From 58c5794b917dae10ff115dd85ec69e2ca41136c1 Mon Sep 17 00:00:00 2001 From: Gian Marco Date: Tue, 28 Nov 2017 09:10:03 +0000 Subject: COMPMID-706 - Add GEMMLowp output stage for scaling by a fixed point number DoD: - Implement NEON kernel for quantizing down the gemmlowp result. The result should be scaled by a fixedpoint number - Implement OpenCL kernel for quantizing down the gemmlowp result. The result should be scaled by a fixedpoint number - Add test for validating the result Required for: - Integration of GEMMLowp in Android NN - Convolution quantized - Fully connected quantized Change-Id: Ia963d25d695471e963961fb49a5600e78374ac4f Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/110981 Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com Reviewed-by: Georgios Pinitas Reviewed-by: Anthony Barbier --- ...tizeDownInt32ToUint8ScaleByFixedPointKernel.cpp | 167 +++++++++++++++++++++ ...GEMMLowpQuantizeDownInt32ToUint8ScaleKernel.cpp | 100 ++++++++---- 2 files changed, 234 insertions(+), 33 deletions(-) create mode 100644 src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.cpp (limited to 'src/core/CL/kernels') diff --git a/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.cpp b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.cpp new file mode 100644 index 0000000000..37a430e8b0 --- /dev/null +++ b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.cpp @@ -0,0 +1,167 @@ +/* + * Copyright (c) 2017 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/CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.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/ToolchainSupport.h" + +using namespace arm_compute; + +namespace arm_compute +{ +namespace +{ +Error 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_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QASYMM8); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); + ARM_COMPUTE_RETURN_ERROR_ON(max > 255); + ARM_COMPUTE_RETURN_ERROR_ON(min < 0 || 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)); + } + return Error{}; +} + +std::pair validate_and_configure_window(ITensorInfo *input, ITensorInfo *bias, ITensorInfo *output) +{ + constexpr unsigned int num_elems_processed_per_iteration = 16; + + // 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); + AccessWindowHorizontal output_result_access(output, 0, num_elems_processed_per_iteration); + + bool window_changed = update_window_and_padding(win, + input_access, + output_result_access); + + 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); + } + + output_result_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape())); + + Error err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Error{}; + return std::make_pair(err, win); +} +} // namespace + +class Coordinates; +} // namespace arm_compute + +CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel::CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel() + : _input(nullptr), _bias(nullptr), _output(nullptr) +{ +} + +Error CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min, int max) +{ + 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 Error{}; +} + +void CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, int result_fixedpoint_multiplier, int result_shift, + int result_offset_after_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_AFTER_SHIFT=" + support::cpp11::to_string(result_offset_after_shift)); + build_opts.add_option("-DRESULT_FIXEDPOINT_MULTIPLIER=" + support::cpp11::to_string(result_fixedpoint_multiplier)); + build_opts.add_option("-DRESULT_SHIFT=" + support::cpp11::to_string(result_shift)); + build_opts.add_option_if((min != 0) && (min != max), "-DMIN_BOUND=" + support::cpp11::to_string(min)); + build_opts.add_option_if((max != 255) && (min != max), "-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_fixedpoint", 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(win_config.second); +} + +void CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel::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); + } + 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 index b5a007e832..343c31c73d 100644 --- a/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.cpp +++ b/src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.cpp @@ -36,6 +36,53 @@ using namespace arm_compute; namespace arm_compute { +namespace +{ +Error 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_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QASYMM8); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); + ARM_COMPUTE_RETURN_ERROR_ON(max > 255); + ARM_COMPUTE_RETURN_ERROR_ON(min < 0 || 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)); + } + return Error{}; +} + +std::pair validate_and_configure_window(ITensorInfo *input, ITensorInfo *bias, ITensorInfo *output) +{ + constexpr unsigned int num_elems_processed_per_iteration = 16; + + // 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); + AccessWindowHorizontal output_result_access(output, 0, num_elems_processed_per_iteration); + + bool window_changed = update_window_and_padding(win, + input_access, + output_result_access); + + 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); + } + + output_result_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape())); + + Error err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Error{}; + return std::make_pair(err, win); +} +} // namespace + class Coordinates; } // namespace arm_compute @@ -43,25 +90,31 @@ CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::CLGEMMLowpQuantizeDownInt32ToUint : _input(nullptr), _bias(nullptr), _output(nullptr) { } +Error CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min, int max) +{ + 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 Error{}; +} 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) { - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::S32); - ARM_COMPUTE_ERROR_ON(max > 255); - ARM_COMPUTE_ERROR_ON(min < 0 || min > max); - - if(bias != nullptr) - { - ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, bias); - ARM_COMPUTE_ERROR_ON(bias->info()->num_dimensions() > 1); - ARM_COMPUTE_ERROR_ON(input->info()->dimension(0) != bias->info()->dimension(0)); - } + // 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_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QASYMM8); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), + (bias != nullptr) ? bias->info() : nullptr, + output->info(), + min, + max)); _input = input; _bias = bias; @@ -79,29 +132,10 @@ void CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::configure(const ICLTensor *i // Create kernel _kernel = static_cast(CLKernelLibrary::get().create_kernel("gemmlowp_output_stage_quantize_down", build_opts.options())); - constexpr unsigned int num_elems_processed_per_iteration = 16; - // Configure kernel window - Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration)); - - AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration); - AccessWindowHorizontal output_result_access(output->info(), 0, num_elems_processed_per_iteration); - - update_window_and_padding(win, - input_access, - output_result_access); - - if(bias != nullptr) - { - AccessWindowStatic bias_access(bias->info(), 0, 0, ceil_to_multiple(bias->info()->dimension(0), num_elems_processed_per_iteration), bias->info()->tensor_shape()[1]); - - update_window_and_padding(win, - bias_access); - } - - output_result_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape())); - - ICLKernel::configure(win); + 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(win_config.second); } void CLGEMMLowpQuantizeDownInt32ToUint8ScaleKernel::run(const Window &window, cl::CommandQueue &queue) -- cgit v1.2.1