Developer Guide and Reference

  • 2022.1
  • 04/11/2022
  • Public Content
Contents

concat.cpp

Annotated version: Concat Primitive Example
Annotated version: Concat Primitive Example
/******************************************************************************* * Copyright 2020 Intel Corporation * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *******************************************************************************/ #include <algorithm> #include <cmath> #include <iostream> #include <string> #include <vector> #include "example_utils.hpp" #include "oneapi/dnnl/dnnl.hpp" using namespace dnnl; using tag = memory::format_tag; using dt = memory::data_type; void concat_example(dnnl::engine::kind engine_kind) { // Create execution dnnl::engine. dnnl::engine engine(engine_kind, 0); // Create dnnl::stream. dnnl::stream engine_stream(engine); // Tensor dimensions. const memory::dim N = 3, // batch size IC = 3, // channels IH = 120, // tensor height IW = 120; // tensor width // Number of source (src) tensors. const int num_src = 10; // Concatenation axis. const int axis = 1; // src tensors dimensions memory::dims src_dims = {N, IC, IH, IW}; // Allocate buffers. std::vector<float> src_data(product(src_dims)); // Initialize src. // NOTE: In this example, the same src memory buffer is used to demonstrate // concatenation for simplicity std::generate(src_data.begin(), src_data.end(), []() { static int i = 0; return std::cos(i++ / 10.f); }); // Create a memory descriptor and memory object for each src tensor. std::vector<memory::desc> src_mds; std::vector<memory> src_mems; for (int n = 0; n < num_src; ++n) { auto md = memory::desc(src_dims, dt::f32, tag::nchw); auto mem = memory(md, engine); // Write data to memory object's handle. write_to_dnnl_memory(src_data.data(), mem); src_mds.push_back(md); src_mems.push_back(mem); } // Create primitive descriptor. auto concat_pd = concat::primitive_desc(axis, src_mds, engine); // Create destination (dst) memory object using the memory descriptor // created by the primitive. auto dst_mem = memory(concat_pd.dst_desc(), engine); // Create the primitive. auto concat_prim = concat(concat_pd); // Primitive arguments. std::unordered_map<int, memory> concat_args; for (int n = 0; n < num_src; ++n) concat_args.insert({DNNL_ARG_MULTIPLE_SRC + n, src_mems[n]}); concat_args.insert({DNNL_ARG_DST, dst_mem}); // Primitive execution: concatenation. concat_prim.execute(engine_stream, concat_args); // Wait for the computation to finalize. engine_stream.wait(); } int main(int argc, char **argv) { return handle_example_errors(concat_example, parse_engine_kind(argc, argv)); }

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