| /* |
| * Copyright (c) 2022 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 "ClTemplateDepthwiseConv2d.h" |
| |
| #include "src/core/helpers/WindowHelpers.h" |
| #include "src/dynamic_fusion/sketch/gpu/GpuKernelComponentGroup.h" |
| |
| namespace arm_compute |
| { |
| namespace experimental |
| { |
| namespace dynamic_fusion |
| { |
| ClTemplateDepthwiseConv2d::ClTemplateDepthwiseConv2d(ComponentId id, |
| const ArgumentPack<ITensorInfo> &tensors, |
| const Attributes &attributes, |
| const Settings &settings) |
| : IGpuTemplateComponentWriter{ id, tensors }, |
| _src{}, |
| _weight{}, |
| _bias{}, |
| _dst{}, |
| _attributes{ attributes }, |
| _settings{ settings } |
| { |
| _src = this->tensors().get_const_tensor(TensorType::ACL_SRC_0); |
| _weight = this->tensors().get_const_tensor(TensorType::ACL_SRC_1); |
| if(this->tensors().get_const_tensor(TensorType::ACL_SRC_2)) |
| { |
| _bias = this->tensors().get_const_tensor(TensorType::ACL_SRC_2); |
| } |
| _dst = this->tensors().get_const_tensor(TensorType::ACL_DST_0); |
| ARM_COMPUTE_ERROR_ON_NULLPTR(_src, _weight, _dst); |
| } |
| |
| std::string ClTemplateDepthwiseConv2d::get_name() const |
| { |
| return "depthwise_conv2d"; |
| } |
| |
| std::string ClTemplateDepthwiseConv2d::get_component_code(const ComponentGroup &comp_group) const |
| { |
| ARM_COMPUTE_UNUSED(comp_group); |
| |
| constexpr int height_idx = 2; // Data Layout is NHWC |
| |
| std::string code = R"_( |
| //------------------ START KERNEL {{meta_kernel_id}} --------------------- |
| // IN_0(src) {{src}} |
| // IN_1(wei) {{weight}} |
| )_"; |
| |
| if(_bias != nullptr && _bias->has_valid_id()) |
| { |
| code += R"_( |
| // IN_1(bia) {{bias}} |
| )_"; |
| } |
| |
| code += R"_( |
| // OUT(dst, accum) {{dst}} |
| |
| TILE(uint, M0, 1, g_dst_indirect_y); |
| |
| { |
| #define _IWEI_WIDTH {{WEI_WIDTH}} |
| #define _IWEI_HEIGHT {{WEI_HEIGHT}} |
| #define _IDST_WIDTH {{arg_dst}}_w |
| #define _IDST_HEIGHT {{arg_dst}}_h |
| #define _IM0_A M0_A |
| #define _IN0_A N0_A |
| #define _IM0_B _IWEI_WIDTH |
| #define _IN0_B N0 |
| #define _IBOUNDARY_CHECK (!((_IWEI_WIDTH == 1 && _IWEI_HEIGHT == 1 && {{PAD_LEFT}} == 0 && {{PAD_TOP}} == 0 && M0 == 1))) |
| )_"; |
| |
| code += R"_( |
| const int yo = g_ind_2 % {{arg_dst}}_h; |
| const int bout = g_ind_2 / {{arg_dst}}_h; |
| )_"; |
| |
| code += R"_( |
| |
| int xi = g_ind_1 * {{STRIDE_X}}; |
| int yi = yo * {{STRIDE_Y}}; |
| xi -= {{PAD_LEFT}}; |
| yi -= {{PAD_TOP}}; |
| |
| LOOP_UNROLLING(int, i, 0, 1, M0, |
| { |
| {{dst}}[i].v = 0; |
| }) |
| )_"; |
| |
| if(_weight->dimension(height_idx) < 5) |
| { |
| code += R"_( |
| LOOP_UNROLLING(int, yk, 0, 1, _IWEI_HEIGHT, |
| )_"; |
| } |
| else |
| { |
| code += R"_( |
| for(int yk = 0; yk < _IWEI_HEIGHT; ++yk) |
| )_"; |
| } |
| |
| code += R"_( |
| { |
| TILE({{SRC_DATA_TYPE}}, _IM0_A, _IN0_A, a); |
| |
| LOOP_UNROLLING(int, i, 0, 1, _IM0_A, |
| { |
| a[i].v = 0; |
| }) |
| |
| T_LOAD_NHWC_WITH_DILATION({{SRC_DATA_TYPE}}, 1, _IM0_A, _IN0_A, {{SRC_TENSOR_TYPE}}, {{src}}, bout, yi + yk * {{DILATION_Y}}, xi, (g_ind_0 / {{DEPTH_MULTIPLIER}}), {{src}}_w, {{src}}_h, {{DILATION_X}}, 1, _IBOUNDARY_CHECK, a); |
| |
| TILE({{WEI_DATA_TYPE}}, _IM0_B, _IN0_B, b); |
| |
| T_LOAD({{WEI_DATA_TYPE}}, _IM0_B, _IN0_B, {{WEI_TENSOR_TYPE}}, {{weight}}, g_ind_0, yk * _IM0_B, 1, {{weight}}_stride_y, b); |
| |
| LOOP_UNROLLING(int, m0, 0, 1, M0, |
| { |
| LOOP_UNROLLING(int, xk, 0, 1, _IWEI_WIDTH, |
| { |
| )_"; |
| |
| if(!_settings.is_fma_available()) |
| { |
| code += R"_( |
| {{dst}}[m0].v += a[xk + m0].v * b[xk].v; |
| )_"; |
| } |
| else |
| { |
| code += R"_( |
| {{dst}}[m0].v = fma(a[xk + m0].v, b[xk].v, {{dst}}[m0].v); |
| )_"; |
| } |
| |
| code += R"_( |
| }) |
| }) |
| } |
| )_"; |
| |
| if(_weight->dimension(height_idx) < 5) |
| { |
| code += R"_( |
| ) |
| )_"; |
| } |
| |
| if(_bias && _bias->has_valid_id()) |
| { |
| code += R"_( |
| TILE({{BIA_DATA_TYPE}}, 1, N0, {{bias}}); |
| |
| T_LOAD({{BIA_DATA_TYPE}}, 1, N0, BUFFER, {{bias}}, g_ind_0, 0, 0, 0, {{bias}}); |
| |
| T_ELTWISE_BROADCAST_ADD_X({{ACC_DATA_TYPE}}, M0, N0, {{dst}}, {{bias}}, {{dst}}); |
| )_"; |
| } |
| |
| code += R"_( |
| LOOP_UNROLLING(int, i, 0, 1, M0, |
| { |
| g_dst_indirect_y[i].v = (uint)min((int)(g_ind_1 + i), (int)({{arg_dst}}_w) - 1); |
| g_dst_indirect_y[i].v += (int)(g_ind_2 % {{arg_dst}}_h) * (int)({{arg_dst}}_w); |
| g_dst_indirect_y[i].v += (int)(g_ind_2 / {{arg_dst}}_h) * (int)({{arg_dst}}_w * {{arg_dst}}_h); |
| }) |
| } |
| //------------------ END KERNEL {{meta_kernel_id}} --------------------- |
| )_"; |
| |
| return code; |
| } |
| |
| void ClTemplateDepthwiseConv2d::declare_variables(GpuKernelVariableTable &vtable, const ComponentGroup &comp_group) const |
| { |
| const GpuKernelArgumentInfo::Type input_type = _settings.export_input_to_cl_image() ? |
| GpuKernelArgumentInfo::Type::Tensor_4D_t_Image : |
| GpuKernelArgumentInfo::Type::Tensor_4D_t_Buffer; |
| |
| vtable.declare_variable( |
| comp_group, |
| _src, |
| GpuKernelArgumentInfo(input_type), |
| "src"); |
| |
| const GpuKernelArgumentInfo::Type weight_type = _settings.export_weights_to_cl_image() ? |
| GpuKernelArgumentInfo::Type::Tensor_4D_t_Image : |
| GpuKernelArgumentInfo::Type::Tensor_4D_t_Buffer; |
| |
| vtable.declare_variable( |
| comp_group, |
| _weight, |
| GpuKernelArgumentInfo(weight_type), |
| "weight"); |
| |
| if(_bias != nullptr && _bias->has_valid_id()) // optional bias |
| { |
| vtable.declare_variable( |
| comp_group, |
| _bias, |
| GpuKernelArgumentInfo(GpuKernelArgumentInfo::Type::Vector), |
| "bias"); |
| } |
| vtable.declare_variable( |
| comp_group, |
| _dst, |
| GpuKernelArgumentInfo(GpuKernelArgumentInfo::Type::Tensor_4D_t_Buffer), |
| "dst"); |
| } |
| |
| TagLUT ClTemplateDepthwiseConv2d::get_tag_lut(const GpuKernelVariableTable &vtable, const ComponentGroup &comp_group) const |
| { |
| TagLUT lut{}; |
| |
| // Arguments and global shared variables |
| lut["src"] = vtable.get_variable(_src); |
| lut["weight"] = vtable.get_variable(_weight); |
| |
| if(_bias != nullptr && _bias->has_valid_id()) // optional bias |
| { |
| lut["bias"] = vtable.get_variable(_bias); |
| lut["BIA_DATA_TYPE"] = get_cl_type_from_data_type(_bias->data_type()); |
| } |
| lut["dst"] = vtable.get_variable(_dst); |
| |
| const auto dst_argument = vtable.get_variable(comp_group.get_any_dst_tensor()); |
| lut["arg_dst"] = dst_argument.uniq_name; |
| |
| // Local build options |
| lut["meta_kernel_id"] = id(); |
| lut["ACC_DATA_TYPE"] = _src->data_type(); |
| lut["SRC_DATA_TYPE"] = _src->data_type(); |
| lut["WEI_DATA_TYPE"] = _weight->data_type(); |
| |
| switch(vtable.get_variable(_src).kernel_argument_info.type) |
| { |
| case GpuKernelArgumentInfo::Type::Image_Export_To_ClImage2D: |
| case GpuKernelArgumentInfo::Type::Image_3D_Export_To_ClImage2D: |
| case GpuKernelArgumentInfo::Type::Tensor_4D_t_Image: |
| lut["SRC_TENSOR_TYPE"] = "IMAGE"; |
| break; |
| default: |
| lut["SRC_TENSOR_TYPE"] = "BUFFER"; |
| break; |
| } |
| |
| switch(vtable.get_variable(_weight).kernel_argument_info.type) |
| { |
| case GpuKernelArgumentInfo::Type::Image_Export_To_ClImage2D: |
| case GpuKernelArgumentInfo::Type::Image_3D_Export_To_ClImage2D: |
| case GpuKernelArgumentInfo::Type::Tensor_4D_t_Image: |
| lut["WEI_TENSOR_TYPE"] = "IMAGE"; |
| break; |
| default: |
| lut["WEI_TENSOR_TYPE"] = "BUFFER"; |
| break; |
| } |
| |
| // Data Layout is NHWC |
| constexpr int width_idx = 1; |
| constexpr int height_idx = 2; |
| |
| lut["WEI_WIDTH"] = _weight->dimension(width_idx); |
| lut["WEI_HEIGHT"] = _weight->dimension(height_idx); |
| |
| lut["STRIDE_X"] = _attributes.stride().x(); |
| lut["STRIDE_Y"] = _attributes.stride().y(); |
| |
| lut["PAD_LEFT"] = _attributes.pad().left; |
| lut["PAD_TOP"] = _attributes.pad().top; |
| |
| lut["DILATION_X"] = _attributes.dilation().x(); |
| lut["DILATION_Y"] = _attributes.dilation().y(); |
| |
| lut["DEPTH_MULTIPLIER"] = _attributes.depth_multiplier(); |
| |
| return lut; |
| } |
| |
| CLBuildOptions ClTemplateDepthwiseConv2d::get_build_options(const ComponentGroup &comp_group) const |
| { |
| ARM_COMPUTE_UNUSED(comp_group); |
| |
| constexpr unsigned int width_idx = 1; // Data Layout is NHWC |
| |
| const unsigned int n0 = _settings.n0(); |
| const unsigned int m0 = _settings.m0(); |
| const unsigned int m0_a = _weight->dimension(width_idx) + m0 - 1; |
| const unsigned int n0_a = _attributes.depth_multiplier() > 1 ? 1 : n0; |
| const unsigned int partial_store_n0 = _dst->dimension(0) % n0; |
| |
| CLBuildOptions build_opts{}; |
| |
| if(_settings.fast_relaxed_math()) |
| { |
| build_opts.add_option("-cl-fast-relaxed-math"); |
| } |
| else |
| { |
| // -cl-fast-relaxed-math also sets -cl-finite-math-only and -cl-unsafe-math-optimizations |
| // to disable -cl-finite-math-only, we only include -cl-unsafe-math-optimizations |
| build_opts.add_option("-cl-unsafe-math-optimizations"); |
| } |
| |
| build_opts.add_option("-DN0=" + support::cpp11::to_string(n0)); |
| build_opts.add_option("-DM0=" + support::cpp11::to_string(m0)); |
| build_opts.add_option("-DN0_A=" + support::cpp11::to_string(n0_a)); |
| build_opts.add_option("-DM0_A=" + support::cpp11::to_string(m0_a)); |
| build_opts.add_option("-DPARTIAL_N0=" + support::cpp11::to_string(partial_store_n0)); |
| |
| return build_opts; |
| } |
| |
| std::string ClTemplateDepthwiseConv2d::get_config_id() const |
| { |
| std::string config_id{}; |
| |
| config_id += support::cpp11::to_string(_src->dimension(0)); |
| config_id += "_"; |
| config_id += support::cpp11::to_string(_src->dimension(1)); |
| config_id += "_"; |
| config_id += support::cpp11::to_string(_src->dimension(2)); |
| config_id += "_"; |
| config_id += support::cpp11::to_string(_dst->dimension(0)); |
| config_id += "_"; |
| config_id += support::cpp11::to_string(_dst->dimension(1)); |
| config_id += "_"; |
| config_id += support::cpp11::to_string(_dst->dimension(2)); |
| config_id += "_"; |
| config_id += string_from_data_type(_src->data_type()); |
| |
| return config_id; |
| } |
| |
| std::set<std::string> ClTemplateDepthwiseConv2d::get_headers_list() const |
| { |
| return std::set<std::string>{ "helpers.h", "tile_helpers.h" }; |
| } |
| |
| Window ClTemplateDepthwiseConv2d::get_window() const |
| { |
| ARM_COMPUTE_ERROR_ON_MSG(_dst->tensor_shape().total_size() == 0U, "Destination tensor is not initialized"); |
| |
| Window win = calculate_max_window(*_dst, Steps(_settings.n0(), _settings.m0())); |
| return win.collapse(win, Window::DimZ); |
| } |
| |
| } // namespace dynamic_fusion |
| } // namespace experimental |
| } // namespace arm_compute |