Developer Guide and Reference

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

Reduction Primitive Example

This C++ API example demonstrates how to create and execute a Reduction primitive.
/******************************************************************************* * 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 <cmath> #include "example_utils.hpp" #include "oneapi/dnnl/dnnl.hpp" using namespace dnnl; using tag = memory::format_tag; using dt = memory::data_type; void reduction_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 = 227, // tensor height IW = 227; // tensor width // Source (src) and destination (dst) tensors dimensions. memory::dims src_dims = {N, IC, IH, IW}; memory::dims dst_dims = {1, IC, 1, 1}; // Allocate buffers. std::vector<float> src_data(product(src_dims)); std::vector<float> dst_data(product(dst_dims)); // Initialize src tensor. std::generate(src_data.begin(), src_data.end(), []() { static int i = 0; return std::cos(i++ / 10.f); }); // Create src and dst memory descriptors and memory objects. auto src_md = memory::desc(src_dims, dt::f32, tag::nchw); auto dst_md = memory::desc(dst_dims, dt::f32, tag::nchw); auto src_mem = memory(src_md, engine); auto dst_mem = memory(dst_md, engine); // Write data to memory object's handle. write_to_dnnl_memory(src_data.data(), src_mem); // Create operation descriptor. auto reduction_d = reduction::desc( algorithm::reduction_sum, src_md, dst_md, 0.f, 0.f); // Create primitive descriptor. auto reduction_pd = reduction::primitive_desc(reduction_d, engine); // Create the primitive. auto reduction_prim = reduction(reduction_pd); // Primitive arguments. std::unordered_map<int, memory> reduction_args; reduction_args.insert({DNNL_ARG_SRC, src_mem}); reduction_args.insert({DNNL_ARG_DST, dst_mem}); // Primitive execution: Reduction (Sum). reduction_prim.execute(engine_stream, reduction_args); // Wait for the computation to finalize. engine_stream.wait(); // Read data from memory object's handle. read_from_dnnl_memory(dst_data.data(), dst_mem); } int main(int argc, char **argv) { return handle_example_errors( reduction_example, parse_engine_kind(argc, argv)); }

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