/* * Copyright (c) 2022-2023 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 "ClTemplateCast.h" #include "arm_compute/core/utils/helpers/AdjustVecSize.h" #include "arm_compute/core/utils/StringUtils.h" #include "src/core/helpers/WindowHelpers.h" #include "src/dynamic_fusion/sketch/gpu/GpuKernelComponentGroup.h" namespace arm_compute { namespace experimental { namespace dynamic_fusion { ClTemplateCast::ClTemplateCast(ComponentId id, const ArgumentPack &tensors, const Attributes &attributes) : IGpuTemplateComponentWriter{id, tensors}, _src{}, _dst{}, _attributes{attributes} { _src = this->tensors().get_const_tensor(TensorType::ACL_SRC_0); _dst = this->tensors().get_const_tensor(TensorType::ACL_DST_0); ARM_COMPUTE_ERROR_ON_NULLPTR(_src, _dst); } std::string ClTemplateCast::get_name() const { const size_t src_size = data_size_from_type(_src->data_type()); const size_t dst_size = data_size_from_type(_dst->data_type()); return (src_size >= dst_size) ? "cast_down" : "cast_up"; } std::string ClTemplateCast::get_component_code(const ComponentGroup &comp_group) const { ARM_COMPUTE_UNUSED(comp_group); const std::string kernel_name = get_name(); const auto is_root = (comp_group.get_root_component()->id() == this->id()); std::string code = R"_( //------------------ START KERNEL {{meta_kernel_id}} CAST --------------------- )_"; if (is_root) { code += R"_( // IN_0(src) {{src}} // OUT(dst, accum) {{dst}} TILE(uint, M0, 1, g_dst_indirect_y); { {{src}}_offset_first_element_in_bytes += get_global_id(2) * {{src}}_stride_z; TILE({{DATA_TYPE_IN}}, M0, N0, {{tmp}}); T_LOAD({{DATA_TYPE_IN}}, M0, N0, BUFFER, {{src}}, g_ind_0, g_ind_1, 1, {{src}}_stride_y, {{tmp}}); )_"; } code += R"_( LOOP_UNROLLING(int, m0, 0, 1, M0, { )_"; if (kernel_name == "cast_down" && is_data_type_quantized(_src->data_type())) { code += R"_( {{tmp}}[m0].v ^= (VEC_DATA_TYPE({{DATA_TYPE_IN}}, N0))0x80; )_"; } if (kernel_name == "cast_down" && (is_data_type_float(_src->data_type()) || _attributes.convert_policy() == ConvertPolicy::SATURATE)) { code += R"_( {{dst}}[m0].v = CONVERT_SAT({{tmp}}[m0].v, VEC_DATA_TYPE({{DATA_TYPE_OUT}}, N0)); )_"; } else { code += R"_( {{dst}}[m0].v = CONVERT({{tmp}}[m0].v, VEC_DATA_TYPE({{DATA_TYPE_OUT}}, N0)); )_"; } code += R"_( }) )_"; if (is_root) { 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); }) } )_"; } code += R"_( //------------------ END KERNEL {{meta_kernel_id}} CAST --------------------- )_"; return code; } void ClTemplateCast::declare_variables(GpuKernelVariableTable &vtable, const ComponentGroup &comp_group) const { vtable.declare_variable(comp_group, _src, GpuKernelArgumentInfo(GpuKernelArgumentInfo::Type::Tensor_4D_t_Buffer), "src"); vtable.declare_variable(comp_group, _dst, GpuKernelArgumentInfo(GpuKernelArgumentInfo::Type::Tensor_4D_t_Buffer), "dst"); } TagLUT ClTemplateCast::get_tag_lut(const GpuKernelVariableTable &vtable, const ComponentGroup &comp_group) const { const auto is_root = (comp_group.get_root_component()->id() == this->id()); TagLUT lut{}; // Arguments and global shared variables lut["src"] = vtable.get_variable(_src); lut["dst"] = vtable.get_variable(_dst); lut["tmp"] = (is_root) ? lut["src"].value + "_in_data" : lut["src"]; 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["DATA_TYPE_IN"] = get_cl_type_from_data_type(_src->data_type()); lut["DATA_TYPE_OUT"] = get_cl_type_from_data_type(_dst->data_type()); return lut; } CLBuildOptions ClTemplateCast::get_build_options(const ComponentGroup &comp_group) const { ARM_COMPUTE_UNUSED(comp_group); const auto root_window = comp_group.get_root_component()->template_writer()->get_window(); const unsigned int n0 = root_window.x().step(); const unsigned int m0 = root_window.y().step(); // Set build options CLBuildOptions build_opts{}; build_opts.add_option("-DN0=" + support::cpp11::to_string(n0)); build_opts.add_option("-DPARTIAL_N0=" + support::cpp11::to_string(_src->dimension(0) % n0)); build_opts.add_option("-DM0=" + support::cpp11::to_string(m0)); return build_opts; } std::string ClTemplateCast::get_config_id() const { std::string config_id{}; config_id += "_"; config_id += lower_string(string_from_data_type(_src->data_type())); config_id += "_"; config_id += lower_string(string_from_data_type(_dst->data_type())); config_id += "_"; config_id += support::cpp11::to_string(_src->dimension(0)); config_id += "_"; config_id += support::cpp11::to_string(_src->dimension(1)); return config_id; } std::set ClTemplateCast::get_headers_list() const { return std::set{"helpers.h", "tile_helpers.h"}; } Window ClTemplateCast::get_window() const { ARM_COMPUTE_ERROR_ON_MSG(_dst->tensor_shape().total_size() == 0U, "Destination tensor is not initialized"); const unsigned int n0 = adjust_vec_size(16 / _dst->element_size(), _dst->dimension(0)); Window win = calculate_max_window(*_dst, Steps(n0)); return win.collapse(win, Window::DimZ); } } // namespace dynamic_fusion } // namespace experimental } // namespace arm_compute