23 class INFERENCE_ENGINE_API_CLASS(BlockingDesc) {
96 return offsetPaddingToData;
105 return offsetPadding;
152 size_t offsetPadding;
158 class INFERENCE_ENGINE_API_CLASS(TensorDesc) {
346 ROI(
size_t id,
size_t posX,
size_t posY,
size_t sizeX,
size_t sizeY) :
347 id(id), posX(posX), posY(posY), sizeX(sizeX), sizeY(sizeY) {
364 bool useOrigMemDesc);
This class describes blocking layouts.
Definition: ie_layouts.h:23
size_t getOffsetPadding() const
Returns the offset to the current memory block.
Definition: ie_layouts.h:104
const SizeVector & getBlockDims() const
Returns the blocked dimensions vector.
Definition: ie_layouts.h:77
BlockingDesc(const SizeVector &blocked_dims, const SizeVector &order)
The constructor allows to create blocking descriptors for blocked memory.
const SizeVector & getStrides() const
Returns strides for each dimension.
Definition: ie_layouts.h:113
BlockingDesc(const SizeVector &blocked_dims, const SizeVector &order, size_t offset, const SizeVector &dimOffsets)
The constructor allows to create blocking descriptors for blocked memory.
bool operator!=(const BlockingDesc &rhs) const
The comparison operator for the BlockingDesc.
BlockingDesc(const SizeVector &blocked_dims, const SizeVector &order, size_t offset, const SizeVector &dimOffsets, const SizeVector &strides)
The constructor allows to create blocking descriptors for blocked memory.
BlockingDesc(const SizeVector &blocked_dims, const SizeVector &order, size_t offset)
The constructor allows to create blocking descriptors for blocked memory.
const SizeVector & getOffsetPaddingToData() const
Returns the per-dimension offset vector.
Definition: ie_layouts.h:95
bool operator==(const BlockingDesc &rhs) const
The comparison operator for the BlockingDesc.
const SizeVector & getOrder() const
Returns the vector of order.
Definition: ie_layouts.h:86
BlockingDesc()
The default constructor which creates empty blocking descriptor.
BlockingDesc(const SizeVector &dims, Layout layout)
The constructor which allows to create blocking descriptors for standard layouts.
void fillDesc(const SizeVector &blocked_dims, const SizeVector &order)
Fills tensor descriptor based on blocking dimensions and specific order.
This class holds precision value and provides precision related operations.
Definition: ie_precision.hpp:23
This class defines Tensor description.
Definition: ie_layouts.h:158
const BlockingDesc & getBlockingDesc() const
Returns the blocking descriptor.
Definition: ie_layouts.h:265
TensorDesc(const Precision &precision, const SizeVector &dims, const BlockingDesc &blockDesc)
The constructor creates the tensor descriptor using blocking descriptor.
Layout getLayout() const
Returns the memory layout.
Definition: ie_layouts.h:231
void reshape(const SizeVector &dims, Layout layout=Layout::ANY)
Reshapes the tensor descriptor.
bool operator==(const TensorDesc &rhs) const
The comparison operator for the TensorDesc.
void reshape(const SizeVector &dims, const BlockingDesc &blockDesc)
Reshapes the tensor descriptor.
void setLayout(Layout l)
Sets the layout.
size_t offset(const SizeVector &v) const
Calculates offset for the vector of dimensions.
TensorDesc(const Precision &precision, Layout layout)
The constructor creates the empty tensor descriptor with precision and layout.
void setPrecision(const Precision &p)
Sets the memory precision.
Definition: ie_layouts.h:256
TensorDesc(const Precision &precision, const SizeVector &dims, Layout layout)
The constructor creates the tensor descriptor using standard layout.
const SizeVector & getDims() const noexcept
Returns the constant vector of dimensions.
Definition: ie_layouts.h:216
static Layout getLayoutByDims(const SizeVector &dims)
Returns the standard layout for dimensions.
void setDims(const SizeVector &dims)
Sets dimensions.
TensorDesc()
The default constructor which creates empty tensor descriptor.
SizeVector & getDims()
Returns the vector of dimensions.
Definition: ie_layouts.h:208
bool operator!=(const TensorDesc &rhs) const
The comparison operator for the TensorDesc.
size_t offset(size_t l) const
Calculates offset for the local offset.
const Precision & getPrecision() const
Returns the memory precision.
Definition: ie_layouts.h:247
The macro defines a symbol import/export mechanism essential for Microsoft Windows(R) OS.
This is a header file with common inference engine definitions.
A header file that provides class for describing precision of data.
Inference Engine C++ API.
Definition: cldnn_config.hpp:15
Layout
Layouts that the inference engine supports.
Definition: ie_common.h:63
std::vector< size_t > SizeVector
Represents tensor size.
Definition: ie_common.h:27
TensorDesc make_roi_desc(const TensorDesc &origDesc, const ROI &roi, bool useOrigMemDesc)
Creates a TensorDesc object for ROI.
This structure describes ROI data for image-like tensors.
Definition: ie_layouts.h:329
ROI(size_t id, size_t posX, size_t posY, size_t sizeX, size_t sizeY)
Creates a ROI objects with given parameters.
Definition: ie_layouts.h:346