Visible to Intel only — GUID: GUID-C08DB8A8-1CBF-4CE1-95AE-98F5E839FF40
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-C08DB8A8-1CBF-4CE1-95AE-98F5E839FF40
Batch Normalization
Overview
A primitive to perform batch normalization. More…
// structs
struct dnnl::batch_normalization_backward;
struct dnnl::batch_normalization_forward;
// global functions
dnnl_status_t DNNL_API dnnl_batch_normalization_forward_primitive_desc_create(
dnnl_primitive_desc_t* primitive_desc,
dnnl_engine_t engine,
dnnl_prop_kind_t prop_kind,
const_dnnl_memory_desc_t src_desc,
const_dnnl_memory_desc_t dst_desc,
float epsilon,
unsigned flags,
const_dnnl_primitive_attr_t attr
);
dnnl_status_t DNNL_API dnnl_batch_normalization_backward_primitive_desc_create(
dnnl_primitive_desc_t* primitive_desc,
dnnl_engine_t engine,
dnnl_prop_kind_t prop_kind,
const_dnnl_memory_desc_t diff_src_desc,
const_dnnl_memory_desc_t diff_dst_desc,
const_dnnl_memory_desc_t src_desc,
float epsilon,
unsigned flags,
const_dnnl_primitive_desc_t hint_fwd_pd,
const_dnnl_primitive_attr_t attr
);Detailed Documentation
A primitive to perform batch normalization.
Both forward and backward propagation primitives support in-place operation; that is, src and dst can refer to the same memory for forward propagation, and diff_dst and diff_src can refer to the same memory for backward propagation.
The batch normalization primitives computations can be controlled by specifying different dnnl::normalization_flags values. For example, batch normalization forward propagation can be configured to either compute the mean and variance or take them as arguments. It can either perform scaling and shifting using gamma and beta parameters or not. Optionally, it can also perform a fused ReLU, which in case of training would also require a workspace.
See also:
Batch Normalization in developer guide
Global Functions
dnnl_status_t DNNL_API dnnl_batch_normalization_forward_primitive_desc_create(
dnnl_primitive_desc_t* primitive_desc,
dnnl_engine_t engine,
dnnl_prop_kind_t prop_kind,
const_dnnl_memory_desc_t src_desc,
const_dnnl_memory_desc_t dst_desc,
float epsilon,
unsigned flags,
const_dnnl_primitive_attr_t attr
)Creates a primitive descriptor for a batch normalization forward propagation primitive.
NOTE:
In-place operation is supported: the dst can refer to the same memory as the src.
Parameters:
primitive_desc |
Output primitive_descriptor. |
engine |
Engine to use. |
prop_kind |
Propagation kind. Possible values are dnnl_forward_training and dnnl_forward_inference. |
src_desc |
Source memory descriptor. |
dst_desc |
Destination memory descriptor. |
epsilon |
Batch normalization epsilon parameter. |
flags |
Batch normalization flags (dnnl_normalization_flags_t). |
attr |
Primitive attributes (can be NULL). |
Returns:
dnnl_success on success and a status describing the error otherwise.
dnnl_status_t DNNL_API dnnl_batch_normalization_backward_primitive_desc_create(
dnnl_primitive_desc_t* primitive_desc,
dnnl_engine_t engine,
dnnl_prop_kind_t prop_kind,
const_dnnl_memory_desc_t diff_src_desc,
const_dnnl_memory_desc_t diff_dst_desc,
const_dnnl_memory_desc_t src_desc,
float epsilon,
unsigned flags,
const_dnnl_primitive_desc_t hint_fwd_pd,
const_dnnl_primitive_attr_t attr
)Creates a primitive descriptor for a batch normalization backward propagation primitive.
NOTE:
In-place operation is supported: the diff_dst can refer to the same memory as the diff_src.
Parameters:
primitive_desc |
Output primitive_descriptor. |
engine |
Engine to use. |
prop_kind |
Propagation kind. Possible values are dnnl_backward_data and dnnl_backward (diffs for all parameters are computed in this case). |
diff_src_desc |
Diff source memory descriptor. |
diff_dst_desc |
Diff destination memory descriptor. |
src_desc |
Source memory descriptor. |
epsilon |
Batch normalization epsilon parameter. |
flags |
Batch normalization flags (dnnl_normalization_flags_t). |
hint_fwd_pd |
Primitive descriptor for a respective forward propagation primitive. |
attr |
Primitive attributes (can be NULL). |
Returns:
dnnl_success on success and a status describing the error otherwise.