Visible to Intel only — GUID: GUID-B66D1C2C-1C0E-4239-95CB-CFDA2DCA209E
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-B66D1C2C-1C0E-4239-95CB-CFDA2DCA209E
enum dnnl::graph::op::attr
Overview
Attributes of operations. More…
#include <dnnl_graph.hpp>
enum attr
{
undef = dnnl_graph_op_attr_undef,
alpha = dnnl_graph_op_attr_alpha,
beta = dnnl_graph_op_attr_beta,
epsilon = dnnl_graph_op_attr_epsilon,
max = dnnl_graph_op_attr_max,
min = dnnl_graph_op_attr_min,
momentum = dnnl_graph_op_attr_momentum,
scales = dnnl_graph_op_attr_scales,
axis = dnnl_graph_op_attr_axis,
begin_norm_axis = dnnl_graph_op_attr_begin_norm_axis,
groups = dnnl_graph_op_attr_groups,
axes = dnnl_graph_op_attr_axes,
dilations = dnnl_graph_op_attr_dilations,
dst_shape = dnnl_graph_op_attr_dst_shape,
kernel = dnnl_graph_op_attr_kernel,
order = dnnl_graph_op_attr_order,
output_padding = dnnl_graph_op_attr_output_padding,
pads_begin = dnnl_graph_op_attr_pads_begin,
pads_end = dnnl_graph_op_attr_pads_end,
shape = dnnl_graph_op_attr_shape,
sizes = dnnl_graph_op_attr_sizes,
src_shape = dnnl_graph_op_attr_src_shape,
strides = dnnl_graph_op_attr_strides,
weights_shape = dnnl_graph_op_attr_weights_shape,
zps = dnnl_graph_op_attr_zps,
exclude_pad = dnnl_graph_op_attr_exclude_pad,
keep_dims = dnnl_graph_op_attr_keep_dims,
keep_stats = dnnl_graph_op_attr_keep_stats,
per_channel_broadcast = dnnl_graph_op_attr_per_channel_broadcast,
special_zero = dnnl_graph_op_attr_special_zero,
transpose_a = dnnl_graph_op_attr_transpose_a,
transpose_b = dnnl_graph_op_attr_transpose_b,
use_affine = dnnl_graph_op_attr_use_affine,
use_dst = dnnl_graph_op_attr_use_dst,
auto_broadcast = dnnl_graph_op_attr_auto_broadcast,
auto_pad = dnnl_graph_op_attr_auto_pad,
coordinate_transformation_mode = dnnl_graph_op_attr_coordinate_transformation_mode,
data_format = dnnl_graph_op_attr_data_format,
mode = dnnl_graph_op_attr_mode,
qtype = dnnl_graph_op_attr_qtype,
rounding_type = dnnl_graph_op_attr_rounding_type,
weights_format = dnnl_graph_op_attr_weights_format,
};Detailed Documentation
Attributes of operations.
Different operations support different attributes. Check the document of each operation for what attributes are supported and what are the potential values for them. Missing required attribute or illegal attribute value may lead to failure when adding the operation to a graph.
Enum Values
undefUndefined op attribute.
alphaSpecifies an alpha attribute to an op.
betaSpecifies an beta attribute to an op.
epsilonSpecifies an epsilon attribute to an op.
maxSpecifies a max attribute to an op.
minSpecifies a min attribute to an op.
momentumSpecifies a momentum attribute to an op.
scalesSpecifies a scales attribute to an op.
axisSpecifies an axis attribute to an op.
begin_norm_axisSpecifies a begin_norm_axis attribute to an op.
groupsSpecifies a groups attribute to an op.
axesSpecifies an axes attribute to an op.
dilationsSpecifies a dilations attribute to an op.
dst_shapeSpecifies an dst_shape attribute to an op.
kernelSpecifies a kernel attribute to an op.
orderSpecifies an order attribute to an op.
output_paddingSpecifies an output_padding attribute to an op.
pads_beginSpecifies a pads_begin attribute to an op.
pads_endSpecifies a pads_end attribute to an op.
shapeSpecifies a shape attribute to an op.
sizesSpecifies a sizes attribute to an op.
src_shapeSpecifies an src_shape attribute to an op.
stridesSpecifies a strides attribute to an op.
weights_shapeSpecifies a weight_shape attribute to an op.
zpsSpecifies a zps attribute to an op.
exclude_padSpecifies an exclude_pad attribute to an op.
keep_dimsSpecifies a keep_dims attribute to an op.
keep_statsSpecifies a keep_stats attribute to an op.
per_channel_broadcastSpecifies a per_channel_broadcast attribute to an op.
special_zeroSpecifies a special_zero attribute to an op.
transpose_aSpecifies a transpose_a attribute to an op.
transpose_bSpecifies a transpose_b attribute to an op.
use_affineSpecifies an use_affine attribute to an op.
use_dstSpecifies an use_dst attribute to an op.
auto_broadcastSpecifies an auto_broadcast attribute to an op.
The value can be “none” or “numpy”.
auto_padSpecifies an auto_pad attribute to an op.
The value can be “none”, “same_upper”, “same_lower”, or “valid”.
coordinate_transformation_modeSpecifies an coordinate_transformation_mode attribute to an op.
The value can be “half_pixel” or “align_corners”. The attribute is defined for Interpolate operations.
data_formatSpecifies a data_format of an op. The value can be “NCX” or “NXC”.
modeSpecifies a mode attribute of an op.
The value can be “nearest”, “linear”, “bilinear”, or “trilinear”. The attribute is defined for Interpolate operations.
qtypeSpecifies a qtype attribute to an op.
The value can be “per_channel” or “per_tensor”. The attribute is defined for quantization operations.
rounding_typeSpecifies a rounding_type attribute to an op.
The value can be “ceil” or “floor”.
weights_formatSpecifies a weights_format of an op.
The value can be “OIX”, “XIO”, “IOX”, or “XOI”. Different operations may support different values.