17 #ifndef MKLDNN_TYPES_H 18 #define MKLDNN_TYPES_H 24 #ifndef DOXYGEN_SHOULD_SKIP_THIS 368 #define TENSOR_MAX_DIMS 12 381 mkldnn_strides_t strides[2];
462 mkldnn_dims_t padding[2];
543 mkldnn_dims_t padding[2];
mkldnn_data_type_t accum_data_type
The accumulator data type.
Definition: mkldnn_types.h:634
LRN within a single channel.
Definition: mkldnn_types.h:318
mkldnn_padding_kind_t padding_kind
The kind of padding to use.
Definition: mkldnn_types.h:545
A descriptor of a Local Response Normalization (LRN) operation.
Definition: mkldnn_types.h:551
4D weights tensor in the format (output channels, width, height, input channels) with output channels...
Definition: mkldnn_types.h:173
A Softmax primitive.
Definition: mkldnn_types.h:283
number of outputs expected
Definition: mkldnn_types.h:764
double lrn_alpha
LRN alpha parameter.
Definition: mkldnn_types.h:570
mkldnn_dims_t dilates
Convolution dilates in each spatial dimension.
Definition: mkldnn_types.h:458
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:428
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:118
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:246
An opaque structure to describe an engine.
Backward data propagation.
Definition: mkldnn_types.h:252
Undefined memory format, used for empty memory descriptors.
Definition: mkldnn_types.h:101
double lrn_k
LRN k parameter.
Definition: mkldnn_types.h:574
#define TENSOR_MAX_DIMS
Maximum number of dimensions a tensor can have.
Definition: mkldnn_types.h:368
4D weights tensor in the format (input channels, output channels, width, height). ...
Definition: mkldnn_types.h:131
A descriptor of a Softmax operation.
Definition: mkldnn_types.h:503
mkldnn_padding_kind_t padding_kind
The kind of padding to use.
Definition: mkldnn_types.h:464
4D data tensor in the nchw format with channels data laid out in memory in 8-element blocks...
Definition: mkldnn_types.h:121
A descriptor of an inner product operation.
Definition: mkldnn_types.h:609
An opaque structure to describe a primitive descriptor .
batch normalization descriptor
Definition: mkldnn_types.h:782
mkldnn_memory_desc_t diff_data_scaleshift_desc
Definition: mkldnn_types.h:596
A convolution primitive.
Definition: mkldnn_types.h:277
mkldnn_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: mkldnn_types.h:620
struct mkldnn_stream * mkldnn_stream_t
An execution stream handle.
Definition: mkldnn_types.h:818
4D data tensor in the nchw format with channels data laid out in memory in 16-element blocks...
Definition: mkldnn_types.h:124
mkldnn_prop_kind_t prop_kind
The kind of propagation.
Definition: mkldnn_types.h:509
struct mkldnn_primitive_desc_iterator * mkldnn_primitive_desc_iterator_t
A primitive descriptor iterator handle.
Definition: mkldnn_types.h:683
Undefined primitive (XXX: why do we have it?).
Definition: mkldnn_types.h:263
An inner product primitive.
Definition: mkldnn_types.h:291
convolution-relu descriptor
Definition: mkldnn_types.h:784
double negative_slope
Scaling factor for negative values.
Definition: mkldnn_types.h:496
mkldnn_memory_desc_t dst_desc
Destination memory descriptor.
Definition: mkldnn_types.h:452
mkldnn_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: mkldnn_types.h:531
Definition: mkldnn_types.h:314
size_t output_index
Desired output index.
Definition: mkldnn_types.h:723
mkldnn_data_type_t data_type
Data type of the tensor elements.
Definition: mkldnn_types.h:414
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:386
32-bit signed integer.
Definition: mkldnn_types.h:68
Max pooling.
Definition: mkldnn_types.h:309
execution engine
Definition: mkldnn_types.h:760
void * mkldnn_op_desc_t
A pointer to any of the operation descriptors.
Definition: mkldnn_types.h:396
mkldnn_data_type_t accum_data_type
The accumulator data type.
Definition: mkldnn_types.h:466
4D weights tensor in the oihw format with input channels data laid out in memory in 16-element blocks...
Definition: mkldnn_types.h:151
mkldnn_prop_kind_t prop_kind
The kind of propagation.
Definition: mkldnn_types.h:558
mkldnn_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: mkldnn_types.h:535
mkldnn_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: mkldnn_types.h:482
A descriptor of a convolution followed by relu operation.
Definition: mkldnn_types.h:638
struct mkldnn_primitive * mkldnn_primitive_t
A primitive handle.
Definition: mkldnn_types.h:714
input memory primitive desc
Definition: mkldnn_types.h:788
ptrdiff_t mkldnn_strides_t[TENSOR_MAX_DIMS]
A type to describe strides within a tensor.
Definition: mkldnn_types.h:373
5D weights tensor in the oihw format with extra outer dimension for groups.
Definition: mkldnn_types.h:179
const_mkldnn_primitive_t primitive
Primitive to specify the output for.
Definition: mkldnn_types.h:721
mkldnn_prop_kind_t prop_kind
The kind of propagation.
Definition: mkldnn_types.h:524
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:568
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:389
A descriptor of a element-wise operation.
Definition: mkldnn_types.h:470
An element-wise primitive.
Definition: mkldnn_types.h:279
mkldnn_memory_desc_t src_desc
Source memory descriptor.
Definition: mkldnn_types.h:618
destination grad.
Definition: mkldnn_types.h:795
eltwise descriptor
Definition: mkldnn_types.h:777
A memory primitive.
Definition: mkldnn_types.h:265
4D weights tensor in the oihw format with both input and output channels data laid out in memory in 1...
Definition: mkldnn_types.h:157
mkldnn_memory_desc_t bias_desc
Bias memory descriptor.
Definition: mkldnn_types.h:448
double beta
Definition: mkldnn_types.h:491
The operation failed due to an out-of-memory condition.
Definition: mkldnn_types.h:43
Backward weights propagation.
Definition: mkldnn_types.h:254
stub
Definition: mkldnn_types.h:774
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:477
const struct mkldnn_primitive_desc_iterator * const_mkldnn_primitive_desc_iterator_t
A constant primitive descriptor iterator handle.
Definition: mkldnn_types.h:687
2D weights tensor in the format (input channels, output channels).
Definition: mkldnn_types.h:126
double batch_norm_epsilon
Batch normalization epsilon parameter.
Definition: mkldnn_types.h:604
Omit statistics.
Definition: mkldnn_types.h:357
Memory descriptor.
Definition: mkldnn_types.h:404
mkldnn_dims_t kernel
Pooling kernel spatial dimensions.
Definition: mkldnn_types.h:539
mkldnn_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: mkldnn_types.h:587
mkldnn_batch_normalization_flag_t
Flags for batch-normalization primititve.
Definition: mkldnn_types.h:322
pooling descriptor
Definition: mkldnn_types.h:780
mkldnn_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: mkldnn_types.h:565
mkldnn_alg_kind_t alg_kind
The kind of pooling algorithm.
Definition: mkldnn_types.h:527
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:431
mkldnn_memory_desc_t dst_desc
Destination memory descriptor.
Definition: mkldnn_types.h:630
mkldnn_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: mkldnn_types.h:450
4D weights tensor in the format (output channels, input channels, height, width) with output channels...
Definition: mkldnn_types.h:165
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:183
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:554
5D weights tensor in the oihw format with output channels data laid out in memory in 16-element block...
Definition: mkldnn_types.h:191
Backward propagation (with respect to all parameters.
Definition: mkldnn_types.h:250
softmax descriptor
Definition: mkldnn_types.h:779
mkldnn_memory_desc_t data_scaleshift_desc
Scale and shift data and gradient memory descriptors.
Definition: mkldnn_types.h:595
Use global statistics.
Definition: mkldnn_types.h:335
4D weights tensor in the format (output channels, width, height, input channels) with output channels...
Definition: mkldnn_types.h:169
no query
Definition: mkldnn_types.h:758
5D weights tensor in the blocked version of goihw format with output channels data laid out in memory...
Definition: mkldnn_types.h:212
mkldnn_memory_desc_t mean_desc
Mean and variance data memory descriptors.
Definition: mkldnn_types.h:601
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:581
8-bit unsigned integer.
Definition: mkldnn_types.h:74
mkldnn_alg_kind_t alg_kind
LRN algorithm.
Definition: mkldnn_types.h:561
Average pooling include padding.
Definition: mkldnn_types.h:311
Unspecified format.
Definition: mkldnn_types.h:104
mkldnn_memory_desc_t diff_src_desc
Source gradient memory descriptor.
Definition: mkldnn_types.h:442
destination memory primitive desc
Definition: mkldnn_types.h:794
Local response normalization (LRN) across multiple channels.
Definition: mkldnn_types.h:316
4D weights tensor in the oihw format with input channels data laid out in memory in 16-element blocks...
Definition: mkldnn_types.h:224
Eager stream.
Definition: mkldnn_types.h:809
implementation name
Definition: mkldnn_types.h:771
Eltwise: parametric exponential linear unit (elu)
Definition: mkldnn_types.h:307
mkldnn_dims_t padding_dims
Size of the data including padding in each dimension.
Definition: mkldnn_types.h:383
Eltwise: ReLU.
Definition: mkldnn_types.h:303
1D data tensor.
Definition: mkldnn_types.h:110
4D weights tensor in the format (input channels, height, width, output channels). ...
Definition: mkldnn_types.h:134
mkldnn_memory_format_t
Memory format specification.
Definition: mkldnn_types.h:99
mkldnn_prop_kind_t prop_kind
The kind of propagation.
Definition: mkldnn_types.h:616
mkldnn_data_type_t accum_data_type
The accumulator data type.
Definition: mkldnn_types.h:547
4D data tensor in the nhwc format typically used in TensorFlow.
Definition: mkldnn_types.h:116
Backward bias propagation.
Definition: mkldnn_types.h:256
5D weights tensor in the goihw format with both input and output channels data laid out in memory in ...
Definition: mkldnn_types.h:218
Use scale and shift parameters.
Definition: mkldnn_types.h:348
mkldnn_memory_desc_t weights_desc
Weights memory descriptor.
Definition: mkldnn_types.h:444
4D weights tensor in the oihw format with input channels data laid out in memory in 8-element blocks...
Definition: mkldnn_types.h:221
5D weights tensor in the oihw format with input channels data laid out in memory in 16-element blocks...
Definition: mkldnn_types.h:195
double negative_slope
Scaling factor for negative values, stored as double-precision but interpreted in a way specific to t...
Definition: mkldnn_types.h:646
int ndims
Number of dimensions.
Definition: mkldnn_types.h:409
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:407
An opaque structure to describe an execution stream.
A convolution primitive merged with relu.
Definition: mkldnn_types.h:293
Undefined propagation type.
Definition: mkldnn_types.h:237
mkldnn_blocking_desc_t blocking
Description of the data layout for memory formats that use blocking.
Definition: mkldnn_types.h:420
mkldnn_dims_t dims
Dimensions in the following order: mini-batch, channel, spatial.
Definition: mkldnn_types.h:412
mkldnn_dims_t strides
Convolution strides in each spatial dimension.
Definition: mkldnn_types.h:456
mkldnn_prop_kind_t
Kinds of propagation.
Definition: mkldnn_types.h:234
CPU engine.
Definition: mkldnn_types.h:659
mkldnn_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: mkldnn_types.h:511
mkldnn_memory_format_t format
Memory format.
Definition: mkldnn_types.h:416
mkldnn_stream_kind_t
Kinds of streams.
Definition: mkldnn_types.h:805
mkldnn_memory_desc_t src_desc
Source memory descriptor.
Definition: mkldnn_types.h:440
4D weights tensor in the format (height, width, input channels, output channels). ...
Definition: mkldnn_types.h:137
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:641
A wrapper structure to specify a particular output of a primitive.
Definition: mkldnn_types.h:719
Winograd convolution.
Definition: mkldnn_types.h:301
A ReLU primitive,.
Definition: mkldnn_types.h:281
mkldnn_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: mkldnn_types.h:589
Direct convolution.
Definition: mkldnn_types.h:299
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:716
source gradient memory primitive desc
Definition: mkldnn_types.h:791
runtime estimation (seconds)
Definition: mkldnn_types.h:766
5D weights tensor in the blocked version of goihw format with output channels data laid out in memory...
Definition: mkldnn_types.h:215
A (in-place) concat primitive.
Definition: mkldnn_types.h:273
mkldnn_memory_desc_t diff_data_desc
Source and destination gradient memory descriptor.
Definition: mkldnn_types.h:484
4D weights tensor in the oihw format with both input and output channels data laid out in memory in 8...
Definition: mkldnn_types.h:140
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:271
mkldnn_query_t
Primitive descriptor query specification.
Definition: mkldnn_types.h:757
A descriptor of a Batch Normalization operation.
Definition: mkldnn_types.h:578
const struct mkldnn_stream * const_mkldnn_stream_t
A constant execution stream handle.
Definition: mkldnn_types.h:820
A sum primitive.
Definition: mkldnn_types.h:275
5D weights tensor in the blocked version of goihw format with output channels data laid out in memory...
Definition: mkldnn_types.h:206
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:506
unsigned flags
Definition: mkldnn_types.h:605
double lrn_beta
LRN beta parameter.
Definition: mkldnn_types.h:572
2D weights tensor in the format (input channels, output channels).
Definition: mkldnn_types.h:128
memory consumption – extra (scratch) memory, additional to all inputs and outputs memory (bytes) ...
Definition: mkldnn_types.h:767
An batch normalization primitive.
Definition: mkldnn_types.h:289
A descriptor of a pooling operation.
Definition: mkldnn_types.h:517
mkldnn_dims_t strides
Pooling kernel strides for spatial dimensions.
Definition: mkldnn_types.h:537
int softmax_axis
The axis along which to perform the softmax.
Definition: mkldnn_types.h:513
8-bit signed integer.
Definition: mkldnn_types.h:72
The data in padding regions is zero.
Definition: mkldnn_types.h:230
mkldnn_memory_desc_t variance_desc
Definition: mkldnn_types.h:602
source memory primitive desc
Definition: mkldnn_types.h:790
mkldnn_primitive_kind_t
Kinds of primitives.
Definition: mkldnn_types.h:261
number of inputs expected
Definition: mkldnn_types.h:763
struct mkldnn_engine * mkldnn_engine_t
An engine handle.
Definition: mkldnn_types.h:666
mkldnn_memory_desc_t weights_desc
Weights memory descriptor.
Definition: mkldnn_types.h:622
An unspecified engine.
Definition: mkldnn_types.h:807
A view primitive.
Definition: mkldnn_types.h:267
4D weights tensor in the format (output channels, input channels, height, width) with output channels...
Definition: mkldnn_types.h:161
Average pooling exclude padding.
Definition: mkldnn_types.h:313
Forward data propagation (inference mode).
Definition: mkldnn_types.h:244
mkldnn_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: mkldnn_types.h:454
4D weights tensor in the oihw format with both input and output channels data laid out in memory in 1...
Definition: mkldnn_types.h:143
stub
Definition: mkldnn_types.h:787
5D weights tensor in the blocked version of goihw format with both input and output channels data lai...
Definition: mkldnn_types.h:199
The operation failed because requested functionality is not implemented.
Definition: mkldnn_types.h:52
Eltwise: hyperbolic tangent non-linearity (tanh)
Definition: mkldnn_types.h:305
mkldnn_memory_desc_t diff_dst_desc
Destination gradient memory descriptor.
Definition: mkldnn_types.h:632
2D data tensor.
Definition: mkldnn_types.h:112
Primitive or engine failed on execution.
Definition: mkldnn_types.h:56
memory descriptor for memory and view
Definition: mkldnn_types.h:775
An LRN primitive.
Definition: mkldnn_types.h:287
mkldnn_padding_kind_t
Kinds of padding.
Definition: mkldnn_types.h:228
mkldnn_memory_desc_t dst_desc
Destination memory descriptor.
Definition: mkldnn_types.h:533
Lazy stream.
Definition: mkldnn_types.h:811
5D weights tensor in the blocked version of goihw format with output channels data laid out in memory...
Definition: mkldnn_types.h:209
const struct mkldnn_primitive_desc * const_mkldnn_primitive_desc_t
A constant primitive descriptor handle.
Definition: mkldnn_types.h:703
Forward data propagation (training mode).
Definition: mkldnn_types.h:240
mkldnn_convolution_desc_t convolution_desc
A descriptor of a convolution operation.
Definition: mkldnn_types.h:643
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:108
mkldnn_data_type_t
Data type specification.
Definition: mkldnn_types.h:62
convolution descriptor
Definition: mkldnn_types.h:776
mkldnn_eltwise_desc_t mkldnn_relu_desc_t
Definition: mkldnn_types.h:500
mkldnn_memory_desc_t src_desc
Source memory descriptor.
Definition: mkldnn_types.h:529
mkldnn_prop_kind_t prop_kind
The kind of propagation.
Definition: mkldnn_types.h:585
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:473
mkldnn_alg_kind_t alg_kind
The kind of eltwise algorithm.
Definition: mkldnn_types.h:480
4D weights tensor in the oihw format with both input and output channels data laid out in memory in 1...
Definition: mkldnn_types.h:176
mkldnn_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: mkldnn_types.h:624
mkldnn_prop_kind_t prop_kind
The kind of propagation.
Definition: mkldnn_types.h:435
mkldnn_engine_kind_t
Kinds of engines.
Definition: mkldnn_types.h:655
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:376
const void * const_mkldnn_op_desc_t
A pointer to any of the operation descriptors (constant variant).
Definition: mkldnn_types.h:398
A reorder primitive.
Definition: mkldnn_types.h:269
5D weights tensor in the blocked version of goihw format with both input and output channels data lai...
Definition: mkldnn_types.h:203
An unspecified engine.
Definition: mkldnn_types.h:657
5D weights tensor in the blocked version of goihw format with both input and output channels data lai...
Definition: mkldnn_types.h:187
mkldnn_alg_kind_t
Kinds of algorithms.
Definition: mkldnn_types.h:297
int mkldnn_dims_t[TENSOR_MAX_DIMS]
A type to describe tensor dimensions.
Definition: mkldnn_types.h:371
inner product descriptor
Definition: mkldnn_types.h:783
mkldnn_memory_desc_t bias_desc
Bias memory descriptor.
Definition: mkldnn_types.h:626
A pooling primitive.
Definition: mkldnn_types.h:285
weights memory primitive descriptor desc
Definition: mkldnn_types.h:792
output memory primitive desc
Definition: mkldnn_types.h:789
mkldnn_memory_desc_t data_desc
Source and destination memory descriptor.
Definition: mkldnn_types.h:563
4D weights tensor in the oihw format with both input and output channels data laid out in memory in 8...
Definition: mkldnn_types.h:154
Forward data propagation (alias for mkldnn_forward_training)
Definition: mkldnn_types.h:248
lrn descriptor
Definition: mkldnn_types.h:781
struct mkldnn_primitive_desc * mkldnn_primitive_desc_t
A primitive descriptor handle.
Definition: mkldnn_types.h:700
workspace memory primitive desc
Definition: mkldnn_types.h:796
mkldnn_memory_desc_t diff_weights_desc
Weights gradient memory descriptor.
Definition: mkldnn_types.h:446
mkldnn_alg_kind_t alg_kind
The kind of the convolution algorithm.
Definition: mkldnn_types.h:438
Definition: mkldnn_types.h:778
weights grad.
Definition: mkldnn_types.h:793
4D data tensor in the nchw format typically used in Caffe.
Definition: mkldnn_types.h:114
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:520
mkldnn_primitive_kind_t primitive_kind
The kind of primitive.
Definition: mkldnn_types.h:612
primitive kind
Definition: mkldnn_types.h:761
mkldnn_memory_desc_t diff_bias_desc
Bias gradient memory descriptor.
Definition: mkldnn_types.h:628
mkldnn_dims_t block_dims
Block size for each of the dimensions.
Definition: mkldnn_types.h:378
4D weights tensor in the oihw format with output channels data laid out in memory in 16-element block...
Definition: mkldnn_types.h:147
An opaque structure to describe a primitive descriptor iterator .