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int8 layers and 8-bit quantization support

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This commit is contained in:
SamFC10
2021-08-19 09:56:47 +05:30
parent 95919051e0
commit fa90e14b06
36 changed files with 6401 additions and 67 deletions
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modules/dnn/include/opencv2/dnn/all_layers.hpp
+86 -1
View File
@@ -258,6 +258,14 @@ CV__DNN_INLINE_NS_BEGIN
static Ptr<BaseConvolutionLayer> create(const LayerParams& params);
};
class CV_EXPORTS ConvolutionLayerInt8 : public BaseConvolutionLayer
{
public:
int input_zp, output_zp;
float output_sc;
static Ptr<BaseConvolutionLayer> create(const LayerParams& params);
};
class CV_EXPORTS DeconvolutionLayer : public BaseConvolutionLayer
{
public:
@@ -300,6 +308,13 @@ CV__DNN_INLINE_NS_BEGIN
static Ptr<PoolingLayer> create(const LayerParams& params);
};
class CV_EXPORTS PoolingLayerInt8 : public PoolingLayer
{
public:
int input_zp, output_zp;
static Ptr<PoolingLayerInt8> create(const LayerParams& params);
};
class CV_EXPORTS SoftmaxLayer : public Layer
{
public:
@@ -308,6 +323,14 @@ CV__DNN_INLINE_NS_BEGIN
static Ptr<SoftmaxLayer> create(const LayerParams& params);
};
class CV_EXPORTS SoftmaxLayerInt8 : public SoftmaxLayer
{
public:
float output_sc;
int output_zp;
static Ptr<SoftmaxLayerInt8> create(const LayerParams& params);
};
class CV_EXPORTS InnerProductLayer : public Layer
{
public:
@@ -315,6 +338,13 @@ CV__DNN_INLINE_NS_BEGIN
static Ptr<InnerProductLayer> create(const LayerParams& params);
};
class CV_EXPORTS InnerProductLayerInt8 : public InnerProductLayer
{
public:
int output_zp;
static Ptr<InnerProductLayerInt8> create(const LayerParams& params);
};
class CV_EXPORTS MVNLayer : public Layer
{
public:
@@ -341,6 +371,22 @@ CV__DNN_INLINE_NS_BEGIN
static Ptr<FlattenLayer> create(const LayerParams &params);
};
class CV_EXPORTS QuantizeLayer : public Layer
{
public:
float scale;
int zeropoint;
static Ptr<QuantizeLayer> create(const LayerParams &params);
};
class CV_EXPORTS DequantizeLayer : public Layer
{
public:
float scale;
int zeropoint;
static Ptr<DequantizeLayer> create(const LayerParams &params);
};
class CV_EXPORTS ConcatLayer : public Layer
{
public:
@@ -352,6 +398,7 @@ CV__DNN_INLINE_NS_BEGIN
* Details: https://github.com/torch/nn/blob/master/doc/containers.md#depthconcat
*/
bool padding;
int paddingValue;
static Ptr<ConcatLayer> create(const LayerParams &params);
};
@@ -459,7 +506,11 @@ CV__DNN_INLINE_NS_BEGIN
{
public:
virtual void forwardSlice(const float* src, float* dst, int len,
size_t outPlaneSize, int cn0, int cn1) const = 0;
size_t outPlaneSize, int cn0, int cn1) const {};
virtual void forwardSlice(const int* src, const int* lut, int* dst, int len,
size_t outPlaneSize, int cn0, int cn1) const {};
virtual void forwardSlice(const int8_t* src, const int8_t* lut, int8_t* dst, int len,
size_t outPlaneSize, int cn0, int cn1) const {};
};
class CV_EXPORTS ReLULayer : public ActivationLayer
@@ -542,6 +593,12 @@ CV__DNN_INLINE_NS_BEGIN
static Ptr<ExpLayer> create(const LayerParams &params);
};
class CV_EXPORTS ActivationLayerInt8 : public ActivationLayer
{
public:
static Ptr<ActivationLayerInt8> create(const LayerParams &params);
};
/* Layers used in semantic segmentation */
class CV_EXPORTS CropLayer : public Layer
@@ -563,6 +620,12 @@ CV__DNN_INLINE_NS_BEGIN
static Ptr<EltwiseLayer> create(const LayerParams &params);
};
class CV_EXPORTS EltwiseLayerInt8 : public Layer
{
public:
static Ptr<EltwiseLayerInt8> create(const LayerParams &params);
};
class CV_EXPORTS BatchNormLayer : public ActivationLayer
{
public:
@@ -572,6 +635,14 @@ CV__DNN_INLINE_NS_BEGIN
static Ptr<BatchNormLayer> create(const LayerParams &params);
};
class CV_EXPORTS BatchNormLayerInt8 : public BatchNormLayer
{
public:
float input_sc, output_sc;
int input_zp, output_zp;
static Ptr<BatchNormLayerInt8> create(const LayerParams &params);
};
class CV_EXPORTS MaxUnpoolLayer : public Layer
{
public:
@@ -591,12 +662,26 @@ CV__DNN_INLINE_NS_BEGIN
static Ptr<ScaleLayer> create(const LayerParams& params);
};
class CV_EXPORTS ScaleLayerInt8 : public ScaleLayer
{
public:
float output_sc;
int output_zp;
static Ptr<ScaleLayerInt8> create(const LayerParams &params);
};
class CV_EXPORTS ShiftLayer : public Layer
{
public:
static Ptr<Layer> create(const LayerParams& params);
};
class CV_EXPORTS ShiftLayerInt8 : public Layer
{
public:
static Ptr<Layer> create(const LayerParams& params);
};
class CV_EXPORTS DataAugmentationLayer : public Layer
{
public:
modules/dnn/include/opencv2/dnn/dnn.hpp
+46
View File
@@ -235,6 +235,15 @@ CV__DNN_INLINE_NS_BEGIN
*/
virtual void forward(InputArrayOfArrays inputs, OutputArrayOfArrays outputs, OutputArrayOfArrays internals);
/** @brief Tries to quantize the given layer and compute the quantization parameters required for fixed point implementation.
* @param[in] scales input and output scales.
* @param[in] zeropoints input and output zeropoints.
* @param[out] params Quantized parameters required for fixed point implementation of that layer.
* @returns True if layer can be quantized.
*/
virtual bool tryQuantize(const std::vector<std::vector<float> > &scales,
const std::vector<std::vector<int> > &zeropoints, LayerParams& params);
/** @brief Given the @p input blobs, computes the output @p blobs.
* @param[in] inputs the input blobs.
* @param[out] outputs allocated output blobs, which will store results of the computation.
@@ -368,6 +377,16 @@ CV__DNN_INLINE_NS_BEGIN
*/
virtual void getScaleShift(Mat& scale, Mat& shift) const;
/**
* @brief Returns scale and zeropoint of layers
* @param[out] scale Output scale
* @param[out] zeropoint Output zeropoint
*
* By default, @p scale is 1 and @p zeropoint is 0.
*/
virtual void getScaleZeropoint(float& scale, int& zeropoint) const;
/**
* @brief "Deattaches" all the layers, attached to particular layer.
*/
@@ -453,13 +472,21 @@ CV__DNN_INLINE_NS_BEGIN
/** @brief Adds new layer to the net.
* @param name unique name of the adding layer.
* @param type typename of the adding layer (type must be registered in LayerRegister).
* @param dtype datatype of output blobs.
* @param params parameters which will be used to initialize the creating layer.
* @returns unique identifier of created layer, or -1 if a failure will happen.
*/
int addLayer(const String &name, const String &type, const int &dtype, LayerParams &params);
/** @overload Datatype of output blobs set to default CV_32F */
int addLayer(const String &name, const String &type, LayerParams &params);
/** @brief Adds new layer and connects its first input to the first output of previously added layer.
* @see addLayer()
*/
int addLayerToPrev(const String &name, const String &type, const int &dtype, LayerParams &params);
/** @overload */
int addLayerToPrev(const String &name, const String &type, LayerParams &params);
/** @brief Converts string name of the layer to the integer identifier.
@@ -551,6 +578,25 @@ CV__DNN_INLINE_NS_BEGIN
CV_WRAP_AS(forwardAndRetrieve) void forward(CV_OUT std::vector<std::vector<Mat> >& outputBlobs,
const std::vector<String>& outBlobNames);
/** @brief Returns a quantized Net from a floating-point Net.
* @param calibData Calibration data to compute the quantization parameters.
* @param inputsDtype Datatype of quantized net's inputs. Can be CV_32F or CV_8S.
* @param outputsDtype Datatype of quantized net's outputs. Can be CV_32F or CV_8S.
*/
CV_WRAP Net quantize(InputArrayOfArrays calibData, int inputsDtype, int outputsDtype);
/** @brief Returns input scale and zeropoint for a quantized Net.
* @param scales output parameter for returning input scales.
* @param zeropoints output parameter for returning input zeropoints.
*/
CV_WRAP void getInputDetails(CV_OUT std::vector<float>& scales, CV_OUT std::vector<int>& zeropoints) const;
/** @brief Returns output scale and zeropoint for a quantized Net.
* @param scales output parameter for returning output scales.
* @param zeropoints output parameter for returning output zeropoints.
*/
CV_WRAP void getOutputDetails(CV_OUT std::vector<float>& scales, CV_OUT std::vector<int>& zeropoints) const;
/**
* @brief Compile Halide layers.
* @param[in] scheduler Path to YAML file with scheduling directives.