Inference Engine API. More...
Namespaces | |
Builder | |
Neural network builder API. | |
CLDNNConfigParams | |
GPU plugin configuration. | |
DLIAConfigParams | |
DLIA plugin configuration. | |
DliaMetrics | |
DLIA plugin metrics. | |
GNAConfigParams | |
GNA plugin configuration. | |
HeteroConfigParams | |
Heterogeneous plugin configuration. | |
Metrics | |
Metrics | |
MultiDeviceConfigParams | |
Multi Device plugin configuration. | |
PluginConfigParams | |
Generic plugin configuration. | |
VPUConfigParams | |
VPU plugin configuration. | |
Data Structures | |
class | BatchNormalizationLayer |
This class represents a Batch Normalization Layer. More... | |
class | BinaryConvolutionLayer |
This class represents a standard binary convolution layer. More... | |
class | Blob |
This class represents a universal container in the Inference Engine. More... | |
class | BlockingDesc |
This class describes blocking layouts. More... | |
class | BroadcastLayer |
This class represents a standard Broadcast layer. More... | |
class | BucketizeLayer |
This class represents Bucketize layer Bucketize layer bucketizes the input based on the boundaries. More... | |
class | ClampLayer |
This class represents a Clamp activation layer. More... | |
class | CNNLayer |
This is a base abstraction Layer - all DNN Layers inherit from this class. More... | |
class | CNNNetwork |
This class contains all the information about the Neural Network and the related binary information. More... | |
class | CompoundBlob |
This class represents a blob that contains other blobs. More... | |
class | ConcatLayer |
This class represents concatenation layer. More... | |
class | Connection |
This class is the main object to describe the Inference Engine connection. More... | |
class | Context |
This class implements object. More... | |
class | ConvolutionLayer |
This class represents a standard 3D Convolution Layer. More... | |
class | Core |
This class represents Inference Engine Core entity. More... | |
class | CropLayer |
This class represents a standard crop layer. More... | |
class | Data |
This class represents the main Data representation node. More... | |
struct | DataConfig |
This structure describes data configuration. More... | |
class | DeconvolutionLayer |
This class represents a standard deconvolution layer. More... | |
class | DeformableConvolutionLayer |
This class represents a standard deformable convolution layer. More... | |
class | DepthToSpaceLayer |
This class represents a standard Depth To Space layer Depth To Space picks from input tensor according parameters. More... | |
class | EltwiseLayer |
This class represents an element wise operation layer. More... | |
class | ExecutableNetwork |
wrapper over IExecutableNetwork More... | |
class | ExperimentalSparseWeightedReduceLayer |
This class represents ExperimentalSparseWeightedReduce layer ExperimentalSparseWeightedReduce layer reduces data along sparse segments of a tensor. More... | |
class | Extension |
This class is a C++ helper to work with objects created using extensions. More... | |
class | FillLayer |
This class represents a standard Fill layer. More... | |
class | FullyConnectedLayer |
This class represents a fully connected layer. More... | |
class | GatherLayer |
This class represents a standard Gather layer. More... | |
class | GemmLayer |
This class represents a general matrix multiplication operation layer. More... | |
class | GeneralError |
This class represents StatusCode::GENERIC_ERROR exception. More... | |
class | GRNLayer |
This class represents standard GRN Layer. More... | |
class | GRUCell |
GRU Cell layer. More... | |
class | I420Blob |
Represents a blob that contains three planes (Y,U and V) in I420 color format. More... | |
class | IAllocator |
Allocator concept to be used for memory management and is used as part of the Blob. More... | |
class | ICNNNetwork |
This is the main interface to describe the NN topology. More... | |
class | ICNNNetworkStats |
This is the interface to describe the NN topology scoring statistics. More... | |
class | IErrorListener |
This class represents a custom error listener. More... | |
class | IExecutableNetwork |
This is an interface of an executable network. More... | |
class | IExtension |
This class is the main extension interface. More... | |
class | IInferRequest |
This is an interface of asynchronous infer request. More... | |
class | ILayer |
This class is the main interface to describe the Inference Engine layer. More... | |
class | ILayerExecImpl |
This class provides interface for the implementation with the custom execution code. More... | |
class | ILayerImpl |
This class provides interface for extension implementations. More... | |
class | ILayerImplFactory |
This class provides interface for extension factories. More... | |
class | IMemoryState |
manages data for reset operations More... | |
class | INetwork |
This class is the main interface to describe the Inference Engine network. More... | |
class | INetwotkIterator |
class | InferenceEngine |
This class is a C++ API wrapper for IInferencePlugin. More... | |
struct | InferenceEngineProfileInfo |
Represents basic inference profiling information per layer. More... | |
class | InferNotStarted |
This class represents StatusCode::INFER_NOT_STARTED exception. More... | |
class | InferRequest |
class | InputInfo |
This class contains information about each input of the network. More... | |
class | IShapeInferExtension |
This class is the reader extension interface to provide implementation for shape propagation. More... | |
class | IShapeInferImpl |
This class provides interface for the implementation with the custom execution code. More... | |
struct | LayerConfig |
This structure describes Layer configuration. More... | |
struct | LayerParams |
This is an internal common Layer parameter parsing arguments. More... | |
class | LockedMemory |
This class represents locked memory for read/write memory. More... | |
class | LockedMemory< const T > |
This class is for read-only segments. More... | |
class | LockedMemory< void > |
This class is for <void*> data and allows casting to any pointers. More... | |
class | LSTMCell |
LSTM Cell layer. More... | |
class | MathLayer |
This class represents a standard Math layers. More... | |
class | MemoryBlob |
This class implements a container object that represents a tensor in memory (host and remote/accelerated) More... | |
class | MemoryState |
C++ exception based error reporting wrapper of API class IMemoryState. More... | |
class | MVNLayer |
This class represents standard MVN Layer. More... | |
class | NetworkNodeStats |
This class implements a container which stores statistics for a layer. More... | |
class | NetworkNotLoaded |
This class represents StatusCode::NETWORK_NOT_LOADED exception. More... | |
class | NonMaxSuppressionLayer |
This class represents a standard NonMaxSuppression layer. More... | |
class | NormLayer |
This class represents a Linear Response Normalization (LRN) Layer. More... | |
class | NotAllocated |
This class represents StatusCode::NOT_ALLOCATED exception. More... | |
class | NotFound |
This class represents StatusCode::NOT_FOUND exception. More... | |
class | NotImplemented |
This class represents StatusCode::NOT_IMPLEMENTED exception. More... | |
class | NV12Blob |
Represents a blob that contains two planes (Y and UV) in NV12 color format. More... | |
class | OneHotLayer |
This class represents a OneHot layer Converts input into OneHot representation. More... | |
class | OutOfBounds |
This class represents StatusCode::OUT_OF_BOUNDS exception. More... | |
class | PadLayer |
This class represents a standard Pad layer. More... | |
class | Parameter |
This class represents an object to work with different parameters. More... | |
class | ParameterMismatch |
This class represents StatusCode::PARAMETER_MISMATCH exception. More... | |
class | PoolingLayer |
This class represents a standard pooling layer. More... | |
class | Port |
This class is the main object to describe the Inference Engine port. More... | |
class | PortData |
class | PortInfo |
This class contains a pair from layerId and port index. More... | |
class | PowerLayer |
This class represents a standard Power Layer. More... | |
class | Precision |
This class holds precision value and provides precision related operations. More... | |
struct | PrecisionTrait |
Particular precision traits. More... | |
class | PReLULayer |
This class represents a Layer which performs Scale and Shift. More... | |
struct | PreProcessChannel |
This structure stores info about pre-processing of network inputs (scale, mean image, ...) More... | |
class | PreProcessInfo |
This class stores pre-process information for the input. More... | |
struct | PrimitiveInfo |
Structure with information about Primitive. More... | |
class | PropertyVector |
class | QuantizeLayer |
This class represents a quantization operation layer. More... | |
struct | QueryNetworkResult |
Responce structure encapsulating information about supported layer. More... | |
class | RangeLayer |
This class represents a standard RangeLayer layer. More... | |
class | ReduceLayer |
This class represents a standard Reduce layers. More... | |
class | ReLU6Layer |
This class represents a ReLU6 activation layer. More... | |
class | ReLULayer |
This class represents a Rectified Linear activation layer. More... | |
class | RemoteBlob |
This class represents an Inference Engine abstraction to the memory allocated on the remote (non-CPU) accelerator device. More... | |
class | RemoteContext |
This class represents an Inference Engine abstraction for remote (non-CPU) accelerator device-specific execution context. Such context represents a scope on the device within which executable networks and remote memory blobs can exist, function and exchange data. More... | |
class | RequestBusy |
This class represents StatusCode::REQUEST_BUSY exception. More... | |
class | ReshapeLayer |
This class represents a standard reshape layer. More... | |
struct | ResponseDesc |
Represents detailed information for an error. More... | |
class | ResultNotReady |
This class represents StatusCode::RESULT_NOT_READY exception. More... | |
class | ReverseSequenceLayer |
This class represents a standard Reverse Sequence layer. More... | |
class | RNNCell |
RNN Cell layer. More... | |
class | RNNCellBase |
Base class for recurrent cell layers. More... | |
class | RNNSequenceLayer |
Sequence of recurrent cells. More... | |
struct | ROI |
This structure describes ROI data. More... | |
class | ScaleShiftLayer |
This class represents a Layer which performs Scale and Shift. More... | |
class | ScatterLayer |
This class represents a standard Scatter layer. More... | |
class | SelectLayer |
This class represents a SelectLayer layer. More... | |
class | ShapeInferExtension |
This class is a C++ helper to work with objects created using extensions. More... | |
class | ShuffleChannelsLayer |
This class represents a standard Shuffle Channels layer Shuffle Channels picks from input tensor according parameters. More... | |
class | SoftMaxLayer |
This class represents standard softmax Layer. More... | |
class | SpaceToDepthLayer |
This class represents a standard Space To Depth layer Depth To Space picks from input tensor according parameters. More... | |
class | SparseFillEmptyRowsLayer |
This class represents SparseFillEmptyRows layer. More... | |
class | SparseSegmentReduceLayer |
This class represents SparseSegmentMean(SqrtN, Sum) layers SparseSegmentMean(SqrtN, Sum) layer reduces data along sparse segments of a tensor. More... | |
class | SparseToDenseLayer |
This class represents SparseToDense layer SparseToDense layer converts a sparse tensor to a dense tensor. More... | |
class | SplitLayer |
This class represents a layer that evenly splits the input into the supplied outputs. More... | |
class | StridedSliceLayer |
This class represents a standard Strided Slice layer. More... | |
class | TBlob |
Represents real host memory allocated for a Tensor/Blob per C type. More... | |
class | TensorDesc |
This class defines Tensor description. More... | |
struct | TensorInfo |
This structure describes tensor information. More... | |
class | TensorIterator |
This class represents TensorIterator layer. More... | |
class | TileLayer |
This class represents a standard Tile Layer. More... | |
class | TopKLayer |
This class represents a standard TopK layer. More... | |
class | Unexpected |
This class represents StatusCode::UNEXPECTED exception. More... | |
class | UniqueLayer |
This class represents Unique layer. More... | |
union | UserValue |
The method holds the user values to enable binding of data per graph node. More... | |
struct | Version |
Represents version information that describes plugins and the inference engine runtime library. More... | |
class | WeightableLayer |
This class represents a layer with Weights and/or Biases (e.g. Convolution/Fully Connected, etc.) More... | |
Typedefs | |
using | gpu_handle_param = void * |
Shortcut for defining a handle parameter. | |
using | BlobMap = std::map< std::string, Blob::Ptr > |
This is a convenient type for working with a map containing pairs(string, pointer to a Blob instance). | |
using | SizeVector = std::vector< size_t > |
Represents tensor size. More... | |
using | CNNLayerPtr = std::shared_ptr< CNNLayer > |
A smart pointer to the CNNLayer. | |
using | CNNLayerWeakPtr = std::weak_ptr< CNNLayer > |
A smart weak pointer to the CNNLayer. | |
using | DataPtr = std::shared_ptr< Data > |
Smart pointer to Data. | |
using | CDataPtr = std::shared_ptr< const Data > |
Smart pointer to constant Data. | |
using | DataWeakPtr = std::weak_ptr< Data > |
Smart weak pointer to Data. | |
using | OutputsDataMap = std::map< std::string, DataPtr > |
A collection that contains string as key, and Data smart pointer as value. | |
using | NetworkNodeStatsPtr = std::shared_ptr< NetworkNodeStats > |
A shared pointer to the NetworkNodeStats object. | |
using | NetworkNodeStatsWeakPtr = std::weak_ptr< NetworkNodeStats > |
A smart pointer to the NetworkNodeStats object. | |
using | NetworkStatsMap = std::map< std::string, NetworkNodeStatsPtr > |
A map of pairs: name of a layer and related statistics. | |
using | ConstOutputsDataMap = std::map< std::string, CDataPtr > |
A collection that contains string as key, and const Data smart pointer as value. | |
using | IExtensionPtr = std::shared_ptr< IExtension > |
using | IShapeInferExtensionPtr = std::shared_ptr< IShapeInferExtension > |
using | InputsDataMap = std::map< std::string, InputInfo::Ptr > |
A collection that contains string as key, and InputInfo smart pointer as value. | |
using | ConstInputsDataMap = std::map< std::string, InputInfo::CPtr > |
A collection that contains string as key, and const InputInfo smart pointer as value. | |
using | GenericLayer = class CNNLayer |
Alias for CNNLayer object. | |
using | idx_t = size_t |
A type of network objects indexes. More... | |
using | InferenceEnginePluginPtr = InferenceEngine::details::SOPointer< IInferencePlugin > |
A C++ helper to work with objects created by the plugin. More... | |
using | ParamMap = std::map< std::string, Parameter > |
An std::map object containing low-level object parameters of classes that are derived from RemoteBlob or RemoteContext. | |
Enumerations | |
enum | LockOp { LOCK_FOR_READ = 0, LOCK_FOR_WRITE } |
Allocator handle mapping type. | |
enum | Layout : uint8_t { ANY = 0, NCHW = 1, NHWC = 2, NCDHW = 3, NDHWC = 4, OIHW = 64, GOIHW = 65, OIDHW = 66, GOIDHW = 67, SCALAR = 95, C = 96, CHW = 128, HW = 192, NC = 193, CN = 194, BLOCKED = 200 } |
Layouts that the inference engine supports. | |
enum | ColorFormat : uint32_t { RAW = 0u, RGB, BGR, RGBX, BGRX, NV12, I420 } |
Extra information about input color format for preprocessing. More... | |
enum | StatusCode : int { OK = 0, GENERAL_ERROR = -1, NOT_IMPLEMENTED = -2, NETWORK_NOT_LOADED = -3, PARAMETER_MISMATCH = -4, NOT_FOUND = -5, OUT_OF_BOUNDS = -6, UNEXPECTED = -7, REQUEST_BUSY = -8, RESULT_NOT_READY = -9, NOT_ALLOCATED = -10, INFER_NOT_STARTED = -11, NETWORK_NOT_READ = -12 } |
This enum contains codes for all possible return values of the interface functions. | |
enum | eDIMS_AXIS : uint8_t { X_AXIS = 0, Y_AXIS, Z_AXIS } |
enum | MeanVariant { MEAN_IMAGE, MEAN_VALUE, NONE } |
Defines available types of mean. More... | |
enum | ResizeAlgorithm { NO_RESIZE = 0, RESIZE_BILINEAR, RESIZE_AREA } |
Represents the list of supported resize algorithms. | |
Functions | |
template<class T > | |
std::shared_ptr< T > | make_so_pointer (const file_name_t &name)=delete |
Creates a special shared_pointer wrapper for the given type from a specific shared module. More... | |
InferenceEngine::IAllocator * | CreateDefaultAllocator () noexcept |
Creates the default implementation of the Inference Engine allocator per plugin. More... | |
template<typename T , typename std::enable_if<!std::is_pointer< T >::value &&!std::is_reference< T >::value, int >::type = 0, typename std::enable_if< std::is_base_of< Blob, T >::value, int >::type = 0> | |
std::shared_ptr< T > | as (const Blob::Ptr &blob) noexcept |
Helper cast function to work with shared Blob objects. More... | |
template<typename T , typename std::enable_if<!std::is_pointer< T >::value &&!std::is_reference< T >::value, int >::type = 0, typename std::enable_if< std::is_base_of< Blob, T >::value, int >::type = 0> | |
std::shared_ptr< const T > | as (const Blob::CPtr &blob) noexcept |
Helper cast function to work with shared Blob objects. More... | |
template<typename Type > | |
InferenceEngine::TBlob< Type >::Ptr | make_shared_blob (const TensorDesc &tensorDesc) |
Creates a blob with the given tensor descriptor. More... | |
template<typename Type > | |
InferenceEngine::TBlob< Type >::Ptr | make_shared_blob (const TensorDesc &tensorDesc, Type *ptr, size_t size=0) |
Creates a blob with the given tensor descriptor from the pointer to the pre-allocated memory. More... | |
template<typename Type > | |
InferenceEngine::TBlob< Type >::Ptr | make_shared_blob (const TensorDesc &tensorDesc, const std::shared_ptr< InferenceEngine::IAllocator > &alloc) |
Creates a blob with the given tensor descriptor and allocator. More... | |
template<typename TypeTo > | |
InferenceEngine::TBlob< TypeTo >::Ptr | make_shared_blob (const TBlob< TypeTo > &arg) |
Creates a copy of given TBlob instance. More... | |
template<typename T , typename... Args, typename std::enable_if< std::is_base_of< Blob, T >::value, int >::type = 0> | |
std::shared_ptr< T > | make_shared_blob (Args &&... args) |
Creates a Blob object of the specified type. More... | |
Blob::Ptr | make_shared_blob (const Blob::Ptr &inputBlob, const ROI &roi) |
Creates a blob describing given ROI object based on the given blob with pre-allocated memory. More... | |
std::ostream & | operator<< (std::ostream &out, const Layout &p) |
std::ostream & | operator<< (std::ostream &out, const ColorFormat &fmt) |
template<> | |
std::shared_ptr< IShapeInferExtension > | make_so_pointer (const file_name_t &name) |
Creates a special shared_pointer wrapper for the given type from a specific shared module. More... | |
template<> | |
std::shared_ptr< IExtension > | make_so_pointer (const file_name_t &name) |
Creates a special shared_pointer wrapper for the given type from a specific shared module. More... | |
StatusCode | CreateExtension (IExtension *&ext, ResponseDesc *resp) noexcept |
Creates the default instance of the extension. More... | |
StatusCode | CreateShapeInferExtension (IShapeInferExtension *&ext, ResponseDesc *resp) noexcept |
Creates the default instance of the shape infer extension. More... | |
template<typename F > | |
void | parallel_nt (int nthr, const F &func) |
template<typename F > | |
void | parallel_nt_static (int nthr, const F &func) |
template<typename I , typename F > | |
void | parallel_sort (I begin, I end, const F &comparator) |
template<typename T0 , typename R , typename F > | |
R | parallel_sum (const T0 &D0, const R &input, const F &func) |
template<typename T0 , typename T1 , typename R , typename F > | |
R | parallel_sum2d (const T0 &D0, const T1 &D1, const R &input, const F &func) |
template<typename T0 , typename T1 , typename T2 , typename R , typename F > | |
R | parallel_sum3d (const T0 &D0, const T1 &D1, const T2 &D2, const R &input, const F &func) |
template<typename T > | |
T | parallel_it_init (T start) |
template<typename T , typename Q , typename R , typename... Args> | |
T | parallel_it_init (T start, Q &x, const R &X, Args &&... tuple) |
bool | parallel_it_step () |
template<typename Q , typename R , typename... Args> | |
bool | parallel_it_step (Q &x, const R &X, Args &&... tuple) |
template<typename T , typename Q > | |
void | splitter (const T &n, const Q &team, const Q &tid, T &n_start, T &n_end) |
template<typename T0 , typename F > | |
void | for_1d (const int &ithr, const int &nthr, const T0 &D0, const F &func) |
template<typename T0 , typename F > | |
void | parallel_for (const T0 &D0, const F &func) |
template<typename T0 , typename T1 , typename F > | |
void | for_2d (const int &ithr, const int &nthr, const T0 &D0, const T1 &D1, const F &func) |
template<typename T0 , typename T1 , typename F > | |
void | parallel_for2d (const T0 &D0, const T1 &D1, const F &func) |
template<typename T0 , typename T1 , typename T2 , typename F > | |
void | for_3d (const int &ithr, const int &nthr, const T0 &D0, const T1 &D1, const T2 &D2, const F &func) |
template<typename T0 , typename T1 , typename T2 , typename F > | |
void | parallel_for3d (const T0 &D0, const T1 &D1, const T2 &D2, const F &func) |
template<typename T0 , typename T1 , typename T2 , typename T3 , typename F > | |
void | for_4d (const int &ithr, const int &nthr, const T0 &D0, const T1 &D1, const T2 &D2, const T3 &D3, const F &func) |
template<typename T0 , typename T1 , typename T2 , typename T3 , typename F > | |
void | parallel_for4d (const T0 &D0, const T1 &D1, const T2 &D2, const T3 &D3, const F &func) |
template<typename T0 , typename T1 , typename T2 , typename T3 , typename T4 , typename F > | |
void | for_5d (const int &ithr, const int &nthr, const T0 &D0, const T1 &D1, const T2 &D2, const T3 &D3, const T4 &D4, const F &func) |
template<typename T0 , typename T1 , typename T2 , typename T3 , typename T4 , typename F > | |
void | parallel_for5d (const T0 &D0, const T1 &D1, const T2 &D2, const T3 &D3, const T4 &D4, const F &func) |
StatusCode | CreatePluginEngine (IInferencePlugin *&plugin, ResponseDesc *resp) noexcept |
Creates the default instance of the interface (per plugin) More... | |
RemoteBlob::Ptr | make_shared_blob (const TensorDesc &desc, RemoteContext::Ptr ctx) |
A wrapper of CreateBlob method of RemoteContext to keep consistency with plugin-specific wrappers. More... | |
std::string | fileNameToString (const file_name_t &str) |
Conversion from possibly-wide character string to a single-byte chain. | |
file_name_t | stringToFileName (const std::string &str) |
Conversion from single-byte character string to a possibly-wide one. | |
const Version * | GetInferenceEngineVersion () noexcept |
Gets the current Inference Engine version. More... | |
template<class T > | |
InferenceEngine utility functions are not a part of public API Will be removed in R2 void | TopResults (unsigned int n, TBlob< T > &input, std::vector< unsigned > &output) |
Gets the top n results from a tblob. More... | |
InferenceEngine utility functions are not a part of public API Will be removed in R2 void | TopResults (unsigned int n, Blob &input, std::vector< unsigned > &output) |
Gets the top n results from a blob. More... | |
template<typename data_t > | |
InferenceEngine utility functions are not a part of public API Will be removed in R2 void | copyFromRGB8 (uint8_t *RGB8, size_t RGB8_size, InferenceEngine::TBlob< data_t > *blob) |
Copies a 8-bit RGB image to the blob. More... | |
InferenceEngine utility functions are not a part of public API Will be removed in R2 void | ConvertImageToInput (unsigned char *imgBufRGB8, size_t lengthbytesSize, Blob &input) |
Splits the RGB channels to either I16 Blob or float blob. More... | |
template<typename T > | |
InferenceEngine utility functions are not a part of public API Will be removed in R2 void | copyToFloat (float *dst, const InferenceEngine::Blob *src) |
Copies data from a certain precision to float. More... | |
Variables | |
constexpr const int | MAX_DIMS_NUMBER = 12 |
Inference Engine API.
using InferenceEngine::idx_t = typedef size_t |
A type of network objects indexes.
using InferenceEngine::InferenceEnginePluginPtr = typedef InferenceEngine::details::SOPointer<IInferencePlugin> |
A C++ helper to work with objects created by the plugin.
Implements different interfaces.
using InferenceEngine::SizeVector = typedef std::vector<size_t> |
Represents tensor size.
The order is opposite to the order in Caffe*: (w,h,n,b) where the most frequently changing element in memory is first.
enum InferenceEngine::ColorFormat : uint32_t |
Extra information about input color format for preprocessing.
|
noexcept |
|
noexcept |
|
inline |
Splits the RGB channels to either I16 Blob or float blob.
The image buffer is assumed to be packed with no support for strides.
imgBufRGB8 | Packed 24bit RGB image (3 bytes per pixel: R-G-B) |
lengthbytesSize | Size in bytes of the RGB image. It is equal to amount of pixels times 3 (number of channels) |
input | Blob to contain the split image (to 3 channels) |
InferenceEngine utility functions are not a part of public API Will be removed in R2 void InferenceEngine::copyFromRGB8 | ( | uint8_t * | RGB8, |
size_t | RGB8_size, | ||
InferenceEngine::TBlob< data_t > * | blob | ||
) |
Copies a 8-bit RGB image to the blob.
Throws an exception in case of dimensions or input size mismatch
data_t | Type of the target blob |
RGB8 | 8-bit RGB image |
RGB8_size | Size of the image |
blob | Target blob to write image to |
InferenceEngine utility functions are not a part of public API Will be removed in R2 void InferenceEngine::copyToFloat | ( | float * | dst, |
const InferenceEngine::Blob * | src | ||
) |
Copies data from a certain precision to float.
dst | Pointer to an output float buffer, must be allocated before the call |
src | Source blob to take data from |
|
noexcept |
Creates the default implementation of the Inference Engine allocator per plugin.
|
noexcept |
Creates the default instance of the extension.
ext | Extension interface |
resp | Response description |
|
noexcept |
Creates the default instance of the interface (per plugin)
plugin | Pointer to the plugin |
resp | Pointer to the response message that holds a description of an error if any occurred |
|
noexcept |
Creates the default instance of the shape infer extension.
ext | Shape Infer Extension interface |
resp | Response description |
|
noexcept |
Gets the current Inference Engine version.
|
inline |
A wrapper of CreateBlob method of RemoteContext to keep consistency with plugin-specific wrappers.
desc | Defines the layout and dims of the blob |
ctx | Poniter to the plugin object derived from RemoteContext. |
|
inline |
Creates a blob with the given tensor descriptor.
Type | Type of the shared pointer to be created |
tensorDesc | Tensor descriptor for Blob creation |
|
inline |
Creates a blob with the given tensor descriptor from the pointer to the pre-allocated memory.
Type | Type of the shared pointer to be created |
tensorDesc | TensorDesc for Blob creation |
ptr | Pointer to the pre-allocated memory |
size | Length of the pre-allocated array |
|
inline |
Creates a blob with the given tensor descriptor and allocator.
Type | Type of the shared pointer to be created |
tensorDesc | Tensor descriptor for Blob creation |
alloc | Shared pointer to IAllocator to use in the blob |
|
inline |
Creates a copy of given TBlob instance.
TypeTo | Type of the shared pointer to be created |
arg | given pointer to blob |
std::shared_ptr<T> InferenceEngine::make_shared_blob | ( | Args &&... | args | ) |
|
inlinedelete |
Creates a special shared_pointer wrapper for the given type from a specific shared module.
name | Name of the shared library file |
name | Name of the shared library file |
|
inlinedelete |
Creates a special shared_pointer wrapper for the given type from a specific shared module.
name | Name of the shared library file |
|
inlinedelete |
Creates a special shared_pointer wrapper for the given type from a specific shared module.
name | Name of the shared library file |
|
inline |
Gets the top n results from a tblob.
n | Top n count |
input | 1D tblob that contains probabilities |
output | Vector of indexes for the top n places |
|
inline |
Gets the top n results from a blob.
n | Top n count |
input | 1D blob that contains probabilities |
output | Vector of indexes for the top n places |