From f202e50a8b89f143f74c393e33e0154817bd3c1d Mon Sep 17 00:00:00 2001 From: Anthony Barbier Date: Thu, 23 Nov 2017 18:02:04 +0000 Subject: COMPMID-556 Improved indentation and error handling in format_doxygen.py Change-Id: I6f51ffe6c324d9da500716b52c97c344f2a2a164 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/110486 Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com Reviewed-by: Georgios Pinitas --- .../runtime/NEON/functions/NEDeconvolutionLayer.h | 24 ++++++------- .../NEON/functions/NEDirectConvolutionLayer.h | 32 ++++++++--------- .../NEGEMMLowpAssemblyMatrixMultiplyCore.h | 10 +++--- .../NEON/functions/NEGEMMLowpMatrixMultiplyCore.h | 24 ++++++------- .../runtime/NEON/functions/NEGEMMLowpOutputStage.h | 42 +++++++++++----------- .../runtime/NEON/functions/NEIntegralImage.h | 8 ++--- 6 files changed, 70 insertions(+), 70 deletions(-) (limited to 'arm_compute/runtime/NEON') 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 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 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 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 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); }; } -- cgit v1.2.1