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openvino/inference-engine/include/ie_layouts.h
2019-10-04 19:26:43 +03:00

441 lines
12 KiB
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// Copyright (C) 2018-2019 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//
/**
* @brief A header file for data layouts and conversion between them
* @file ie_layouts.h
*/
#pragma once
#include <algorithm>
#include "ie_api.h"
#include "ie_common.h"
#include "ie_precision.hpp"
namespace InferenceEngine {
/**
* @brief This class describes blocking layouts
*/
class INFERENCE_ENGINE_API_CLASS(BlockingDesc) {
public:
/**
* @brief The default constructor which creates empty blocking descriptor
*/
BlockingDesc();
/**
* @brief The constructor which allows to create blocking descriptors for standard layouts
* @param dims real dimensions
* @param layout memory layout
*/
BlockingDesc(const SizeVector& dims, Layout layout);
/**
* @brief The constructor allows to create blocking descriptors for blocked memory
* @param blocked_dims blocked dimensions
* @param order the order of dimensions
*/
BlockingDesc(const SizeVector& blocked_dims, const SizeVector& order);
/**
* @brief The constructor allows to create blocking descriptors for blocked memory
* @param blocked_dims blocked dimensions
* @param order the order of dimensions
* @param offset offset to the current memory block
*/
BlockingDesc(const SizeVector& blocked_dims, const SizeVector& order, size_t offset);
/**
* @brief The constructor allows to create blocking descriptors for blocked memory
* @param blocked_dims blocked dimensions
* @param order the order of dimensions
* @param offset offset to the current memory block
* @param dimOffsets per-dimension offset from the padding to actual data,
*/
BlockingDesc(const SizeVector& blocked_dims, const SizeVector& order, size_t offset, SizeVector dimOffsets);
/**
* @brief The constructor allows to create blocking descriptors for blocked memory
* @param blocked_dims blocked dimensions
* @param order the order of dimensions
* @param offset offset to the current memory block
* @param dimOffsets per-dimension offset from the padding to actual data,
* @param strides strides for each dimension
*/
BlockingDesc(const SizeVector& blocked_dims, const SizeVector& order, size_t offset, SizeVector dimOffsets, SizeVector strides);
/**
* @brief Destructor
*/
virtual ~BlockingDesc() = default;
/**
* @brief Returns the blocked dimensions vector
* @return blocked dimensions
*/
const SizeVector& getBlockDims() const {
return blockedDims;
}
/**
* @brief Returns the vector of order
* @return order
*/
const SizeVector& getOrder() const {
return order;
}
/**
* @brief Returns the per-dimension offset vector
* @return offsets
*/
const SizeVector& getOffsetPaddingToData() const {
return offsetPaddingToData;
}
/**
* @brief Returns the offset to the current memory block
* @return offset
*/
size_t getOffsetPadding() const {
return offsetPadding;
}
/**
* @brief Returns strides for each dimension
* @return strides
*/
const SizeVector& getStrides() const {
return strides;
}
/**
* @brief The comparison operator for the BlockingDesc
* @param rhs object to compare
* @return true if objects are equal
*/
bool operator == (const BlockingDesc& rhs) const;
/**
* @brief The comparison operator for the BlockingDesc
* @param rhs object to compare
* @return true if objects aren't equal
*/
bool operator != (const BlockingDesc& rhs) const;
protected:
void fillDesc(const SizeVector& blocked_dims, const SizeVector& order);
private:
/** Blocked dimensions. */
SizeVector blockedDims;
/** Strides for blocked dimensions */
SizeVector strides;
/** The order of blocked dimensions **/
SizeVector order;
/** Per-dimension offset from the padding to actual data, the top-level
* tensor with offsets applied must lie within the padding area. */
SizeVector offsetPaddingToData;
/** Offset from memory origin to the current block, non-zero only in
* a description of a memory sub-block. */
size_t offsetPadding;
};
/**
* @brief This class defines Tensor description
*/
class INFERENCE_ENGINE_API_CLASS(TensorDesc) {
public:
/**
* @brief The constructor creates the tensor descriptor using blocking descriptor
* @param precision memory precision
* @param dims memory dimensions
* @param blockDesc blocking descriptor
*/
TensorDesc(const Precision& precision, SizeVector dims, const BlockingDesc& blockDesc);
/**
* @brief The constructor creates the tensor descriptor using standard layout
* @param precision memory precision
* @param dims memory dimensions
* @param layout memory layout
*/
TensorDesc(const Precision& precision, SizeVector dims, Layout layout);
/**
* @brief The constructor creates the empty tensor descriptor with precision and layout
* @param precision memory precision
* @param layout memory layout
*/
TensorDesc(const Precision& precision, Layout layout);
/**
* @brief The default constructor which creates empty tensor descriptor
*/
TensorDesc();
/**
* @brief Destructor
*/
virtual ~TensorDesc() = default;
/**
* @brief Reshapes the tensor descriptor
* @param dims new dimensions
* @param layout new layout if it is necessary
*/
void reshape(const SizeVector &dims, Layout layout = Layout::ANY);
/**
* @brief Reshapes the tensor descriptor
* @param dims new dimensions
* @param blockDesc new blocking descriptor
*/
void reshape(const SizeVector &dims, const BlockingDesc &blockDesc);
/**
* @brief Returns the vector of dimensions
* @return dimensions
*/
SizeVector& getDims() {
return dims;
}
/**
* @brief Returns the constant vector of dimensions
* @return dimensions
*/
const SizeVector& getDims() const noexcept {
return dims;
}
/**
* @brief Sets dimensions
* @param dims new dimensions
*/
void setDims(const SizeVector& dims);
/**
* @brief Returns the memory layout
* @return layout
*/
Layout getLayout() const {
return layout;
}
/**
* @brief Sets the layout
* @param l memory layout
*/
void setLayout(Layout l) {
bool inconsistentLayout = true;
switch (l) {
case Layout::SCALAR:
inconsistentLayout = !dims.empty();
break;
case Layout::C:
inconsistentLayout = dims.size() != 1;
break;
case Layout::BLOCKED:
case Layout::ANY:
inconsistentLayout = false;
break;
case Layout::NCDHW:
case Layout::NDHWC:
inconsistentLayout = dims.size() != 5;
break;
case Layout::OIHW:
case Layout::NCHW:
case Layout::NHWC:
inconsistentLayout = dims.size() != 4;
break;
case Layout::CHW:
inconsistentLayout = dims.size() != 3;
break;
case Layout::CN:
case Layout::NC:
case Layout::HW:
inconsistentLayout = dims.size() != 2;
break;
default:
break;
}
if (inconsistentLayout)
THROW_IE_EXCEPTION << "Size of dims(" << std::to_string(dims.size()) << ") and format(" << l << ") are inconsistent.";
layout = l;
}
/**
* @brief Returns the memory precision
* @return precision
*/
const Precision& getPrecision() const {
return precision;
}
/**
* @brief Sets the memory precision
* @param p precision
*/
void setPrecision(const Precision& p) {
precision = p;
}
/**
* @brief Returns the blocking descriptor
* @return blocking descriptor
*/
const BlockingDesc& getBlockingDesc() const {
return blockingDesc;
}
/**
* @brief The comparison operator for the TensorDesc
* @param rhs object to compare
* @return true if objects are equal
*/
bool operator == (const TensorDesc& rhs) const;
/**
* @brief The comparison operator for the TensorDesc
* @param rhs object to compare
* @return true if objects aren't equal
*/
bool operator != (const TensorDesc& rhs) const;
/**
* @brief Calculates offset for the vector of dimensions
* @param v vector of dimensions
* @return offset
*/
size_t offset(const SizeVector& v) const;
/**
* @brief Calculates offset for the local offset
* @param l local offset
* @return offset
*/
size_t offset(size_t l) const;
/**
* @brief Returns the standard layout for dimensions
* @param dims the vector of dimensions
* @return the standard memory layout
*/
static Layout getLayoutByDims(SizeVector dims);
private:
/**
* Memory layout
*/
Layout layout;
/**
* @brief blob's dimensions
*/
SizeVector dims;
/**
* @brief memory precision
*/
Precision precision;
/**
* Detailed information about layout construction
*/
BlockingDesc blockingDesc;
};
/**
* @deprecated Deprecated since provides dims in reverse order
*/
INFERENCE_ENGINE_DEPRECATED
static const size_t I_N = 3;
/**
* @deprecated Deprecated since provides dims in reverse order
*/
INFERENCE_ENGINE_DEPRECATED
static const size_t I_C = 2;
/**
* @deprecated Deprecated since provides dims in reverse order
*/
INFERENCE_ENGINE_DEPRECATED
static const size_t I_H = 1;
/**
* @deprecated Deprecated since provides dims in reverse order
*/
INFERENCE_ENGINE_DEPRECATED
static const size_t I_W = 0;
/**
* @deprecated Uses TensorDesc working with layouts
* @brief This class helps calculating offset in different layouts
*/
class INFERENCE_ENGINE_DEPRECATED INFERENCE_ENGINE_API_CLASS(LayoutOffsetCounter) {
private:
Layout _layout;
SizeVector _dims;
size_t _dims_count;
/**
* @brief Stores multipliers that are calculated during the LayoutOffsetCounter construction.
* The multipliers are used for conversion.
*/
SizeVector _muls;
public:
/**
* @brief A default constructor
* @param dims Tensor dimension array (reverse NCHW order as in the IR: w,h,c,n)
*/
LayoutOffsetCounter(Layout layout, SizeVector dims);
IE_SUPPRESS_DEPRECATED_START
/**
* @brief A copy constructor
*/
LayoutOffsetCounter(const LayoutOffsetCounter & l);
/**
* @brief A copy assignment operator
* @param l A value to copy from
*/
LayoutOffsetCounter & operator = (const LayoutOffsetCounter & l);
IE_SUPPRESS_DEPRECATED_END
/**
* @brief A destructor
*/
~LayoutOffsetCounter();
/**
* @brief Calculates an offset for the specified layout
* @param pos Tensor position array (reverse NCHW order as in the IR: w,h,c,n)
*/
size_t Offset(SizeVector pos);
};
/**
* @deprecated Please use TensorDesc for conversion
*/
template<typename T>
INFERENCE_ENGINE_DEPRECATED
void ConvertLayout(Layout sourceLayout, Layout destLayout, const T* sourceBuffer, T* destBuffer, SizeVector dims) {
IE_SUPPRESS_DEPRECATED_START
if (dims.size() == 0) return;
SizeVector pos(dims.size(), 0);
LayoutOffsetCounter srcOffsetCounter(sourceLayout, dims);
LayoutOffsetCounter destOffsetCounter(destLayout, dims);
while (true) {
// Setting the current item
size_t ps = srcOffsetCounter.Offset(pos);
size_t pd = destOffsetCounter.Offset(pos);
destBuffer[pd] = sourceBuffer[ps];
// Advancing pos
size_t caret = 0;
pos[caret]++;
while (pos[caret] >= dims[caret]) {
pos[caret] = 0;
caret++;
if (caret == pos.size()) {
// We have finished converting
return;
}
pos[caret]++;
}
}
IE_SUPPRESS_DEPRECATED_END
}
} // namespace InferenceEngine