From 689c968239180eda4263e34c3d450093d4a0450d Mon Sep 17 00:00:00 2001 From: Luca Foschiani Date: Wed, 26 Feb 2020 14:30:14 +0000 Subject: COMPMID-2967 Add support for QASYMM8_SIGNED in CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel Signed-off-by: Luca Foschiani Change-Id: I4f7918630ea95fc28597b3d7b189f3d8fd35aef8 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/2890 Tested-by: Arm Jenkins Reviewed-by: Georgios Pinitas Comments-Addressed: Arm Jenkins --- Android.bp | 2 +- arm_compute/core/CL/CLKernels.h | 4 +- .../CLGEMMLowpQuantizeDownInt32ScaleKernel.h | 93 +++++++++++ ...CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h | 97 ------------ .../runtime/CL/functions/CLGEMMLowpOutputStage.h | 5 +- docs/00_introduction.dox | 1 - src/core/CL/cl_kernels/gemmlowp.cl | 18 ++- .../CLGEMMLowpQuantizeDownInt32ScaleKernel.cpp | 172 ++++++++++++++++++++ ...GEMMLowpQuantizeDownInt32ToUint8ScaleKernel.cpp | 175 --------------------- src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp | 107 ++++++++++--- tests/validation/CL/GEMMLowp.cpp | 79 ---------- 11 files changed, 365 insertions(+), 388 deletions(-) create mode 100644 arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.h delete mode 100644 arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h create mode 100644 src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.cpp delete mode 100644 src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.cpp diff --git a/Android.bp b/Android.bp index 3dd91d3109..f9a41000dd 100644 --- a/Android.bp +++ b/Android.bp @@ -126,11 +126,11 @@ cc_library_static { "src/core/CL/kernels/CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel.cpp", "src/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.cpp", "src/core/CL/kernels/CLGEMMLowpOffsetContributionOutputStageKernel.cpp", + "src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.cpp", "src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.cpp", "src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.cpp", "src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.cpp", "src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFloatKernel.cpp", - "src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.cpp", "src/core/CL/kernels/CLGEMMLowpReductionKernel.cpp", "src/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.cpp", "src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp", diff --git a/arm_compute/core/CL/CLKernels.h b/arm_compute/core/CL/CLKernels.h index d070d6a8c8..f2e16ca139 100644 --- a/arm_compute/core/CL/CLKernels.h +++ b/arm_compute/core/CL/CLKernels.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2016-2019 ARM Limited. + * Copyright (c) 2016-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -79,11 +79,11 @@ #include "arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel.h" #include "arm_compute/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.h" #include "arm_compute/core/CL/kernels/CLGEMMLowpOffsetContributionOutputStageKernel.h" +#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.h" #include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.h" #include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.h" #include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.h" #include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFloatKernel.h" -#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h" #include "arm_compute/core/CL/kernels/CLGEMMLowpReductionKernel.h" #include "arm_compute/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.h" #include "arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h" diff --git a/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.h b/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.h new file mode 100644 index 0000000000..f9599b5a0e --- /dev/null +++ b/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.h @@ -0,0 +1,93 @@ +/* + * Copyright (c) 2020 ARM Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#ifndef ARM_COMPUTE_CLGEMMLOWPQUANTIZEDOWNINT32SCALEKERNEL_H +#define ARM_COMPUTE_CLGEMMLOWPQUANTIZEDOWNINT32SCALEKERNEL_H + +#include "arm_compute/core/CL/ICLKernel.h" + +namespace arm_compute +{ +class ICLTensor; + +/** OpenCL kernel used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8/QASYMM8_SIGNED + * + * This kernel takes a final int32 accumulator value (the output of @ref CLGEMMLowpMatrixMultiplyKernel), and processes it to obtain the final QASYMM8/QASYMM8_SIGNED value. + * The following computations will be performed by the kernel: + * + * -# Add offset terms to final result + * -# Multiply each entry of result by result_mult_int + * -# Add bias to final result if bias tensor is not a nullptr + * -# Shift the int32 accumulator by result_shift + * -# Clamp the value between the specified min and max bounds + * -# Clamp the resulting int32 values: + * -# -to the [0..255] range and cast to QASYMM8. + * -# -to the [-128..127] range and cast to QASYMM8/SIGNED. + * + */ +class CLGEMMLowpQuantizeDownInt32ScaleKernel : public ICLKernel +{ +public: + /** Constructor */ + CLGEMMLowpQuantizeDownInt32ScaleKernel(); + /** Prevent instances of this class from being copied (As this class contains pointers)*/ + CLGEMMLowpQuantizeDownInt32ScaleKernel(const CLGEMMLowpQuantizeDownInt32ScaleKernel &) = delete; + /** Prevent instances of this class from being copied (As this class contains pointers)*/ + CLGEMMLowpQuantizeDownInt32ScaleKernel &operator=(const CLGEMMLowpQuantizeDownInt32ScaleKernel &) = delete; + /** Allow instances of this class to be moved */ + CLGEMMLowpQuantizeDownInt32ScaleKernel(CLGEMMLowpQuantizeDownInt32ScaleKernel &&) = default; + /** Allow instances of this class to be moved */ + CLGEMMLowpQuantizeDownInt32ScaleKernel &operator=(CLGEMMLowpQuantizeDownInt32ScaleKernel &&) = 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/QASYMM8_SIGNED + * @param[in] output_stage Output stage info. Used to pass the quantized output data type + */ + void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const GEMMLowpOutputStageInfo *output_stage); + /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpQuantizeDownInt32ScaleKernel + * + * @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/QASYMM8_SIGNED + * @param[in] output_stage Output stage info. Used to pass the quantized output data type + * + * @return a status + */ + static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage); + + // Inherited methods overridden: + void run(const Window &window, cl::CommandQueue &queue) override; + +private: + const ICLTensor *_input; + const ICLTensor *_bias; + ICLTensor *_output; + const GEMMLowpOutputStageInfo *_output_stage; +}; +} // namespace arm_compute + +#endif /* ARM_COMPUTE_CLGEMMLOWPQUANTIZEDOWNINT32SCALEKERNEL_H */ \ No newline at end of file diff --git a/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h b/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h deleted file mode 100644 index 9cd726a2ec..0000000000 --- a/arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h +++ /dev/null @@ -1,97 +0,0 @@ -/* - * Copyright (c) 2017-2019 ARM Limited. - * - * SPDX-License-Identifier: MIT - * - * Permission is hereby granted, free of charge, to any person obtaining a copy - * of this software and associated documentation files (the "Software"), to - * deal in the Software without restriction, including without limitation the - * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or - * sell copies of the Software, and to permit persons to whom the Software is - * furnished to do so, subject to the following conditions: - * - * The above copyright notice and this permission notice shall be included in all - * copies or substantial portions of the Software. - * - * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR - * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, - * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE - * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER - * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, - * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE - * SOFTWARE. - */ -#ifndef ARM_COMPUTE_CLGEMMLOWPQUANTIZEDOWNINT32TOUINT8SCALEKERNEL_H -#define ARM_COMPUTE_CLGEMMLOWPQUANTIZEDOWNINT32TOUINT8SCALEKERNEL_H - -#include "arm_compute/core/CL/ICLKernel.h" - -namespace arm_compute -{ -class ICLTensor; - -/** OpenCL kernel used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8 - * - * This kernel takes a final int32 accumulator value (the output of @ref CLGEMMLowpMatrixMultiplyKernel), and processes it to obtain the final QASYMM8 value. - * The following computations will be performed by the kernel: - * - * -# Add offset terms to final result - * -# Multiply each entry of result by result_mult_int - * -# Add bias to final result if bias tensor is not a nullptr - * -# Shift the int32 accumulator by result_shift - * -# Clamp the value between the specified min and max bounds - * -# Clamp the resulting int32 values to the [0..255] range and cast to QASYMM8. - * - */ -class CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel : public ICLKernel -{ -public: - /** Constructor */ - CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel(); - /** Prevent instances of this class from being copied (As this class contains pointers)*/ - CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel(const CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel &) = delete; - /** Prevent instances of this class from being copied (As this class contains pointers)*/ - CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel &operator=(const CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel &) = delete; - /** Allow instances of this class to be moved */ - CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel(CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel &&) = default; - /** Allow instances of this class to be moved */ - CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel &operator=(CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel &&) = 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 - */ - void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *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 CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel - * - * @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 - * - * @return a status - */ - static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min = 0, int max = 0); - - // Inherited methods overridden: - void run(const Window &window, cl::CommandQueue &queue) override; - -private: - const ICLTensor *_input; - const ICLTensor *_bias; - ICLTensor *_output; -}; -} // namespace arm_compute - -#endif /* ARM_COMPUTE_CLGEMMLOWPQUANTIZEDOWNINT32TOUINT8SCALEKERNEL_H */ \ No newline at end of file diff --git a/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h b/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h index b6619da5d2..184d827d4b 100644 --- a/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h +++ b/arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h @@ -51,7 +51,7 @@ class ITensor; * * This function calls the following OpenCL kernels: * - * -# @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel + * -# @ref CLGEMMLowpQuantizeDownInt32ScaleKernel * * @note The function accepts also 2 optional input arguments (min and max) which can be used to implement "rectified linear unit" activation functions * after the result is shifted right by result_shift @@ -72,6 +72,7 @@ public: * @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. */ + ARM_COMPUTE_DEPRECATED_REL(20.05) void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_offset, int result_mult_int, int result_shift, int min = std::numeric_limits::lowest(), int max = std::numeric_limits::max()); /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpQuantizeDownInt32ToUint8Scale @@ -86,6 +87,7 @@ public: * * @return a status */ + ARM_COMPUTE_DEPRECATED_REL(20.05) static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min = std::numeric_limits::lowest(), int max = std::numeric_limits::max()); }; @@ -314,6 +316,7 @@ public: * * This function calls the following CL kernels: * + * -# @ref CLGEMMLowpQuantizeDownInt32ScaleKernel * -# @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel * -# @ref CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel */ diff --git a/docs/00_introduction.dox b/docs/00_introduction.dox index a8455b1831..d3ec24d743 100644 --- a/docs/00_introduction.dox +++ b/docs/00_introduction.dox @@ -861,7 +861,6 @@ v17.12 Public major release - New OpenCL kernels / functions - @ref CLGEMMLowpOffsetContributionKernel / @ref CLGEMMLowpMatrixAReductionKernel / @ref CLGEMMLowpMatrixBReductionKernel / @ref CLGEMMLowpMatrixMultiplyCore - @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel / @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint - - @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel / @ref CLGEMMLowpQuantizeDownInt32ToUint8Scale - New graph nodes for NEON and OpenCL - graph::BranchLayer diff --git a/src/core/CL/cl_kernels/gemmlowp.cl b/src/core/CL/cl_kernels/gemmlowp.cl index 8e7db9326f..3fba781ede 100644 --- a/src/core/CL/cl_kernels/gemmlowp.cl +++ b/src/core/CL/cl_kernels/gemmlowp.cl @@ -2042,9 +2042,9 @@ __kernel void gemmlowp_offset_contribution_quantize_down_fixedpoint(TENSOR3D_DEC #endif // defined(K_OFFSET) #if defined(RESULT_OFFSET) && defined(RESULT_MULT_INT) && defined(RESULT_SHIFT) -/** This OpenCL kernel is used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8 +/** This OpenCL kernel is used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8/QASYMM8_SIGNED * - * This kernel takes a final int32 accumulator value and processes it to obtain the final QASYMM8 value. + * This kernel takes a final int32 accumulator value and processes it to obtain the final QASYMM8/QASYMM8_SIGNED value. * The following computations will be performed by the kernel: * * -# Add offset terms to final result @@ -2052,11 +2052,14 @@ __kernel void gemmlowp_offset_contribution_quantize_down_fixedpoint(TENSOR3D_DEC * -# Add bias to final result (if -DADD_BIAS is passed at compile time) * -# Shift the int32 accumulator by result_shift * -# Clamp the value between the specified min and max bounds (if -DMIN_BOUND and/or -DMAX_BOUND are passed at compile time) - * -# Clamp the resulting int32 values to the [0..255] range and cast to QASYMM8. + * -# Clamp the resulting int32 values: + * -# - to the [0..255] range and cast to QASYMM8. + * -# - to the [-128..127] range and cast to QASYMM8_SIGNED. * * @attention The offset, scalar scale factor and number of bits to shift right of output tensor must be passed at compile time using -DRESULT_OFFSET, -RESULT_MULT_INT and -DRESULT_SHIFT * * @note In case the addition of int32 biases is required, -DADD_BIAS should be passed at compile time + * @note The output datatype should be passed at compile time using -DOUTPUT_DATA_TYPE * @note In case the clamping of the result is required, the min and max bounds can be passed at compile time using -DMIN_BOUND and -DMAX_BOUND. * These values can be used to implement "rectified linear unit" activation functions * @@ -2072,7 +2075,7 @@ __kernel void gemmlowp_offset_contribution_quantize_down_fixedpoint(TENSOR3D_DEC * @param[in] biases_stride_x (Optional) Stride of the biases tensor 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 tensor - * @param[out] dst_ptr Pointer to the destination tensor Supported data type: QASYMM8 + * @param[out] dst_ptr Pointer to the destination tensor Supported data type: QASYMM8/QASYMM8_SIGNED * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) * @param[in] dst_step_x dst_gx_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) @@ -2118,13 +2121,14 @@ __kernel void gemmlowp_output_stage_quantize_down(TENSOR3D_DECLARATION(src), input_values >>= RESULT_SHIFT; #endif // RESULT_SHIFT < 0 - uchar4 res = convert_uchar4_sat(input_values); + VEC_DATA_TYPE(OUTPUT_DATA_TYPE, 4) + res = CONVERT_SAT(input_values, VEC_DATA_TYPE(OUTPUT_DATA_TYPE, 4)); #if defined(MIN_BOUND) - res = max(res, (uchar4)MIN_BOUND); + res = max(res, (VEC_DATA_TYPE(OUTPUT_DATA_TYPE, 4))MIN_BOUND); #endif // defined(MIN_BOUND) #if defined(MAX_BOUND) - res = min(res, (uchar4)MAX_BOUND); + res = min(res, (VEC_DATA_TYPE(OUTPUT_DATA_TYPE, 4))MAX_BOUND); #endif // defined(MAX_BOUND) // Store the result diff --git a/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.cpp b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.cpp new file mode 100644 index 0000000000..002af6b471 --- /dev/null +++ b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.cpp @@ -0,0 +1,172 @@ +/* + * Copyright (c) 2020 ARM Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.h" + +#include "arm_compute/core/AccessWindowStatic.h" +#include "arm_compute/core/CL/CLHelpers.h" +#include "arm_compute/core/CL/ICLTensor.h" +#include "arm_compute/core/Error.h" +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/core/Window.h" +#include "arm_compute/core/utils/quantization/AsymmHelpers.h" +#include "support/StringSupport.h" + +namespace arm_compute +{ +namespace +{ +Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage) +{ + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::S32); + ARM_COMPUTE_RETURN_ERROR_ON((output_stage->output_data_type != DataType::QASYMM8) && (output_stage->output_data_type != DataType::QASYMM8_SIGNED)); + ARM_COMPUTE_RETURN_ERROR_ON(output_stage->gemmlowp_max_bound > std::get<1>(quantization::get_min_max_values_from_quantized_data_type(output_stage->output_data_type))); + ARM_COMPUTE_RETURN_ERROR_ON(output_stage->gemmlowp_min_bound < std::get<0>(quantization::get_min_max_values_from_quantized_data_type(output_stage->output_data_type)) + || output_stage->gemmlowp_min_bound > output_stage->gemmlowp_max_bound); + + // Check biases if exist + if(bias != nullptr) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, bias); + ARM_COMPUTE_RETURN_ERROR_ON(bias->num_dimensions() > 1); + ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(0) != bias->dimension(0)); + } + + if(output->total_size() != 0) + { + ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() != output_stage->output_data_type, "Mismatching output data type"); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); + } + + return Status{}; +} + +std::pair validate_and_configure_window(ITensorInfo *input, ITensorInfo *bias, ITensorInfo *output, DataType output_data_type) +{ + // Output auto inizialitation if not yet initialized + auto_init_if_empty(*output, input->clone()->set_data_type(output_data_type)); + + constexpr unsigned int num_elems_processed_per_iteration = 4; + + // Configure kernel window + Window win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration)); + + AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration); + + bool window_changed = update_window_and_padding(win, + input_access); + + AccessWindowHorizontal output_result_access(output, 0, num_elems_processed_per_iteration); + window_changed = window_changed || update_window_and_padding(win, output_result_access); + output_result_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape())); + + if(bias != nullptr) + { + AccessWindowStatic bias_access(bias, 0, 0, ceil_to_multiple(bias->dimension(0), num_elems_processed_per_iteration), bias->tensor_shape()[1]); + window_changed = window_changed || update_window_and_padding(win, bias_access); + } + + Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; + return std::make_pair(err, win); +} +} //namespace + +CLGEMMLowpQuantizeDownInt32ScaleKernel::CLGEMMLowpQuantizeDownInt32ScaleKernel() + : _input(nullptr), _bias(nullptr), _output(nullptr), _output_stage(nullptr) +{ +} +Status CLGEMMLowpQuantizeDownInt32ScaleKernel::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, bias, output, output_stage)); + + return Status{}; +} + +void CLGEMMLowpQuantizeDownInt32ScaleKernel::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const GEMMLowpOutputStageInfo *output_stage) +{ + // Perform validate step + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); + + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), + (bias != nullptr) ? bias->info() : nullptr, + output->info(), + output_stage)); + + _input = input; + _bias = bias; + _output = output; + _output_stage = output_stage; + + // Set the arguments to pass at compile time + auto min = output_stage->gemmlowp_min_bound; + auto max = output_stage->gemmlowp_max_bound; + CLBuildOptions build_opts; + build_opts.add_option("-DRESULT_OFFSET=" + support::cpp11::to_string(output_stage->gemmlowp_offset)); + build_opts.add_option("-DRESULT_MULT_INT=" + support::cpp11::to_string(output_stage->gemmlowp_multiplier)); + build_opts.add_option("-DRESULT_SHIFT=" + support::cpp11::to_string(output_stage->gemmlowp_shift)); + build_opts.add_option_if((min > std::get<0>(quantization::get_min_max_values_from_quantized_data_type(output_stage->output_data_type))) && (min != max), + "-DMIN_BOUND=" + support::cpp11::to_string(min)); + build_opts.add_option_if((max < std::get<1>(quantization::get_min_max_values_from_quantized_data_type(output_stage->output_data_type))) && (min != max), + "-DMAX_BOUND=" + support::cpp11::to_string(max)); + build_opts.add_option("-DOUTPUT_DATA_TYPE=" + get_cl_type_from_data_type(output->info()->data_type())); + build_opts.add_option_if(bias != nullptr, "-DADD_BIAS"); + + // Create kernel + _kernel = static_cast(CLKernelLibrary::get().create_kernel("gemmlowp_output_stage_quantize_down", build_opts.options())); + + // Configure kernel window + auto win_config = validate_and_configure_window(input->info(), (bias != nullptr) ? bias->info() : nullptr, output->info(), output_stage->output_data_type); + ARM_COMPUTE_ERROR_THROW_ON(win_config.first); + ICLKernel::configure_internal(win_config.second); +} + +void CLGEMMLowpQuantizeDownInt32ScaleKernel::run(const Window &window, cl::CommandQueue &queue) +{ + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); + + Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); + Window slice = collapsed.first_slice_window_3D(); + + unsigned int idx1 = num_arguments_per_3D_tensor(); + if(_bias != nullptr) + { + Window biases_slice(slice); + biases_slice.set(Window::DimY, Window::Dimension(0, 1, 1)); + biases_slice.set(Window::DimZ, Window::Dimension(0, 1, 1)); + add_1D_tensor_argument(idx1, _bias, biases_slice); + } + + do + { + unsigned int idx = 0; + add_3D_tensor_argument(idx, _input, slice); + add_3D_tensor_argument(idx1, _output, slice); + enqueue(queue, *this, slice, lws_hint()); + } + while(collapsed.slide_window_slice_3D(slice)); +} +} \ No newline at end of file diff --git a/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.cpp b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.cpp deleted file mode 100644 index d3211f6ee8..0000000000 --- a/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.cpp +++ /dev/null @@ -1,175 +0,0 @@ -/* - * Copyright (c) 2017-2020 ARM Limited. - * - * SPDX-License-Identifier: MIT - * - * Permission is hereby granted, free of charge, to any person obtaining a copy - * of this software and associated documentation files (the "Software"), to - * deal in the Software without restriction, including without limitation the - * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or - * sell copies of the Software, and to permit persons to whom the Software is - * furnished to do so, subject to the following conditions: - * - * The above copyright notice and this permission notice shall be included in all - * copies or substantial portions of the Software. - * - * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR - * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, - * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE - * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER - * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, - * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE - * SOFTWARE. - */ -#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h" - -#include "arm_compute/core/AccessWindowStatic.h" -#include "arm_compute/core/CL/ICLTensor.h" -#include "arm_compute/core/Error.h" -#include "arm_compute/core/Helpers.h" -#include "arm_compute/core/Types.h" -#include "arm_compute/core/Validate.h" -#include "arm_compute/core/Window.h" -#include "support/StringSupport.h" - -using namespace arm_compute; - -namespace arm_compute -{ -namespace -{ -Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min, int max) -{ - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::S32); - ARM_COMPUTE_RETURN_ERROR_ON(min > max); - - // Check biases if exist - if(bias != nullptr) - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, bias); - ARM_COMPUTE_RETURN_ERROR_ON(bias->num_dimensions() > 1); - ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(0) != bias->dimension(0)); - } - - if(output->total_size() != 0) - { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QASYMM8); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); - } - - return Status{}; -} - -std::pair validate_and_configure_window(ITensorInfo *input, ITensorInfo *bias, ITensorInfo *output) -{ - constexpr unsigned int num_elems_processed_per_iteration = 4; - - // Configure kernel window - Window win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration)); - - AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration); - - bool window_changed = update_window_and_padding(win, - input_access); - - if(output->total_size() != 0) - { - AccessWindowHorizontal output_result_access(output, 0, num_elems_processed_per_iteration); - window_changed = window_changed || update_window_and_padding(win, output_result_access); - - output_result_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape())); - } - - if(bias != nullptr) - { - AccessWindowStatic bias_access(bias, 0, 0, ceil_to_multiple(bias->dimension(0), num_elems_processed_per_iteration), bias->tensor_shape()[1]); - window_changed = window_changed || update_window_and_padding(win, bias_access); - } - - Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; - return std::make_pair(err, win); -} -} // namespace - -class Coordinates; -} // namespace arm_compute - -CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel() - : _input(nullptr), _bias(nullptr), _output(nullptr) -{ -} -Status CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min, int max) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, bias, output, min, max)); - ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), - (bias != nullptr) ? bias->clone().get() : nullptr, - output->clone().get()) - .first); - - return Status{}; -} - -void CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_offset, int result_mult_int, int result_shift, int min, - int max) -{ - // Perform validate step - ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - - // Output auto inizialitation if not yet initialized - auto_init_if_empty(*output->info(), input->info()->clone()->set_data_type(DataType::QASYMM8)); - - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), - (bias != nullptr) ? bias->info() : nullptr, - output->info(), - min, - max)); - - _input = input; - _bias = bias; - _output = output; - - // Set the arguments to pass at compile time - CLBuildOptions build_opts; - build_opts.add_option("-DRESULT_OFFSET=" + support::cpp11::to_string(result_offset)); - build_opts.add_option("-DRESULT_MULT_INT=" + support::cpp11::to_string(result_mult_int)); - build_opts.add_option("-DRESULT_SHIFT=" + support::cpp11::to_string(result_shift)); - build_opts.add_option_if((min > 0), "-DMIN_BOUND=" + support::cpp11::to_string(min)); - build_opts.add_option_if((max < 255), "-DMAX_BOUND=" + support::cpp11::to_string(max)); - build_opts.add_option_if(bias != nullptr, "-DADD_BIAS"); - - // Create kernel - _kernel = static_cast(CLKernelLibrary::get().create_kernel("gemmlowp_output_stage_quantize_down", build_opts.options())); - - // Configure kernel window - auto win_config = validate_and_configure_window(input->info(), (bias != nullptr) ? bias->info() : nullptr, output->info()); - ARM_COMPUTE_ERROR_THROW_ON(win_config.first); - ICLKernel::configure_internal(win_config.second); -} - -void CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::run(const Window &window, cl::CommandQueue &queue) -{ - ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); - ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); - - Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); - Window slice = collapsed.first_slice_window_3D(); - - unsigned int idx1 = num_arguments_per_3D_tensor(); - if(_bias != nullptr) - { - Window biases_slice(slice); - biases_slice.set(Window::DimY, Window::Dimension(0, 1, 1)); - biases_slice.set(Window::DimZ, Window::Dimension(0, 1, 1)); - add_1D_tensor_argument(idx1, _bias, biases_slice); - } - - do - { - unsigned int idx = 0; - add_3D_tensor_argument(idx, _input, slice); - add_3D_tensor_argument(idx1, _output, slice); - enqueue(queue, *this, slice, lws_hint()); - } - while(collapsed.slide_window_slice_3D(slice)); -} diff --git a/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp b/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp index a1b7b23c62..e86f303ff4 100644 --- a/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp +++ b/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp @@ -24,25 +24,36 @@ #include "arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h" #include "arm_compute/core/CL/ICLTensor.h" +#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.h" #include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.h" #include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.h" #include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.h" #include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFloatKernel.h" -#include "arm_compute/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h" #include "support/MemorySupport.h" namespace arm_compute { void CLGEMMLowpQuantizeDownInt32ToUint8Scale::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_offset, int result_mult_int, int result_shift, int min, int max) { - auto k = arm_compute::support::cpp14::make_unique(); - k->configure(input, bias, output, result_offset, result_mult_int, result_shift, min, max); + GEMMLowpOutputStageInfo info = GEMMLowpOutputStageInfo(); + info.gemmlowp_offset = result_offset; + info.gemmlowp_multiplier = result_mult_int; + info.gemmlowp_shift = result_shift; + info.gemmlowp_min_bound = min; + info.gemmlowp_max_bound = max; + + auto k = arm_compute::support::cpp14::make_unique(); + k->configure(input, bias, output, &info); _kernel = std::move(k); } Status CLGEMMLowpQuantizeDownInt32ToUint8Scale::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min, int max) { - return CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::validate(input, bias, output, min, max); + GEMMLowpOutputStageInfo info = GEMMLowpOutputStageInfo(); + info.gemmlowp_min_bound = min; + info.gemmlowp_max_bound = max; + + return CLGEMMLowpQuantizeDownInt32ScaleKernel::validate(input, bias, output, &info); } void CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, @@ -108,45 +119,91 @@ Status CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint::validate(const ITens void CLGEMMLowpOutputStage::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const GEMMLowpOutputStageInfo &info) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - ARM_COMPUTE_ERROR_ON(info.type != GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT); - switch(info.output_data_type) + switch(info.type) { - case DataType::QASYMM8: + case GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT: { - auto k = arm_compute::support::cpp14::make_unique(); - k->configure(input, bias, output, info.gemmlowp_multiplier, info.gemmlowp_shift, info.gemmlowp_offset, info.gemmlowp_min_bound, info.gemmlowp_max_bound); - _kernel = std::move(k); + switch(info.output_data_type) + { + case DataType::QASYMM8: + { + auto k = arm_compute::support::cpp14::make_unique(); + k->configure(input, bias, output, info.gemmlowp_multiplier, info.gemmlowp_shift, info.gemmlowp_offset, info.gemmlowp_min_bound, info.gemmlowp_max_bound); + _kernel = std::move(k); + break; + } + case DataType::QASYMM8_SIGNED: + { + auto k = arm_compute::support::cpp14::make_unique(); + k->configure(input, bias, output, info.gemmlowp_multiplier, info.gemmlowp_shift, info.gemmlowp_offset, info.gemmlowp_min_bound, info.gemmlowp_max_bound); + _kernel = std::move(k); + break; + } + default: + ARM_COMPUTE_ERROR("Unsupported output data type."); + } break; } - case DataType::QASYMM8_SIGNED: + case GEMMLowpOutputStageType::QUANTIZE_DOWN: { - auto k = arm_compute::support::cpp14::make_unique(); - k->configure(input, bias, output, info.gemmlowp_multiplier, info.gemmlowp_shift, info.gemmlowp_offset, info.gemmlowp_min_bound, info.gemmlowp_max_bound); - _kernel = std::move(k); + switch(info.output_data_type) + { + case DataType::QASYMM8: + case DataType::QASYMM8_SIGNED: + { + auto k = arm_compute::support::cpp14::make_unique(); + k->configure(input, bias, output, &info); + _kernel = std::move(k); + break; + } + default: + { + ARM_COMPUTE_ERROR("Unsupported output data type."); + break; + } + } break; } default: - ARM_COMPUTE_ERROR("Unsupported output data type."); + ARM_COMPUTE_ERROR("Unsupported GEMMLowpOutputStage type."); } - } Status CLGEMMLowpOutputStage::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo &info) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED); - ARM_COMPUTE_RETURN_ERROR_ON(info.type != GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT); - switch(output->data_type()) + switch(info.type) { - case DataType::QASYMM8: - return CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel::validate(input, bias, output, info.gemmlowp_min_bound, info.gemmlowp_max_bound); - case DataType::QASYMM8_SIGNED: - return CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::validate(input, bias, output, info.gemmlowp_min_bound, info.gemmlowp_max_bound); + case GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT: + { + switch(output->data_type()) + { + case DataType::QASYMM8: + return CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel::validate(input, bias, output, info.gemmlowp_min_bound, info.gemmlowp_max_bound); + case DataType::QASYMM8_SIGNED: + return CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::validate(input, bias, output, info.gemmlowp_min_bound, info.gemmlowp_max_bound); + default: + return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Unsupported output data type."); + } + } + case GEMMLowpOutputStageType::QUANTIZE_DOWN: + { + switch(output->data_type()) + { + case DataType::QASYMM8: + case DataType::QASYMM8_SIGNED: + { + return CLGEMMLowpQuantizeDownInt32ScaleKernel::validate(input, bias, output, &info); + } + default: + return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Unsupported output data type."); + } + } default: - return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Unsupported output data type."); + return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Unsupported GEMMLowpOutputStage type."); } - } -} // namespace arm_compute +} // namespace arm_compute \ No newline at end of file diff --git a/tests/validation/CL/GEMMLowp.cpp b/tests/validation/CL/GEMMLowp.cpp index 94621b4393..3d7c76aa2b 100644 --- a/tests/validation/CL/GEMMLowp.cpp +++ b/tests/validation/CL/GEMMLowp.cpp @@ -146,86 +146,7 @@ TEST_SUITE_END() // InputOutput3D TEST_SUITE_END() // MatrixMultiplyCore TEST_SUITE(OutputStage) -TEST_SUITE(QuantizeDownInt32ToUint8Scale) -const auto quantize_down_int32_to_uint8_scale_cases = framework::dataset::make("result_offset", -2, 1) * framework::dataset::make("result_mult_int", 1, 2) * framework::dataset::make("result_shift", 2, - 3) - * framework::dataset::make("min", 0) * framework::dataset::make("max", 255) * framework::dataset::make("addBias", { false, true }); - -const auto quantize_down_int32_to_uint8_scale_relu_cases = framework::dataset::make("result_offset", -2, 1) * framework::dataset::make("result_mult_int", 1, - 2) - * framework::dataset::make("result_shift", 2, 3) * framework::dataset::make("min", 0, 2) * framework::dataset::make("max", 171, 173) * framework::dataset::make("addBias", { false, true }); - -using CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture = GEMMLowpQuantizeDownInt32ToUint8ScaleValidationFixture; - -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_cases), - shape, result_offset, result_mult_int, result_shift, min, max, add_bias) -{ - TensorShape shape_bias(shape[0]); - - // Create tensors - CLTensor in = create_tensor(shape, DataType::S32); - CLTensor bias = create_tensor(shape_bias, DataType::S32); - CLTensor out = create_tensor(shape, DataType::QASYMM8); - - ARM_COMPUTE_EXPECT(in.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(out.info()->is_resizable(), framework::LogLevel::ERRORS); - - // Create and configure function - CLGEMMLowpQuantizeDownInt32ToUint8Scale output_stage; - output_stage.configure(&in, add_bias ? &bias : nullptr, &out, result_offset, result_mult_int, result_shift, min, max); - - // Validate valid region input and output - const ValidRegion valid_region = shape_to_valid_region(shape); - validate(in.info()->valid_region(), valid_region); - validate(out.info()->valid_region(), valid_region); - - // Validate valid region bias - if(add_bias) - { - const ValidRegion valid_region_bias = shape_to_valid_region(shape_bias); - validate(bias.info()->valid_region(), valid_region_bias); - } - - // Validate padding - const PaddingSize padding = PaddingCalculator(shape.x(), 4).required_padding(); - validate(in.info()->padding(), padding); - validate(out.info()->padding(), padding); - - if(add_bias) - { - validate(bias.info()->padding(), padding); - } -} - -FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_cases)) -{ - // Validate output - validate(CLAccessor(_target), _reference); -} - -FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), quantize_down_int32_to_uint8_scale_cases)) -{ - // Validate output - validate(CLAccessor(_target), _reference); -} - -TEST_SUITE(BoundedReLu) -FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), quantize_down_int32_to_uint8_scale_relu_cases)) -{ - // Validate output - validate(CLAccessor(_target), _reference); -} - -FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMLowpQuantizeDownInt32ToUint8ScaleFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeShapes(), - quantize_down_int32_to_uint8_scale_relu_cases)) -{ - // Validate output - validate(CLAccessor(_target), _reference); -} -TEST_SUITE_END() // BoundedReLu -TEST_SUITE_END() // QuantizeDownInt32ToUint8Scale TEST_SUITE(QuantizeDownInt32ToUint8ScaleByFixedPoint) const auto quantize_down_int32_to_uint8_scale_by_fixedpoint_cases = framework::dataset::make("result_fixedpoint_multiplier", 254601600, 254601602) * framework::dataset::make("result_shift", 1, 2) -- cgit v1.2.1