From 0cdbda5e51e6ef9e03017231e56ee85ede69bb9a Mon Sep 17 00:00:00 2001 From: Sheri Zhang Date: Tue, 25 Feb 2020 15:57:21 +0000 Subject: COMPMID-2789: Add support for QASYMM8_SIGNED in CLGEMMDeconvolutionLayer Change-Id: I7e3bcb01025e827f6f62491749c691c205ee7481 Signed-off-by: Sheri Zhang Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/2844 Tested-by: Arm Jenkins Reviewed-by: Michele Di Giorgio Comments-Addressed: Arm Jenkins --- .../CL/functions/CLGEMMDeconvolutionLayer.h | 28 ++++++------ .../runtime/CL/functions/CLGEMMLowpOutputStage.h | 51 +++++++++++++++++----- 2 files changed, 56 insertions(+), 23 deletions(-) (limited to 'arm_compute') diff --git a/arm_compute/runtime/CL/functions/CLGEMMDeconvolutionLayer.h b/arm_compute/runtime/CL/functions/CLGEMMDeconvolutionLayer.h index 3df9205f48..01687b69ec 100644 --- a/arm_compute/runtime/CL/functions/CLGEMMDeconvolutionLayer.h +++ b/arm_compute/runtime/CL/functions/CLGEMMDeconvolutionLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019 ARM Limited. + * Copyright (c) 2019-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -68,7 +68,7 @@ class ICLTensor; * This function calls the following OpenCL kernels/functions: * * -# @ref CLGEMMLowpMatrixMultiplyCore - * -# @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint + * -# @ref CLGEMMLowpOutputStage * -# @ref CLPermute * -# @ref CLPermute * -# @ref CLReshapeLayer @@ -91,7 +91,8 @@ public: CLGEMMDeconvolutionLayer &operator=(CLGEMMDeconvolutionLayer &&) = default; /** 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: F16/F32. Data layout supported: NHWC + * @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: QASYMM8/QASYMM8_SIGNED/F16/F32. Data layout supported: NHWC * @param[in] weights The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input. Data layout supported: same as @p input. * @param[in] bias (Optional) The biases have one dimension. Data type supported: Same as @p input. Data layout supported: same as @p input. * @param[out] output Output tensor. The output has the same number of dimensions as the @p input. Data layout supported: same as @p input. @@ -100,7 +101,8 @@ public: void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *bias, ICLTensor *output, const PadStrideInfo &deconv_info); /** Static function to check if given info will lead to a valid configuration of @ref CLDeconvolutionLayer * - * @param[in] input Input tensor info. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: F16/F32. Data layout supported: NHWC + * @param[in] input Input tensor info. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. + * Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. Data layout supported: NHWC * @param[in] weights The 4d weights info with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input. Data layout supported: same as @p input. * @param[in] bias (Optional) The biases have one dimension. Data type supported: Same as @p input. Data layout supported: same as @p input. * @param[in] output Output tensor info. The output has the same number of dimensions as the @p input. Data layout supported: same as @p input. @@ -117,15 +119,15 @@ public: private: MemoryGroup _memory_group; - CLGEMM _mm_gemm; - CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp; - CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint _gemmlowp_output_stage; - CLPermute _permute_input_to_nhwc; - CLPermute _permute_weights_to_nhwc; - CLReshapeLayer _reshape_weights; - CLTranspose _transpose_weights; - CLDeconvolutionReshapeOutputKernel _deconv_reshape; - CLSlice _slice_gemm; + CLGEMM _mm_gemm; + CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp; + CLGEMMLowpOutputStage _gemmlowp_output_stage; + CLPermute _permute_input_to_nhwc; + CLPermute _permute_weights_to_nhwc; + CLReshapeLayer _reshape_weights; + CLTranspose _transpose_weights; + CLDeconvolutionReshapeOutputKernel _deconv_reshape; + CLSlice _slice_gemm; CLTensor _gemmlowp_final; CLTensor _reshaped_weights; diff --git a/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h b/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h index 564135eed8..b6619da5d2 100644 --- a/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h +++ b/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h @@ -64,7 +64,7 @@ public: * @param[in] input Input tensor. It is the output of @ref CLGEMMLowpMatrixMultiplyCore 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[out] output Output tensor. 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 @@ -79,7 +79,7 @@ public: * @param[in] input Input tensor. It is the output of @ref CLGEMMLowpMatrixMultiplyCore 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] output Output tensor. Data type supported: QASYMM8 * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8. Defaults to the minimum possible 32-bit signed integer. * @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. Defaults to the maximum possible 32-bit signed integer. @@ -125,7 +125,7 @@ public: * @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[out] output Output tensor. Data type supported: QASYMM8 * @param[in] result_fixedpoint_multiplier Fixed point 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 after the fixed point multiplication * @param[in] result_offset_after_shift Offset to be applied to result before converting it back to QASYMM8 @@ -140,7 +140,7 @@ public: * @param[in] input Input tensor. It is the output of @ref CLGEMMLowpMatrixMultiplyCore 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] output Output tensor. Data type supported: QASYMM8 * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8. Defaults to the minimum possible 32-bit signed integer. * @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. Defaults to the maximum possible 32-bit signed integer. @@ -186,7 +186,7 @@ public: * @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_SIGNED + * @param[out] output Output tensor. Data type supported: QASYMM8_SIGNED * @param[in] result_fixedpoint_multiplier Fixed point 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 after the fixed point multiplication * @param[in] result_offset_after_shift Offset to be applied to result before converting it back to QASYMM8_SIGNED @@ -201,7 +201,7 @@ public: * @param[in] input Input tensor. It is the output of @ref CLGEMMLowpMatrixMultiplyCore 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_SIGNED + * @param[in] output Output tensor. Data type supported: QASYMM8_SIGNED * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8_SIGNED. Defaults to the minimum possible 32-bit signed integer. * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QASYMM8_SIGNED. Defaults to 0 * Along with @p min, this value can be used to implement "rectified linear unit" activation functions. Defaults to the maximum possible 32-bit signed integer. @@ -228,7 +228,7 @@ public: * @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[out] output Output tensor. Data type supported: QASYMM8 * @param[in] multiplier Float multiplier to be multiplied to each element of the input matrix * @param[in] offset Offset to be applied to result before converting it back to QASYMM8 * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8. Defaults to the minimum possible 32-bit signed integer. @@ -242,7 +242,7 @@ public: * @param[in] input Input tensor. It is the output of @ref CLGEMMLowpMatrixMultiplyCore 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] output Output tensor. Data type supported: QASYMM8 * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QASYMM8. Defaults to the minimum possible 32-bit signed integer. * @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. Defaults to the maximum possible 32-bit signed integer. @@ -287,7 +287,7 @@ public: * @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: QSYMM16 + * @param[out] output Output tensor. Data type supported: QSYMM16 * @param[in] result_fixedpoint_multiplier Fixed point 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 after the fixed point multiplication * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QSYMM16. Defaults to the minimum possible 32-bit signed integer. @@ -301,7 +301,7 @@ public: * @param[in] input Input tensor info. It is the output of @ref CLGEMMLowpMatrixMultiplyCore function. Data type supported: S32 * @param[in] bias Biases tensor info. 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 info. Data type supported: Data type supported: QSYMM16 + * @param[in] output Output tensor info. Data type supported: QSYMM16 * @param[in] min (Optional) Min value used to saturate down the output result before converting back to QSYMM16. Defaults to the minimum possible 32-bit signed integer. * @param[in] max (Optional) Max value used to saturate up the output result before converting back to QSYMM16, * Along with @p min, this value can be used to implement "rectified linear unit" activation functions. Defaults to the maximum possible 32-bit signed integer. @@ -310,5 +310,36 @@ public: */ static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min = std::numeric_limits::lowest(), int max = std::numeric_limits::max()); }; +/** Basic function to execute GEMMLowpQuantizeDown kernels on CL. + * + * This function calls the following CL kernels: + * + * -# @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel + * -# @ref CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel +*/ +class CLGEMMLowpOutputStage : public ICLSimpleFunction +{ +public: + /** Initialise the kernel's inputs, 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: QASYMM8/QASYMM8_SIGNED + * @param[in] info GEMMLowp output stage metadata. + */ + void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const GEMMLowpOutputStageInfo &info); + /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel + * + * @param[in] input Input tensor. It is the output of @ref CLGEMMLowpMatrixMultiplyCore 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: QASYMM8/QASYMM8_SIGNED + * @param[in] info GEMMLowp output stage metadata. + * + * @return a status + */ + static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo &info); +}; } // namespace arm_compute #endif /*ARM_COMPUTE_CLGEMMLOWPOUTPUTSTAGE_H */ \ No newline at end of file -- cgit v1.2.1