17 #ifndef MKLDNN_TYPES_H 18 #define MKLDNN_TYPES_H 24 #ifndef DOXYGEN_SHOULD_SKIP_THIS 420 #define TENSOR_MAX_DIMS 12 433 mkldnn_strides_t strides[2];
514 mkldnn_dims_t padding[2];
604 mkldnn_dims_t padding[2];
mkldnn_data_type_t accum_data_type
The accumulator data type.
Definition: mkldnn_types.h:695
LRN within a single channel.
Definition: mkldnn_types.h:361
struct mkldnn_post_ops * mkldnn_post_ops_t
A post operation chain handle.
Definition: mkldnn_types.h:809
mkldnn_padding_kind_t padding_kind
The kind of padding to use.
Definition: mkldnn_types.h:606
A descriptor of a Local Response Normalization (LRN) operation.
Definition: mkldnn_types.h:612
4D weights tensor in the format (output channels, width, height, input channels) with output channels...
Definition: mkldnn_types.h:188
A Softmax primitive.
Definition: mkldnn_types.h:312
number of outputs expected
Definition: mkldnn_types.h:873
mkldnn_dims_t dilates
Convolution dilates in each spatial dimension.
Definition: mkldnn_types.h:510
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:480
The operation failed and should be retried.
Definition: mkldnn_types.h:45
4D data tensor in the chwn format typically used in Neon.
Definition: mkldnn_types.h:126
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:275
An opaque structure to describe an engine.
Backward data propagation.
Definition: mkldnn_types.h:281
4D weights tensor in the oihw format with both input and output channels data laid out in memory in 1...
Definition: mkldnn_types.h:172
Undefined memory format, used for empty memory descriptors.
Definition: mkldnn_types.h:109
#define TENSOR_MAX_DIMS
Maximum number of dimensions a tensor can have.
Definition: mkldnn_types.h:420
4D weights tensor in the format (input channels, output channels, width, height). ...
Definition: mkldnn_types.h:139
A descriptor of a Softmax operation.
Definition: mkldnn_types.h:564
mkldnn_padding_kind_t padding_kind
The kind of padding to use.
Definition: mkldnn_types.h:516
4D data tensor in the nchw format with channels data laid out in memory in 8-element blocks...
Definition: mkldnn_types.h:129
A descriptor of an inner product operation.
Definition: mkldnn_types.h:670
An opaque structure for a chain of post operations.
An opaque structure to describe a primitive descriptor .
batch normalization descriptor
Definition: mkldnn_types.h:891
mkldnn_memory_desc_t diff_data_scaleshift_desc
Definition: mkldnn_types.h:657
A convolution primitive.
Definition: mkldnn_types.h:306
mkldnn_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: mkldnn_types.h:681
struct mkldnn_stream * mkldnn_stream_t
An execution stream handle.
Definition: mkldnn_types.h:927
4D data tensor in the nchw format with channels data laid out in memory in 16-element blocks...
Definition: mkldnn_types.h:132
mkldnn_prop_kind_t prop_kind
The kind of propagation.
Definition: mkldnn_types.h:570
struct mkldnn_primitive_desc_iterator * mkldnn_primitive_desc_iterator_t
A primitive descriptor iterator handle.
Definition: mkldnn_types.h:744
Undefined primitive (XXX: why do we have it?).
Definition: mkldnn_types.h:292
An inner product primitive.
Definition: mkldnn_types.h:320
Round down.
Definition: mkldnn_types.h:82
convolution-relu descriptor
Definition: mkldnn_types.h:893
mkldnn_memory_desc_t dst_desc
Destination memory descriptor.
Definition: mkldnn_types.h:504
mkldnn_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: mkldnn_types.h:592
Definition: mkldnn_types.h:357
size_t output_index
Desired output index.
Definition: mkldnn_types.h:832
mkldnn_data_type_t data_type
Data type of the tensor elements.
Definition: mkldnn_types.h:466
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:438
float lrn_beta
LRN beta parameter.
Definition: mkldnn_types.h:633
32-bit signed integer.
Definition: mkldnn_types.h:68
Max pooling.
Definition: mkldnn_types.h:352
4D weights tensor in the oihw format with output channels data laid out in memory in 16-element block...
Definition: mkldnn_types.h:155
execution engine
Definition: mkldnn_types.h:869
void * mkldnn_op_desc_t
A pointer to any of the operation descriptors.
Definition: mkldnn_types.h:448
mkldnn_data_type_t accum_data_type
The accumulator data type.
Definition: mkldnn_types.h:518
4D weights tensor in the oihw format with input channels data laid out in memory in 16-element blocks...
Definition: mkldnn_types.h:163
mkldnn_prop_kind_t prop_kind
The kind of propagation.
Definition: mkldnn_types.h:619
mkldnn_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: mkldnn_types.h:596
mkldnn_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: mkldnn_types.h:537
A descriptor of a convolution followed by relu operation.
Definition: mkldnn_types.h:699
float lrn_alpha
LRN alpha parameter.
Definition: mkldnn_types.h:631
struct mkldnn_primitive * mkldnn_primitive_t
A primitive handle.
Definition: mkldnn_types.h:823
input memory primitive desc
Definition: mkldnn_types.h:897
ptrdiff_t mkldnn_strides_t[TENSOR_MAX_DIMS]
A type to describe strides within a tensor.
Definition: mkldnn_types.h:425
5D weights tensor in the oihw format with extra outer dimension for groups.
Definition: mkldnn_types.h:194
const_mkldnn_primitive_t primitive
Primitive to specify the output for.
Definition: mkldnn_types.h:830
mkldnn_prop_kind_t prop_kind
The kind of propagation.
Definition: mkldnn_types.h:585
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:629
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:441
A descriptor of a element-wise operation.
Definition: mkldnn_types.h:522
An element-wise primitive.
Definition: mkldnn_types.h:308
float beta
Definition: mkldnn_types.h:553
mkldnn_memory_desc_t src_desc
Source memory descriptor.
Definition: mkldnn_types.h:679
destination grad.
Definition: mkldnn_types.h:904
eltwise descriptor
Definition: mkldnn_types.h:886
A memory primitive.
Definition: mkldnn_types.h:294
4D weights tensor in the oihw format with both input and output channels data laid out in memory in 1...
Definition: mkldnn_types.h:169
mkldnn_memory_desc_t bias_desc
Bias memory descriptor.
Definition: mkldnn_types.h:500
Eltwise: soft_relu.
Definition: mkldnn_types.h:348
The operation failed due to an out-of-memory condition.
Definition: mkldnn_types.h:43
float negative_slope
ReLU scaling factor for negative values.
Definition: mkldnn_types.h:557
Backward weights propagation.
Definition: mkldnn_types.h:283
stub
Definition: mkldnn_types.h:883
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:529
const struct mkldnn_primitive_desc_iterator * const_mkldnn_primitive_desc_iterator_t
A constant primitive descriptor iterator handle.
Definition: mkldnn_types.h:748
2D weights tensor in the format (input channels, output channels).
Definition: mkldnn_types.h:134
Omit statistics.
Definition: mkldnn_types.h:400
Memory descriptor.
Definition: mkldnn_types.h:456
mkldnn_dims_t kernel
Pooling kernel spatial dimensions.
Definition: mkldnn_types.h:600
mkldnn_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: mkldnn_types.h:648
mkldnn_batch_normalization_flag_t
Flags for batch-normalization primititve.
Definition: mkldnn_types.h:365
pooling descriptor
Definition: mkldnn_types.h:889
mkldnn_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: mkldnn_types.h:626
mkldnn_alg_kind_t alg_kind
The kind of pooling algorithm.
Definition: mkldnn_types.h:588
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:483
mkldnn_memory_desc_t dst_desc
Destination memory descriptor.
Definition: mkldnn_types.h:691
mkldnn_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: mkldnn_types.h:502
4D weights tensor in the format (output channels, input channels, height, width) with output channels...
Definition: mkldnn_types.h:180
The operation was successful.
Definition: mkldnn_types.h:41
5D weights tensor in the blocked version of goihw format with both input and output channels data lai...
Definition: mkldnn_types.h:201
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:615
5D weights tensor in the oihw format with output channels data laid out in memory in 16-element block...
Definition: mkldnn_types.h:213
Backward propagation (with respect to all parameters.
Definition: mkldnn_types.h:279
softmax descriptor
Definition: mkldnn_types.h:888
mkldnn_round_mode_t
Rounding mode.
Definition: mkldnn_types.h:78
mkldnn_memory_desc_t data_scaleshift_desc
Scale and shift data and gradient memory descriptors.
Definition: mkldnn_types.h:656
Use global statistics.
Definition: mkldnn_types.h:378
4D weights tensor in the format (output channels, width, height, input channels) with output channels...
Definition: mkldnn_types.h:184
no query
Definition: mkldnn_types.h:867
5D weights tensor in the blocked version of goihw format with output channels data laid out in memory...
Definition: mkldnn_types.h:238
mkldnn_memory_desc_t mean_desc
Mean and variance data memory descriptors.
Definition: mkldnn_types.h:662
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:642
8-bit unsigned integer.
Definition: mkldnn_types.h:74
mkldnn_alg_kind_t alg_kind
LRN algorithm.
Definition: mkldnn_types.h:622
Average pooling include padding.
Definition: mkldnn_types.h:354
Unspecified format.
Definition: mkldnn_types.h:112
mkldnn_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: mkldnn_types.h:494
destination memory primitive desc
Definition: mkldnn_types.h:903
Local response normalization (LRN) across multiple channels.
Definition: mkldnn_types.h:359
4D weights tensor in the oihw format with input channels data laid out in memory in 16-element blocks...
Definition: mkldnn_types.h:253
Eager stream.
Definition: mkldnn_types.h:918
implementation name
Definition: mkldnn_types.h:880
Eltwise: parametric exponential linear unit (elu)
Definition: mkldnn_types.h:336
mkldnn_dims_t padding_dims
Size of the data including padding in each dimension.
Definition: mkldnn_types.h:435
Eltwise: ReLU.
Definition: mkldnn_types.h:332
1D data tensor.
Definition: mkldnn_types.h:118
float lrn_k
LRN k parameter.
Definition: mkldnn_types.h:635
4D weights tensor in the format (input channels, height, width, output channels). ...
Definition: mkldnn_types.h:142
mkldnn_memory_format_t
Memory format specification.
Definition: mkldnn_types.h:107
Eltwise: square.
Definition: mkldnn_types.h:338
mkldnn_prop_kind_t prop_kind
The kind of propagation.
Definition: mkldnn_types.h:677
mkldnn_data_type_t accum_data_type
The accumulator data type.
Definition: mkldnn_types.h:608
4D data tensor in the nhwc format typically used in TensorFlow.
Definition: mkldnn_types.h:124
Backward bias propagation.
Definition: mkldnn_types.h:285
5D weights tensor in the goihw format with both input and output channels data laid out in memory in ...
Definition: mkldnn_types.h:247
Use scale and shift parameters.
Definition: mkldnn_types.h:391
mkldnn_memory_desc_t weights_desc
Weights memory descriptor.
Definition: mkldnn_types.h:496
4D weights tensor in the oihw format with input channels data laid out in memory in 8-element blocks...
Definition: mkldnn_types.h:250
5D weights tensor in the oihw format with input channels data laid out in memory in 16-element blocks...
Definition: mkldnn_types.h:217
5D weights tensor in the blocked version of goihw format with group data laid out in memory in 8-elem...
Definition: mkldnn_types.h:244
int ndims
Number of dimensions.
Definition: mkldnn_types.h:461
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:459
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:785
A convolution primitive merged with relu.
Definition: mkldnn_types.h:322
Undefined propagation type.
Definition: mkldnn_types.h:266
mkldnn_blocking_desc_t blocking
Description of the data layout for memory formats that use blocking.
Definition: mkldnn_types.h:472
float negative_slope
Scaling factor for negative values, stored as float-precision but interpreted in a way specific to th...
Definition: mkldnn_types.h:707
mkldnn_dims_t dims
Dimensions in the following order: mini-batch, channel, spatial.
Definition: mkldnn_types.h:464
mkldnn_dims_t strides
Convolution strides in each spatial dimension.
Definition: mkldnn_types.h:508
mkldnn_prop_kind_t
Kinds of propagation.
Definition: mkldnn_types.h:263
CPU engine.
Definition: mkldnn_types.h:720
Eltwise: square root.
Definition: mkldnn_types.h:342
mkldnn_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: mkldnn_types.h:572
mkldnn_memory_format_t format
Memory format.
Definition: mkldnn_types.h:468
mkldnn_stream_kind_t
Kinds of streams.
Definition: mkldnn_types.h:914
mkldnn_memory_desc_t src_desc
Source memory descriptor.
Definition: mkldnn_types.h:492
4D weights tensor in the format (height, width, input channels, output channels). ...
Definition: mkldnn_types.h:145
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:702
A wrapper structure to specify a particular output of a primitive.
Definition: mkldnn_types.h:828
Winograd convolution.
Definition: mkldnn_types.h:330
A ReLU primitive,.
Definition: mkldnn_types.h:310
Eltwise: linear.
Definition: mkldnn_types.h:344
mkldnn_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: mkldnn_types.h:650
Eltwise: logistic.
Definition: mkldnn_types.h:350
Direct convolution.
Definition: mkldnn_types.h:328
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:825
source gradient memory primitive desc
Definition: mkldnn_types.h:900
An opaque structure for primitive descriptor attributes.
float batch_norm_epsilon
Batch normalization epsilon parameter.
Definition: mkldnn_types.h:665
runtime estimation (seconds)
Definition: mkldnn_types.h:875
5D weights tensor in the blocked version of goihw format with output channels data laid out in memory...
Definition: mkldnn_types.h:241
A (in-place) concat primitive.
Definition: mkldnn_types.h:302
mkldnn_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: mkldnn_types.h:539
4D weights tensor in the oihw format with both input and output channels data laid out in memory in 8...
Definition: mkldnn_types.h:148
Undefined data type, used for empty memory descriptors.
Definition: mkldnn_types.h:64
16-bit signed integer.
Definition: mkldnn_types.h:70
A (out-of-place) concat primitive.
Definition: mkldnn_types.h:300
Fuse with ReLU.
Definition: mkldnn_types.h:409
mkldnn_query_t
Primitive descriptor query specification.
Definition: mkldnn_types.h:866
A descriptor of a Batch Normalization operation.
Definition: mkldnn_types.h:639
const struct mkldnn_stream * const_mkldnn_stream_t
A constant execution stream handle.
Definition: mkldnn_types.h:929
A sum primitive.
Definition: mkldnn_types.h:304
5D weights tensor in the blocked version of goihw format with output channels data laid out in memory...
Definition: mkldnn_types.h:232
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:567
unsigned flags
Definition: mkldnn_types.h:666
2D weights tensor in the format (input channels, output channels).
Definition: mkldnn_types.h:136
memory consumption – extra (scratch) memory, additional to all inputs and outputs memory (bytes) ...
Definition: mkldnn_types.h:876
An batch normalization primitive.
Definition: mkldnn_types.h:318
A descriptor of a pooling operation.
Definition: mkldnn_types.h:578
mkldnn_dims_t strides
Pooling kernel strides for spatial dimensions.
Definition: mkldnn_types.h:598
int softmax_axis
The axis along which to perform the softmax.
Definition: mkldnn_types.h:574
8-bit signed integer.
Definition: mkldnn_types.h:72
The data in padding regions is zero.
Definition: mkldnn_types.h:259
mkldnn_memory_desc_t variance_desc
Definition: mkldnn_types.h:663
source memory primitive desc
Definition: mkldnn_types.h:899
mkldnn_primitive_kind_t
Kinds of primitives.
Definition: mkldnn_types.h:290
number of inputs expected
Definition: mkldnn_types.h:872
struct mkldnn_engine * mkldnn_engine_t
An engine handle.
Definition: mkldnn_types.h:727
mkldnn_memory_desc_t weights_desc
Weights memory descriptor.
Definition: mkldnn_types.h:683
An unspecified engine.
Definition: mkldnn_types.h:916
A view primitive.
Definition: mkldnn_types.h:296
4D weights tensor in the format (output channels, input channels, height, width) with output channels...
Definition: mkldnn_types.h:176
Average pooling exclude padding.
Definition: mkldnn_types.h:356
Forward data propagation (inference mode).
Definition: mkldnn_types.h:273
Eltwise: abs.
Definition: mkldnn_types.h:340
5D weights tensor in the oihw format with output channels data laid out in memory in 16-element block...
Definition: mkldnn_types.h:209
mkldnn_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: mkldnn_types.h:506
4D weights tensor in the oihw format with both input and output channels data laid out in memory in 1...
Definition: mkldnn_types.h:151
5D weights tensor in the hwio format with extra dimension for groups that comes after the output chan...
Definition: mkldnn_types.h:197
stub
Definition: mkldnn_types.h:896
5D weights tensor in the blocked version of goihw format with both input and output channels data lai...
Definition: mkldnn_types.h:221
The operation failed because requested functionality is not implemented.
Definition: mkldnn_types.h:52
Eltwise: hyperbolic tangent non-linearity (tanh)
Definition: mkldnn_types.h:334
mkldnn_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: mkldnn_types.h:693
2D data tensor.
Definition: mkldnn_types.h:120
Primitive or engine failed on execution.
Definition: mkldnn_types.h:56
memory descriptor for memory and view
Definition: mkldnn_types.h:884
const struct mkldnn_post_ops * const_mkldnn_post_ops_t
A constant post operation chain handle.
Definition: mkldnn_types.h:812
An LRN primitive.
Definition: mkldnn_types.h:316
mkldnn_padding_kind_t
Kinds of padding.
Definition: mkldnn_types.h:257
mkldnn_memory_desc_t dst_desc
Destination memory descriptor.
Definition: mkldnn_types.h:594
Lazy stream.
Definition: mkldnn_types.h:920
5D weights tensor in the blocked version of goihw format with output channels data laid out in memory...
Definition: mkldnn_types.h:235
const struct mkldnn_primitive_desc * const_mkldnn_primitive_desc_t
A constant primitive descriptor handle.
Definition: mkldnn_types.h:764
Forward data propagation (training mode).
Definition: mkldnn_types.h:269
mkldnn_convolution_desc_t convolution_desc
A descriptor of a convolution operation.
Definition: mkldnn_types.h:704
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:116
mkldnn_data_type_t
Data type specification.
Definition: mkldnn_types.h:62
convolution descriptor
Definition: mkldnn_types.h:885
mkldnn_eltwise_desc_t mkldnn_relu_desc_t
Definition: mkldnn_types.h:561
mkldnn_memory_desc_t src_desc
Source memory descriptor.
Definition: mkldnn_types.h:590
mkldnn_prop_kind_t prop_kind
The kind of propagation.
Definition: mkldnn_types.h:646
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:525
mkldnn_alg_kind_t alg_kind
The kind of eltwise algorithm.
Definition: mkldnn_types.h:535
4D weights tensor in the oihw format with both input and output channels data laid out in memory in 1...
Definition: mkldnn_types.h:191
Eltwise: bounded_relu.
Definition: mkldnn_types.h:346
mkldnn_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: mkldnn_types.h:685
mkldnn_prop_kind_t prop_kind
The kind of propagation.
Definition: mkldnn_types.h:487
mkldnn_engine_kind_t
Kinds of engines.
Definition: mkldnn_types.h:716
Queried element is not required for given primitive.
Definition: mkldnn_types.h:58
Generic description of blocked data layout for most memory formats.
Definition: mkldnn_types.h:428
Round nearest.
Definition: mkldnn_types.h:80
const void * const_mkldnn_op_desc_t
A pointer to any of the operation descriptors (constant variant).
Definition: mkldnn_types.h:450
A reorder primitive.
Definition: mkldnn_types.h:298
5D weights tensor in the blocked version of goihw format with both input and output channels data lai...
Definition: mkldnn_types.h:225
An unspecified engine.
Definition: mkldnn_types.h:718
5D weights tensor in the blocked version of goihw format with both input and output channels data lai...
Definition: mkldnn_types.h:229
5D weights tensor in the blocked version of goihw format with both input and output channels data lai...
Definition: mkldnn_types.h:205
mkldnn_alg_kind_t
Kinds of algorithms.
Definition: mkldnn_types.h:326
int mkldnn_dims_t[TENSOR_MAX_DIMS]
A type to describe tensor dimensions.
Definition: mkldnn_types.h:423
inner product descriptor
Definition: mkldnn_types.h:892
mkldnn_memory_desc_t bias_desc
Bias memory descriptor.
Definition: mkldnn_types.h:687
A pooling primitive.
Definition: mkldnn_types.h:314
weights memory primitive descriptor desc
Definition: mkldnn_types.h:901
output memory primitive desc
Definition: mkldnn_types.h:898
mkldnn_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: mkldnn_types.h:624
4D weights tensor in the oihw format with both input and output channels data laid out in memory in 8...
Definition: mkldnn_types.h:166
Forward data propagation (alias for mkldnn_forward_training)
Definition: mkldnn_types.h:277
lrn descriptor
Definition: mkldnn_types.h:890
struct mkldnn_primitive_desc * mkldnn_primitive_desc_t
A primitive descriptor handle.
Definition: mkldnn_types.h:761
workspace memory primitive desc
Definition: mkldnn_types.h:905
mkldnn_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: mkldnn_types.h:498
mkldnn_alg_kind_t alg_kind
The kind of the convolution algorithm.
Definition: mkldnn_types.h:490
Definition: mkldnn_types.h:887
weights grad.
Definition: mkldnn_types.h:902
4D data tensor in the nchw format typically used in Caffe.
Definition: mkldnn_types.h:122
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:581
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:673
primitive kind
Definition: mkldnn_types.h:870
mkldnn_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: mkldnn_types.h:689
mkldnn_dims_t block_dims
Block size for each of the dimensions.
Definition: mkldnn_types.h:430
4D weights tensor in the oihw format with output channels data laid out in memory in 16-element block...
Definition: mkldnn_types.h:159
struct mkldnn_primitive_attr * mkldnn_primitive_attr_t
A primitive descriptor attributes handle that controls primitive behavior.
Definition: mkldnn_types.h:782
An opaque structure to describe a primitive descriptor iterator .