn_types.h:338
shuffle descriptor
Definition: mkldnn_types.h:1226
Forward data propagation (training mode).
Definition: mkldnn_types.h:441
3D data tensor with the physical layout nwc.
Definition: mkldnn_types.h:162
The operation failed because a primitive was not ready for execution.
Definition: mkldnn_types.h:57
Intel(R) MKL-DNN Version type.
Definition: mkldnn_types.h:39
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:152
mkldnn_data_type_t
Data type specification.
Definition: mkldnn_types.h:70
convolution descriptor
Definition: mkldnn_types.h:1224
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:1009
mkldnn_memory_desc_t src_desc
Source memory descriptor.
Definition: mkldnn_types.h:858
mkldnn_prop_kind_t prop_kind
The kind of propagation.
Definition: mkldnn_types.h:914
blocked weights format
Definition: mkldnn_types.h:326
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:798
mkldnn_alg_kind_t alg_kind
The kind of eltwise algorithm.
Definition: mkldnn_types.h:808
blocked weights format
Definition: mkldnn_types.h:317
mkldnn_memory_desc_t diff_src_layer_desc
Source gradient layer memory descriptor.
Definition: mkldnn_types.h:1032
Eltwise: bounded_relu.
Definition: mkldnn_types.h:527
mkldnn_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: mkldnn_types.h:953
Definition: mkldnn_types.h:995
mkldnn_prop_kind_t prop_kind
The kind of propagation.
Definition: mkldnn_types.h:740
mkldnn_engine_kind_t
Kinds of engines.
Definition: mkldnn_types.h:1053
Definition: mkldnn_types.h:968
Queried element is not required for given primitive.
Definition: mkldnn_types.h:66
blocked weights format
Definition: mkldnn_types.h:414
blocked weights format
Definition: mkldnn_types.h:366
Weights format used in 8bit Winograd convolution.
Definition: mkldnn_types.h:419
Generic description of blocked data layout for most memory formats.
Definition: mkldnn_types.h:617
Round nearest.
Definition: mkldnn_types.h:88
blocked weights format
Definition: mkldnn_types.h:413
const void * const_mkldnn_op_desc_t
A pointer to any of the operation descriptors (constant variant).
Definition: mkldnn_types.h:686
blocked weights format
Definition: mkldnn_types.h:272
blocked weights format
Definition: mkldnn_types.h:410
int r
Definition: mkldnn_types.h:647
4D weights tensor with physical layout iohw.
Definition: mkldnn_types.h:201
A reorder primitive.
Definition: mkldnn_types.h:470
blocked weights format
Definition: mkldnn_types.h:390
blocked weights format with additional buffer with size equal to the number of output channels multip...
Definition: mkldnn_types.h:380
blocked weights format
Definition: mkldnn_types.h:320
An unspecified engine.
Definition: mkldnn_types.h:1055
blocked weights format
Definition: mkldnn_types.h:341
blocked weights format
Definition: mkldnn_types.h:391
int oc2_block
Definition: mkldnn_types.h:654
blocked weights format
Definition: mkldnn_types.h:368
mkldnn_alg_kind_t
Kinds of algorithms.
Definition: mkldnn_types.h:500
int mkldnn_dims_t[TENSOR_MAX_DIMS]
A type to describe tensor dimensions.
Definition: mkldnn_types.h:610
inner product descriptor
Definition: mkldnn_types.h:1232
blocked weights format
Definition: mkldnn_types.h:375
mkldnn_memory_desc_t bias_desc
Bias memory descriptor.
Definition: mkldnn_types.h:955
A pooling primitive.
Definition: mkldnn_types.h:488
weights memory primitive descriptor desc
Definition: mkldnn_types.h:1241
output memory primitive desc
Definition: mkldnn_types.h:1238
blocked weights format
Definition: mkldnn_types.h:396
mkldnn_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: mkldnn_types.h:892
5D weights tensor with physical layout dhwio, used in TensorFlow.
Definition: mkldnn_types.h:207
blocked weights format
Definition: mkldnn_types.h:308
Forward data propagation (alias for mkldnn_forward_training)
Definition: mkldnn_types.h:449
3D RNN data tensor in the format (batch, seq_length, input channels).
Definition: mkldnn_types.h:227
lrn descriptor
Definition: mkldnn_types.h:1230
struct mkldnn_primitive_desc * mkldnn_primitive_desc_t
A primitive descriptor handle.
Definition: mkldnn_types.h:1098
workspace memory primitive desc
Definition: mkldnn_types.h:1245
mkldnn_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: mkldnn_types.h:751
blocked weights format
Definition: mkldnn_types.h:269
blocked weights format
Definition: mkldnn_types.h:278
mkldnn_alg_kind_t alg_kind
The kind of the convolution algorithm.
Definition: mkldnn_types.h:743
blocked weights format
Definition: mkldnn_types.h:327
weights format with additional buffer size equal to the number of output channels and containing the ...
Definition: mkldnn_types.h:294
int n_parts
Definition: mkldnn_types.h:672
weights grad.
Definition: mkldnn_types.h:1242
mkldnn_memory_desc_t diff_dst_layer_desc
Destination gradient layer memory descriptor.
Definition: mkldnn_types.h:1042
4D data tensor with the physical layout nchw, used in Caffe.
Definition: mkldnn_types.h:165
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:849
mkldnn_memory_desc_t diff_weights_iter_desc
Weights gradient iter memory descriptor.
Definition: mkldnn_types.h:1038
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:941
primitive kind
Definition: mkldnn_types.h:1208
blocked data format
Definition: mkldnn_types.h:259
mkldnn_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: mkldnn_types.h:957
mkldnn_dims_t block_dims
Block size for each of the dimensions.
Definition: mkldnn_types.h:619
blocked weights format
Definition: mkldnn_types.h:306
struct mkldnn_primitive_attr * mkldnn_primitive_attr_t
A primitive descriptor attributes handle that controls primitive behavior.
Definition: mkldnn_types.h:1119
An opaque structure to describe a primitive descriptor iterator.
Tensor of weights for 4x3 convolution.
Definition: mkldnn_types.h:641