diff options
Diffstat (limited to 'src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp')
| -rw-r--r-- | src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp | 432 |
1 files changed, 0 insertions, 432 deletions
diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp deleted file mode 100644 index dda70d2231..0000000000 --- a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp +++ /dev/null @@ -1,432 +0,0 @@ -/* - * Copyright (c) 2018-2021 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 "src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.h" - -#include "arm_compute/core/CL/CLHelpers.h" -#include "arm_compute/core/CL/CLKernelLibrary.h" -#include "arm_compute/core/CL/ICLTensor.h" -#include "arm_compute/core/Helpers.h" -#include "arm_compute/core/TensorInfo.h" -#include "arm_compute/core/Utils.h" -#include "arm_compute/core/utils/misc/ShapeCalculator.h" -#include "arm_compute/core/utils/quantization/AsymmHelpers.h" -#include "src/core/AccessWindowStatic.h" -#include "src/core/CL/CLValidate.h" -#include "src/core/CL/ICLKernel.h" -#include "src/core/helpers/AutoConfiguration.h" -#include "src/core/helpers/WindowHelpers.h" -#include "support/StringSupport.h" - -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, unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D dilation, - const ITensorInfo *output_multipliers, const ITensorInfo *output_shifts) -{ - ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MSG((act_info.enabled()) && (input->data_type() == DataType::QASYMM8 || input->data_type() == DataType::QASYMM8_SIGNED) - && (act_info.activation() != ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU) - && (act_info.activation() != ActivationLayerInfo::ActivationFunction::BOUNDED_RELU) - && (act_info.activation() != ActivationLayerInfo::ActivationFunction::RELU) - && (act_info.activation() != ActivationLayerInfo::ActivationFunction::LOGISTIC), - "For QASYMM8 only logistic, relu, lower bounded relu and lower-upper bounded relu are supported"); - ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(0) != 3 || weights->dimension(1) != 3); - ARM_COMPUTE_RETURN_ERROR_ON(conv_info.stride().first < 1 || conv_info.stride().first > 3); - - ARM_COMPUTE_RETURN_ERROR_ON((dilation.x() < 1) || (dilation.y() < 1)); - - const bool is_qasymm = is_data_type_quantized_asymmetric(input->data_type()); - - if(biases != nullptr) - { - if(is_qasymm) - { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(biases, 1, DataType::S32); - } - else - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(weights, biases); - } - ARM_COMPUTE_RETURN_ERROR_ON((biases->dimension(0) != weights->dimension(2)) && (weights->dimension(2) != 1 || biases->dimension(0) != weights->dimension(3))); - ARM_COMPUTE_RETURN_ERROR_ON(biases->num_dimensions() > 1); - } - - if(is_qasymm) - { - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output_multipliers, output_shifts); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output_multipliers, 1, DataType::S32); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output_shifts, 1, DataType::S32); - ARM_COMPUTE_RETURN_ERROR_ON(output_multipliers->num_dimensions() > 1); - ARM_COMPUTE_RETURN_ERROR_ON(output_shifts->num_dimensions() > 1); - - if(is_data_type_quantized_per_channel(weights->data_type())) - { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(weights, 1, DataType::QSYMM8_PER_CHANNEL); - ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(2) != output_multipliers->dimension(0)); - ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(2) != output_shifts->dimension(0)); - } - else - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); - ARM_COMPUTE_RETURN_ERROR_ON(1 != output_multipliers->dimension(0)); - ARM_COMPUTE_RETURN_ERROR_ON(1 != output_shifts->dimension(0)); - } - } - else - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); - } - - if(output->total_size() != 0) - { - const ConvolutionInfo info{ conv_info, depth_multiplier, ActivationLayerInfo(), dilation }; - const TensorShape output_shape = compute_depthwise_convolution_shape(*input, *weights, info); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape); - } - - return Status{}; -} - -std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *output, const PadStrideInfo &conv_info, - unsigned int depth_multiplier, std::string &kernel_name, const Size2D dilation) -{ - // Output auto inizialitation if not yet initialized - const ConvolutionInfo info - { - conv_info, depth_multiplier, ActivationLayerInfo(), dilation - }; - const TensorShape output_shape = compute_depthwise_convolution_shape(*input, *weights, info); - auto_init_if_empty(*output, input->clone()->set_tensor_shape(output_shape).set_quantization_info(output->quantization_info())); - - const unsigned int conv_stride_x = conv_info.stride().first; - const unsigned int conv_stride_y = conv_info.stride().second; - const bool is_qasymm = is_data_type_quantized_asymmetric(input->data_type()); - - // 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; - - if(input->data_type() == DataType::F16) - { - kernel_name = "depthwise_convolution_3x3_f16"; - num_elems_written_per_iteration_x = 8 / data_size_from_type(input->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(conv_stride_x == 1 && conv_stride_y == 1) - { - kernel_name = "depthwise_convolution_3x3_stridex1_stridey1_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_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->data_type() == DataType::F32) - { - if(conv_stride_x == 1 && conv_stride_y == 1) - { - kernel_name = "depthwise_convolution_3x3_stridex1_stridey1_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_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->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 - { - const bool is_dot8_supported = dot8_supported(CLKernelLibrary::get().get_device()) && !is_data_type_quantized_per_channel(weights->data_type()); - - kernel_name = is_qasymm ? "dwc_3x3_native_quantized8" : "depthwise_convolution_3x3"; - kernel_name += (is_qasymm && is_dot8_supported ? "_dot8" : ""); - kernel_name += (is_qasymm ? "_nchw" : ""); - - num_elems_written_per_iteration_x = 8 / data_size_from_type(input->data_type()); - num_elems_written_per_iteration_y = (is_qasymm && conv_stride_y == 1 && dilation.y() == 1) ? 2 : 1; - num_elems_read_per_iteration_x = 3 + (num_elems_written_per_iteration_x - 1) * conv_stride_x + (conv_stride_x > 1 ? 1 : 0); - num_elems_read_per_iteration_y = num_elems_written_per_iteration_y + 2; - } - // The OpenCL routine convolution1x3 does loadn(addr), loadn(addr + dilation_x) and loadn(addr + 2 * dilation_x) on the input. - // Each of the three convolution1x3 gets called by passing addr, (addr + dilation_y) and (addr + 2 * dilation_y) - // Hence we must add 2 * dilation.x/y() to the number of elements read in those axes per thread - num_elems_read_per_iteration_x += 2 * dilation.x(); - num_elems_read_per_iteration_y += 2 * dilation.y(); - - // Create window and update padding - Window win = calculate_max_window(*output, Steps(num_elems_written_per_iteration_x, num_elems_written_per_iteration_y)); - - AccessWindowRectangle input_access(input, -conv_info.pad_left(), -conv_info.pad_top(), - num_elems_read_per_iteration_x, num_elems_read_per_iteration_y, - conv_stride_x, conv_stride_y); - AccessWindowStatic weights_access(weights, 0, 0, 3, 3); - AccessWindowRectangle output_access(output, 0, 0, num_elems_written_per_iteration_x, num_elems_written_per_iteration_y); - - bool window_changed = update_window_and_padding(win, input_access, weights_access, output_access); - - Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; - return std::make_pair(err, win); -} -} // namespace - -CLDepthwiseConvolutionLayer3x3NCHWKernel::CLDepthwiseConvolutionLayer3x3NCHWKernel() - : _border_size(0), _input(), _output(), _weights(), _biases(), _conv_stride_y(1), _output_multipliers(), _output_shifts(), _is_quantized(false), _conv_stride_x(0), _conv_pad_top(0), _conv_pad_left(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, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation, - const ICLTensor *output_multipliers, const ICLTensor *output_shifts) -{ - configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation, output_multipliers, output_shifts); -} - -void CLDepthwiseConvolutionLayer3x3NCHWKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, - const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation, - const ICLTensor *output_multipliers, const ICLTensor *output_shifts) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), - conv_info, depth_multiplier, act_info, dilation, - (output_multipliers != nullptr) ? output_multipliers->info() : nullptr, - (output_shifts != nullptr) ? output_shifts->info() : nullptr)); - - _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(); - _output_multipliers = output_multipliers; - _output_shifts = output_shifts; - _is_quantized = is_data_type_quantized_asymmetric(input->info()->data_type()); - - // Configure kernel window - std::string kernel_name; - - auto win_config = validate_and_configure_window(input->info(), weights->info(), output->info(), conv_info, depth_multiplier, kernel_name, dilation); - ARM_COMPUTE_ERROR_THROW_ON(win_config.first); - ICLKernel::configure_internal(win_config.second); - - _border_size = BorderSize(input->info()->padding()); - - // Set build options - CLBuildOptions build_opts; - build_opts.add_option("-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(act_info.activation()))); - build_opts.add_option("-DDST_CHANNELS=" + support::cpp11::to_string(_output->info()->tensor_shape().z())); - build_opts.add_option("-DDEPTH_MULTIPLIER=" + support::cpp11::to_string(depth_multiplier)); - build_opts.add_option("-DCONV_STRIDE_X=" + support::cpp11::to_string(_conv_stride_x)); - build_opts.add_option("-DDILATION_X=" + support::cpp11::to_string(dilation.x())); - build_opts.add_option("-DDILATION_Y=" + support::cpp11::to_string(dilation.y())); - build_opts.add_option_if(_biases != nullptr, "-DHAS_BIAS"); - - if(_is_quantized) - { - const UniformQuantizationInfo iq_info = _input->info()->quantization_info().uniform(); - const UniformQuantizationInfo wq_info = _weights->info()->quantization_info().uniform(); - const UniformQuantizationInfo oq_info = _output->info()->quantization_info().uniform(); - - const bool is_quantized_per_channel = is_data_type_quantized_per_channel(weights->info()->data_type()); - const bool is_dot8_supported = dot8_supported(CLKernelLibrary::get().get_device()) && !is_quantized_per_channel; - build_opts.add_option("-DCONV_STRIDE_Y=" + support::cpp11::to_string(_conv_stride_y)); - build_opts.add_option("-DINPUT_OFFSET=" + support::cpp11::to_string(-iq_info.offset)); - build_opts.add_option("-DWEIGHTS_OFFSET=" + support::cpp11::to_string(-wq_info.offset)); - build_opts.add_option("-DOUTPUT_OFFSET=" + support::cpp11::to_string(oq_info.offset)); - build_opts.add_option("-DK_OFFSET=" + support::cpp11::to_string(9 * iq_info.offset * wq_info.offset)); - build_opts.add_option_if(is_quantized_per_channel, "-DPER_CHANNEL_QUANTIZATION"); - build_opts.add_option_if(is_dot8_supported, "-DIS_DOT8"); - - // Compute non-per-channel multiplier and shift anyway to make OpenCL kernel simpler - float multiplier = iq_info.scale * wq_info.scale / oq_info.scale; - int output_multiplier = 0; - int output_shift = 0; - quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift); - 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()) - { - int a_val{}; - int b_val{}; - std::tie(b_val, a_val) = get_quantized_activation_min_max(act_info, input->info()->data_type(), oq_info); - - const int o1 = oq_info.offset; - - 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)); - - const float s1 = iq_info.scale; - build_opts.add_option("-DS1_VAL=" + float_to_string_with_full_precision(s1)); - build_opts.add_option("-DO1_VAL=" + support::cpp11::to_string(o1)); - } - - build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())); - build_opts.add_option("-DWEIGHTS_TYPE=" + get_cl_type_from_data_type(weights->info()->data_type())); - build_opts.add_option("-DWEIGHTS_PROMOTED_TYPE=" + get_cl_promoted_type_from_data_type(weights->info()->data_type())); - } - else - { - build_opts.add_option_if(act_info.enabled(), "-DA_VAL=" + float_to_string_with_full_precision(act_info.a())); - build_opts.add_option_if(act_info.enabled(), "-DB_VAL=" + float_to_string_with_full_precision(act_info.b())); - build_opts.add_option_if(act_info.enabled(), "-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())); - build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(win_config.second.x().step())); - } - - build_opts.add_option_if(input->info()->data_type() == DataType::F16, "-DIS_F16"); - build_opts.add_option_if(input->info()->data_type() == DataType::F32, "-DIS_F32"); - - _kernel = create_kernel(compile_context, 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)); -} - -Status CLDepthwiseConvolutionLayer3x3NCHWKernel::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, - const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, - const Size2D &dilation, const ITensorInfo *output_multipliers, const ITensorInfo *output_shifts) -{ - std::string kernel_name; - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation, output_multipliers, output_shifts)); - ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(), output->clone().get(), - conv_info, depth_multiplier, kernel_name, dilation) - .first); - - return Status{}; -} - -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); - - Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); - - // Create input window and adjust - Window collapsed_in = collapsed; - collapsed_in.adjust(Window::DimX, -_conv_pad_left, true); - collapsed_in.adjust(Window::DimY, -_conv_pad_top, true); - collapsed_in.set_dimension_step(Window::DimX, collapsed_in.x().step() * _conv_stride_x); - collapsed_in.set_dimension_step(Window::DimY, collapsed_in.y().step() * _conv_stride_y); - - Window slice_in = collapsed_in.first_slice_window_3D(); - Window slice_out = collapsed.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); - - unsigned int idx = 3 * num_arguments_per_3D_tensor(); - - // Set output multipliers in case of quantized data type - if(_is_quantized) - { - Window slice; - slice.use_tensor_dimensions(_output_multipliers->info()->tensor_shape()); - add_1D_tensor_argument(idx, _output_multipliers, slice); - add_1D_tensor_argument(idx, _output_shifts, slice); - } - - // Set biases - if(_biases != nullptr) - { - Window slice_biases; - slice_biases.use_tensor_dimensions(_biases->info()->tensor_shape()); - add_1D_tensor_argument(idx, _biases, slice_biases); - } - - do - { - 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(collapsed.slide_window_slice_3D(slice_out) && collapsed_in.slide_window_slice_3D(slice_in)); -} -} // namespace arm_compute |