diff options
37 files changed, 617 insertions, 606 deletions
diff --git a/arm_compute/core/CL/CLKernelLibrary.h b/arm_compute/core/CL/CLKernelLibrary.h index 8e2bb66684..25c7f75ba6 100644 --- a/arm_compute/core/CL/CLKernelLibrary.h +++ b/arm_compute/core/CL/CLKernelLibrary.h @@ -227,8 +227,8 @@ public: return _kernel_path; }; /** Gets the source of the selected program - * - * @param[in] program_name Program name. + * + * @param[in] program_name Program name. */ std::string get_program_source(const std::string &program_name); /** Sets the CL context used to create programs. diff --git a/arm_compute/core/CL/ICLMultiHOG.h b/arm_compute/core/CL/ICLMultiHOG.h index 9f3c775230..90082a611f 100644 --- a/arm_compute/core/CL/ICLMultiHOG.h +++ b/arm_compute/core/CL/ICLMultiHOG.h @@ -35,14 +35,14 @@ class ICLMultiHOG : public IMultiHOG public: /** Return a pointer to the requested OpenCL HOG model * - * @param[in] index The index of the wanted OpenCL HOG model. + * @param[in] index The index of the wanted OpenCL HOG model. * * @return A pointer pointed to the HOG model */ virtual ICLHOG *cl_model(size_t index) = 0; /** Return a constant pointer to the requested OpenCL HOG model * - * @param[in] index The index of the wanted OpenCL HOG model. + * @param[in] index The index of the wanted OpenCL HOG model. * * @return A constant pointer pointed to the OpenCL HOG model */ diff --git a/arm_compute/core/CL/ICLMultiImage.h b/arm_compute/core/CL/ICLMultiImage.h index e8705b1824..774175607b 100644 --- a/arm_compute/core/CL/ICLMultiImage.h +++ b/arm_compute/core/CL/ICLMultiImage.h @@ -37,14 +37,14 @@ class ICLMultiImage : public IMultiImage public: /** Return a pointer to the requested OpenCL plane of the image. * - * @param[in] index The index of the wanted planed. + * @param[in] index The index of the wanted planed. * * @return A pointer pointed to the OpenCL plane */ virtual ICLImage *cl_plane(unsigned int index) = 0; /** Return a constant pointer to the requested OpenCL plane of the image. * - * @param[in] index The index of the wanted planed. + * @param[in] index The index of the wanted planed. * * @return A constant pointer pointed to the OpenCL plane */ diff --git a/arm_compute/core/FixedPoint.h b/arm_compute/core/FixedPoint.h index 82c2d3347e..6e00500b10 100644 --- a/arm_compute/core/FixedPoint.h +++ b/arm_compute/core/FixedPoint.h @@ -225,96 +225,96 @@ qint16_t sqmull_qs8(qint8_t a, qint8_t b, int fixed_point_position); qint32_t sqmull_qs16(qint16_t a, qint16_t b, int fixed_point_position); /** 16 bit fixed point scalar saturating multiply -* -* @param[in] a First 16 bit fixed point input -* @param[in] b Second 16 bit fixed point input -* @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number -* -* @return The result of the 16 bit fixed point multiplication. The result is saturated in case of overflow -*/ + * + * @param[in] a First 16 bit fixed point input + * @param[in] b Second 16 bit fixed point input + * @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number + * + * @return The result of the 16 bit fixed point multiplication. The result is saturated in case of overflow + */ qint16_t sqmul_qs16(qint16_t a, qint16_t b, int fixed_point_position); /** 8 bit fixed point scalar inverse square root -* -* @param[in] a 8 bit fixed point input -* @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number -* -* @return The result of the 8 bit fixed point inverse square root. -*/ + * + * @param[in] a 8 bit fixed point input + * @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number + * + * @return The result of the 8 bit fixed point inverse square root. + */ qint8_t sinvsqrt_qs8(qint8_t a, int fixed_point_position); /** 16 bit fixed point scalar inverse square root -* -* @param[in] a 16 bit fixed point input -* @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number -* -* @return The result of the 16 bit fixed point inverse square root. -*/ + * + * @param[in] a 16 bit fixed point input + * @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number + * + * @return The result of the 16 bit fixed point inverse square root. + */ qint16_t sinvsqrt_qs16(qint16_t a, int fixed_point_position); /** 8 bit fixed point scalar division -* -* @param[in] a First 8 bit fixed point input -* @param[in] b Second 8 bit fixed point input -* @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number -* -* @return The result of the 8 bit fixed point division. -*/ + * + * @param[in] a First 8 bit fixed point input + * @param[in] b Second 8 bit fixed point input + * @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number + * + * @return The result of the 8 bit fixed point division. + */ qint8_t sdiv_qs8(qint8_t a, qint8_t b, int fixed_point_position); /** 16 bit fixed point scalar division -* -* @param[in] a First 16 bit fixed point input -* @param[in] b Second 16 bit fixed point input -* @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number -* -* @return The result of the 16 bit fixed point division. -*/ + * + * @param[in] a First 16 bit fixed point input + * @param[in] b Second 16 bit fixed point input + * @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number + * + * @return The result of the 16 bit fixed point division. + */ qint16_t sdiv_qs16(qint16_t a, qint16_t b, int fixed_point_position); /** 8 bit fixed point scalar exponential -* -* @param[in] a 8 bit fixed point input -* @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number -* -* @return The result of the 8 bit fixed point exponential. -*/ + * + * @param[in] a 8 bit fixed point input + * @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number + * + * @return The result of the 8 bit fixed point exponential. + */ qint8_t sqexp_qs8(qint8_t a, int fixed_point_position); /** 16 bit fixed point scalar exponential -* -* @param[in] a 16 bit fixed point input -* @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number -* -* @return The result of the 16 bit fixed point exponential. -*/ + * + * @param[in] a 16 bit fixed point input + * @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number + * + * @return The result of the 16 bit fixed point exponential. + */ qint16_t sqexp_qs16(qint16_t a, int fixed_point_position); /** 16 bit fixed point scalar exponential -* -* @param[in] a 16 bit fixed point input -* @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number -* -* @return The result of the 16 bit fixed point exponential. -*/ + * + * @param[in] a 16 bit fixed point input + * @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number + * + * @return The result of the 16 bit fixed point exponential. + */ qint16_t sexp_qs16(qint16_t a, int fixed_point_position); /** 8 bit fixed point scalar logarithm -* -* @param[in] a 8 bit fixed point input -* @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number -* -* @return The result of the 8 bit fixed point logarithm. -*/ + * + * @param[in] a 8 bit fixed point input + * @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number + * + * @return The result of the 8 bit fixed point logarithm. + */ qint8_t slog_qs8(qint8_t a, int fixed_point_position); /** 16 bit fixed point scalar logarithm -* -* @param[in] a 16 bit fixed point input -* @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number -* -* @return The result of the 16 bit fixed point logarithm. -*/ + * + * @param[in] a 16 bit fixed point input + * @param[in] fixed_point_position Fixed point position that expresses the number of bits for the fractional part of the number + * + * @return The result of the 16 bit fixed point logarithm. + */ qint16_t slog_qs16(qint16_t a, int fixed_point_position); /** Convert an 8 bit fixed point to float diff --git a/arm_compute/core/GLES_COMPUTE/IGCKernel.h b/arm_compute/core/GLES_COMPUTE/IGCKernel.h index 0d3bfb30fd..11b2b17e51 100644 --- a/arm_compute/core/GLES_COMPUTE/IGCKernel.h +++ b/arm_compute/core/GLES_COMPUTE/IGCKernel.h @@ -58,7 +58,7 @@ public: * * @param[in] binding Tensor's binding point. * @param[in] shift Number of bits to be shift for offset calculation - */ + */ BufferParam(const unsigned int binding, const unsigned int shift) : binding_point(binding), buffer_data_type_shift(shift) { diff --git a/arm_compute/core/IArray.h b/arm_compute/core/IArray.h index 960e18f3df..bc01df9817 100644 --- a/arm_compute/core/IArray.h +++ b/arm_compute/core/IArray.h @@ -124,7 +124,7 @@ public: /** Resizes the array to contain "num" elements. If "num" is smaller than the maximum array size, the content is reduced to its first "num" elements, * "num" elements can't be bigger than the maximum number of values which can be stored in this array. * - * @param[in] num The new array size in number of elements + * @param[in] num The new array size in number of elements */ void resize(size_t num) { diff --git a/arm_compute/core/IMultiHOG.h b/arm_compute/core/IMultiHOG.h index e91da75398..5e9ee3a4ff 100644 --- a/arm_compute/core/IMultiHOG.h +++ b/arm_compute/core/IMultiHOG.h @@ -43,14 +43,14 @@ public: virtual size_t num_models() const = 0; /** Return a pointer to the requested HOG model * - * @param[in] index The index of the wanted HOG model. + * @param[in] index The index of the wanted HOG model. * * @return A pointer pointed to the HOG model */ virtual IHOG *model(size_t index) = 0; /** Return a const pointer to the requested HOG model * - * @param[in] index The index of the wanted HOG model. + * @param[in] index The index of the wanted HOG model. * * @return A const pointer pointed to the HOG model */ diff --git a/arm_compute/core/IMultiImage.h b/arm_compute/core/IMultiImage.h index 6ed3c785ca..0d11c2c6b8 100644 --- a/arm_compute/core/IMultiImage.h +++ b/arm_compute/core/IMultiImage.h @@ -43,14 +43,14 @@ public: virtual const MultiImageInfo *info() const = 0; /** Return a pointer to the requested plane of the image. * - * @param[in] index The index of the wanted planed. + * @param[in] index The index of the wanted planed. * * @return A pointer pointed to the plane */ virtual IImage *plane(unsigned int index) = 0; /** Return a constant pointer to the requested plane of the image. * - * @param[in] index The index of the wanted planed. + * @param[in] index The index of the wanted planed. * * @return A constant pointer pointed to the plane */ diff --git a/arm_compute/core/ITensorInfo.h b/arm_compute/core/ITensorInfo.h index 4f69442b48..9a67712f3d 100644 --- a/arm_compute/core/ITensorInfo.h +++ b/arm_compute/core/ITensorInfo.h @@ -90,11 +90,11 @@ public: */ virtual ITensorInfo &set_fixed_point_position(int fixed_point_position) = 0; /** Set the quantization settings (scale and offset) of the tensor. - * - * @param[in] quantization_info QuantizationInfo containing the scale and offset - * - * @return Reference to this ITensorInfo object - */ + * + * @param[in] quantization_info QuantizationInfo containing the scale and offset + * + * @return Reference to this ITensorInfo object + */ virtual ITensorInfo &set_quantization_info(QuantizationInfo quantization_info) = 0; /** Resets the padding settings of the tensor. * diff --git a/arm_compute/core/NEON/NEFixedPoint.h b/arm_compute/core/NEON/NEFixedPoint.h index f8579e08b5..5719b63618 100644 --- a/arm_compute/core/NEON/NEFixedPoint.h +++ b/arm_compute/core/NEON/NEFixedPoint.h @@ -179,19 +179,19 @@ void vst1_qs16(qint16_t *addr, qint16x4_t b); void vst1q_qs8(qint8_t *addr, qint8x16_t b); /** Store a single 16 bit fixed point vector to memory (8 elements) -* -* @param[in] addr Memory address where the 16 bit fixed point vector should be stored -* @param[in] b 16 bit fixed point vector to store -* -*/ + * + * @param[in] addr Memory address where the 16 bit fixed point vector should be stored + * @param[in] b 16 bit fixed point vector to store + * + */ void vst1q_qs16(qint16_t *addr, qint16x8_t b); /** Store two 16 bit fixed point vector to memory (8x2 elements) -* -* @param[in] addr Memory address where the 16 bit fixed point vectors should be stored -* @param[in] b 16 bit fixed point vectors to store -* -*/ + * + * @param[in] addr Memory address where the 16 bit fixed point vectors should be stored + * @param[in] b 16 bit fixed point vectors to store + * + */ void vst2q_qs16(qint16_t *addr, qint16x8x2_t b); /** 16 bit fixed point vector saturating narrow (8 elements) diff --git a/arm_compute/core/NEON/kernels/NEActivationLayerKernel.h b/arm_compute/core/NEON/kernels/NEActivationLayerKernel.h index a3fd3feb58..ef51cbe841 100644 --- a/arm_compute/core/NEON/kernels/NEActivationLayerKernel.h +++ b/arm_compute/core/NEON/kernels/NEActivationLayerKernel.h @@ -72,27 +72,27 @@ private: using ActivationFunctionExecutorPtr = void (NEActivationLayerKernel::*)(const Window &window); /** Function to apply an activation function on a tensor. * - * @param[in] window Region on which to execute the kernel + * @param[in] window Region on which to execute the kernel */ template <ActivationLayerInfo::ActivationFunction F, typename T> typename std::enable_if<std::is_same<T, float>::value, void>::type activation(const Window &window); #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC /** Function to apply an activation function on a tensor. * - * @param[in] window Region on which to execute the kernel + * @param[in] window Region on which to execute the kernel */ template <ActivationLayerInfo::ActivationFunction F, typename T> typename std::enable_if<std::is_same<T, float16_t>::value, void>::type activation(const Window &window); #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ /** Function to apply an activation function on a tensor. * - * @param[in] window Region on which to execute the kernel + * @param[in] window Region on which to execute the kernel */ template <ActivationLayerInfo::ActivationFunction F, typename T> typename std::enable_if<std::is_same<T, qint8_t>::value, void>::type activation(const Window &window); /** Function to apply an activation function on a tensor. * - * @param[in] window Region on which to execute the kernel + * @param[in] window Region on which to execute the kernel */ template <ActivationLayerInfo::ActivationFunction F, typename T> typename std::enable_if<std::is_same<T, qint16_t>::value, void>::type activation(const Window &window); diff --git a/arm_compute/core/NEON/kernels/NEDerivativeKernel.h b/arm_compute/core/NEON/kernels/NEDerivativeKernel.h index 7613b586d0..5d46516f68 100644 --- a/arm_compute/core/NEON/kernels/NEDerivativeKernel.h +++ b/arm_compute/core/NEON/kernels/NEDerivativeKernel.h @@ -64,17 +64,17 @@ public: private: /** Function to perform derivative along the X direction on the given window * - * @param[in] window Region on which to execute the kernel + * @param[in] window Region on which to execute the kernel */ void derivative_x(const Window &window); /** Function to perform derivative along the Y direction on the given window * - * @param[in] window Region on which to execute the kernel + * @param[in] window Region on which to execute the kernel */ void derivative_y(const Window &window); /** Function to perform derivative along the X and Y direction on the given window * - * @param[in] window Region on which to execute the kernel + * @param[in] window Region on which to execute the kernel */ void derivative_xy(const Window &window); /** Common signature for all the specialised derivative functions diff --git a/arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h b/arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h index 654dee21af..7684350c0f 100644 --- a/arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h +++ b/arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h @@ -58,27 +58,27 @@ public: NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel &operator=(NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel &&) = default; /** Initialise the kernel's input and output. * - * @param[in] input Input tensor. Data type supported: S32 - * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required. - * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. - * @param[out] output Output tensor. Data type supported: Data type supported: QASYMM8 - * @param[in] result_offset Offset to be added to each element of the input matrix - * @param[in] result_mult_int Value to be multiplied to each element of the input matrix when once the result_offset has been add - * @param[in] result_shift Number of bits to shift right the result before converting back to QASYMM8 - * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8 - * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8, - * Along with @p min, this value can be used to implement "rectified linear unit" activation functions + * @param[in] input Input tensor. Data type supported: S32 + * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required. + * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. + * @param[out] output Output tensor. Data type supported: Data type supported: QASYMM8 + * @param[in] result_offset Offset to be added to each element of the input matrix + * @param[in] result_mult_int Value to be multiplied to each element of the input matrix when once the result_offset has been add + * @param[in] result_shift Number of bits to shift right the result before converting back to QASYMM8 + * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8 + * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8, + * Along with @p min, this value can be used to implement "rectified linear unit" activation functions */ void configure(const ITensor *input, const ITensor *bias, ITensor *output, int result_offset, int result_mult_int, int result_shift, int min = 0, int max = 0); /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel * - * @param[in] input Input tensor. Data type supported: S32 - * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required. - * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. - * @param[in] output Output tensor. Data type supported: Data type supported: QASYMM8 - * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8 - * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8, - * Along with @p min, this value can be used to implement "rectified linear unit" activation functions + * @param[in] input Input tensor. Data type supported: S32 + * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required. + * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. + * @param[in] output Output tensor. Data type supported: Data type supported: QASYMM8 + * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8 + * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8, + * Along with @p min, this value can be used to implement "rectified linear unit" activation functions */ static Error validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min = 0, int max = 0); diff --git a/arm_compute/core/NEON/kernels/NEHistogramKernel.h b/arm_compute/core/NEON/kernels/NEHistogramKernel.h index 0fa911dbf0..672472e082 100644 --- a/arm_compute/core/NEON/kernels/NEHistogramKernel.h +++ b/arm_compute/core/NEON/kernels/NEHistogramKernel.h @@ -82,28 +82,28 @@ public: private: /** Function to merge multiple partial histograms. * - * @param[out] global_hist Pointer to the final histogram. - * @param[in] local_hist Pointer to the partial histograms. - * @param[in] bins Number of bins. + * @param[out] global_hist Pointer to the final histogram. + * @param[in] local_hist Pointer to the partial histograms. + * @param[in] bins Number of bins. */ void merge_histogram(uint32_t *global_hist, const uint32_t *local_hist, size_t bins); /** Function to merge multiple minimum values of partial histograms. * - * @param[out] global_min Pointer to the global min value. - * @param[in] local_min Local min value. + * @param[out] global_min Pointer to the global min value. + * @param[in] local_min Local min value. */ void merge_min(uint8_t *global_min, const uint8_t &local_min); /** Function to perform histogram on the given window - * - * @param[in] win Region on which to execute the kernel - * @param[in] info Info about the executing thread + * + * @param[in] win Region on which to execute the kernel + * @param[in] info Info about the executing thread */ void histogram_U8(Window win, const ThreadInfo &info); /** Function to perform histogram on the given window where histogram is * of fixed size 256 without ranges and offsets. * - * @param[in] win Region on which to execute the kernel - * @param[in] info Info about the executing thread + * @param[in] win Region on which to execute the kernel + * @param[in] info Info about the executing thread */ void histogram_fixed_U8(Window win, const ThreadInfo &info); /** Pre-calculate the pixel windowing for every possible pixel diff --git a/arm_compute/core/NEON/kernels/NEMagnitudePhaseKernel.h b/arm_compute/core/NEON/kernels/NEMagnitudePhaseKernel.h index 46b2a8ddb4..76c6163607 100644 --- a/arm_compute/core/NEON/kernels/NEMagnitudePhaseKernel.h +++ b/arm_compute/core/NEON/kernels/NEMagnitudePhaseKernel.h @@ -66,17 +66,17 @@ public: private: /** Function to perform magnitude on the given window * - * @param[in] window Region on which to execute the kernel + * @param[in] window Region on which to execute the kernel */ void magnitude(const Window &window); /** Function to perform phase on the given window * - * @param[in] window Region on which to execute the kernel + * @param[in] window Region on which to execute the kernel */ void phase(const Window &window); /** Function to perform magnitude and phase on the given window * - * @param[in] window Region on which to execute the kernel + * @param[in] window Region on which to execute the kernel */ void magnitude_phase(const Window &window); @@ -130,17 +130,17 @@ public: private: /** Function to perform magnitude on the given window * - * @param[in] window Region on which to execute the kernel + * @param[in] window Region on which to execute the kernel */ void magnitude(const Window &window); /** Function to perform phase on the given window * - * @param[in] window Region on which to execute the kernel + * @param[in] window Region on which to execute the kernel */ void phase(const Window &window); /** Function to perform magnitude and phase on the given window * - * @param[in] window Region on which to execute the kernel + * @param[in] window Region on which to execute the kernel */ void magnitude_phase(const Window &window); diff --git a/arm_compute/core/NEON/kernels/NEWarpKernel.h b/arm_compute/core/NEON/kernels/NEWarpKernel.h index 3a1cab1585..d7cb82f27e 100644 --- a/arm_compute/core/NEON/kernels/NEWarpKernel.h +++ b/arm_compute/core/NEON/kernels/NEWarpKernel.h @@ -66,17 +66,17 @@ public: protected: /** function to perform warp affine or warp perspective on the given window when border mode == UNDEFINED * - * @param[in] window Region on which to execute the kernel + * @param[in] window Region on which to execute the kernel */ virtual void warp_undefined(const Window &window) = 0; /** function to perform warp affine or warp perspective on the given window when border mode == CONSTANT * - * @param[in] window Region on which to execute the kernel + * @param[in] window Region on which to execute the kernel */ virtual void warp_constant(const Window &window) = 0; /** function to perform warp affine or warp perspective on the given window when border mode == REPLICATE * - * @param[in] window Region on which to execute the kernel + * @param[in] window Region on which to execute the kernel */ virtual void warp_replicate(const Window &window) = 0; /** Common signature for all the specialised warp functions diff --git a/arm_compute/core/Utils.h b/arm_compute/core/Utils.h index b8c5b34e5a..af9cf23548 100644 --- a/arm_compute/core/Utils.h +++ b/arm_compute/core/Utils.h @@ -384,14 +384,14 @@ inline DataType get_promoted_data_type(DataType dt) } /** Separate a 2D convolution into two 1D convolutions -* -* @param[in] conv 2D convolution -* @param[out] conv_col 1D vertical convolution -* @param[out] conv_row 1D horizontal convolution -* @param[in] size Size of the 2D convolution -* -* @return true if the separation was successful -*/ + * + * @param[in] conv 2D convolution + * @param[out] conv_col 1D vertical convolution + * @param[out] conv_row 1D horizontal convolution + * @param[in] size Size of the 2D convolution + * + * @return true if the separation was successful + */ inline bool separate_matrix(const int16_t *conv, int16_t *conv_col, int16_t *conv_row, uint8_t size) { int32_t min_col = -1; diff --git a/arm_compute/core/Validate.h b/arm_compute/core/Validate.h index 4f3b6102f5..227c3e7d69 100644 --- a/arm_compute/core/Validate.h +++ b/arm_compute/core/Validate.h @@ -123,10 +123,10 @@ struct get_tensor_info_t<ITensorInfo *> /** Create an error if one of the pointers is a nullptr. * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] pointers Pointers to check against nullptr. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] pointers Pointers to check against nullptr. * * @return Error */ @@ -153,11 +153,11 @@ inline arm_compute::Error error_on_nullptr(const char *function, const char *fil * - Its dimensions don't match the full window's ones * - The step for each of its dimension is not identical to the corresponding one of the full window. * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] full Full size window - * @param[in] win Window to validate. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] full Full size window + * @param[in] win Window to validate. * * @return Error */ @@ -175,11 +175,11 @@ arm_compute::Error error_on_mismatching_windows(const char *function, const char * - It is not fully contained inside the full window * - The step for each of its dimension is not identical to the corresponding one of the full window. * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] full Full size window - * @param[in] sub Sub-window to validate. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] full Full size window + * @param[in] sub Sub-window to validate. * * @return Error */ @@ -194,12 +194,12 @@ arm_compute::Error error_on_invalid_subwindow(const char *function, const char * * * The window cannot be collapsed if the given dimension not equal to the full window's dimension or not start from 0. * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] full Full size window - * @param[in] window Window to be collapsed. - * @param[in] dim Dimension need to be checked. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] full Full size window + * @param[in] window Window to be collapsed. + * @param[in] dim Dimension need to be checked. * * @return Error */ @@ -214,11 +214,11 @@ arm_compute::Error error_on_window_not_collapsable_at_dimension(const char *func * * The coordinates have too many dimensions if any of the dimensions greater or equal to max_dim is different from 0. * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] pos Coordinates to validate - * @param[in] max_dim Maximum number of dimensions allowed. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] pos Coordinates to validate + * @param[in] max_dim Maximum number of dimensions allowed. * * @return Error */ @@ -233,11 +233,11 @@ arm_compute::Error error_on_coordinates_dimensions_gte(const char *function, con * * The window has too many dimensions if any of the dimension greater or equal to max_dim is different from 0. * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] win Window to validate - * @param[in] max_dim Maximum number of dimensions allowed. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] win Window to validate + * @param[in] max_dim Maximum number of dimensions allowed. * * @return Error */ @@ -250,12 +250,12 @@ arm_compute::Error error_on_window_dimensions_gte(const char *function, const ch /** Return an error if the passed dimension objects differ. * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] dim1 The first object to be compared. - * @param[in] dim2 The second object to be compared. - * @param[in] dims (Optional) Further allowed objects. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] dim1 The first object to be compared. + * @param[in] dim2 The second object to be compared. + * @param[in] dims (Optional) Further allowed objects. * * @return Error */ @@ -273,12 +273,12 @@ arm_compute::Error error_on_mismatching_dimensions(const char *function, const c /** Return an error if the passed two tensor infos have different shapes from the given dimension * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] tensor_info_1 The first tensor info to be compared. - * @param[in] tensor_info_2 The second tensor info to be compared. - * @param[in] tensor_infos (Optional) Further allowed tensor infos. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] tensor_info_1 The first tensor info to be compared. + * @param[in] tensor_info_2 The second tensor info to be compared. + * @param[in] tensor_infos (Optional) Further allowed tensor infos. * * @return Error */ @@ -290,12 +290,12 @@ inline arm_compute::Error error_on_mismatching_shapes(const char *function, cons } /** Return an error if the passed two tensors have different shapes from the given dimension * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] tensor_1 The first tensor to be compared. - * @param[in] tensor_2 The second tensor to be compared. - * @param[in] tensors (Optional) Further allowed tensors. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] tensor_1 The first tensor to be compared. + * @param[in] tensor_2 The second tensor to be compared. + * @param[in] tensors (Optional) Further allowed tensors. * * @return Error */ @@ -307,13 +307,13 @@ inline arm_compute::Error error_on_mismatching_shapes(const char *function, cons } /** Return an error if the passed two tensors have different shapes from the given dimension * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] upper_dim The dimension from which to check. - * @param[in] tensor_info_1 The first tensor info to be compared. - * @param[in] tensor_info_2 The second tensor info to be compared. - * @param[in] tensor_infos (Optional) Further allowed tensor infos. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] upper_dim The dimension from which to check. + * @param[in] tensor_info_1 The first tensor info to be compared. + * @param[in] tensor_info_2 The second tensor info to be compared. + * @param[in] tensor_infos (Optional) Further allowed tensor infos. * * @return Error */ @@ -335,13 +335,13 @@ inline arm_compute::Error error_on_mismatching_shapes(const char *function, cons } /** Return an error if the passed two tensors have different shapes from the given dimension * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] upper_dim The dimension from which to check. - * @param[in] tensor_1 The first tensor to be compared. - * @param[in] tensor_2 The second tensor to be compared. - * @param[in] tensors (Optional) Further allowed tensors. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] upper_dim The dimension from which to check. + * @param[in] tensor_1 The first tensor to be compared. + * @param[in] tensor_2 The second tensor to be compared. + * @param[in] tensors (Optional) Further allowed tensors. * * @return Error */ @@ -363,11 +363,11 @@ inline arm_compute::Error error_on_mismatching_shapes(const char *function, cons /** Return an error if the passed two tensor infos have different data types * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] tensor_info The first tensor info to be compared. - * @param[in] tensor_infos (Optional) Further allowed tensor infos. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] tensor_info The first tensor info to be compared. + * @param[in] tensor_infos (Optional) Further allowed tensor infos. * * @return Error */ @@ -389,11 +389,11 @@ inline arm_compute::Error error_on_mismatching_data_types(const char *function, } /** Return an error if the passed two tensors have different data types * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] tensor The first tensor to be compared. - * @param[in] tensors (Optional) Further allowed tensors. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] tensor The first tensor to be compared. + * @param[in] tensors (Optional) Further allowed tensors. * * @return Error */ @@ -416,12 +416,12 @@ inline arm_compute::Error error_on_mismatching_data_types(const char *function, * * @note: If the first tensor doesn't have fixed point data type, the function returns without throwing an error * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] tensor_info_1 The first tensor info to be compared. - * @param[in] tensor_info_2 The second tensor info to be compared. - * @param[in] tensor_infos (Optional) Further allowed tensor infos. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] tensor_info_1 The first tensor info to be compared. + * @param[in] tensor_info_2 The second tensor info to be compared. + * @param[in] tensor_infos (Optional) Further allowed tensor infos. * * @return Error */ @@ -455,12 +455,12 @@ inline arm_compute::Error error_on_mismatching_fixed_point(const char *function, * * @note: If the first tensor doesn't have fixed point data type, the function returns without throwing an error * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] tensor_1 The first tensor to be compared. - * @param[in] tensor_2 The second tensor to be compared. - * @param[in] tensors (Optional) Further allowed tensors. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] tensor_1 The first tensor to be compared. + * @param[in] tensor_2 The second tensor to be compared. + * @param[in] tensors (Optional) Further allowed tensors. * * @return Error */ @@ -481,12 +481,12 @@ inline arm_compute::Error error_on_mismatching_fixed_point(const char *function, * * @note: If the first tensor info doesn't have asymmetric quantized data type, the function returns without throwing an error * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] tensor_info_1 The first tensor info to be compared. - * @param[in] tensor_info_2 The second tensor info to be compared. - * @param[in] tensor_infos (Optional) Further allowed tensor infos. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] tensor_info_1 The first tensor info to be compared. + * @param[in] tensor_info_2 The second tensor info to be compared. + * @param[in] tensor_infos (Optional) Further allowed tensor infos. * * @return Error */ @@ -520,12 +520,12 @@ inline arm_compute::Error error_on_mismatching_quantization_info(const char *fun * * @note: If the first tensor doesn't have asymmetric quantized data type, the function returns without throwing an error * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] tensor_1 The first tensor to be compared. - * @param[in] tensor_2 The second tensor to be compared. - * @param[in] tensors (Optional) Further allowed tensors. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] tensor_1 The first tensor to be compared. + * @param[in] tensor_2 The second tensor to be compared. + * @param[in] tensors (Optional) Further allowed tensors. * * @return Error */ @@ -544,12 +544,12 @@ inline arm_compute::Error error_on_mismatching_quantization_info(const char *fun /** Throw an error if the format of the passed tensor/multi-image does not match any of the formats provided. * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] object Tensor/multi-image to validate. - * @param[in] format First format allowed. - * @param[in] formats (Optional) Further allowed formats. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] object Tensor/multi-image to validate. + * @param[in] format First format allowed. + * @param[in] formats (Optional) Further allowed formats. */ template <typename T, typename F, typename... Fs> void error_on_format_not_in(const char *function, const char *file, const int line, @@ -575,12 +575,12 @@ void error_on_format_not_in(const char *function, const char *file, const int li /** Return an error if the data type of the passed tensor info does not match any of the data types provided. * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] tensor_info Tensor info to validate. - * @param[in] dt First data type allowed. - * @param[in] dts (Optional) Further allowed data types. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] tensor_info Tensor info to validate. + * @param[in] dt First data type allowed. + * @param[in] dts (Optional) Further allowed data types. * * @return Error */ @@ -603,12 +603,12 @@ inline arm_compute::Error error_on_data_type_not_in(const char *function, const } /** Return an error if the data type of the passed tensor does not match any of the data types provided. * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] tensor Tensor to validate. - * @param[in] dt First data type allowed. - * @param[in] dts (Optional) Further allowed data types. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] tensor Tensor to validate. + * @param[in] dt First data type allowed. + * @param[in] dts (Optional) Further allowed data types. * * @return Error */ @@ -627,13 +627,13 @@ inline arm_compute::Error error_on_data_type_not_in(const char *function, const /** Return an error if the data type or the number of channels of the passed tensor info does not match any of the data types and number of channels provided. * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] tensor_info Tensor info to validate. - * @param[in] num_channels Number of channels to check - * @param[in] dt First data type allowed. - * @param[in] dts (Optional) Further allowed data types. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] tensor_info Tensor info to validate. + * @param[in] num_channels Number of channels to check + * @param[in] dt First data type allowed. + * @param[in] dts (Optional) Further allowed data types. * * @return Error */ @@ -648,13 +648,13 @@ inline arm_compute::Error error_on_data_type_channel_not_in(const char *function } /** Return an error if the data type or the number of channels of the passed tensor does not match any of the data types and number of channels provided. * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] tensor Tensor to validate. - * @param[in] num_channels Number of channels to check - * @param[in] dt First data type allowed. - * @param[in] dts (Optional) Further allowed data types. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] tensor Tensor to validate. + * @param[in] num_channels Number of channels to check + * @param[in] dt First data type allowed. + * @param[in] dts (Optional) Further allowed data types. * * @return Error */ @@ -673,10 +673,10 @@ inline arm_compute::Error error_on_data_type_channel_not_in(const char *function /** Return an error if the tensor is not 2D. * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] tensor Tensor to validate. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] tensor Tensor to validate. * * @return Error */ @@ -689,12 +689,12 @@ arm_compute::Error error_on_tensor_not_2d(const char *function, const char *file /** Return an error if the channel is not in channels. * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] cn Input channel - * @param[in] channel First channel allowed. - * @param[in] channels (Optional) Further allowed channels. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] cn Input channel + * @param[in] channel First channel allowed. + * @param[in] channels (Optional) Further allowed channels. * * @return Error */ @@ -719,11 +719,11 @@ inline arm_compute::Error error_on_channel_not_in(const char *function, const ch /** Return an error if the channel is not in format. * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] fmt Input channel - * @param[in] cn First channel allowed. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] fmt Input channel + * @param[in] cn First channel allowed. * * @return Error */ @@ -742,10 +742,10 @@ arm_compute::Error error_on_channel_not_in_known_format(const char *function, co * -# it doesn't contain models * -# it doesn't have the HOG data objects with the same phase_type, normalization_type and l2_hyst_threshold (if normalization_type == L2HYS_NORM) * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] multi_hog IMultiHOG container to validate + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] multi_hog IMultiHOG container to validate * * @return Error */ @@ -758,10 +758,10 @@ arm_compute::Error error_on_invalid_multi_hog(const char *function, const char * /** Return an error if the kernel is not configured. * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] kernel Kernel to validate. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] kernel Kernel to validate. */ arm_compute::Error error_on_unconfigured_kernel(const char *function, const char *file, const int line, const IKernel *kernel); @@ -807,12 +807,12 @@ arm_compute::Error error_on_invalid_subtensor_valid_region(const char *function, /** Return an error if the input fixed-point positions are different. * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] tensor_info_1 The first tensor info to be compared. - * @param[in] tensor_info_2 The second tensor info to be compared. - * @param[in] tensor_infos (Optional) Further allowed tensor infos. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] tensor_info_1 The first tensor info to be compared. + * @param[in] tensor_info_2 The second tensor info to be compared. + * @param[in] tensor_infos (Optional) Further allowed tensor infos. * * @return Error */ @@ -830,12 +830,12 @@ inline arm_compute::Error error_on_mismatching_fixed_point_position(const char * } /** Return an error if the input fixed-point positions are different. * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] tensor_1 The first tensor to be compared. - * @param[in] tensor_2 The second tensor to be compared. - * @param[in] tensors (Optional) Further allowed tensors. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] tensor_1 The first tensor to be compared. + * @param[in] tensor_2 The second tensor to be compared. + * @param[in] tensors (Optional) Further allowed tensors. * * @return Error */ @@ -854,11 +854,11 @@ inline arm_compute::Error error_on_mismatching_fixed_point_position(const char * /** Return an error if the fixed-point value is not representable in the specified Q format. * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] value The floating point value to be checked. - * @param[in] tensor_info Input tensor info that has information on data type and fixed-point position. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] value The floating point value to be checked. + * @param[in] tensor_info Input tensor info that has information on data type and fixed-point position. * * @return Error */ @@ -876,11 +876,11 @@ inline arm_compute::Error error_on_value_not_representable_in_fixed_point(const } /** Return an error an error if the fixed-point value is not representable in the specified Q format. * - * @param[in] function Function in which the error occurred. - * @param[in] file Name of the file where the error occurred. - * @param[in] line Line on which the error occurred. - * @param[in] value The floating point value to be checked. - * @param[in] tensor Input tensor that has information on data type and fixed-point position. + * @param[in] function Function in which the error occurred. + * @param[in] file Name of the file where the error occurred. + * @param[in] line Line on which the error occurred. + * @param[in] value The floating point value to be checked. + * @param[in] tensor Input tensor that has information on data type and fixed-point position. * * @return Error */ diff --git a/arm_compute/runtime/CL/CLMultiImage.h b/arm_compute/runtime/CL/CLMultiImage.h index f70929db07..2c2b4709b4 100644 --- a/arm_compute/runtime/CL/CLMultiImage.h +++ b/arm_compute/runtime/CL/CLMultiImage.h @@ -44,18 +44,18 @@ public: CLMultiImage(); /** Init the multi-planar image * - * @param[in] width Width of the whole image - * @param[in] height Heigth of the whole image - * @param[in] format Format of the whole image + * @param[in] width Width of the whole image + * @param[in] height Heigth of the whole image + * @param[in] format Format of the whole image */ void init(unsigned int width, unsigned int height, Format format); /** Init the multi-planar image * * @note Uses conservative padding strategy which fits all kernels. * - * @param[in] width Width of the whole image - * @param[in] height Height of the whole image - * @param[in] format Format of the whole image + * @param[in] width Width of the whole image + * @param[in] height Height of the whole image + * @param[in] format Format of the whole image */ void init_auto_padding(unsigned int width, unsigned int height, Format format); /** Allocated a previously initialised multi image @@ -73,10 +73,10 @@ public: private: /** Init the multi-planar image * - * @param[in] width Width of the whole image - * @param[in] height Height of the whole image - * @param[in] format Format of the whole image - * @param[in] auto_padding Specifies whether the image uses auto padding + * @param[in] width Width of the whole image + * @param[in] height Height of the whole image + * @param[in] format Format of the whole image + * @param[in] auto_padding Specifies whether the image uses auto padding */ void internal_init(unsigned int width, unsigned int height, Format format, bool auto_padding); diff --git a/arm_compute/runtime/CL/functions/CLGEMMLowp.h b/arm_compute/runtime/CL/functions/CLGEMMLowp.h index 613fcaa7e0..ffd997f6ec 100644 --- a/arm_compute/runtime/CL/functions/CLGEMMLowp.h +++ b/arm_compute/runtime/CL/functions/CLGEMMLowp.h @@ -52,26 +52,26 @@ public: /** Constructor */ CLGEMMLowp(std::shared_ptr<IMemoryManager> memory_manager = nullptr); /** Initialise the kernel's inputs, output - * - * @note GEMM_LOWP: low precision matrix multiply kernel - * This kernel performs the following computation: - * - * -# Convert a values from uint8 to int32 and add a_offset to each of them. - * -# Convert b values from uint8 to int32 and add b_offset to each of them. - * -# Compute the int32 matrix product of the resulting a * b. - * -# Add output_offset to each entry of the result. - * -# Multiply each entry of the result and round to the nearest integer - * -# Clamp the resulting int32 values to the [0..255] range and cast to uint8. - * - * @param[in] a First input tensor (Matrix A). Data types supported: U8. - * @param[in] b Second input tensor (Matrix B). Data types supported: same as @p a. - * @param[out] output Output tensor. Data types supported: same as @p a. - * @param[in] a_offset Offset to be added to each element of the matrix A. - * @param[in] b_offset Offset to be added to each element of the matrix B. - * @param[in] output_offset Offset to be added to each element of the output matrix - * @param[in] output_mult_int Multiplied with each element of the output matrix - * @param[in] shift Number of bits to shift right the result. - */ + * + * @note GEMM_LOWP: low precision matrix multiply kernel + * This kernel performs the following computation: + * + * -# Convert a values from uint8 to int32 and add a_offset to each of them. + * -# Convert b values from uint8 to int32 and add b_offset to each of them. + * -# Compute the int32 matrix product of the resulting a * b. + * -# Add output_offset to each entry of the result. + * -# Multiply each entry of the result and round to the nearest integer + * -# Clamp the resulting int32 values to the [0..255] range and cast to uint8. + * + * @param[in] a First input tensor (Matrix A). Data types supported: U8. + * @param[in] b Second input tensor (Matrix B). Data types supported: same as @p a. + * @param[out] output Output tensor. Data types supported: same as @p a. + * @param[in] a_offset Offset to be added to each element of the matrix A. + * @param[in] b_offset Offset to be added to each element of the matrix B. + * @param[in] output_offset Offset to be added to each element of the output matrix + * @param[in] output_mult_int Multiplied with each element of the output matrix + * @param[in] shift Number of bits to shift right the result. + */ void configure(const ICLTensor *a, const ICLTensor *b, ICLTensor *output, int32_t a_offset, int32_t b_offset, int32_t output_offset, int32_t output_mult_int, int32_t shift); // Inherited methods overridden: diff --git a/arm_compute/runtime/CL/functions/CLIntegralImage.h b/arm_compute/runtime/CL/functions/CLIntegralImage.h index 25fc549b29..71f6897d1b 100644 --- a/arm_compute/runtime/CL/functions/CLIntegralImage.h +++ b/arm_compute/runtime/CL/functions/CLIntegralImage.h @@ -43,10 +43,10 @@ public: /** Default Constructor. */ CLIntegralImage(); /** Initialise the function's source, destinations and border mode. - * - * @param[in] input Source tensor. Data types supported: U8. - * @param[out] output Destination tensor, Data types supported: U32. - */ + * + * @param[in] input Source tensor. Data types supported: U8. + * @param[out] output Destination tensor, Data types supported: U32. + */ void configure(const ICLTensor *input, ICLTensor *output); // Inherited methods overridden: diff --git a/arm_compute/runtime/MultiImage.h b/arm_compute/runtime/MultiImage.h index 917e586ef8..30fa9b0256 100644 --- a/arm_compute/runtime/MultiImage.h +++ b/arm_compute/runtime/MultiImage.h @@ -45,18 +45,18 @@ public: MultiImage(); /** Allocate the multi-planar image * - * @param[in] width Width of the whole image - * @param[in] height Height of the whole image - * @param[in] format Format of the whole image + * @param[in] width Width of the whole image + * @param[in] height Height of the whole image + * @param[in] format Format of the whole image */ void init(unsigned int width, unsigned int height, Format format); /** Allocate the multi-planar image * * @note Uses conservative padding strategy which fits all kernels. * - * @param[in] width Width of the whole image - * @param[in] height Height of the whole image - * @param[in] format Format of the whole image + * @param[in] width Width of the whole image + * @param[in] height Height of the whole image + * @param[in] format Format of the whole image */ void init_auto_padding(unsigned int width, unsigned int height, Format format); /** Allocated a previously initialised multi image @@ -67,10 +67,10 @@ public: void allocate(); /** Create a subimage from an existing MultiImage. * - * @param[in] image Image to use backing memory from - * @param[in] coords Starting coordinates of the new image. Should be within the parent image sizes - * @param[in] width The width of the subimage - * @param[in] height The height of the subimage + * @param[in] image Image to use backing memory from + * @param[in] coords Starting coordinates of the new image. Should be within the parent image sizes + * @param[in] width The width of the subimage + * @param[in] height The height of the subimage */ void create_subimage(MultiImage *image, const Coordinates &coords, unsigned int width, unsigned int height); @@ -82,10 +82,10 @@ public: private: /** Init the multi-planar image * - * @param[in] width Width of the whole image - * @param[in] height Height of the whole image - * @param[in] format Format of the whole image - * @param[in] auto_padding Specifies whether the image uses auto padding + * @param[in] width Width of the whole image + * @param[in] height Height of the whole image + * @param[in] format Format of the whole image + * @param[in] auto_padding Specifies whether the image uses auto padding */ void internal_init(unsigned int width, unsigned int height, Format format, bool auto_padding); diff --git a/arm_compute/runtime/NEON/functions/NEDeconvolutionLayer.h b/arm_compute/runtime/NEON/functions/NEDeconvolutionLayer.h index 3433e77ba1..8757bc63aa 100644 --- a/arm_compute/runtime/NEON/functions/NEDeconvolutionLayer.h +++ b/arm_compute/runtime/NEON/functions/NEDeconvolutionLayer.h @@ -68,18 +68,18 @@ public: /** Constructor */ NEDeconvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr); /** Set the input, weights, biases and output tensors. - * - * @param[in,out] input Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: F32. - * @param[in] weights The 4d weights with dimensions [width, height, OFM, IFM]. Data type supported: Same as @p input. - * @param[in] bias Optional, ignored if NULL. The biases have one dimension. Data type supported: Same as @p input. - * @param[out] output Output tensor. The output has the same number of dimensions as the @p input. - * @param[in] info Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo. - * @param[in] ax The number of zeros added to right edge of the input. - * @param[in] ay The number of zeros added to top edge of the input. - * @param[in] upscalex How much to scale the X axis. - * @param[in] upscaley How much to scale the Y axis. - * - */ + * + * @param[in,out] input Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: F32. + * @param[in] weights The 4d weights with dimensions [width, height, OFM, IFM]. Data type supported: Same as @p input. + * @param[in] bias Optional, ignored if NULL. The biases have one dimension. Data type supported: Same as @p input. + * @param[out] output Output tensor. The output has the same number of dimensions as the @p input. + * @param[in] info Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo. + * @param[in] ax The number of zeros added to right edge of the input. + * @param[in] ay The number of zeros added to top edge of the input. + * @param[in] upscalex How much to scale the X axis. + * @param[in] upscaley How much to scale the Y axis. + * + */ void configure(ITensor *input, const ITensor *weights, const ITensor *bias, ITensor *output, const PadStrideInfo &info, unsigned int ax, unsigned int ay, float upscalex, float upscaley); diff --git a/arm_compute/runtime/NEON/functions/NEDirectConvolutionLayer.h b/arm_compute/runtime/NEON/functions/NEDirectConvolutionLayer.h index daaf18f297..c731bf278f 100644 --- a/arm_compute/runtime/NEON/functions/NEDirectConvolutionLayer.h +++ b/arm_compute/runtime/NEON/functions/NEDirectConvolutionLayer.h @@ -51,22 +51,22 @@ public: /** Constructor */ NEDirectConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr); /** Set the input, weights, biases and output tensors. - * - * @note: DirectConvolution only works in the following configurations: - * 1x1 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = QS8/QS16/F16/F32 - * 3x3 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = QS8/F16/F32 - * 5x5 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F32 - * - * @param[in, out] input Input tensor. Data types supported: QS8/QS16/F16/F32. - * @param[in] weights Set of kernels to convolve the input volume. - * Supported sizes: 1x1, 3x3 and 5x5. - * The 3rd dimension must be the same as the input's volume 3rd dimension. - * Data type supported: Same as @p input. - * @param[in] bias Set of biases. Data type supported: Same as @p input. - * @param[out] output Output tensor. - * The 3rd dimensions must be equal to the 4th dimension of the @p kernels tensor. Data types supported: Same as @p input. - * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. - */ + * + * @note: DirectConvolution only works in the following configurations: + * 1x1 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = QS8/QS16/F16/F32 + * 3x3 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = QS8/F16/F32 + * 5x5 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F32 + * + * @param[in, out] input Input tensor. Data types supported: QS8/QS16/F16/F32. + * @param[in] weights Set of kernels to convolve the input volume. + * Supported sizes: 1x1, 3x3 and 5x5. + * The 3rd dimension must be the same as the input's volume 3rd dimension. + * Data type supported: Same as @p input. + * @param[in] bias Set of biases. Data type supported: Same as @p input. + * @param[out] output Output tensor. + * The 3rd dimensions must be equal to the 4th dimension of the @p kernels tensor. Data types supported: Same as @p input. + * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. + */ void configure(ITensor *input, const ITensor *weights, const ITensor *bias, ITensor *output, const PadStrideInfo &conv_info); // Inherited methods overridden: diff --git a/arm_compute/runtime/NEON/functions/NEGEMMLowpAssemblyMatrixMultiplyCore.h b/arm_compute/runtime/NEON/functions/NEGEMMLowpAssemblyMatrixMultiplyCore.h index 3b6aa1c7db..3d213a7668 100644 --- a/arm_compute/runtime/NEON/functions/NEGEMMLowpAssemblyMatrixMultiplyCore.h +++ b/arm_compute/runtime/NEON/functions/NEGEMMLowpAssemblyMatrixMultiplyCore.h @@ -46,11 +46,11 @@ public: /** Constructor */ NEGEMMLowpAssemblyMatrixMultiplyCore(std::shared_ptr<IMemoryManager> memory_manager = nullptr); /** Initialise the kernel's inputs, output - * - * @param[in] a First input tensor (Matrix A). Data type supported: U8, S8. - * @param[in] b Second input tensor (Matrix B). Data type supported: same as @p a - * @param[out] output Output tensor. Data type supported: Data type supported: S32 - */ + * + * @param[in] a First input tensor (Matrix A). Data type supported: U8, S8. + * @param[in] b Second input tensor (Matrix B). Data type supported: same as @p a + * @param[out] output Output tensor. Data type supported: Data type supported: S32 + */ void configure(const ITensor *a, const ITensor *b, ITensor *output); // Inherited methods overridden: diff --git a/arm_compute/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.h b/arm_compute/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.h index 598756e435..889bbca7f2 100644 --- a/arm_compute/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.h +++ b/arm_compute/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.h @@ -58,18 +58,18 @@ public: /** Constructor */ NEGEMMLowpMatrixMultiplyCore(std::shared_ptr<IMemoryManager> memory_manager = nullptr); /** Initialise the kernel's inputs, output - * - * @note GEMM_LOWP: low precision GEMM kernel - * This kernel performs the following computations: - * - * -# Convert a values from QASYMM8 to int32 and add a_offset to each of them. - * -# Convert b values from QASYMM8 to int32 add b_offset to each of them. - * -# Compute the matrix product of the resulting a * b in int32. - * - * @param[in] a First input tensor (Matrix A). Data type supported: QASYMM8. - * @param[in] b Second input tensor (Matrix B). Data type supported: same as @p a - * @param[out] output Output tensor. Data type supported: Data type supported: S32 - */ + * + * @note GEMM_LOWP: low precision GEMM kernel + * This kernel performs the following computations: + * + * -# Convert a values from QASYMM8 to int32 and add a_offset to each of them. + * -# Convert b values from QASYMM8 to int32 add b_offset to each of them. + * -# Compute the matrix product of the resulting a * b in int32. + * + * @param[in] a First input tensor (Matrix A). Data type supported: QASYMM8. + * @param[in] b Second input tensor (Matrix B). Data type supported: same as @p a + * @param[out] output Output tensor. Data type supported: Data type supported: S32 + */ void configure(const ITensor *a, const ITensor *b, ITensor *output); /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMLowpMatrixMultiplyCore * diff --git a/arm_compute/runtime/NEON/functions/NEGEMMLowpOutputStage.h b/arm_compute/runtime/NEON/functions/NEGEMMLowpOutputStage.h index 9270d5581f..533a41c888 100644 --- a/arm_compute/runtime/NEON/functions/NEGEMMLowpOutputStage.h +++ b/arm_compute/runtime/NEON/functions/NEGEMMLowpOutputStage.h @@ -60,29 +60,29 @@ class NEGEMMLowpQuantizeDownInt32ToUint8Scale : public INESimpleFunction { public: /** Initialise the kernel's inputs, output - * - * @param[in] input Input tensor. It is the output of @ref NEGEMMLowpMatrixMultiplyCore function. Data type supported: S32 - * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the addition of biases is not required. - * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. - * @param[out] output Output tensor. Data type supported: Data type supported: QASYMM8 - * @param[in] result_offset Offset to be added to each element of the input matrix - * @param[in] result_mult_int Value to be multiplied to each element of the input matrix when once the result_offset has been add - * @param[in] result_shift Number of bits to shift right the result before converting back to QASYMM8 - * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8 - * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8, - * Along with @p min, this value can be used to implement "rectified linear unit" activation functions - */ + * + * @param[in] input Input tensor. It is the output of @ref NEGEMMLowpMatrixMultiplyCore function. Data type supported: S32 + * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the addition of biases is not required. + * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. + * @param[out] output Output tensor. Data type supported: Data type supported: QASYMM8 + * @param[in] result_offset Offset to be added to each element of the input matrix + * @param[in] result_mult_int Value to be multiplied to each element of the input matrix when once the result_offset has been add + * @param[in] result_shift Number of bits to shift right the result before converting back to QASYMM8 + * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8 + * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8, + * Along with @p min, this value can be used to implement "rectified linear unit" activation functions + */ void configure(const ITensor *input, const ITensor *bias, ITensor *output, int result_offset, int result_mult_int, int result_shift, int min = 0, int max = 0); /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMLowpQuantizeDownInt32ToUint8Scale - * - * @param[in] input Input tensor. It is the output of @ref NEGEMMLowpMatrixMultiplyCore function. Data type supported: S32 - * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the addition of biases is not required. - * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. - * @param[in] output Output tensor. Data type supported: Data type supported: QASYMM8 - * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8 - * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8, - * Along with @p min, this value can be used to implement "rectified linear unit" activation functions - */ + * + * @param[in] input Input tensor. It is the output of @ref NEGEMMLowpMatrixMultiplyCore function. Data type supported: S32 + * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the addition of biases is not required. + * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input. + * @param[in] output Output tensor. Data type supported: Data type supported: QASYMM8 + * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8 + * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8, + * Along with @p min, this value can be used to implement "rectified linear unit" activation functions + */ static Error validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min = 0, int max = 0); }; } diff --git a/arm_compute/runtime/NEON/functions/NEIntegralImage.h b/arm_compute/runtime/NEON/functions/NEIntegralImage.h index 6d7dd697e8..1ac501c994 100644 --- a/arm_compute/runtime/NEON/functions/NEIntegralImage.h +++ b/arm_compute/runtime/NEON/functions/NEIntegralImage.h @@ -35,10 +35,10 @@ class NEIntegralImage : public INESimpleFunction { public: /** Initialise the function's source, destinations and border mode. - * - * @param[in] input Source tensor. Data type supported: U8. - * @param[out] output Destination tensor. Data type supported: U32. - */ + * + * @param[in] input Source tensor. Data type supported: U8. + * @param[out] output Destination tensor. Data type supported: U32. + */ void configure(const ITensor *input, ITensor *output); }; } diff --git a/scripts/format_doxygen.py b/scripts/format_doxygen.py index 423c2bfbf9..e18f24eb52 100755 --- a/scripts/format_doxygen.py +++ b/scripts/format_doxygen.py @@ -12,32 +12,38 @@ def process_comment(fd, comment, first_param, last_param): else: params = list() - # Copy the non param lines unmodified: - fd.write("".join(comment[:first_param])) - # Measure the indentation of the first param and use that to create an empty comment line string: - m = re.match(r" *\*", comment[first_param]) + m = re.match(r" */", comment[0]) if not m: - raise Exception("Not a comment ? '{}'".format(comment[first_param])) + raise Exception("{}: Not a comment ? '{}'".format(path,comment[first_param])) + + line_prefix = " " * len(m.group(0)) + "*" + empty_line = line_prefix +"\n" - empty_line = "{}\n".format(m.group(0)) + fd.write(comment[0]) + # Copy the non param lines with the correct indentation: + for comment_line in range(1,first_param): + line = comment[comment_line] + m = re.match(" *\*(.*)", line) + if not m: + raise Exception("{}:{}: Not a comment line ? ".format(path, n_line - len(comment) + comment_line + 1)) + fd.write(line_prefix+ m.group(1)+"\n") # For each param split the line into 3 columns: param, param_name, description for param in range(first_param, last_param): - m = re.match(r"([^@]+@param\[[^\]]+\]) +(\S+) +(.+)", comment[param]) + m = re.match(r"[^@]+(@param\[[^\]]+\]) +(\S+) +(.+)", comment[param]) if m: - params.append( (m.group(1), m.group(2), m.group(3)) ) + params.append( (" "+m.group(1), m.group(2), m.group(3)) ) else: # If it's not a match then it must be a multi-line param description: - m = re.match("( *\*) +(.*)", comment[param]) - + m = re.match(" *\* +(.*)", comment[param]) if not m: - raise Exception("Not a comment line ? ({})".format(n_line - len(comment) + param)) + raise Exception("{}:{}: Not a comment line ? ".format(path, n_line - len(comment) + param + 1)) - params.append( (m.group(1), "", m.group(2)) ) + params.append( ("", "", m.group(1)) ) # Now that we've got a list of params, find what is the longest string for each column: max_len = [0, 0] @@ -55,7 +61,7 @@ def process_comment(fd, comment, first_param, last_param): # Write out the formatted list of params: for p in params: - fd.write("{}{} {}{} {}\n".format( + fd.write("{}{}{} {}{} {}\n".format( line_prefix, p[0], " " * (max_len[0] - len(p[0])), p[1], " " * (max_len[1] - len(p[1])), p[2])) @@ -66,8 +72,13 @@ def process_comment(fd, comment, first_param, last_param): # insert empty line fd.write(empty_line) - # Copy the remaining of the comment unmodified: - fd.write("".join(comment[last_param:])) + # Copy the remaining of the comment with the correct indentation: + for comment_line in range(last_param,len(comment)): + line = comment[comment_line] + m = re.match(" *\*(.*)", line) + if not m: + raise Exception("{}:{}: Not a comment line ? ".format(path, n_line - len(comment) + comment_line + 1)) + fd.write(line_prefix+ m.group(1)+"\n") if __name__ == "__main__": n_file=0 @@ -111,7 +122,7 @@ if __name__ == "__main__": #print("Start comment {}".format(n_line)) if len(comment) > 0: - raise Exception("Already in a comment! ({})".format(n_line)) + raise Exception("{}:{}: Already in a comment!".format(path,n_line)) comment.append(line) @@ -146,7 +157,7 @@ if __name__ == "__main__": #print("End comment {}".format(n_line)) if len(comment) < 1: - raise Exception("Was not in a comment! ({})".format(n_line)) + raise Exception("{}:{}: Was not in a comment! ".format(path, n_line)) #print("Process comment {} {}".format(first_param, last_param)) diff --git a/src/core/CL/cl_kernels/canny.cl b/src/core/CL/cl_kernels/canny.cl index ec6719213c..166d681755 100644 --- a/src/core/CL/cl_kernels/canny.cl +++ b/src/core/CL/cl_kernels/canny.cl @@ -229,16 +229,16 @@ __kernel void suppress_non_maximum( #define hysteresis_local_stack_L2 16 // The size of level 2 stack, adjust this can impact the match rate with VX implementation /** Check whether pixel is valid -* -* Skip the pixel if the early_test fails. -* Otherwise, it tries to add the pixel coordinate to the stack, and proceed to popping the stack instead if the stack is full -* -* @param[in] early_test Boolean condition based on the minv check and visited buffer check -* @param[in] x_pos X-coordinate of pixel that is going to be recorded, has to be within the boundary -* @param[in] y_pos Y-coordinate of pixel that is going to be recorded, has to be within the boundary -* @param[in] x_cur X-coordinate of current central pixel -* @param[in] y_cur Y-coordinate of current central pixel -*/ + * + * Skip the pixel if the early_test fails. + * Otherwise, it tries to add the pixel coordinate to the stack, and proceed to popping the stack instead if the stack is full + * + * @param[in] early_test Boolean condition based on the minv check and visited buffer check + * @param[in] x_pos X-coordinate of pixel that is going to be recorded, has to be within the boundary + * @param[in] y_pos Y-coordinate of pixel that is going to be recorded, has to be within the boundary + * @param[in] x_cur X-coordinate of current central pixel + * @param[in] y_cur Y-coordinate of current central pixel + */ #define check_pixel(early_test, x_pos, y_pos, x_cur, y_cur) \ { \ if(!early_test) \ diff --git a/src/core/CL/cl_kernels/depthwise_convolution.cl b/src/core/CL/cl_kernels/depthwise_convolution.cl index 411e097dc8..89555a0cb6 100644 --- a/src/core/CL/cl_kernels/depthwise_convolution.cl +++ b/src/core/CL/cl_kernels/depthwise_convolution.cl @@ -145,36 +145,36 @@ inline float2 convolution3x3( } /** This function computes the horizontal integral of the image. - * - * @param[in] src_ptr Pointer to the source image. Supported data types: U8 - * @param[in] src_stride_x Stride of the source image in X dimension (in bytes) - * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] src_stride_y Stride of the source image in Y dimension (in bytes) - * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source image - * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) - * @param[in] src_step_z src_stride_z * number of elements along Y processed per workitem(in bytes) - * @param[in] dst_ptr Pointer to the destination tensor. Supported data types: F16/F32 - * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) - * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) - * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) - * @param[in] dst_step_z dst_stride_z * number of elements along Y processed per workitem(in bytes) - * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor - * @param[in] weights_ptr Pointer to the weights tensor. Supported data types: F16/F32 - * @param[in] weights_stride_x Stride of the weights tensor in X dimension (in bytes) - * @param[in] weights_step_x weights_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] weights_stride_y Stride of the weights tensor in Y dimension (in bytes) - * @param[in] weights_step_y weights_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] weights_stride_z Stride of the weights tensor in Z dimension (in bytes) - * @param[in] weights_step_z weights_stride_z * number of elements along Y processed per workitem(in bytes) - * @param[in] weights_offset_first_element_in_bytes The offset of the first element in the biases vector - * @param[in] biases_ptr (Optional) Pointer to the biases vector. Supported data types: F16/F32 - * @param[in] biases_stride_x (Optional) Stride of the biases vector in X dimension (in bytes) - * @param[in] biases_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] biases_offset_first_element_in_bytes (Optional) The offset of the first element in the biases vector - */ + * + * @param[in] src_ptr Pointer to the source image. Supported data types: U8 + * @param[in] src_stride_x Stride of the source image in X dimension (in bytes) + * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] src_stride_y Stride of the source image in Y dimension (in bytes) + * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source image + * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] src_step_z src_stride_z * number of elements along Y processed per workitem(in bytes) + * @param[in] dst_ptr Pointer to the destination tensor. Supported data types: F16/F32 + * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) + * @param[in] dst_step_z dst_stride_z * number of elements along Y processed per workitem(in bytes) + * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor + * @param[in] weights_ptr Pointer to the weights tensor. Supported data types: F16/F32 + * @param[in] weights_stride_x Stride of the weights tensor in X dimension (in bytes) + * @param[in] weights_step_x weights_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] weights_stride_y Stride of the weights tensor in Y dimension (in bytes) + * @param[in] weights_step_y weights_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] weights_stride_z Stride of the weights tensor in Z dimension (in bytes) + * @param[in] weights_step_z weights_stride_z * number of elements along Y processed per workitem(in bytes) + * @param[in] weights_offset_first_element_in_bytes The offset of the first element in the biases vector + * @param[in] biases_ptr (Optional) Pointer to the biases vector. Supported data types: F16/F32 + * @param[in] biases_stride_x (Optional) Stride of the biases vector in X dimension (in bytes) + * @param[in] biases_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] biases_offset_first_element_in_bytes (Optional) The offset of the first element in the biases vector + */ __kernel void depthwise_convolution_3x3( TENSOR3D_DECLARATION(src), diff --git a/src/core/CL/cl_kernels/depthwise_convolution_quantized.cl b/src/core/CL/cl_kernels/depthwise_convolution_quantized.cl index 19a509bd0a..0cd4e7148e 100644 --- a/src/core/CL/cl_kernels/depthwise_convolution_quantized.cl +++ b/src/core/CL/cl_kernels/depthwise_convolution_quantized.cl @@ -176,41 +176,41 @@ inline uchar2 convolution3x3( } /** This function computes the horizontal integral of the image. - * - * @param[in] src_ptr Pointer to the source image. Supported data types: QASYMM8 - * @param[in] src_stride_x Stride of the source image in X dimension (in bytes) - * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] src_stride_y Stride of the source image in Y dimension (in bytes) - * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source image - * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) - * @param[in] src_step_z src_stride_z * number of elements along Y processed per workitem(in bytes) - * @param[in] dst_ptr Pointer to the destination tensor. Supported data types: QASYMM8 - * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) - * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) - * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) - * @param[in] dst_step_z dst_stride_z * number of elements along Y processed per workitem(in bytes) - * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor - * @param[in] weights_ptr Pointer to the weights tensor. Supported data types: QASYMM8 - * @param[in] weights_stride_x Stride of the weights tensor in X dimension (in bytes) - * @param[in] weights_step_x weights_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] weights_stride_y Stride of the weights tensor in Y dimension (in bytes) - * @param[in] weights_step_y weights_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] weights_stride_z Stride of the weights tensor in Z dimension (in bytes) - * @param[in] weights_step_z weights_stride_z * number of elements along Y processed per workitem(in bytes) - * @param[in] weights_offset_first_element_in_bytes The offset of the first element in the weights tensor - * @param[in] biases_ptr (Optional) Pointer to the biases vector. Supported data types: QASYMM8 - * @param[in] biases_stride_x (Optional) Stride of the biases vector in X dimension (in bytes) - * @param[in] biases_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] biases_offset_first_element_in_bytes (Optional) The offset of the first element in the biases vector - * @param[in] input_offset Quantized offset of zero point of the input tensor data range - * @param[in] weight_offset Quantized offset of zero point of the weights tensor data range - * @param[in] output_offset Quantized offset of zero point of the output tensor data range - * @param[in] output_multiplier Output scale multiplier - * @param[in] output_shift Output scale divisor exponent - */ + * + * @param[in] src_ptr Pointer to the source image. Supported data types: QASYMM8 + * @param[in] src_stride_x Stride of the source image in X dimension (in bytes) + * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] src_stride_y Stride of the source image in Y dimension (in bytes) + * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source image + * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) + * @param[in] src_step_z src_stride_z * number of elements along Y processed per workitem(in bytes) + * @param[in] dst_ptr Pointer to the destination tensor. Supported data types: QASYMM8 + * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) + * @param[in] dst_step_z dst_stride_z * number of elements along Y processed per workitem(in bytes) + * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor + * @param[in] weights_ptr Pointer to the weights tensor. Supported data types: QASYMM8 + * @param[in] weights_stride_x Stride of the weights tensor in X dimension (in bytes) + * @param[in] weights_step_x weights_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] weights_stride_y Stride of the weights tensor in Y dimension (in bytes) + * @param[in] weights_step_y weights_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] weights_stride_z Stride of the weights tensor in Z dimension (in bytes) + * @param[in] weights_step_z weights_stride_z * number of elements along Y processed per workitem(in bytes) + * @param[in] weights_offset_first_element_in_bytes The offset of the first element in the weights tensor + * @param[in] biases_ptr (Optional) Pointer to the biases vector. Supported data types: QASYMM8 + * @param[in] biases_stride_x (Optional) Stride of the biases vector in X dimension (in bytes) + * @param[in] biases_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] biases_offset_first_element_in_bytes (Optional) The offset of the first element in the biases vector + * @param[in] input_offset Quantized offset of zero point of the input tensor data range + * @param[in] weight_offset Quantized offset of zero point of the weights tensor data range + * @param[in] output_offset Quantized offset of zero point of the output tensor data range + * @param[in] output_multiplier Output scale multiplier + * @param[in] output_shift Output scale divisor exponent + */ __kernel void depthwise_convolution_3x3_quantized( TENSOR3D_DECLARATION(src), diff --git a/src/core/CL/cl_kernels/fixed_point.h b/src/core/CL/cl_kernels/fixed_point.h index b329118f14..d55346b532 100644 --- a/src/core/CL/cl_kernels/fixed_point.h +++ b/src/core/CL/cl_kernels/fixed_point.h @@ -103,11 +103,11 @@ TYPE_ALIAS(int, qs32) #define CONVERT_SAT(x, type) CONVERT_SAT_STR(x, type) /** Computes saturating absolute value of fixed point vector. - * - * @param[in] type the actual data type. - * - * @return The result of the fixed point absolute value. - */ + * + * @param[in] type the actual data type. + * + * @return The result of the fixed point absolute value. + */ #define ABSQ_SAT_IMPL(type) \ inline type abs_##type##_sat(type VopA) \ { \ @@ -121,11 +121,11 @@ ABSQ_SAT_IMPL(qs16x8) #define ABS_SAT_OP_EXPAND(a, type, size) ABS_SAT_OP_EXPAND_STR(a, type, size) /** Computes max of fixed point types. - * - * @param[in] type the actual data type. - * - * @return The result of the fixed point maximum. - */ + * + * @param[in] type the actual data type. + * + * @return The result of the fixed point maximum. + */ #define MAXQ_IMPL(type) \ inline type max_##type(type VopA, type VopB) \ { \ @@ -147,11 +147,11 @@ MAXQ_IMPL(qs16x16) #define MAX_OP_EXPAND(a, b, type, size) MAX_OP_EXPAND_STR(a, b, type, size) /** Computes saturated addition of fixed point types. - * - * @param[in] type the actual data type. - * - * @return The result of the fixed point addition. The result is saturated in case of overflow - */ + * + * @param[in] type the actual data type. + * + * @return The result of the fixed point addition. The result is saturated in case of overflow + */ #define ADDQ_SAT_IMPL(type) \ inline type add_sat_##type(type VopA, type VopB) \ { \ @@ -178,11 +178,11 @@ ADDQ_SAT_IMPL(qs32x16) #define ADD_SAT_OP_EXPAND(a, b, type, size) ADD_SAT_OP_EXPAND_STR(a, b, type, size) /** Computes saturated subtraction of fixed point types. - * - * @param[in] type the actual data type. - * - * @return The result of the fixed point subtraction. The result is saturated in case of overflow - */ + * + * @param[in] type the actual data type. + * + * @return The result of the fixed point subtraction. The result is saturated in case of overflow + */ #define SUBQ_SAT_IMPL(type) \ inline type sub_sat_##type(type VopA, type VopB) \ { \ @@ -258,12 +258,12 @@ MULQ_SAT_IMPL(qs16x16, qs32x16) #define MUL_SAT_OP_EXPAND(a, b, type, size, position) MUL_SAT_OP_EXPAND_STR(a, b, type, size, position) /** Saturate multiply-accumulate - * - * @param[in] type the actual data type. - * @param[in] itype the intermediate data type. - * - * @return The result of the fixed point multiply-accumulate. The result is saturated in case of overflow - */ + * + * @param[in] type the actual data type. + * @param[in] itype the intermediate data type. + * + * @return The result of the fixed point multiply-accumulate. The result is saturated in case of overflow + */ #define MLAQ_SAT_IMPL(type, itype) \ type mla_sat_##type(type VopA, type VopB, type VopC, int fixed_point_position) \ { \ @@ -279,12 +279,12 @@ MLAQ_SAT_IMPL(qs16x8, qs32x8) #define MLA_SAT_OP_EXPAND(a, b, c, type, size, position) MLA_SAT_OP_EXPAND_STR(a, b, c, type, size, position) /** Saturate multiply-accumulate long - * - * @param[in] type the actual data type. - * @param[in] itype the intermediate data type. - * - * @return The result of the fixed point multiply-accumulate long. The result is saturated in case of overflow - */ + * + * @param[in] type the actual data type. + * @param[in] itype the intermediate data type. + * + * @return The result of the fixed point multiply-accumulate long. The result is saturated in case of overflow + */ #define MLALQ_SAT_IMPL(type, itype) \ itype mlal_sat_##type(itype VopA, type VopB, type VopC, int fixed_point_position) \ { \ @@ -299,13 +299,13 @@ MLALQ_SAT_IMPL(qs16x8, qs32x8) #define MLAL_SAT_OP_EXPAND(a, b, c, type, size, position) MLAL_SAT_OP_EXPAND_STR(a, b, c, type, size, position) /** Saturate division of two fixed point vectors - * - * @param[in] stype the actual scalar data type. - * @param[in] type the actual data type. - * @param[in] itype the intermediate data type. - * - * @return The result of the fixed point division. The result is saturated in case of overflow - */ + * + * @param[in] stype the actual scalar data type. + * @param[in] type the actual data type. + * @param[in] itype the intermediate data type. + * + * @return The result of the fixed point division. The result is saturated in case of overflow + */ #define DIVQ_SAT_IMPL(stype, type, itype) \ inline type div_sat_##type(type VopA, type VopB, int fixed_point_position) \ { \ @@ -329,15 +329,15 @@ DIVQ_SAT_IMPL(qs16, qs16, qs32) #define DIV_SAT_OP_VEC_EXPAND(a, b, type, size, position) DIV_SAT_OP_VEC_EXPAND_STR(a, b, type, size, position) /** Saturate exponential of a fixed point vector - * - * @note Implemented approach uses taylor polynomial to approximate the exponential function. - * - * @param[in] stype the actual scalar data type. - * @param[in] type the actual data type. - * @param[in] size the number of the calculated elements. - * - * @return The result of the fixed point exponential. The result is saturated in case of overflow - */ + * + * @note Implemented approach uses taylor polynomial to approximate the exponential function. + * + * @param[in] stype the actual scalar data type. + * @param[in] type the actual data type. + * @param[in] size the number of the calculated elements. + * + * @return The result of the fixed point exponential. The result is saturated in case of overflow + */ #define EXPQ_IMPL(stype, type, size) \ inline type exp_sat_##type(type VopA, int fixed_point_position) \ { \ @@ -372,15 +372,15 @@ EXPQ_IMPL(qs16, qs16x16, 16) #define EXP_OP_EXPAND(a, type, size, position) EXP_OP_EXPAND_STR(a, type, size, position) /** Saturate logarithm of a fixed point vector - * - * @note Implemented approach uses taylor polynomial to approximate the logarithm function. - * - * @param[in] stype the actual scalar data type. - * @param[in] type the actual data type. - * @param[in] size the number of the calculated elements. - * - * @return The result of the fixed point logarithm. The result is saturated in case of overflow - */ + * + * @note Implemented approach uses taylor polynomial to approximate the logarithm function. + * + * @param[in] stype the actual scalar data type. + * @param[in] type the actual data type. + * @param[in] size the number of the calculated elements. + * + * @return The result of the fixed point logarithm. The result is saturated in case of overflow + */ #define LOGQ_IMPL(stype, type, size) \ inline type log_sat_##type(type VopA, int fixed_point_position) \ { \ @@ -410,15 +410,15 @@ LOGQ_IMPL(qs16, qs16x16, 16) #define LOG_OP_EXPAND(a, type, size, position) LOG_OP_EXPAND_STR(a, type, size, position) /** Saturate inverse square root of a fixed point vector - * - * @note Implemented approach uses Newton's method to approximate the inverse square root function. - * - * @param[in] stype the actual scalar data type. - * @param[in] type the actual data type. - * @param[in] size the number of the calculated elements. - * - * @return The result of the fixed point inverse square root. The result is saturated in case of overflow - */ + * + * @note Implemented approach uses Newton's method to approximate the inverse square root function. + * + * @param[in] stype the actual scalar data type. + * @param[in] type the actual data type. + * @param[in] size the number of the calculated elements. + * + * @return The result of the fixed point inverse square root. The result is saturated in case of overflow + */ #define INVSQRTQ_IMPL(stype, type, size) \ inline type invsqrt_sat_##type(type VopA, int fixed_point_position) \ { \ @@ -447,15 +447,15 @@ INVSQRTQ_IMPL(qs16, qs16x8, 8) #define INVSQRT_OP_EXPAND(a, type, size, position) INVSQRT_OP_EXPAND_STR(a, type, size, position) /** Saturate hyperbolic tangent of a fixed point vector - * - * tanh(x) = (e^2x - 1)/(e^2x + 1) - * - * @param[in] stype the actual scalar data type. - * @param[in] type the actual data type. - * @param[in] size the number of the calculated elements. - * - * @return The result of the fixed point hyperbolic tangent. The result is saturated in case of overflow - */ + * + * tanh(x) = (e^2x - 1)/(e^2x + 1) + * + * @param[in] stype the actual scalar data type. + * @param[in] type the actual data type. + * @param[in] size the number of the calculated elements. + * + * @return The result of the fixed point hyperbolic tangent. The result is saturated in case of overflow + */ #define TANHQ_IMPL(stype, type, size) \ inline type tanh_sat_##type(type VopA, int fixed_point_position) \ { \ diff --git a/src/core/CL/cl_kernels/warp_helpers.h b/src/core/CL/cl_kernels/warp_helpers.h index 76f0a4a104..9afec7d081 100644 --- a/src/core/CL/cl_kernels/warp_helpers.h +++ b/src/core/CL/cl_kernels/warp_helpers.h @@ -78,7 +78,7 @@ inline const float2 get_current_coords() * @param[in] coord Input coordinates * * @return vector of 8 floats with the coordinates, even positions are x and odd y. -*/ + */ inline const float8 get_neighbour_coords(const float2 coord) { return (float8)(/*tl*/ coord.s0, coord.s1, /*tr*/ coord.s0 + 1, coord.s1, /*bl*/ coord.s0, coord.s1 + 1, /*br*/ coord.s0 + 1, coord.s1 + 1); @@ -91,7 +91,7 @@ inline const float8 get_neighbour_coords(const float2 coord) * @param[in] width Width of the image * @param[in] height Height of the image * @param[in] border_size Border size -*/ + */ inline const VEC_DATA_TYPE(DATA_TYPE, 4) bilinear_interpolate_with_border(const Image *in, const float8 coords, const float width, const float height, const float border_size) { // If any of the 4 texels is out of the image's boundaries we use the border value (REPLICATE or CONSTANT) for any texel out of the image. @@ -133,7 +133,7 @@ inline const VEC_DATA_TYPE(DATA_TYPE, 4) bilinear_interpolate_with_border(const * @param[in] coords Vector of four 2D coordinates. Even pos is x and odd y. * @param[in] width Width of the image * @param[in] height Height of the image -*/ + */ inline const VEC_DATA_TYPE(DATA_TYPE, 4) bilinear_interpolate(const Image *in, const float8 coords, const float width, const float height) { return bilinear_interpolate_with_border(in, coords, width, height, 1); diff --git a/src/core/CL/cl_kernels/warp_perspective.cl b/src/core/CL/cl_kernels/warp_perspective.cl index d955e427c4..6ffb7e4a00 100644 --- a/src/core/CL/cl_kernels/warp_perspective.cl +++ b/src/core/CL/cl_kernels/warp_perspective.cl @@ -62,7 +62,7 @@ inline const float8 apply_perspective_transform(const float2 coord, const float1 * x0 = M[1][1] * x + M[1][2] * y + M[1][3] * y0 = M[2][1] * x + M[2][2] * y + M[2][3] * z0 = M[3][1] * x + M[3][2] * y + M[3][3] - + * * output(x,y) = input(x0/z0,y0/z0) * * @attention The matrix coefficients need to be passed at compile time:\n diff --git a/tests/IArrayAccessor.h b/tests/IArrayAccessor.h index f128d8f67e..8c73046cd9 100644 --- a/tests/IArrayAccessor.h +++ b/tests/IArrayAccessor.h @@ -51,7 +51,7 @@ public: /** Resize array. * - * @param[in] num The new array size in number of elements + * @param[in] num The new array size in number of elements */ virtual void resize(size_t num) = 0; diff --git a/tests/validation/Helpers.h b/tests/validation/Helpers.h index b5e156c5f7..ab7dbd8a41 100644 --- a/tests/validation/Helpers.h +++ b/tests/validation/Helpers.h @@ -207,7 +207,7 @@ std::pair<T, T> get_batchnormalization_layer_test_bounds(int fixed_point_positio * @param[in] src Quantized tensor. * * @return Float tensor. -*/ + */ SimpleTensor<float> convert_from_asymmetric(const SimpleTensor<uint8_t> &src); /** Convert float simple tensor into quantized using specified quantization information. @@ -216,7 +216,7 @@ SimpleTensor<float> convert_from_asymmetric(const SimpleTensor<uint8_t> &src); * @param[in] quantization_info Quantification information. * * @return Quantized tensor. -*/ + */ SimpleTensor<uint8_t> convert_to_asymmetric(const SimpleTensor<float> &src, const QuantizationInfo &quantization_info); } // namespace validation } // namespace test |