/* * The MIT License (MIT) * * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved. * * 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 #include #include #include #include #include namespace migraphx { inline namespace MIGRAPHX_INLINE_NS { namespace gpu { using namespace migraphx::gpu::gen; // NOLINT // NOLINTNEXTLINE static const char* const concat_kernel = R"__migraphx__( #include #include #include #include namespace migraphx { ${preamble} extern "C" { __global__ void ${kernel}(${params}) { transform_args(make_tensors(), rotate_last(), ${transformers})(${args})([](auto y, ${concat_params}, auto... xs) { concat<${axis}>(${concat_args})(${post}, y, xs...); }); } } } // namespace migraphx )__migraphx__"; struct concat_compiler : compiler { std::vector names() const { return {"concat"}; } static std::size_t get_concat_elements(const std::vector& inputs) { return inputs.back().elements() / (inputs.size() - 1); } operation compile_op(context& ctx, const std::vector& inputs, const value& v) const { auto num_of_concat_inputs = v.get("concat_inputs", inputs.size() - 1); hip_compile_options options; options.inputs = inputs; options.output = inputs.back(); options.params = "-Wno-float-equal"; options.kernel_name = v.get("kernel", "concat_kernel"); auto axis = find_fast_axis(options.inputs); auto vec = vectorize::elements(ctx, axis, options.inputs); options.kernel_name = v.get("kernel", "concat_kernel"); options.set_launch_params( v, compute_global_for(ctx, get_concat_elements(options.inputs) / vec.size, 256)); auto src = interpolate_string( concat_kernel, {{"kernel", options.kernel_name}, {"params", enum_params(inputs.size(), "void * private_p")}, {"args", enum_params(inputs.size(), "private_p")}, {"concat_params", enum_params(num_of_concat_inputs, "auto concat_x")}, {"concat_args", enum_params(num_of_concat_inputs, "concat_x")}, {"post", v.get("post", std::string{"op::id{}"})}, {"transformers", make_transformer_args(vec)}, {"preamble", v.get("preamble", std::string{})}, {"axis", v.at("axis").to()}}); return compile_hip_code_object(src, options); } compiler_replace compile(context& ctx, instruction_ref ins, const operation& op) const { auto v = op.to_value(); if(not ins->module_inputs().empty()) { auto* pm = ins->module_inputs().front(); v["concat_inputs"] = ins->inputs().size() - pm->get_parameter_names().size(); v["preamble"] = generate_pointwise(*pm, "post_concat"); v["post"] = "MIGRAPHX_LIFT(post_concat)"; v["kernel"] = "concat_" + generate_name_from_ops(*pm) + "_kernel"; } return replace(compile_op(ctx, to_shapes(ins->inputs()), v)); } }; } // namespace gpu } // namespace MIGRAPHX_INLINE_NS } // namespace migraphx