Visible to Intel only — GUID: GUID-F7EDB5A5-894A-4207-B2E4-78D6FF610D65
Abs
AbsBackward
Add
AvgPool
AvgPoolBackward
BatchNormForwardTraining
BatchNormInference
BatchNormTrainingBackward
BiasAdd
BiasAddBackward
Clamp
ClampBackward
Concat
Convolution
ConvolutionBackwardData
ConvolutionBackwardWeights
ConvTranspose
ConvTransposeBackwardData
ConvTransposeBackwardWeights
Dequantize
Divide
DynamicDequantize
DynamicQuantize
Elu
EluBackward
End
Exp
GELU
GELUBackward
HardSigmoid
HardSigmoidBackward
HardSwish
HardSwishBackward
Interpolate
InterpolateBackward
LayerNorm
LayerNormBackward
LeakyReLU
Log
LogSoftmax
LogSoftmaxBackward
MatMul
Maximum
MaxPool
MaxPoolBackward
Minimum
Mish
MishBackward
Multiply
Pow
PReLU
PReLUBackward
Quantize
Reciprocal
ReduceL1
ReduceL2
ReduceMax
ReduceMean
ReduceMin
ReduceProd
ReduceSum
ReLU
ReLUBackward
Reorder
Round
Select
Sigmoid
SigmoidBackward
SoftMax
SoftMaxBackward
SoftPlus
SoftPlusBackward
Sqrt
SqrtBackward
Square
SquaredDifference
StaticReshape
StaticTranspose
Subtract
Tanh
TanhBackward
TypeCast
Wildcard
enum dnnl_alg_kind_t
enum dnnl_normalization_flags_t
enum dnnl_primitive_kind_t
enum dnnl_prop_kind_t
enum dnnl_query_t
enum dnnl::normalization_flags
enum dnnl::query
struct dnnl_exec_arg_t
struct dnnl_primitive
struct dnnl_primitive_desc
struct dnnl::primitive
struct dnnl::primitive_desc
struct dnnl::primitive_desc_base
enum dnnl_rnn_direction_t
enum dnnl_rnn_flags_t
enum dnnl::rnn_direction
enum dnnl::rnn_flags
struct dnnl::augru_backward
struct dnnl::augru_forward
struct dnnl::gru_backward
struct dnnl::gru_forward
struct dnnl::lbr_augru_backward
struct dnnl::lbr_augru_forward
struct dnnl::lbr_gru_backward
struct dnnl::lbr_gru_forward
struct dnnl::lstm_backward
struct dnnl::lstm_forward
struct dnnl::rnn_primitive_desc_base
struct dnnl::vanilla_rnn_backward
struct dnnl::vanilla_rnn_forward
Visible to Intel only — GUID: GUID-F7EDB5A5-894A-4207-B2E4-78D6FF610D65
Primitive Attributes
A quick recap of the primitive creation step, which consists of the following:
Creating a primitive descriptor based on the engine, operation parameters, and attributes. During creation of a primitive for backward propagation, the primitive descriptor from the forward propagation might be required as well (see Training-Specific Aspects).
Creating a primitive, solely based on a primitive descriptor.
Details on why all these steps are required can be found in Basic Concepts. The fact that is important for us now is that a primitive descriptor created at step 2 fully defines the operation that the corresponding primitive will execute. Once the primitive descriptor is created, it cannot be changed.
The parameters passed to create a primitive descriptor specify the problem. An engine specifies where the primitive will be executed. Primitive parameters specify the basics: the operation kind; the propagation kind; the source, destination, and other tensors; the strides (if applicable); and so on.
Attributes specify some extra properties of the primitive. The attributes were designed to be extensible, hence they are an opaque structure. Users must create them before use and must set required specifics using the corresponding setters. The attributes are copied during primitive descriptor creation, so users can change or destroy attributes right after that.
If not modified, attributes can stay empty, which is equivalent to the default attributes. For that purpose, in the C API users can pass NULL as an attribute upon primitive descriptor creation. In the C++ API, primitive descriptors’ constructors have empty attributes as default parameters, so, unless they are required, users can simply omit them.
Attributes Usage
Below are the skeletons of using attributes with the C and C++ APIs. Error handling is omitted to simplify reading.
// ### C API ###
dnnl_primitive_attr_t attr; // opaque attributes
dnnl_primitive_attr_create(&attr);
dnnl_primitive_attr_set_SOMETHING(attr, params); // setting attributes params
dnnl_primitive_attr_set_SOMETHING_ELSE(attr, other_params);
dnnl_eltwise_backward_primitive_desc_create(&op_pd, engine, ..., hint_fwd_pd, attr);
// changing attr object here does not have any effect on op_pd
// once attr is no more used we can immediately destroy it
dnnl_primitive_attr_destroy(attr);
...
// ### C++ API ###
dnnl::primitive_attr attr;
attr.set_SOMETHING(params);
attr.set_SOMETHING_ELSE(params);
primitive::primitive_desc pd(..., attr);
// in C++ destroying of attr happens automaticallySupported Attributes
As mentioned above, the attributes enable extending or changing the default primitive behavior. Currently the following attributes are supported. The detailed explanation is provided in the corresponding sections.
Scratchpad behavior: handling the intermediate temporary memory by the library or a user;
Floating-point math mode to allow implicit down-conversions of f32 values during computation;
Accumulation mode to allow the usage of lower precision datatypes for accumulation;
Deterministic mode to enforce run-to-run deterministic primitive execution.
Quantization settings used in INT8 inference;
Post-ops to fuse a primitive with some operation applied to the primitive’s result. Used mostly for inference.
Attribute Related Error Handling
Because the attributes are created separately from the corresponding primitive descriptor, consistency checks are delayed. Users can successfully set attributes in whatever configuration they want. However, when they try to create a primitive descriptor with the attributes they set, it might happen that there is no primitive implementation that supports such a configuration. In this case, the library will return dnnl_unimplemented in the case of the C API or throw a corresponding dnnl::error exception in the case of the C++ API. Unfortunately, the library does not currently provide any hints about what exactly is going wrong in this case. The corresponding section of the documentation simply documents the primitives’ capabilities.