/* * Copyright (c) 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 "src/dynamic_fusion/sketch/gpu/template_writer/cl/ClTemplateLogits1DNorm.h" #include "arm_compute/core/utils/helpers/AdjustVecSize.h" #include "src/core/helpers/WindowHelpers.h" #include "src/dynamic_fusion/sketch/gpu/GpuKernelComponentGroup.h" #include "support/StringSupport.h" namespace arm_compute { namespace experimental { namespace dynamic_fusion { ClTemplateLogits1DNorm::ClTemplateLogits1DNorm(ComponentId id, const ArgumentPack &tensors, const Attributes &attributes) : IGpuTemplateComponentWriter{id, tensors}, _src{}, _sum{}, _dst{}, _attributes{attributes} { _src = this->tensors().get_const_tensor(TensorType::ACL_SRC_0); _sum = this->tensors().get_const_tensor(TensorType::ACL_SRC_1); _dst = this->tensors().get_const_tensor(TensorType::ACL_DST_0); ARM_COMPUTE_ERROR_ON_NULLPTR(_src); ARM_COMPUTE_ERROR_ON_NULLPTR(_sum); ARM_COMPUTE_ERROR_ON_NULLPTR(_dst); } std::string ClTemplateLogits1DNorm::get_name() const { return "logits_1d_norm"; } std::string ClTemplateLogits1DNorm::get_component_code(const ComponentGroup &comp_group) const { ARM_COMPUTE_UNUSED(comp_group); std::string code = R"_( //------------------ START KERNEL {{meta_kernel_id}} --------------------- { const int x_offs = g_ind_0 * sizeof({{DATA_TYPE}}); __global uchar *src_addr = {{src}}_ptr + {{src}}_offset_first_element_in_bytes + x_offs + g_ind_1 * {{src}}_stride_y + g_ind_2 * {{src}}_stride_z; __global uchar *dst_addr = {{dst}}_ptr + {{dst}}_offset_first_element_in_bytes + x_offs + g_ind_1 * {{dst}}_stride_y + g_ind_2 * {{dst}}_stride_z; Image sum = CONVERT_TENSOR3D_TO_IMAGE_STRUCT_NO_STEP({{sum}}); )_"; // Load max value of 1D logits vector (row) code += R"_( {{DATA_TYPE}} sum_val = *((__global {{DATA_TYPE}} *)offset(&sum, 0, g_ind_1)); VEC_DATA_TYPE({{DATA_TYPE}}, N0) data0 = VLOAD(N0)(0, (__global {{DATA_TYPE}} *)src_addr); )_"; if (_attributes.is_log_softmax()) { code += R"_( sum_val = log(sum_val); data0 -= sum_val; )_"; } else { code += R"_( data0 /= sum_val; )_"; } code += R"_( STORE_VECTOR_SELECT(data, {{DATA_TYPE}}, dst_addr, N0, PARTIAL_N0, PARTIAL_N0 != 0 && g_ind_0 == 0); } //------------------ END KERNEL {{meta_kernel_id}} --------------------- )_"; return code; } void ClTemplateLogits1DNorm::declare_variables(GpuKernelVariableTable &vtable, const ComponentGroup &comp_group) const { vtable.declare_variable(comp_group, _src, GpuKernelArgumentInfo(GpuKernelArgumentInfo::Type::Tensor_3D), "src"); vtable.declare_variable(comp_group, _sum, GpuKernelArgumentInfo(GpuKernelArgumentInfo::Type::Tensor_3D), "sum"); vtable.declare_variable(comp_group, _dst, GpuKernelArgumentInfo(GpuKernelArgumentInfo::Type::Tensor_3D), "dst"); } TagLUT ClTemplateLogits1DNorm::get_tag_lut(const GpuKernelVariableTable &vtable, const ComponentGroup &comp_group) const { ARM_COMPUTE_UNUSED(comp_group); TagLUT lut{}; // Arguments and global shared variables lut["src"] = vtable.get_variable(_src); lut["sum"] = vtable.get_variable(_sum); lut["dst"] = vtable.get_variable(_dst); // Local build options lut["meta_kernel_id"] = id(); const DataType data_type = _src->data_type(); lut["DATA_TYPE"] = get_cl_type_from_data_type(data_type); return lut; } CLBuildOptions ClTemplateLogits1DNorm::get_build_options(const ComponentGroup &comp_group) const { ARM_COMPUTE_UNUSED(comp_group); CLBuildOptions build_opts{}; const auto root_window = comp_group.get_root_component()->template_writer()->get_window(); const unsigned int n0 = root_window.x().step(); build_opts.add_option("-DN0=" + support::cpp11::to_string(n0)); build_opts.add_option("-DPARTIAL_N0=" + support::cpp11::to_string((_src->dimension(0) % n0))); return build_opts; } std::string ClTemplateLogits1DNorm::get_config_id() const { std::string config_id = get_name(); config_id += "_"; config_id += support::cpp11::to_string(_src->dimension(0)); config_id += "_"; config_id += string_from_data_type(_src->data_type()); return config_id; } std::set ClTemplateLogits1DNorm::get_headers_list() const { return std::set{"helpers.h", "tile_helpers.h"}; } Window ClTemplateLogits1DNorm::get_window() const { ARM_COMPUTE_ERROR_ON_MSG(_dst->tensor_shape().total_size() == 0U, "Destination tensor is not initialized"); constexpr unsigned int serial_vector_size = 16; const unsigned int vector_size = adjust_vec_size(serial_vector_size, _src->dimension(0)); Window win = calculate_max_window(*_src, Steps(vector_size)); return win.collapse(win, Window::DimZ); } } // namespace dynamic_fusion } // namespace experimental } // namespace arm_compute