Files
openvino/inference-engine/include/ie_icnn_network.hpp
openvino-pushbot 866530fb04 Publishing R3
2018-10-16 13:45:03 +03:00

182 lines
6.9 KiB
C++

// Copyright (C) 2018 Intel Corporation
//
// SPDX-License-Identifier: Apache-2.0
//
/**
* @brief This is a header file for the ICNNNetwork class
* @file ie_icnn_network.hpp
*/
#pragma once
#include "ie_common.h"
#include "ie_layers.h"
#include "ie_data.h"
#include "ie_device.hpp"
#include "ie_blob.h"
#include "details/ie_irelease.hpp"
#include "ie_preprocess.hpp"
#include "ie_input_info.hpp"
#include "ie_iextension.h"
#include <memory>
#include <map>
#include <string>
namespace InferenceEngine {
/**
* @brief A collection that contains string as key, and Data smart pointer as value
*/
using OutputsDataMap = std::map<std::string, DataPtr>;
/**
* @brief This is the main interface to describe the NN topology
*/
class ICNNNetwork : public details::IRelease {
public:
/**
* @brief Returns the main network operating precision.
* This may be MIXED if not homogeneous.
* @return A precision type
*/
virtual Precision getPrecision() const noexcept = 0;
/**
* @brief Gets the network output Data node information. The received info is stored in the given Data node.
* For single and multiple outputs networks.
* @param out Reference to the OutputsDataMap object
*/
virtual void getOutputsInfo(OutputsDataMap& out) const noexcept = 0;
/**
* @brief Gets the network input Data node information. The received info is stored in the given InputsDataMap object.
* For single and multiple inputs networks.
* This method must be called to find out input names for using them later during filling of a map
* of blobs passed later to InferenceEngine::IInferencePlugin::Infer()
* @param inputs Reference to InputsDataMap object.
*/
virtual void getInputsInfo(InputsDataMap& inputs) const noexcept = 0;
/**
* @brief Returns information on certain input pointed by inputName
* @param inputName Name of input layer to get info on
* @return A smart pointer to the input information
*/
virtual InputInfo::Ptr getInput(const std::string& inputName) const noexcept = 0;
/**
* @brief Gets the network name. The name is stored in the given pName string.
* @param pName - will receive actual network name, specified in IR file,
* pName should point to valid memory address before invoking this function
* @param len - size in bytes of pName buffer, actual name is trimmed by this size
*/
virtual void getName(char* pName, size_t len) const noexcept = 0;
/**
* @brief Returns the network name.
* @return Network name
*/
virtual const std::string& getName() const noexcept = 0;
/**
* @brief Returns the number of layers in the network as an integer value
* @return The number of layers as an integer value
*/
virtual size_t layerCount() const noexcept = 0;
/**
* @brief Returns a smart pointer reference to a Data node given its name.
* If the Data node is missing, returns reference to a default initialized new empty data pointer with given name.
* @param dname Name of the Data node
* @return Data node smart pointer
*/
virtual DataPtr& getData(const char* dname) noexcept = 0;
/**
* @brief Insert a layer into the network. A user is responsible to connect it to other data elements.
* @param layer Const reference to a layer smart pointer
*/
virtual void addLayer(const CNNLayerPtr& layer) noexcept = 0;
/**
* @brief Adds output to the layer
* @param layerName Name of the layer
* @param outputIndex Index of the output
* @param resp Response message
* @return Status code of the operation
*/
virtual StatusCode
addOutput(const std::string& layerName, size_t outputIndex = 0, ResponseDesc* resp = nullptr) noexcept = 0;
/**
* @brief Gets network layer with the given name
* @param layerName Given name of the layer
* @param out Pointer to the found CNNLayer object with the given name
* @param resp Pointer to the response message that holds a description of an error if any occurred
* @return Status code of the operation. OK if succeeded
*/
virtual StatusCode getLayerByName(const char* layerName, CNNLayerPtr& out, ResponseDesc* resp) const noexcept = 0;
/**
* @brief Sets a desirable device to perform all work on.
* Some plug-ins might not support some target devices and may abort execution with an appropriate error message.
* @param device Device to set as a target
*/
virtual void setTargetDevice(TargetDevice device) noexcept = 0;
/**
* @brief Gets the target device.
* If setTargetDevice() was not called before, returns eDefault
* @return A TargetDevice instance
*/
virtual TargetDevice getTargetDevice() const noexcept = 0;
/**
* @deprecated use setBatchSize with ResponseDesc to get error message
* @brief Changes the inference batch size
*/
virtual StatusCode setBatchSize(const size_t size) noexcept = 0;
/**
* @brief Changes the inference batch size.
* @note There are several limitations and it's not recommended to use it. Set batch to the input shape and call @reshape.
* @param size Size of batch to set
* @return Status code of the operation
* @note: Current implementation of the function sets batch size to the first dimension of 4D input layers in the networks
* and starts shape inference for IR starting from v3, for IR v2 it sets batch to the first dimension for all layers.
* Custom layers might require custom shape infer implementation, use @IShapeInferExtension interface to register them.
*/
virtual StatusCode setBatchSize(size_t size, ResponseDesc* responseDesc) noexcept = 0;
/**
* @brief Gets the inference batch size
* @return The size of batch as a size_t value
*/
virtual size_t getBatchSize() const noexcept = 0;
/**
* @brief Map of pairs: name of corresponding data and its dimension.
*/
using InputShapes = std::map<std::string, SizeVector>;
/**
* @brief - Run shape inference with new input shapes for the network
* @param inputShapes - map of pairs: name of corresponding data and its dimension.
* @note currently all inputs are required
* @param resp Pointer to the response message that holds a description of an error if any occurred
* @return Status code of the operation
*/
virtual StatusCode reshape(const InputShapes& inputShapes, ResponseDesc* resp) noexcept { return NOT_IMPLEMENTED; };
/**
* @brief Registers extension within the plugin
* @param extension Pointer to already loaded reader extension with shape propagation implementations
* @param resp Pointer to the response message that holds a description of an error if any occurred
* @return Status code of the operation. OK if succeeded
*/
virtual StatusCode
AddExtension(const IShapeInferExtensionPtr& extension, ResponseDesc* resp) noexcept { return NOT_IMPLEMENTED; };
};
} // namespace InferenceEngine