Intel® oneAPI Deep Neural Network Developer Guide and Reference
ID
768875
Date
6/30/2025
Public
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
GroupNorm
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
Overview
Detailed Documentation
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
enum dnnl_prop_kind_t
Overview
Kinds of propagation. More…
#include <dnnl_types.h>
enum dnnl_prop_kind_t
{
dnnl_prop_kind_undef = 0,
dnnl_forward_training = 64,
dnnl_forward_inference = 96,
dnnl_forward = dnnl_forward_training,
dnnl_backward = 128,
dnnl_backward_data = 160,
dnnl_backward_weights = 192,
dnnl_backward_bias = 193,
};
Detailed Documentation
Kinds of propagation.
Enum Values
dnnl_prop_kind_undef
Undefined propagation type.
dnnl_forward_training
Forward data propagation (training mode).
In this mode primitives perform computations necessary for subsequent backward propagation.
dnnl_forward_inference
Forward data propagation (inference mode).
In this mode primitives perform only computations that are necessary for inference and omit computations that are necessary only for backward propagation.
dnnl_forward
Forward data propagation (alias for dnnl_forward_training).
dnnl_backward
Backward propagation (with respect to all parameters).
dnnl_backward_data
Backward data propagation.
dnnl_backward_weights
Backward weights propagation.
dnnl_backward_bias
Backward bias propagation.