From dfca60b8e8805966624c7c941f289e090e3d73bb Mon Sep 17 00:00:00 2001 From: Giorgio Arena Date: Wed, 31 Jan 2018 10:30:59 +0000 Subject: COMPMID-811 Add NHWC data format support for CL depthwise convolution QASYMM8 Change-Id: I89de432f3fbcba7abf9e1d4f8396a4334b4fa2c2 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/118324 Tested-by: Jenkins Reviewed-by: Gian Marco Iodice --- .../CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp | 306 +++++++++++++++++++++ 1 file changed, 306 insertions(+) create mode 100644 src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp (limited to 'src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp') diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp new file mode 100644 index 0000000000..de68ceda11 --- /dev/null +++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp @@ -0,0 +1,306 @@ +/* + * Copyright (c) 2018 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/CLDepthwiseConvolutionLayer3x3NCHWKernel.h" + +#include "arm_compute/core/AccessWindowStatic.h" +#include "arm_compute/core/CL/CLHelpers.h" +#include "arm_compute/core/CL/CLKernelLibrary.h" +#include "arm_compute/core/CL/ICLKernel.h" +#include "arm_compute/core/CL/ICLTensor.h" +#include "arm_compute/core/Error.h" +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Utils.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" +#include "arm_compute/core/utils/quantization/AsymmHelpers.h" + +using namespace arm_compute; +using namespace arm_compute::misc::shape_calculator; + +CLDepthwiseConvolutionLayer3x3NCHWKernel::CLDepthwiseConvolutionLayer3x3NCHWKernel() + : _conv_stride_x(0), _conv_pad_top(0) +{ +} + +BorderSize CLDepthwiseConvolutionLayer3x3NCHWKernel::border_size() const +{ + return _border_size; +} + +void CLDepthwiseConvolutionLayer3x3NCHWKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, + ActivationLayerInfo act_info) +{ + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32); + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); + ARM_COMPUTE_ERROR_ON(weights->info()->dimension(0) != 3 || weights->info()->dimension(1) != 3); + + bool is_qasymm = is_data_type_quantized_asymmetric(input->info()->data_type()); + + if(biases != nullptr) + { + if(is_qasymm) + { + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(biases, 1, DataType::S32); + } + else + { + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(weights, biases); + } + ARM_COMPUTE_ERROR_ON(biases->info()->dimension(0) != weights->info()->dimension(2)); + ARM_COMPUTE_ERROR_ON(biases->info()->num_dimensions() > 1); + } + + // Get convolved dimensions + const TensorShape output_shape = compute_depthwise_convolution_shape(*input->info(), *weights->info(), conv_info); + + // Output auto inizialitation if not yet initialized + auto_init_if_empty(*output->info(), + output_shape, + 1, + input->info()->data_type(), + input->info()->fixed_point_position(), + input->info()->quantization_info()); + + ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(output->info()->tensor_shape(), output_shape); + + _input = input; + _output = output; + _weights = weights; + _biases = biases; + _conv_stride_x = conv_info.stride().first; + _conv_stride_y = conv_info.stride().second; + _conv_pad_left = conv_info.pad_left(); + _conv_pad_top = conv_info.pad_top(); + _border_size = BorderSize(_conv_pad_top, conv_info.pad_right(), conv_info.pad_bottom(), _conv_pad_left); + + // Set build options + ARM_COMPUTE_ERROR_ON(_conv_stride_x < 1 || _conv_stride_x > 3); + CLBuildOptions build_opts; + build_opts.add_option("-DCONV_STRIDE_X=" + support::cpp11::to_string(_conv_stride_x)); + build_opts.add_option_if(_biases != nullptr, "-DHAS_BIAS"); + + if(is_qasymm) + { + float multiplier = _input->info()->quantization_info().scale * _weights->info()->quantization_info().scale / _output->info()->quantization_info().scale; + int output_multiplier = 0; + int output_shift = 0; + quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift); + + build_opts.add_option("-DCONV_STRIDE_Y=" + support::cpp11::to_string(_conv_stride_y)); + build_opts.add_option("-DINPUT_OFFSET=" + support::cpp11::to_string(-_input->info()->quantization_info().offset)); + build_opts.add_option("-DWEIGHTS_OFFSET=" + support::cpp11::to_string(-_weights->info()->quantization_info().offset)); + build_opts.add_option("-DOUTPUT_OFFSET=" + support::cpp11::to_string(_output->info()->quantization_info().offset)); + build_opts.add_option("-DK_OFFSET=" + support::cpp11::to_string(9 * input->info()->quantization_info().offset * weights->info()->quantization_info().offset)); + build_opts.add_option("-DOUTPUT_MULTIPLIER=" + support::cpp11::to_string(output_multiplier)); + build_opts.add_option("-DOUTPUT_SHIFT=" + support::cpp11::to_string(output_shift)); + + if(act_info.enabled()) + { + const int a_val = input->info()->quantization_info().quantize(act_info.a(), RoundingPolicy::TO_NEAREST_UP); + const int b_val = input->info()->quantization_info().quantize(act_info.b(), RoundingPolicy::TO_NEAREST_UP); + const int o1 = input->info()->quantization_info().offset; + + build_opts.add_option("-DFUSED_ACTIVATION=" + lower_string(string_from_activation_func(act_info.activation()))); + build_opts.add_option("-DA_VAL=" + support::cpp11::to_string(a_val)); + build_opts.add_option("-DB_VAL=" + support::cpp11::to_string(b_val)); + build_opts.add_option("-DCONST_0=" + support::cpp11::to_string(o1)); + + if(output != nullptr) + { + const float s1 = input->info()->quantization_info().scale; + const float s2 = output->info()->quantization_info().scale; + const int o2 = output->info()->quantization_info().offset; + + if(o1 != o2 || s1 != s2) + { + build_opts.add_option("-DS1_VAL=" + float_to_string_with_full_precision(s1)); + build_opts.add_option("-DS2_VAL=" + float_to_string_with_full_precision(s2)); + build_opts.add_option("-DO1_VAL=" + support::cpp11::to_string(o1)); + build_opts.add_option("-DO2_VAL=" + support::cpp11::to_string(o2)); + } + } + } + } + + const GPUTarget gpu_target = get_target(); + const bool is_bifrost = gpu_target_is_in(gpu_target, GPUTarget::G71, GPUTarget::G72, GPUTarget::G51, GPUTarget::G51BIG, GPUTarget::G51LIT, GPUTarget::TNOX); + + // Configure kernel window + unsigned int num_elems_read_per_iteration_x = 0; + unsigned int num_elems_read_per_iteration_y = 0; + unsigned int num_elems_written_per_iteration_x = 0; + unsigned int num_elems_written_per_iteration_y = 0; + + // Create kernel + std::string kernel_name; + + if(input->info()->data_type() == DataType::F16) + { + kernel_name = "depthwise_convolution_3x3_f16"; + num_elems_written_per_iteration_x = 8 / data_size_from_type(input->info()->data_type()); + num_elems_written_per_iteration_y = 1; + num_elems_read_per_iteration_y = 3; + switch(_conv_stride_x) + { + case 1: + num_elems_read_per_iteration_x = 8; + break; + case 2: + num_elems_read_per_iteration_x = 9; + break; + case 3: + num_elems_read_per_iteration_x = 16; + break; + default: + num_elems_read_per_iteration_x = 3 + (num_elems_written_per_iteration_x - 1) * _conv_stride_x; + break; + } + if(is_bifrost) + { + if(_conv_stride_x == 1 && _conv_stride_y == 1) + { + kernel_name = "depthwise_convolution_3x3_stridex1_stridey1_bifrost_f16"; + num_elems_read_per_iteration_x = 8; + num_elems_written_per_iteration_x = 4; + num_elems_read_per_iteration_y = 6; + num_elems_written_per_iteration_y = 4; + } + else if(_conv_stride_x == 2 && _conv_stride_y == 2) + { + kernel_name = "depthwise_convolution_3x3_stridex2_stridey2_bifrost_f16"; + num_elems_read_per_iteration_x = 10; + num_elems_written_per_iteration_x = 4; + num_elems_read_per_iteration_y = 5; + num_elems_written_per_iteration_y = 2; + } + } + } + else if(input->info()->data_type() == DataType::F32 && is_bifrost) + { + if(_conv_stride_x == 1 && _conv_stride_y == 1) + { + kernel_name = "depthwise_convolution_3x3_stridex1_stridey1_bifrost_f32"; + num_elems_read_per_iteration_x = 4; + num_elems_read_per_iteration_y = 6; + num_elems_written_per_iteration_x = 2; + num_elems_written_per_iteration_y = 4; + } + else if(_conv_stride_x == 2 && _conv_stride_y == 2) + { + kernel_name = "depthwise_convolution_3x3_stridex2_stridey2_bifrost_f32"; + num_elems_read_per_iteration_x = 6; + num_elems_read_per_iteration_y = 5; + num_elems_written_per_iteration_x = 2; + num_elems_written_per_iteration_y = 2; + } + else + { + kernel_name = "depthwise_convolution_3x3"; + num_elems_written_per_iteration_x = 8 / data_size_from_type(input->info()->data_type()); + num_elems_written_per_iteration_y = 1; + num_elems_read_per_iteration_x = 3 + (num_elems_written_per_iteration_x - 1) * _conv_stride_x; + num_elems_read_per_iteration_y = 3; + } + } + else + { + kernel_name = is_qasymm ? "depthwise_convolution_3x3_quantized_nchw" : "depthwise_convolution_3x3"; + num_elems_written_per_iteration_x = 8 / data_size_from_type(input->info()->data_type()); + num_elems_written_per_iteration_y = (is_qasymm && _conv_stride_y < 3) ? (2 / _conv_stride_y) : 1; + num_elems_read_per_iteration_x = 3 + (num_elems_written_per_iteration_x - 1) * _conv_stride_x; + num_elems_read_per_iteration_y = num_elems_written_per_iteration_y + 2; + } + + // Create window and update padding + Window win = calculate_max_window(*output->info(), Steps(num_elems_written_per_iteration_x, num_elems_written_per_iteration_y)); + + AccessWindowRectangle input_access(input->info(), -_conv_pad_left, -_conv_pad_top, + num_elems_read_per_iteration_x, num_elems_read_per_iteration_y, + _conv_stride_x, _conv_stride_y); + AccessWindowStatic weights_access(weights->info(), 0, 0, 3, 3); + AccessWindowRectangle output_access(output->info(), 0, 0, num_elems_written_per_iteration_x, num_elems_written_per_iteration_y); + + update_window_and_padding(win, input_access, weights_access, output_access); + + output_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape())); + + ICLKernel::configure(win); + + _kernel = static_cast(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options())); + + // Set config_id for enabling LWS tuning + _config_id = kernel_name; + _config_id += "_"; + _config_id += lower_string(string_from_data_type(input->info()->data_type())); + _config_id += "_"; + _config_id += support::cpp11::to_string(input->info()->dimension(0)); + _config_id += "_"; + _config_id += support::cpp11::to_string(input->info()->dimension(1)); + _config_id += "_"; + _config_id += support::cpp11::to_string(input->info()->dimension(2)); + _config_id += "_"; + _config_id += support::cpp11::to_string(output->info()->dimension(0)); + _config_id += "_"; + _config_id += support::cpp11::to_string(output->info()->dimension(1)); +} + +void CLDepthwiseConvolutionLayer3x3NCHWKernel::run(const Window &window, cl::CommandQueue &queue) +{ + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); + + // Create input window and adjust + Window win_in = window; + win_in.adjust(Window::DimX, -_conv_pad_left, true); + win_in.adjust(Window::DimY, -_conv_pad_top, true); + win_in.set_dimension_step(Window::DimX, window.x().step() * _conv_stride_x); + win_in.set_dimension_step(Window::DimY, window.y().step() * _conv_stride_y); + + Window slice_in = win_in.first_slice_window_3D(); + Window slice_out = window.first_slice_window_3D(); + Window slice_weights = window.first_slice_window_3D(); + slice_weights.set_dimension_step(Window::DimX, 0); + slice_weights.set_dimension_step(Window::DimY, 0); + + // Set biases + if(_biases != nullptr) + { + unsigned int idx = 3 * num_arguments_per_3D_tensor(); + Window slice_biases; + slice_biases.use_tensor_dimensions(_biases->info()->tensor_shape()); + add_1D_tensor_argument(idx, _biases, slice_biases); + } + + do + { + unsigned int idx = 0; + add_3D_tensor_argument(idx, _input, slice_in); + add_3D_tensor_argument(idx, _output, slice_out); + add_3D_tensor_argument(idx, _weights, slice_weights); + + enqueue(queue, *this, slice_out, _lws_hint); + } + while(window.slide_window_slice_3D(slice_out) && win_in.slide_window_slice_3D(slice_in)); +} -- cgit v1.2.1