.. index:: pair: page; Local Response Normalization Primitive Example
.. _doxid-lrn_example_cpp:

Local Response Normalization Primitive Example
==============================================

This C++ API demonstrates how to create and execute a :ref:`Local response normalization <doxid-dev_guide_lrn>` primitive in forward training propagation mode.

.. ref-code-block:: cpp

	/*******************************************************************************
	* 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 :ref:`dnnl <doxid-namespacednnl>`;
	
	void lrn_example(:ref:`dnnl::engine::kind <doxid-structdnnl_1_1engine_1a2635da16314dcbdb9bd9ea431316bb1a>` engine_kind) {
	
	    // Create execution dnnl::engine.
	    :ref:`dnnl::engine <doxid-structdnnl_1_1engine>` :ref:`engine <doxid-structdnnl_1_1engine>`(engine_kind, 0);
	
	    // Create dnnl::stream.
	    :ref:`dnnl::stream <doxid-structdnnl_1_1stream>` engine_stream(:ref:`engine <doxid-structdnnl_1_1engine>`);
	
	    // Tensor dimensions.
	    const :ref:`memory::dim <doxid-structdnnl_1_1memory_1a281426f169daa042dcf5379c8fce21a9>` N = 3, // batch size
	            IC = 3, // channels
	            IH = 227, // tensor height
	            IW = 227; // tensor width
	
	    // Source (src) and destination (dst) tensors dimensions.
	    :ref:`memory::dims <doxid-structdnnl_1_1memory_1a7d9f4b6ad8caf3969f436cd9ff27e9bb>` src_dims = {N, IC, IH, IW};
	
	    // Allocate buffers.
	    std::vector<float> src_data(product(src_dims));
	    std::vector<float> dst_data(product(src_dims));
	
	    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 :ref:`src_md <doxid-group__dnnl__api__primitives__common_1gga94efdd650364f4d9776cfb9b711cbdc1a90a729e395453e1d9411ad416c796819>` = :ref:`memory::desc <doxid-structdnnl_1_1memory_1_1desc>`(
	            src_dims, :ref:`memory::data_type::f32 <doxid-structdnnl_1_1memory_1a8e83474ec3a50e08e37af76c8c075dcea512dc597be7ae761876315165dc8bd2e>`, :ref:`memory::format_tag::nhwc <doxid-structdnnl_1_1memory_1a8e71077ed6a5f7fb7b3e6e1a5a2ecf3fa763cbf7ba1b7b8793dcdc6e2157b5c42>`);
	    auto :ref:`dst_md <doxid-group__dnnl__api__primitives__common_1gga94efdd650364f4d9776cfb9b711cbdc1a701158248eed4e5fc84610f2f6026493>` = :ref:`memory::desc <doxid-structdnnl_1_1memory_1_1desc>`(
	            src_dims, :ref:`memory::data_type::f32 <doxid-structdnnl_1_1memory_1a8e83474ec3a50e08e37af76c8c075dcea512dc597be7ae761876315165dc8bd2e>`, :ref:`memory::format_tag::nhwc <doxid-structdnnl_1_1memory_1a8e71077ed6a5f7fb7b3e6e1a5a2ecf3fa763cbf7ba1b7b8793dcdc6e2157b5c42>`);
	    auto src_mem = :ref:`memory <doxid-structdnnl_1_1memory>`(src_md, :ref:`engine <doxid-structdnnl_1_1engine>`);
	    auto dst_mem = :ref:`memory <doxid-structdnnl_1_1memory>`(dst_md, :ref:`engine <doxid-structdnnl_1_1engine>`);
	
	    // Write data to memory object's handle.
	    write_to_dnnl_memory(src_data.data(), src_mem);
	
	    // Create primitive descriptor.
	    const :ref:`memory::dim <doxid-structdnnl_1_1memory_1a281426f169daa042dcf5379c8fce21a9>` local_size = 5;
	    const float alpha = 1.e-4f;
	    const float beta = 0.75f;
	    const float k = 1.f;
	    auto lrn_pd = :ref:`lrn_forward::primitive_desc <doxid-structdnnl_1_1lrn__forward_1_1primitive__desc>`(:ref:`engine <doxid-structdnnl_1_1engine>`,
	            :ref:`prop_kind::forward_training <doxid-group__dnnl__api__attributes_1ggac7db48f6583aa9903e54c2a39d65438fa24775787fab8f13aa4809e1ce8f82aeb>`, :ref:`algorithm::lrn_across_channels <doxid-group__dnnl__api__attributes_1gga00377dd4982333e42e8ae1d09a309640ab9e2d858b551792385a4b5b86672b24b>`, src_md,
	            dst_md, local_size, alpha, beta, k);
	
	    // Create workspace memory object using memory descriptors created by the
	    // primitive descriptor.
	    // NOTE: Here, workspace may or may not be required in forward training
	    // mode, and is used to speed-up the backward propagation.
	    auto workspace_mem = :ref:`memory <doxid-structdnnl_1_1memory>`(lrn_pd.workspace_desc(), :ref:`engine <doxid-structdnnl_1_1engine>`);
	
	    // Create the primitive.
	    auto lrn_prim = :ref:`lrn_forward <doxid-structdnnl_1_1lrn__forward>`(lrn_pd);
	
	    // Primitive arguments.
	    std::unordered_map<int, memory> lrn_args;
	    lrn_args.insert({:ref:`DNNL_ARG_SRC <doxid-group__dnnl__api__primitives__common_1gac37ad67b48edeb9e742af0e50b70fe09>`, src_mem});
	    lrn_args.insert({:ref:`DNNL_ARG_WORKSPACE <doxid-group__dnnl__api__primitives__common_1ga550c80e1b9ba4f541202a7ac98be117f>`, workspace_mem});
	    lrn_args.insert({:ref:`DNNL_ARG_DST <doxid-group__dnnl__api__primitives__common_1ga3ca217e4a06d42a0ede3c018383c388f>`, dst_mem});
	
	    // Primitive execution.
	    lrn_prim.execute(engine_stream, lrn_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(lrn_example, parse_engine_kind(argc, argv));
	}