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 --- .../CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp | 254 +++++++++++++++++++++ 1 file changed, 254 insertions(+) create mode 100644 src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp (limited to 'src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp') diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp new file mode 100644 index 0000000000..d783b9e159 --- /dev/null +++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp @@ -0,0 +1,254 @@ +/* + * 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/CLDepthwiseConvolutionLayer3x3NHWCKernel.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; + +namespace +{ +Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, + const ActivationLayerInfo &act_info) +{ + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8); + ARM_COMPUTE_RETURN_ERROR_ON_MSG((act_info.enabled()) && (act_info.activation() != ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU) + && (act_info.activation() != ActivationLayerInfo::ActivationFunction::BOUNDED_RELU) + && (act_info.activation() != ActivationLayerInfo::ActivationFunction::RELU), + "For QASYMM8 only relu, lower bounded relu and lower-upper bounded relu are supported"); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); + ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(1) != 3 || weights->dimension(2) != 3); + + if(biases != nullptr) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(biases, 1, DataType::S32); + ARM_COMPUTE_RETURN_ERROR_ON(biases->dimension(0) != weights->dimension(0)); + ARM_COMPUTE_RETURN_ERROR_ON(biases->num_dimensions() > 1); + } + + if(output->total_size() != 0) + { + const TensorShape output_shape = compute_depthwise_convolution_shape(*input, *weights, conv_info); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape); + } + + return Status{}; +} + +std::pair validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *output, const PadStrideInfo &conv_info) +{ + const unsigned int num_rows_processed_per_iteration = 4; + const unsigned int num_elems_accessed_per_iteration = 4; + const unsigned int num_rows_read_per_iteration = num_rows_processed_per_iteration + 2; + const unsigned int num_rows_written_per_iteration = num_rows_processed_per_iteration / conv_info.stride().first; + + const BorderSize border_size(conv_info.pad_left() + num_rows_read_per_iteration * std::max(conv_info.pad_top(), conv_info.pad_bottom()), 0, conv_info.pad_right(), 0); + + // Configure kernel window + Window win = calculate_max_window(*output, Steps(num_elems_accessed_per_iteration, num_rows_written_per_iteration)); + + AccessWindowStatic input_access(input, 0, -border_size.top, ceil_to_multiple(input->dimension(0), num_elems_accessed_per_iteration), + ceil_to_multiple(input->dimension(1) + border_size.bottom, num_rows_read_per_iteration)); + AccessWindowRectangle output_access(output, 0, 0, num_elems_accessed_per_iteration, num_rows_written_per_iteration); + AccessWindowHorizontal weights_access(weights, 0, num_elems_accessed_per_iteration); + + bool window_changed = update_window_and_padding(win, input_access, weights_access, output_access); + + output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape())); + + Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; + return std::make_pair(err, win); +} +} // namespace + +CLDepthwiseConvolutionLayer3x3NHWCKernel::CLDepthwiseConvolutionLayer3x3NHWCKernel() + : _num_rows_processed_per_iteration(1) +{ +} + +BorderSize CLDepthwiseConvolutionLayer3x3NHWCKernel::border_size() const +{ + return _border_size; +} + +void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, + ActivationLayerInfo act_info) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); + + // 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_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), conv_info, act_info)); + + const unsigned int conv_stride_x = conv_info.stride().first; + ARM_COMPUTE_ERROR_ON(conv_stride_x < 1 || conv_stride_x > 2); + ARM_COMPUTE_ERROR_ON(std::max(conv_info.pad_top(), conv_info.pad_bottom()) > 1); + + _input = input; + _output = output; + _weights = weights; + _biases = biases; + _conv_stride_y = conv_info.stride().second; + _conv_pad_left = conv_info.pad_left(); + _num_rows_processed_per_iteration = 4; + + const unsigned int num_elems_accessed_per_iteration = 4; + const unsigned int num_rows_read_per_iteration = _num_rows_processed_per_iteration + 2; + + _border_size = BorderSize(_conv_pad_left + num_rows_read_per_iteration * std::max(conv_info.pad_top(), conv_info.pad_bottom()), 0, conv_info.pad_right(), 0); + + 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); + + CLBuildOptions build_opts; + build_opts.add_option_if(_biases != nullptr, "-DHAS_BIAS"); + 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)); + build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_accessed_per_iteration)); + build_opts.add_option("-DSRC_DEPTH=" + support::cpp11::to_string(_input->info()->dimension(2))); + build_opts.add_option("-DCONV_PAD_TOP=" + support::cpp11::to_string(conv_info.pad_top())); + build_opts.add_option("-DROWS_READ=" + support::cpp11::to_string(num_rows_read_per_iteration)); + + 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)); + } + } + } + + // Create kernel + std::string kernel_name = std::string("depthwise_convolution_3x3_quantized_nhwc_stride") + support::cpp11::to_string(conv_stride_x); + _kernel = static_cast(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options())); + + // Configure kernel window + auto win_config = validate_and_configure_window(input->info(), weights->info(), output->info(), conv_info); + ARM_COMPUTE_ERROR_THROW_ON(win_config.first); + ICLKernel::configure(win_config.second); + + // Set config_id for enabling LWS tuning + _config_id = kernel_name; + _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)); +} + +Status CLDepthwiseConvolutionLayer3x3NHWCKernel::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, + ActivationLayerInfo act_info) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info, act_info)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(), output->clone().get(), conv_info).first); + + return Status{}; +} + +void CLDepthwiseConvolutionLayer3x3NHWCKernel::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::DimY, -_conv_pad_left, true); + win_in.set_dimension_step(Window::DimY, _num_rows_processed_per_iteration); + win_in.set_dimension_step(Window::DimZ, _conv_stride_y); + + ARM_COMPUTE_ERROR_ON((win_in.y().step() < window.y().step()) || (win_in.z().step() < window.z().step())); + + Window slice_in = win_in.first_slice_window_3D(); + Window slice_out = window.first_slice_window_3D(); + + if(_biases != nullptr) + { + unsigned int idx = 3 * num_arguments_per_3D_tensor(); + Window win_biases; + win_biases.use_tensor_dimensions(_biases->info()->tensor_shape()); + win_biases.set_dimension_step(Window::DimX, window.x().step()); + add_1D_tensor_argument(idx, _biases, win_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_out); + + 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