diff options
Diffstat (limited to 'inference-engine/include/ie_layers.h')
| -rw-r--r-- | inference-engine/include/ie_layers.h | 249 |
1 files changed, 161 insertions, 88 deletions
diff --git a/inference-engine/include/ie_layers.h b/inference-engine/include/ie_layers.h index 6ee6e61ec..46d5d3efc 100644 --- a/inference-engine/include/ie_layers.h +++ b/inference-engine/include/ie_layers.h @@ -20,6 +20,9 @@ #include "ie_data.h" #include "ie_blob.h" #include "ie_device.hpp" +#include "ie_layers_property.hpp" + +#include "ie_icnn_network.hpp" namespace InferenceEngine { /** @@ -460,107 +463,91 @@ public: }; /** + * @brief convinenent way to declare property with backward compatibility to 2D members + */ +#define DEFINE_PROP(prop_name) \ +PropertyVector<unsigned int> prop_name;\ +unsigned int &prop_name##_x = prop_name.at(X_AXIS);\ +unsigned int &prop_name##_y = prop_name.at(Y_AXIS);\ + +/** * @brief This class represents a standard 3D Convolution Layer */ class ConvolutionLayer : public WeightableLayer { public: /** - * @brief A convolution kernel width + * @brief A convolution kernel array [X, Y, Z, ...] */ - unsigned int _kernel_x = 0; + DEFINE_PROP(_kernel); /** - * @brief A convolution kernel height + * @brief A convolution paddings begin array [X, Y, Z, ...] */ - unsigned int _kernel_y = 0; + DEFINE_PROP(_padding); /** - * @brief An input convolution stride width + * @brief A convolution paddings end array [X, Y, Z, ...] */ - unsigned int _stride_x = 1; + PropertyVector<unsigned int> _pads_end; /** - * @brief An Input convolution stride height + * @brief A convolution strides array [X, Y, Z, ...] */ - unsigned int _stride_y = 1; + DEFINE_PROP(_stride); /** - * @brief A number of output feature maps (size) generating the 3'rd output dimension + * @brief A convolution dilations array [X, Y, Z, ...] */ - unsigned int _out_depth = 0; + DEFINE_PROP(_dilation); /** - * @brief Input padding width + * @brief A number of output feature maps (size) generating the 3'rd output dimension */ - unsigned int _padding_x = 0; + unsigned int _out_depth = 0u; /** - * @brief Input padding height + * @brief Number of groups */ - unsigned int _padding_y = 0; + unsigned int _group = 1u; + /** - * @brief Dilation width + * @brief Creates a new ConvolutionLayer instance. */ - unsigned int _dilation_x = 1; + explicit ConvolutionLayer(const LayerParams &p) : WeightableLayer(p), + _kernel(2, 0u), _padding(2, 0u), _stride(2, 1u), _dilation(2, 1u) {} + /** + * @brief assignment operator + */ + ConvolutionLayer & operator = (const ConvolutionLayer & that) { + if (&that != this) { + WeightableLayer::operator=(that); + _kernel = that._kernel; + _padding = that._padding; + _pads_end = that._pads_end; + _stride = that._stride; + _dilation = that._dilation; + _out_depth = that._out_depth; + _group = that._group; + } + return *this; + } /** - * @brief Dilation height + * @brief move assignment operator */ - unsigned int _dilation_y = 1; + ConvolutionLayer& operator = (ConvolutionLayer &&) = default; /** - * @brief Number of groups + * @brief copy constructor */ - unsigned int _group = 1; - + ConvolutionLayer(const ConvolutionLayer & that) : WeightableLayer(that) { + operator = (that); + } /** - * @brief Creates a new ConvolutionLayer instance. + * @brief move constructor */ - using WeightableLayer::WeightableLayer; + ConvolutionLayer(ConvolutionLayer &&) = default; }; /** * @brief This class represents a standard deconvolution layer */ -class DeconvolutionLayer : public WeightableLayer { -public: - /** - * @brief Deconvolution kernel width - */ - unsigned int _kernel_x = 0; - /** - * @brief Deconvolution kernel height - */ - unsigned int _kernel_y = 0; - /** - * @brief Input Deconvolution stride width - */ - unsigned int _stride_x = 0; - /** - * @brief Input Deconvolution stride height - */ - unsigned int _stride_y = 0; - /** - * @brief number of output feature maps (size) generating the 3'rd output dimension - */ - unsigned int _out_depth = 0; - /** - * @brief Input padding width - */ - unsigned int _padding_x = 0; - /** - * @brief Input padding height - */ - unsigned int _padding_y = 0; - /** - * @brief Dilation width - */ - unsigned int _dilation_x = 0; - /** - * @brief Dilation height - */ - unsigned int _dilation_y = 0; - /** - * @brief Number of groups - */ - unsigned int _group = 0; - - /** - * @brief Creates a new DeconvolutionLayer instance. - */ - using WeightableLayer::WeightableLayer; +class DeconvolutionLayer : public ConvolutionLayer { + public: + using ConvolutionLayer::ConvolutionLayer; + using ConvolutionLayer::operator=; }; /** @@ -569,29 +556,21 @@ public: class PoolingLayer : public CNNLayer { public: /** - * @brief Pooling kernel width + * @brief Pooling kernel array [X, Y, Z, ...] */ - unsigned int _kernel_x = 0; + DEFINE_PROP(_kernel); /** - * @brief Pooling kernel height + * @brief Pooling paddings begin array [X, Y, Z, ...] */ - unsigned int _kernel_y = 0; + DEFINE_PROP(_padding); /** - * @brief Input Pooling stride width + * @brief Pooling paddings end array [X, Y, Z, ...] */ - unsigned int _stride_x = 0; + PropertyVector<unsigned int> _pads_end; /** - * @brief Input Pooling stride height + * @brief Pooling strides array [X, Y, Z, ...] */ - unsigned int _stride_y = 0; - /** - * @brief Input padding width - */ - unsigned int _padding_x = 0; - /** - * @brief Input padding height - */ - unsigned int _padding_y = 0; + DEFINE_PROP(_stride); /** * @enum PoolType @@ -618,9 +597,44 @@ public: /** * @brief Creates a new PoolingLayer instance. */ - using CNNLayer::CNNLayer; + explicit PoolingLayer(const LayerParams &p) : CNNLayer(p), + _kernel(2, 0u), _padding(2, 0u), _stride(2, 0u) {} + + /** + * @brief assignment operator + */ + PoolingLayer & operator = (const PoolingLayer & that) { + if (&that != this) { + CNNLayer::operator=(that); + _kernel = that._kernel; + _padding = that._padding; + _pads_end = that._pads_end; + _stride = that._stride; + _type = that._type; + _exclude_pad = that._exclude_pad; + } + return *this; + } + /** + * @brief move assignment operator + */ + PoolingLayer& operator = (PoolingLayer &&) = default; + + /** + * @brief copy constructor + */ + PoolingLayer(const PoolingLayer & that) : CNNLayer(that) { + operator=(that); + } + + /** + * @brief move constructor + */ + PoolingLayer(PoolingLayer &&) = default; }; +#undef DEFINE_PROP + /** * @brief This class represents a fully connected layer */ @@ -836,7 +850,6 @@ public: */ std::vector<int> axis; /** - * @deprecated result size is defined by second input * @brief A vector of dimensions to be preserved */ std::vector<int> dim; @@ -913,6 +926,66 @@ public: }; /** +* @brief This class represents RNN sequence layer +*/ +class RNNLayer : public WeightableLayer { +public: + CellType cellType; + + /** + * @brief An axis by which iteration is performed. Axis=0 means first input blob dimension is sequence, axis=1 means first dimension is batch. + */ + unsigned int _axis = 1; + + using WeightableLayer::WeightableLayer; + + /** + * @brief Creates a new RNNLayer instance. + */ + explicit RNNLayer(const LayerParams &p) : WeightableLayer(p) {} +}; + +/** +* @brief This class represents LSTMCell pseudo-layer to be used in TensorIterator +*/ +class LSTMCell : public WeightableLayer { +public: + using WeightableLayer::WeightableLayer; +}; + +class ICNNNetReader; +/** +* @brief This class represents TensorIterator layer +*/ +class TensorIterator : public CNNLayer { +public: + using CNNNetReaderPtr = std::shared_ptr<ICNNNetReader>; + CNNNetReaderPtr reader; + + struct BackEdge { + int fromLayer; + int fromPort; + int toLayer; + int toPort; + }; + + struct Port { + int external_port_id; + int internal_layer_id; + int internal_port_id; + int axis; + int part_size; + int stride; + }; + + std::vector<Port> input_ports; + std::vector<Port> output_ports; + std::vector<BackEdge> backEdges; + + using CNNLayer::CNNLayer; +}; + +/** * @class PReLULayer * @brief This class represents a Layer which performs Scale and Shift */ |