38 struct INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(LayerParams) {
59 IE_SUPPRESS_DEPRECATED_START
65 LayerParams(
const LayerParams & other);
72 LayerParams & operator= (
const LayerParams & other);
74 IE_SUPPRESS_DEPRECATED_END
82 LayerParams(
const std::string & name,
const std::string & type,
Precision precision);
89 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(CNNLayer) {
91 std::shared_ptr<ngraph::Node> node;
96 IE_SUPPRESS_DEPRECATED_START
97 using Ptr = std::shared_ptr<CNNLayer>;
98 IE_SUPPRESS_DEPRECATED_END
128 IE_SUPPRESS_DEPRECATED_START_WIN
130 IE_SUPPRESS_DEPRECATED_END_WIN
142 IE_SUPPRESS_DEPRECATED_START
149 explicit CNNLayer(
const LayerParams& prms);
155 std::shared_ptr<ngraph::Node> getNode() {
163 CNNLayer(
const CNNLayer& other);
165 IE_SUPPRESS_DEPRECATED_END
177 IE_SUPPRESS_DEPRECATED_START_WIN
178 void fuse(Ptr& layer) {
181 IE_SUPPRESS_DEPRECATED_END_WIN
188 virtual const DataPtr input()
const;
193 void validateLayer();
202 static float ie_parse_float(
const std::string& str);
208 static std::string ie_serialize_float(
float value);
217 float GetParamAsFloat(
const char* param,
float def)
const;
225 float GetParamAsFloat(
const char* param)
const;
234 std::vector<float> GetParamAsFloats(
const char* param, std::vector<float> def)
const;
242 std::vector<float> GetParamAsFloats(
const char* param)
const;
251 int GetParamAsInt(
const char* param,
int def)
const;
259 int GetParamAsInt(
const char* param)
const;
268 std::vector<int> GetParamAsInts(
const char* param, std::vector<int> def)
const;
276 std::vector<int> GetParamAsInts(
const char* param)
const;
285 unsigned int GetParamAsUInt(
const char* param,
unsigned int def)
const;
293 unsigned int GetParamAsUInt(
const char* param)
const;
302 std::vector<unsigned int> GetParamAsUInts(
const char* param, std::vector<unsigned int> def)
const;
310 std::vector<unsigned int> GetParamAsUInts(
const char* param)
const;
320 bool GetParamAsBool(
const char* param,
bool def)
const;
328 bool GetParamAsBool(
const char* param)
const;
337 std::string GetParamAsString(
const char* param,
const char* def)
const;
345 bool CheckParamPresence(
const char* param)
const;
354 std::string GetParamAsString(
const char* param)
const;
362 std::vector<std::string> GetParamAsStrings(
const char* param, std::vector<std::string> def)
const;
367 std::map<std::string, std::string>
params;
372 std::map<std::string, Blob::Ptr>
blobs;
378 IE_SUPPRESS_DEPRECATED_START
380 IE_SUPPRESS_DEPRECATED_END
382 IE_SUPPRESS_DEPRECATED_START_WIN
388 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(WeightableLayer):
public CNNLayer {
390 IE_SUPPRESS_DEPRECATED_START
398 explicit WeightableLayer(
const LayerParams & prms);
400 IE_SUPPRESS_DEPRECATED_END
414 using CNNLayer::CNNLayer;
416 ~WeightableLayer()
override;
422 #define DEFINE_PROP(prop_name) \ 423 PropertyVector<unsigned int> prop_name; \ 424 unsigned int& prop_name##_x = prop_name.at(X_AXIS); \ 425 unsigned int& prop_name##_y = prop_name.at(Y_AXIS) 431 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(ConvolutionLayer):
public WeightableLayer {
466 IE_SUPPRESS_DEPRECATED_START
471 explicit ConvolutionLayer(
const LayerParams& p)
477 ConvolutionLayer& operator=(
const ConvolutionLayer& that) {
479 WeightableLayer::operator=(that);
482 _pads_end = that._pads_end;
485 _out_depth = that._out_depth;
486 _group = that._group;
494 ConvolutionLayer(
const ConvolutionLayer& that): WeightableLayer(that) {
500 ConvolutionLayer(ConvolutionLayer&&) =
default;
502 IE_SUPPRESS_DEPRECATED_END
504 ~ConvolutionLayer()
override;
511 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(DeconvolutionLayer):
public ConvolutionLayer {
513 using ConvolutionLayer::ConvolutionLayer;
514 using ConvolutionLayer::operator=;
516 ~DeconvolutionLayer()
override;
523 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(DeformableConvolutionLayer):
public ConvolutionLayer {
525 using ConvolutionLayer::ConvolutionLayer;
526 using ConvolutionLayer::operator=;
533 ~DeformableConvolutionLayer()
override;
540 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(PoolingLayer):
public CNNLayer {
563 enum PoolType { MAX = 1, AVG = 2, STOCH = 3, ROI = 4, SPACIAL_PYRAMID = 5 };
579 IE_SUPPRESS_DEPRECATED_START
584 explicit PoolingLayer(
const LayerParams& p): CNNLayer(p),
_kernel(2, 0u),
_padding(2, 0u),
_stride(2, 0u) {}
589 PoolingLayer& operator=(
const PoolingLayer& that) {
591 CNNLayer::operator=(that);
594 _pads_end = that._pads_end;
597 _exclude_pad = that._exclude_pad;
604 PoolingLayer(
const PoolingLayer& that): CNNLayer(that) {
611 PoolingLayer(PoolingLayer&&) =
default;
613 IE_SUPPRESS_DEPRECATED_END
615 ~PoolingLayer()
override;
622 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(BinaryConvolutionLayer):
public WeightableLayer {
678 IE_SUPPRESS_DEPRECATED_START
683 explicit BinaryConvolutionLayer(
const LayerParams& p)
689 BinaryConvolutionLayer& operator=(
const BinaryConvolutionLayer& that) {
691 WeightableLayer::operator=(that);
694 _pads_end = that._pads_end;
697 _out_depth = that._out_depth;
698 _group = that._group;
700 _in_depth = that._in_depth;
701 _pad_value = that._pad_value;
708 BinaryConvolutionLayer(
const BinaryConvolutionLayer& that): WeightableLayer(that) {
714 BinaryConvolutionLayer(BinaryConvolutionLayer&&) =
default;
716 IE_SUPPRESS_DEPRECATED_END
718 ~BinaryConvolutionLayer()
override;
727 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(FullyConnectedLayer):
public WeightableLayer {
737 using WeightableLayer::WeightableLayer;
739 ~FullyConnectedLayer()
override;
748 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(ConcatLayer):
public CNNLayer {
761 using CNNLayer::CNNLayer;
763 ~ConcatLayer()
override;
770 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(SplitLayer):
public CNNLayer {
775 unsigned int _axis = 1;
780 using CNNLayer::CNNLayer;
782 ~SplitLayer()
override;
789 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(NormLayer):
public CNNLayer {
815 using CNNLayer::CNNLayer;
817 ~NormLayer()
override;
824 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(SoftMaxLayer):
public CNNLayer {
833 using CNNLayer::CNNLayer;
835 ~SoftMaxLayer()
override;
842 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(GRNLayer):
public CNNLayer {
848 using CNNLayer::CNNLayer;
855 ~GRNLayer()
override;
862 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(MVNLayer):
public CNNLayer {
868 using CNNLayer::CNNLayer;
880 ~MVNLayer()
override;
887 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(ReLULayer):
public CNNLayer {
897 using CNNLayer::CNNLayer;
899 ~ReLULayer()
override;
908 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(ClampLayer):
public CNNLayer {
922 using CNNLayer::CNNLayer;
924 ~ClampLayer()
override;
933 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(ReLU6Layer):
public ClampLayer {
935 IE_SUPPRESS_DEPRECATED_START
940 explicit ReLU6Layer(
const LayerParams& prms): ClampLayer(prms) {
943 IE_SUPPRESS_DEPRECATED_END
945 ~ReLU6Layer()
override;
952 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(EltwiseLayer):
public CNNLayer {
994 using CNNLayer::CNNLayer;
996 ~EltwiseLayer()
override;
1003 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(CropLayer):
public CNNLayer {
1008 std::vector<int>
axis;
1021 using CNNLayer::CNNLayer;
1023 ~CropLayer()
override;
1030 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(ReshapeLayer):
public CNNLayer {
1048 using CNNLayer::CNNLayer;
1050 ~ReshapeLayer()
override;
1057 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(TileLayer):
public CNNLayer {
1071 using CNNLayer::CNNLayer;
1073 ~TileLayer()
override;
1080 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(ScaleShiftLayer):
public WeightableLayer {
1091 using WeightableLayer::WeightableLayer;
1093 ~ScaleShiftLayer()
override;
1100 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(TensorIterator):
public CNNLayer {
1129 using CNNLayer::CNNLayer;
1131 ~TensorIterator()
override;
1138 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(RNNCellBase):
public WeightableLayer {
1140 using WeightableLayer::WeightableLayer;
1190 ~RNNCellBase()
override;
1231 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(LSTMCell):
public RNNCellBase {
1233 using RNNCellBase::RNNCellBase;
1234 using RNNCellBase::operator=;
1236 ~LSTMCell()
override;
1273 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(GRUCell):
public RNNCellBase {
1275 using RNNCellBase::RNNCellBase;
1276 using RNNCellBase::operator=;
1278 ~GRUCell()
override;
1310 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(RNNCell):
public RNNCellBase {
1312 using RNNCellBase::RNNCellBase;
1313 using RNNCellBase::operator=;
1315 ~RNNCell()
override;
1347 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(RNNSequenceLayer):
public RNNCellBase {
1349 using RNNCellBase::RNNCellBase;
1357 unsigned int axis = 1;
1371 ~RNNSequenceLayer()
override;
1378 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(PReLULayer):
public WeightableLayer {
1392 using WeightableLayer::WeightableLayer;
1394 ~PReLULayer()
override;
1403 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(PowerLayer):
public CNNLayer {
1421 using CNNLayer::CNNLayer;
1423 ~PowerLayer()
override;
1430 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(BatchNormalizationLayer):
public WeightableLayer {
1440 using WeightableLayer::WeightableLayer;
1442 ~BatchNormalizationLayer()
override;
1451 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(GemmLayer):
public CNNLayer {
1472 using CNNLayer::CNNLayer;
1474 ~GemmLayer()
override;
1483 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(PadLayer):
public CNNLayer {
1489 enum ePadMode { Constant = 0, Edge, Reflect, Symmetric };
1510 using CNNLayer::CNNLayer;
1512 ~PadLayer()
override;
1521 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(GatherLayer):
public CNNLayer {
1530 using CNNLayer::CNNLayer;
1532 ~GatherLayer()
override;
1541 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(StridedSliceLayer):
public CNNLayer {
1571 using CNNLayer::CNNLayer;
1573 ~StridedSliceLayer()
override;
1581 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(ShuffleChannelsLayer):
public CNNLayer {
1596 using CNNLayer::CNNLayer;
1598 ~ShuffleChannelsLayer()
override;
1606 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(DepthToSpaceLayer):
public CNNLayer {
1616 using CNNLayer::CNNLayer;
1618 ~DepthToSpaceLayer()
override;
1626 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(SpaceToDepthLayer):
public CNNLayer {
1636 using CNNLayer::CNNLayer;
1638 ~SpaceToDepthLayer()
override;
1647 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(SpaceToBatchLayer):
public CNNLayer {
1661 std::vector<size_t> _pads_end;
1666 using CNNLayer::CNNLayer;
1668 ~SpaceToBatchLayer()
override;
1677 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(BatchToSpaceLayer):
public CNNLayer {
1699 using CNNLayer::CNNLayer;
1701 ~BatchToSpaceLayer()
override;
1710 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(SparseFillEmptyRowsLayer):
public CNNLayer {
1715 using CNNLayer::CNNLayer;
1717 ~SparseFillEmptyRowsLayer()
override;
1725 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(SparseSegmentReduceLayer):
public CNNLayer {
1730 using CNNLayer::CNNLayer;
1732 ~SparseSegmentReduceLayer()
override;
1740 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(ExperimentalSparseWeightedReduceLayer) :
public CNNLayer {
1745 using CNNLayer::CNNLayer;
1747 ~ExperimentalSparseWeightedReduceLayer()
override;
1755 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(SparseToDenseLayer) :
public CNNLayer {
1760 using CNNLayer::CNNLayer;
1762 ~SparseToDenseLayer()
override;
1770 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(BucketizeLayer) :
public CNNLayer {
1780 using CNNLayer::CNNLayer;
1782 ~BucketizeLayer()
override;
1791 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(ReverseSequenceLayer):
public CNNLayer {
1806 using CNNLayer::CNNLayer;
1808 ~ReverseSequenceLayer()
override;
1816 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(OneHotLayer):
public CNNLayer {
1841 using CNNLayer::CNNLayer;
1843 ~OneHotLayer()
override;
1852 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(RangeLayer):
public CNNLayer {
1857 using CNNLayer::CNNLayer;
1859 ~RangeLayer()
override;
1868 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(FillLayer):
public CNNLayer {
1873 using CNNLayer::CNNLayer;
1875 ~FillLayer()
override;
1886 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(SelectLayer):
public CNNLayer {
1891 using CNNLayer::CNNLayer;
1893 ~SelectLayer()
override;
1902 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(BroadcastLayer):
public CNNLayer {
1907 using CNNLayer::CNNLayer;
1909 ~BroadcastLayer()
override;
1918 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(QuantizeLayer):
public CNNLayer {
1928 using CNNLayer::CNNLayer;
1930 ~QuantizeLayer()
override;
1939 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(MathLayer):
public CNNLayer {
1944 using CNNLayer::CNNLayer;
1946 ~MathLayer()
override;
1955 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(ReduceLayer):
public CNNLayer {
1965 using CNNLayer::CNNLayer;
1967 ~ReduceLayer()
override;
1976 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(TopKLayer):
public CNNLayer {
1994 using CNNLayer::CNNLayer;
1996 ~TopKLayer()
override;
2005 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(UniqueLayer):
public CNNLayer {
2023 using CNNLayer::CNNLayer;
2025 ~UniqueLayer()
override;
2032 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(NonMaxSuppressionLayer):
public CNNLayer {
2046 using CNNLayer::CNNLayer;
2048 ~NonMaxSuppressionLayer()
override;
2055 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(ScatterUpdateLayer):
public CNNLayer {
2060 using CNNLayer::CNNLayer;
2062 ~ScatterUpdateLayer()
override;
2069 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(ScatterElementsUpdateLayer):
public CNNLayer {
2074 using CNNLayer::CNNLayer;
2076 ~ScatterElementsUpdateLayer()
override;
2083 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(ExperimentalDetectronPriorGridGeneratorLayer):
public CNNLayer {
2109 using CNNLayer::CNNLayer;
2111 virtual ~ExperimentalDetectronPriorGridGeneratorLayer();
2117 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(ExperimentalDetectronTopKROIs):
public CNNLayer {
2126 using CNNLayer::CNNLayer;
2128 virtual ~ExperimentalDetectronTopKROIs();
2134 class INFERENCE_ENGINE_INTERNAL_CNNLAYER_CLASS(ExperimentalDetectronGenerateProposalsSingleImageLayer):
public CNNLayer {
2156 using CNNLayer::CNNLayer;
2158 virtual ~ExperimentalDetectronGenerateProposalsSingleImageLayer();
2161 IE_SUPPRESS_DEPRECATED_END_WIN
std::vector< int > dim
A vector of dimensions to be preserved.
Definition: ie_layers.h:1012
#define DEFINE_PROP(prop_name)
convinenent way to declare property with backward compatibility to 2D members
Definition: ie_layers.h:422
CellType cellType
Direct type of recurrent cell (including subtypes) Description of particular cell semantics is in LST...
Definition: ie_layers.h:1154
unsigned int depth
A depth of representation.
Definition: ie_layers.h:1821
std::string sort
top K values sort mode could be 'value' or 'index'
Definition: ie_layers.h:1985
Ptr _fusedWith
If suggested to fuse - a pointer to the layer which needs to be fused with this layer.
Definition: ie_layers.h:129
float epsilon
A small value to add to the variance estimate to avoid division by zero.
Definition: ie_layers.h:1435
Direction
Direction of iteration through sequence dimension.
Definition: ie_layers.h:1362
int seq_axis
The seq_axis dimension in tensor which is partially reversed.
Definition: ie_layers.h:1796
std::string type
Layer type.
Definition: ie_layers.h:47
int hidden_size
Size of hidden state data.
Definition: ie_layers.h:1161
bool sort_result_descending
The 'sort_result_descending' indicates that result will sort descending by score through all batches ...
Definition: ie_layers.h:2042
std::vector< float > activation_beta
Beta parameters of activations.
Definition: ie_layers.h:1188
eBinaryConvolutionMode
Defines possible modes of binary convolution operation.
Definition: ie_layers.h:628
float off_value
The locations not represented by indices in input take value off_value.
Definition: ie_layers.h:1831
The method holds the user values to enable binding of data per graph node.
Definition: ie_common.h:69
bool _isAcrossMaps
Flag to specify normalization across feature maps (true) or across channels.
Definition: ie_layers.h:810
int axis
Definition: ie_layers.h:1108
Direction direction
Direction of iteration through sequence dimension.
Definition: ie_layers.h:1369
Definition: cldnn_config.hpp:16
PropertyVector< unsigned int > pads_end
Size of padding in the end of each axis.
Definition: ie_layers.h:1498
float max_value
A maximum value.
Definition: ie_layers.h:918
int axis
Axis number for a softmax operation.
Definition: ie_layers.h:829
std::string _auto_pad
Auto padding type.
Definition: ie_layers.h:464
std::vector< int > offset
A vector of offsets for each dimension.
Definition: ie_layers.h:1016
std::string new_axis_mask
The new_axis_mask_ is a bitmask where bit i being 1 means the i-th position creates a new 1 dimension...
Definition: ie_layers.h:1561
std::vector< float > activation_alpha
Alpha parameters of activations.
Definition: ie_layers.h:1181
Body body
A Tensor Iterator body.
Definition: ie_layers.h:1127
unsigned int _axis
An axis on which concatenation operation is performed.
Definition: ie_layers.h:753
unsigned int _size
Response size.
Definition: ie_layers.h:794
unsigned int block_size
The group of output shuffled channels.
Definition: ie_layers.h:1611
std::vector< DataWeakPtr > insData
A vector of weak pointers to the input data elements of this layer in the di-graph (order matters) ...
Definition: ie_layers.h:123
Blob::Ptr _biases
A pointer to a biases blob.
Definition: ie_layers.h:409
A header file for Blob and generic TBlob<>
std::vector< size_t > _block_shape
Spatial dimensions blocks sizes.
Definition: ie_layers.h:1652
bool transpose_a
A flag that indicates if the src1 matrix is to be transposed.
Definition: ie_layers.h:1464
eBinaryConvolutionMode _mode
Mode of binary convolution operation.
Definition: ie_layers.h:633
std::vector< PortMap > output_port_map
Output ports map.
Definition: ie_layers.h:1124
std::string shrink_axis_mask
The shrink_axis_mask is a bitmask where bit i being 1 means the i-th position shrinks the dimensional...
Definition: ie_layers.h:1566
Definition: ie_layers.h:1364
int batch_axis
The batch_axis dimension in tensor along which reversal is performed.
Definition: ie_layers.h:1801
int grid_h
Value of grid height.
Definition: ie_layers.h:2096
int across_channels
Indicate that mean value is calculated across channels.
Definition: ie_layers.h:873
Definition: ie_layers.h:1147
std::vector< size_t > _crops_begin
It specifies how many elements to crop from the intermediate result across the spatial dimensions...
Definition: ie_layers.h:1688
Definition: ie_layers.h:1102
Definition: ie_layers.h:1363
class CNNLayer GenericLayer
Alias for CNNLayer object.
Definition: ie_layers.h:379
PropertyVector< unsigned int > _kernel
A convolution kernel array [X, Y, Z, ...].
Definition: ie_layers.h:436
Describes a tensor iterator body.
Definition: ie_layers.h:1118
std::vector< DataPtr > outputs
Outputs data.
Definition: ie_layers.h:1120
std::vector< size_t > _crops_end
It specifies how many elements to crop from the intermediate result across the spatial dimensions...
Definition: ie_layers.h:1694
eOperation _operation
A type of the operation to use.
Definition: ie_layers.h:984
bool return_counts
A flag indicating whether to return a number of occurences for each unique element.
Definition: ie_layers.h:2018
PoolType _type
A pooling type.
Definition: ie_layers.h:568
Definition: ie_layers.h:1150
float stride_h
Value of height step between grid cells.
Definition: ie_layers.h:2104
std::string name
Layer name.
Definition: ie_layers.h:42
Precision precision
Layer precision.
Definition: ie_layers.h:52
std::vector< size_t > _pads_begin
Size of padding in the beginning of each axis.
Definition: ie_layers.h:1657
float nms_threshold
Non max suppression threshold.
Definition: ie_layers.h:2143
Definition: ie_layers.h:1365
int max_rois
The maximum number of output rois.
Definition: ie_layers.h:2122
float negative_slope
Negative slope is used to takle negative inputs instead of setting them to 0.
Definition: ie_layers.h:892
Definition: ie_layers_property.hpp:22
bool center_point_box
The 'center_point_box' indicates the format of the box data.
Definition: ie_layers.h:2037
PropertyVector< unsigned int > _stride
A convolution strides array [X, Y, Z, ...].
Definition: ie_layers.h:448
int tiles
A number of copies to be made.
Definition: ie_layers.h:1066
PropertyVector< unsigned int > _dilation
A convolution dilations array [X, Y, Z, ...].
Definition: ie_layers.h:452
std::string affinity
Layer affinity set by user.
Definition: ie_layers.h:140
int post_nms_topn
Maximum number of anchors selected after nms.
Definition: ie_layers.h:2151
std::string ellipsis_mask
The ellipsis_mask is a bitmask where bit i being 1 means the i-th is actually an ellipsis.
Definition: ie_layers.h:1556
unsigned int _out_num
A size of output.
Definition: ie_layers.h:732
std::shared_ptr< Blob > Ptr
A smart pointer containing Blob object.
Definition: ie_blob.h:42
float _beta
Beta coefficient.
Definition: ie_layers.h:806
bool transpose_b
A flag that indicates if the src2 matrix is to be transposed.
Definition: ie_layers.h:1468
float min_size
Minimium width and height for boxes.
Definition: ie_layers.h:2139
Definition: ie_layers.h:1148
int grid_w
Value of grid width.
Definition: ie_layers.h:2092
PropertyVector< unsigned int > _pads_end
A convolution paddings end array [X, Y, Z, ...].
Definition: ie_layers.h:444
int start
Definition: ie_layers.h:1110
a header file for describing property style structure used by CNNLayers
Definition: ie_cnn_network.h:27
float scale
A scale factor.
Definition: ie_layers.h:1412
CellType
Direct type of recurrent cell (including subtypes) Description of particular cell semantics is in LST...
Definition: ie_layers.h:1146
float pad_value
A pad value which is used for filling in Constant mode.
Definition: ie_layers.h:1506
bool with_right_bound
Indicates whether the intervals include the right or the left bucket edge.
Definition: ie_layers.h:1775
std::vector< PortMap > back_edges
Back edges map.
Definition: ie_layers.h:1125
float alpha
A scale factor of src1 matrix.
Definition: ie_layers.h:1456
This header file defines the main Data representation node.
bool keep_dims
The keep_dims dimension in tensor which is partially reversed.
Definition: ie_layers.h:1960
bool return_inverse
A flag indicating whether to return indices of input data elements in the output of uniques...
Definition: ie_layers.h:2014
unsigned int _group
Number of groups.
Definition: ie_layers.h:460
Blob::Ptr _weights
A pointer to a weights blob.
Definition: ie_layers.h:405
std::vector< float > coeff
A vector of coefficients to scale the operands.
Definition: ie_layers.h:989
std::vector< PortMap > input_port_map
Input ports map.
Definition: ie_layers.h:1123
PropertyVector< unsigned int > _padding
A convolution paddings begin array [X, Y, Z, ...].
Definition: ie_layers.h:440
int from
Definition: ie_layers.h:1104
float clip
Clip data into range [-clip, clip] on input of activations.
Definition: ie_layers.h:1168
ePadMode pad_mode
Mode of pad operation.
Definition: ie_layers.h:1502
int end
Definition: ie_layers.h:1111
unsigned int _in_depth
A number of input feature maps (size) generating the 3'rd input dimension.
Definition: ie_layers.h:638
int part_size
Definition: ie_layers.h:1112
float bias
Bias for squares sum.
Definition: ie_layers.h:853
unsigned int _k
K.
Definition: ie_layers.h:798
float power
An exponent value.
Definition: ie_layers.h:1408
float min_value
A minimum value.
Definition: ie_layers.h:913
std::map< std::string, Blob::Ptr > blobs
Map of pairs: (name, weights/biases blob)
Definition: ie_layers.h:372
int normalize
Indicate that the result needs to be normalized.
Definition: ie_layers.h:878
int num_axes
A number of first axises to be taken for a reshape.
Definition: ie_layers.h:1043
float _pad_value
A pad value which is used to fill pad area.
Definition: ie_layers.h:643
unsigned int _deformable_group
Number of deformable groups.
Definition: ie_layers.h:531
std::string end_mask
Analogous to begin_mask.
Definition: ie_layers.h:1551
std::vector< std::string > activations
Activations used inside recurrent cell.
Definition: ie_layers.h:1174
int to
Definition: ie_layers.h:1105
PropertyVector< unsigned int > pads_begin
Size of padding in the beginning of each axis.
Definition: ie_layers.h:1494
std::vector< DataPtr > outData
A vector of pointers to the output data elements of this layer in the di-graph (order matters) ...
Definition: ie_layers.h:118
float stride_w
Value of width step between grid cells.
Definition: ie_layers.h:2100
std::vector< DataPtr > inputs
Inputs data.
Definition: ie_layers.h:1119
int stride
Definition: ie_layers.h:1109
std::shared_ptr< Data > DataPtr
Smart pointer to Data.
Definition: ie_common.h:53
unsigned int _out_depth
A number of output feature maps (size) generating the 3'rd output dimension.
Definition: ie_layers.h:456
Definition: ie_layers.h:1149
std::string begin_mask
The begin_mask is a bitmask where bit i being 0 means to ignore the begin value and instead use the d...
Definition: ie_layers.h:1547
std::string mode
The mode could be 'max' or 'min'.
Definition: ie_layers.h:1981
unsigned int group
The group of output shuffled channels.
Definition: ie_layers.h:1591
std::map< std::string, std::string > params
Map of pairs: (parameter name, parameter value)
Definition: ie_layers.h:367
bool _channel_shared
A flag that indicates if the same negative_slope value is used for all the features. If false, the value is used pixel wise.
Definition: ie_layers.h:1384
int levels
The number of quantization levels.
Definition: ie_layers.h:1923
eOperation
Defines possible operations that can be used.
Definition: ie_layers.h:958
PoolType
Defines available pooling types.
Definition: ie_layers.h:563
unsigned int _broadcast
A flag that indicates if the same value is used for all the features. If false, the value is used pix...
Definition: ie_layers.h:1086
bool sorted
A flag indicating whether to sort unique elements.
Definition: ie_layers.h:2010
float _alpha
Alpha coefficient.
Definition: ie_layers.h:802
int pre_nms_topn
Maximum number of anchors selected before nms.
Definition: ie_layers.h:2147
float on_value
The locations represented by indices in input take value on_value.
Definition: ie_layers.h:1826
float beta
A scale factor of src3 matrix.
Definition: ie_layers.h:1460
ePadMode
Defines possible modes of pad operation.
Definition: ie_layers.h:1489
This is a header file with common inference engine definitions.
bool _exclude_pad
A flag that indicates if padding is excluded or not.
Definition: ie_layers.h:573
int flatten
flatten value
Definition: ie_layers.h:2088
std::vector< int > shape
A vector of sizes of the shape.
Definition: ie_layers.h:1035
This class holds precision value and provides precision related operations.
Definition: ie_precision.hpp:22
UserValue userValue
Convenience user values to store in this object as extra data.
Definition: ie_layers.h:135