Visible to Intel only — GUID: GUID-C0969495-F2D8-42AC-9E09-62DB2E5D7D2F
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
Overview
Detailed Documentation
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-C0969495-F2D8-42AC-9E09-62DB2E5D7D2F
Common
Overview
Common operations to create, destroy and inspect primitives. More…
// typedefs
typedef struct dnnl_primitive_desc* dnnl_primitive_desc_t;
typedef const struct dnnl_primitive_desc* const_dnnl_primitive_desc_t;
typedef struct dnnl_primitive* dnnl_primitive_t;
typedef const struct dnnl_primitive* const_dnnl_primitive_t;
// enums
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;
// structs
struct dnnl_exec_arg_t;
struct dnnl_primitive;
struct dnnl_primitive_desc;
struct dnnl::primitive;
struct dnnl::primitive_desc;
struct dnnl::primitive_desc_base;
// global functions
dnnl_primitive_kind_t dnnl::convert_to_c(primitive::kind akind);
dnnl_normalization_flags_t dnnl::convert_to_c(normalization_flags flags);
dnnl_query_t dnnl::convert_to_c(query aquery);
dnnl_status_t DNNL_API dnnl_primitive_desc_next_impl(dnnl_primitive_desc_t primitive_desc);
dnnl_status_t DNNL_API dnnl_primitive_desc_clone(
dnnl_primitive_desc_t* primitive_desc,
const_dnnl_primitive_desc_t existing_primitive_desc
);
dnnl_status_t DNNL_API dnnl_primitive_desc_get_attr(
const_dnnl_primitive_desc_t primitive_desc,
const_dnnl_primitive_attr_t* attr
);
dnnl_status_t DNNL_API dnnl_primitive_desc_destroy(dnnl_primitive_desc_t primitive_desc);
dnnl_status_t DNNL_API dnnl_primitive_desc_query(
const_dnnl_primitive_desc_t primitive_desc,
dnnl_query_t what,
int index,
void* result
);
const_dnnl_memory_desc_t DNNL_API dnnl_primitive_desc_query_md(
const_dnnl_primitive_desc_t primitive_desc,
dnnl_query_t what,
int index
);
int DNNL_API dnnl_primitive_desc_query_s32(
const_dnnl_primitive_desc_t primitive_desc,
dnnl_query_t what,
int index
);
dnnl_status_t DNNL_API dnnl_primitive_create(
dnnl_primitive_t* primitive,
const_dnnl_primitive_desc_t primitive_desc
);
dnnl_status_t DNNL_API dnnl_primitive_create_from_cache_blob(
dnnl_primitive_t* primitive,
const_dnnl_primitive_desc_t primitive_desc,
size_t size,
const uint8_t* cache_blob
);
dnnl_status_t DNNL_API dnnl_primitive_execute(
const_dnnl_primitive_t primitive,
dnnl_stream_t stream,
int nargs,
const dnnl_exec_arg_t* args
);
dnnl_status_t DNNL_API dnnl_primitive_get_primitive_desc(
const_dnnl_primitive_t primitive,
const_dnnl_primitive_desc_t* primitive_desc
);
dnnl_status_t DNNL_API dnnl_primitive_get_cache_blob(
const_dnnl_primitive_t primitive,
size_t* size,
uint8_t* cache_blob
);
dnnl_status_t DNNL_API dnnl_primitive_destroy(dnnl_primitive_t primitive);
// macros
#define DNNL_ARG_ATTR_MULTIPLE_POST_OP(idx)
#define DNNL_ARG_ATTR_MULTIPLE_POST_OP_BASE
#define DNNL_ARG_ATTR_OUTPUT_SCALES
#define DNNL_ARG_ATTR_POST_OP_DW
#define DNNL_ARG_ATTR_SCALES
#define DNNL_ARG_ATTR_ZERO_POINTS
#define DNNL_ARG_AUGRU_ATTENTION
#define DNNL_ARG_BIAS
#define DNNL_ARG_DIFF_AUGRU_ATTENTION
#define DNNL_ARG_DIFF_BIAS
#define DNNL_ARG_DIFF_DST
#define DNNL_ARG_DIFF_DST_0
#define DNNL_ARG_DIFF_DST_1
#define DNNL_ARG_DIFF_DST_2
#define DNNL_ARG_DIFF_DST_ITER
#define DNNL_ARG_DIFF_DST_ITER_C
#define DNNL_ARG_DIFF_DST_LAYER
#define DNNL_ARG_DIFF_SCALE
#define DNNL_ARG_DIFF_SHIFT
#define DNNL_ARG_DIFF_SRC
#define DNNL_ARG_DIFF_SRC_0
#define DNNL_ARG_DIFF_SRC_1
#define DNNL_ARG_DIFF_SRC_2
#define DNNL_ARG_DIFF_SRC_3
#define DNNL_ARG_DIFF_SRC_ITER
#define DNNL_ARG_DIFF_SRC_ITER_C
#define DNNL_ARG_DIFF_SRC_LAYER
#define DNNL_ARG_DIFF_WEIGHTS
#define DNNL_ARG_DIFF_WEIGHTS_0
#define DNNL_ARG_DIFF_WEIGHTS_1
#define DNNL_ARG_DIFF_WEIGHTS_2
#define DNNL_ARG_DIFF_WEIGHTS_3
#define DNNL_ARG_DIFF_WEIGHTS_ITER
#define DNNL_ARG_DIFF_WEIGHTS_LAYER
#define DNNL_ARG_DIFF_WEIGHTS_PEEPHOLE
#define DNNL_ARG_DIFF_WEIGHTS_PROJECTION
#define DNNL_ARG_DST
#define DNNL_ARG_DST_0
#define DNNL_ARG_DST_1
#define DNNL_ARG_DST_2
#define DNNL_ARG_DST_ITER
#define DNNL_ARG_DST_ITER_C
#define DNNL_ARG_DST_LAYER
#define DNNL_ARG_FROM
#define DNNL_ARG_MEAN
#define DNNL_ARG_MULTIPLE_DST
#define DNNL_ARG_MULTIPLE_SRC
#define DNNL_ARG_SCALE
#define DNNL_ARG_SCRATCHPAD
#define DNNL_ARG_SHIFT
#define DNNL_ARG_SRC
#define DNNL_ARG_SRC_0
#define DNNL_ARG_SRC_1
#define DNNL_ARG_SRC_2
#define DNNL_ARG_SRC_3
#define DNNL_ARG_SRC_ITER
#define DNNL_ARG_SRC_ITER_C
#define DNNL_ARG_SRC_LAYER
#define DNNL_ARG_TO
#define DNNL_ARG_VARIANCE
#define DNNL_ARG_WEIGHTS
#define DNNL_ARG_WEIGHTS_0
#define DNNL_ARG_WEIGHTS_1
#define DNNL_ARG_WEIGHTS_2
#define DNNL_ARG_WEIGHTS_3
#define DNNL_ARG_WEIGHTS_ITER
#define DNNL_ARG_WEIGHTS_LAYER
#define DNNL_ARG_WEIGHTS_PEEPHOLE
#define DNNL_ARG_WEIGHTS_PROJECTION
#define DNNL_ARG_WORKSPACEDetailed Documentation
Common operations to create, destroy and inspect primitives.
Typedefs
typedef struct dnnl_primitive_desc* dnnl_primitive_desc_tA primitive descriptor handle.
typedef const struct dnnl_primitive_desc* const_dnnl_primitive_desc_tA constant primitive descriptor handle.
typedef struct dnnl_primitive* dnnl_primitive_tA primitive handle.
typedef const struct dnnl_primitive* const_dnnl_primitive_tA constant primitive handle.
Global Functions
dnnl_primitive_kind_t dnnl::convert_to_c(primitive::kind akind)Converts primitive kind enum value from C++ API to C API type.
Parameters:
akind |
C++ API primitive kind enum value. |
Returns:
Corresponding C API primitive kind enum value.
dnnl_normalization_flags_t dnnl::convert_to_c(normalization_flags flags)Converts normalization flags enum value from C++ API to C API type.
Parameters:
flags |
C++ API normalization flags enum value. |
Returns:
Corresponding C API normalization flags enum value.
dnnl_query_t dnnl::convert_to_c(query aquery)Converts query enum value from C++ API to C API type.
Parameters:
aquery |
C++ API query enum value. |
Returns:
Corresponding C API query enum value.
dnnl_status_t DNNL_API dnnl_primitive_desc_next_impl(dnnl_primitive_desc_t primitive_desc)Changes the primitive descriptor to point to the next available implementation.
Parameters:
primitive_desc |
A primitive descriptor to change. |
Returns:
dnnl_success on success and a status describing the error otherwise.
dnnl_last_impl_reached if no more implementations available, in which case the primitive descriptor itself is kept unchanged.
dnnl_status_t DNNL_API dnnl_primitive_desc_clone(
dnnl_primitive_desc_t* primitive_desc,
const_dnnl_primitive_desc_t existing_primitive_desc
)Clones a primitive descriptor.
The resulting primitive descriptor must be destroyed separately.
Parameters:
primitive_desc |
Output primitive descriptor. |
existing_primitive_desc |
Primitive descriptor to clone. |
Returns:
dnnl_success on success and a status describing the error otherwise.
dnnl_status_t DNNL_API dnnl_primitive_desc_get_attr(
const_dnnl_primitive_desc_t primitive_desc,
const_dnnl_primitive_attr_t* attr
)Returns a constant reference to the attributes of a primitive descriptor.
WARNING:
It is an error to destroy the resulting attr.
WARNING:
The lifetime of an attr is the same as that of a primitive_desc, so it is an error to use the attr once the primitive_desc has been destroyed.
Parameters:
primitive_desc |
Primitive descriptor. |
attr |
Output primitive attributes. |
Returns:
dnnl_success on success and a status describing the error otherwise.
dnnl_status_t DNNL_API dnnl_primitive_desc_destroy(dnnl_primitive_desc_t primitive_desc)Destroys a primitive descriptor.
Parameters:
primitive_desc |
Primitive descriptor to destroy. |
Returns:
dnnl_success on success and a status describing the error otherwise.
dnnl_status_t DNNL_API dnnl_primitive_desc_query(
const_dnnl_primitive_desc_t primitive_desc,
dnnl_query_t what,
int index,
void* result
)Queries a primitive descriptor for various pieces of information.
The most common use case is to query a primitive descriptor, created with source, weights, and destination memory descriptors with format tags set to dnnl_format_tag_any, for the corresponding memory descriptors (in this case the what is set to dnnl_query_src_md, dnnl_query_weights_md, and dnnl_query_dst_md respectively) so that it is possible to create memory objects and reorder primitives if necessary.
Another typical use case is to query a primitive descriptor for workspace memory descriptor (with what set to dnnl_query_workspace_md). If this query returns dnnl_not_required status, then workspace memory is not required.
NOTE:
When querying for a memory descriptor for a scratchpad, a workspace, or an optional parameter, the query will return a pointer to a zero memory descriptor if the parameter is not needed.
A few other use cases:
query a primitive descriptor for the implementation information string (dnnl_query_impl_info_str)
query a primitive descriptor for the number of inputs and outputs (dnnl_query_num_of_inputs_s32 and dnnl_query_num_of_outputs_s32 respectively)
Parameters:
primitive_desc |
Primitive descriptor. |
what |
Parameter to query. |
index |
Index of the parameter to query for. |
result |
Output result. The type depends on the query. For example, it must be a dnnl_memory_desc_t* if querying for a memory descriptor. |
Returns:
dnnl_success on success and a status describing the error otherwise.
See also:
dnnl_query_t for more options
const_dnnl_memory_desc_t DNNL_API dnnl_primitive_desc_query_md(
const_dnnl_primitive_desc_t primitive_desc,
dnnl_query_t what,
int index
)Queries primitive descriptor for a memory descriptor.
NOTE:
This function is a convenience version of dnnl_primitive_desc_query().
Parameters:
primitive_desc |
Primitive descriptor. |
what |
Kind of memory descriptor parameter to query for. |
index |
Index of the parameter to query. |
Returns:
A pointer to the requested memory descriptor.
A pointer to a zero memory descriptor if the parameter is not needed.
NULL in case of any error.
int DNNL_API dnnl_primitive_desc_query_s32(
const_dnnl_primitive_desc_t primitive_desc,
dnnl_query_t what,
int index
)Queries primitive descriptor for a signed 32bit int.
NOTE:
This function is a convenience version of dnnl_primitive_desc_query().
Parameters:
primitive_desc |
Primitive descriptor. |
what |
Kind of the value to query for. |
index |
Index of the parameter to query. |
Returns:
The requested value.
0 in case of any error (in particular if the queried entity is not of type int32_t). Note that 0 may also be the actual returned value.
dnnl_status_t DNNL_API dnnl_primitive_create(
dnnl_primitive_t* primitive,
const_dnnl_primitive_desc_t primitive_desc
)Creates a primitive.
Parameters:
primitive |
Output primitive. |
primitive_desc |
Primitive descriptor used to create the primitive. |
Returns:
dnnl_success on success and a status describing the error otherwise.
dnnl_status_t DNNL_API dnnl_primitive_create_from_cache_blob(
dnnl_primitive_t* primitive,
const_dnnl_primitive_desc_t primitive_desc,
size_t size,
const uint8_t* cache_blob
)Creates a primitive from a cache blob.
Parameters:
primitive |
Output primitive. |
primitive_desc |
Primitive descriptor used to create the primitive. |
size |
Size of the cache blob in bytes. |
cache_blob |
Cache blob of size size. |
Returns:
dnnl_success on success and a status describing the error otherwise.
dnnl_status_t DNNL_API dnnl_primitive_execute(
const_dnnl_primitive_t primitive,
dnnl_stream_t stream,
int nargs,
const dnnl_exec_arg_t* args
)Executes a primitive.
NOTE:
If any argument in args is padded (padded_dims > dims), the primitive execution will assume properly zero-padded input arguments, and produce zero-padded output arguments.
Parameters:
primitive |
Primitive to execute. |
stream |
Stream to use. |
nargs |
Number of arguments. |
args |
Array of arguments. Each argument is an <index, dnnl_memory_t> pair. The index is one of the DNNL_ARG_* values such as DNNL_ARG_SRC. Unless runtime shapes are used (see DNNL_RUNTIME_DIM_VAL), the memory object must have the same memory descriptor as that returned by dnnl_primitive_desc_query_md (dnnl_query_exec_arg_md, index). |
Returns:
dnnl_success on success and a status describing the error otherwise.
dnnl_status_t DNNL_API dnnl_primitive_get_primitive_desc(
const_dnnl_primitive_t primitive,
const_dnnl_primitive_desc_t* primitive_desc
)Retrieves a constant reference to the primitive descriptor of a given primitive.
WARNING:
It is an error to destroy the returned object. It is owned by the primitive. The const qualifier of the returned object prevents such attempts.
Parameters:
primitive |
Primitive to query for the primitive descriptor. |
primitive_desc |
Output primitive descriptor. |
Returns:
dnnl_success on success and a status describing the error otherwise.
dnnl_status_t DNNL_API dnnl_primitive_get_cache_blob(
const_dnnl_primitive_t primitive,
size_t* size,
uint8_t* cache_blob
)Retrieves a cache blob associated with the given primitive.
NOTE:
The cache blob can be empty. It’s the user’s responsibility to check whether it’s empty prior to passing it to dnnl_primitive_create_from_cache_blob().
Parameters:
primitive |
Primitive to query for the cache blob. |
size |
Size of the cache blob in bytes. |
cache_blob |
Cache blob of size size. If the cache_blob is nullptr then the size of the cache blob is returned in size. |
Returns:
dnnl_success on success and a status describing the error otherwise.
dnnl_status_t DNNL_API dnnl_primitive_destroy(dnnl_primitive_t primitive)Destroys a primitive.
Parameters:
primitive |
The primitive to destroy. |
Returns:
dnnl_success on success and a status describing the error otherwise.
Macros
#define DNNL_ARG_ATTR_MULTIPLE_POST_OP(idx)Arguments for a binary post operation.
Up to 32 arguments are supported. See dev_guide_attributes_post_ops_binary_fusion
#define DNNL_ARG_ATTR_MULTIPLE_POST_OP_BASEStarting point for a binary post operation.
#define DNNL_ARG_ATTR_OUTPUT_SCALESOutput scaling factors provided at execution time.
#define DNNL_ARG_ATTR_POST_OP_DWArguments for fused depthwise convolution.
See dev_guide_attributes_post_ops_depthwise_fusion
#define DNNL_ARG_ATTR_SCALESScaling factors provided at execution time.
#define DNNL_ARG_ATTR_ZERO_POINTSZero points provided at execution time.
#define DNNL_ARG_AUGRU_ATTENTIONA special mnemonic for RNN input recurrent cell attention vector.
An alias for DNNL_ARG_SRC_3.
#define DNNL_ARG_BIASBias tensor argument.
#define DNNL_ARG_DIFF_AUGRU_ATTENTIONA special mnemonic for gradient (diff) of RNN input recurrent cell attention vector.
An alias for DNNL_ARG_DIFF_SRC_3.
#define DNNL_ARG_DIFF_BIASGradient (diff) of the bias tensor argument.
#define DNNL_ARG_DIFF_DSTA special mnemonic for primitives that have a single diff destination argument.
An alias for DNNL_ARG_DIFF_DST_0.
#define DNNL_ARG_DIFF_DST_0Gradient (diff) of the destination argument #0.
#define DNNL_ARG_DIFF_DST_1Gradient (diff) of the destination argument #1.
#define DNNL_ARG_DIFF_DST_2Gradient (diff) of the destination argument #2.
#define DNNL_ARG_DIFF_DST_ITERA special mnemonic for gradient (diff) of RNN input recurrent hidden state vector.
An alias for DNNL_ARG_DIFF_DST_1.
#define DNNL_ARG_DIFF_DST_ITER_CA special mnemonic for gradient (diff) of RNN input recurrent cell state vector.
An alias for DNNL_ARG_DIFF_DST_2.
#define DNNL_ARG_DIFF_DST_LAYERA special mnemonic for gradient (diff) of RNN output vector.
An alias for DNNL_ARG_DIFF_DST_0.
#define DNNL_ARG_DIFF_SCALEA special mnemonic for scale argument of normalization primitives.
#define DNNL_ARG_DIFF_SHIFTA special mnemonic for shift argument of normalization primitives.
#define DNNL_ARG_DIFF_SRCA special mnemonic for primitives that have a single diff source argument.
An alias for DNNL_ARG_DIFF_SRC_0.
#define DNNL_ARG_DIFF_SRC_0Gradient (diff) of the source argument #0.
#define DNNL_ARG_DIFF_SRC_1Gradient (diff) of the source argument #1.
#define DNNL_ARG_DIFF_SRC_2Gradient (diff) of the source argument #2.
#define DNNL_ARG_DIFF_SRC_3Gradient (diff) of the source argument #3.
#define DNNL_ARG_DIFF_SRC_ITERA special mnemonic for gradient (diff) of RNN input recurrent hidden state vector.
An alias for DNNL_ARG_DIFF_SRC_1.
#define DNNL_ARG_DIFF_SRC_ITER_CA special mnemonic for gradient (diff) of RNN input recurrent cell state vector.
An alias for DNNL_ARG_DIFF_SRC_1.
#define DNNL_ARG_DIFF_SRC_LAYERA special mnemonic for gradient (diff) of RNN input vector.
An alias for DNNL_ARG_DIFF_SRC_0.
#define DNNL_ARG_DIFF_WEIGHTSA special mnemonic for primitives that have a single diff weights argument.
Alias for DNNL_ARG_DIFF_WEIGHTS_0.
#define DNNL_ARG_DIFF_WEIGHTS_0Gradient (diff) of the weights argument #0.
#define DNNL_ARG_DIFF_WEIGHTS_1Gradient (diff) of the weights argument #1.
#define DNNL_ARG_DIFF_WEIGHTS_2Gradient (diff) of the weights argument #2.
#define DNNL_ARG_DIFF_WEIGHTS_3Gradient (diff) of the weights argument #3.
#define DNNL_ARG_DIFF_WEIGHTS_ITERA special mnemonic for diff of RNN weights applied to the recurrent input.
An alias for DNNL_ARG_DIFF_WEIGHTS_1.
#define DNNL_ARG_DIFF_WEIGHTS_LAYERA special mnemonic for diff of RNN weights applied to the layer input.
An alias for DNNL_ARG_DIFF_WEIGHTS_0.
#define DNNL_ARG_DIFF_WEIGHTS_PEEPHOLEA special mnemonic for diff of RNN weights applied to the peephole weights.
An alias for DNNL_ARG_DIFF_WEIGHTS_2.
#define DNNL_ARG_DIFF_WEIGHTS_PROJECTIONA special mnemonic for diff of RNN weights applied to the projection weights.
An alias for DNNL_ARG_DIFF_WEIGHTS_3.
#define DNNL_ARG_DSTA special mnemonic for destination argument for primitives that have a single destination.
An alias for DNNL_ARG_DST_0.
#define DNNL_ARG_DST_0Destination argument #0.
#define DNNL_ARG_DST_1Destination argument #1.
#define DNNL_ARG_DST_2Destination argument #2.
#define DNNL_ARG_DST_ITERA special mnemonic for RNN input recurrent hidden state vector.
An alias for DNNL_ARG_DST_1.
#define DNNL_ARG_DST_ITER_CA special mnemonic for LSTM output recurrent cell state vector.
An alias for DNNL_ARG_DST_2.
#define DNNL_ARG_DST_LAYERA special mnemonic for RNN output vector. An alias for DNNL_ARG_DST_0.
#define DNNL_ARG_FROMA special mnemonic for reorder source argument.
An alias for DNNL_ARG_SRC_0.
#define DNNL_ARG_MEANMean values tensor argument.
#define DNNL_ARG_MULTIPLE_DSTStarting index for destination arguments for primitives that produce a variable number of destination arguments.
#define DNNL_ARG_MULTIPLE_SRCStarting index for source arguments for primitives that take a variable number of source arguments.
#define DNNL_ARG_SCALEA special mnemonic for scale argument of normalization primitives.
#define DNNL_ARG_SCRATCHPADScratchpad (temporary storage) tensor argument.
#define DNNL_ARG_SHIFTA special mnemonic for shift argument of normalization primitives.
#define DNNL_ARG_SRCA special mnemonic for source argument for primitives that have a single source.
An alias for DNNL_ARG_SRC_0.
#define DNNL_ARG_SRC_0Source argument #0.
#define DNNL_ARG_SRC_1Source argument #1.
#define DNNL_ARG_SRC_2Source argument #2.
#define DNNL_ARG_SRC_3Source argument #3.
#define DNNL_ARG_SRC_ITERA special mnemonic for RNN input recurrent hidden state vector.
An alias for DNNL_ARG_SRC_1.
#define DNNL_ARG_SRC_ITER_CA special mnemonic for RNN input recurrent cell state vector.
An alias for DNNL_ARG_SRC_2.
#define DNNL_ARG_SRC_LAYERA special mnemonic for RNN input vector.
An alias for DNNL_ARG_SRC_0.
#define DNNL_ARG_TOA special mnemonic for reorder destination argument.
An alias for DNNL_ARG_DST_0.
#define DNNL_ARG_VARIANCEVariance values tensor argument.
#define DNNL_ARG_WEIGHTSA special mnemonic for primitives that have a single weights argument.
Alias for DNNL_ARG_WEIGHTS_0.
#define DNNL_ARG_WEIGHTS_0Weights argument #0.
#define DNNL_ARG_WEIGHTS_1Weights argument #1.
#define DNNL_ARG_WEIGHTS_2Weights argument #2.
#define DNNL_ARG_WEIGHTS_3Weights argument #3.
#define DNNL_ARG_WEIGHTS_ITERA special mnemonic for RNN weights applied to the recurrent input.
An alias for DNNL_ARG_WEIGHTS_1.
#define DNNL_ARG_WEIGHTS_LAYERA special mnemonic for RNN weights applied to the layer input.
An alias for DNNL_ARG_WEIGHTS_0.
#define DNNL_ARG_WEIGHTS_PEEPHOLEA special mnemonic for RNN weights applied to the peephole weights.
An alias for DNNL_ARG_WEIGHTS_2.
#define DNNL_ARG_WEIGHTS_PROJECTIONA special mnemonic for RNN weights applied to the projection weights.
An alias for DNNL_ARG_WEIGHTS_3.
#define DNNL_ARG_WORKSPACEWorkspace tensor argument.
Workspace is used to pass information from forward propagation to backward propagation computations.