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16
17/// @example lrn.cpp
18/// > Annotated version: @ref lrn_example_cpp
19///
20/// @page lrn_example_cpp_short
21///
22/// This C++ API demonstrates how to create and execute a
23/// [Local response normalization](@ref dev_guide_lrn) primitive in forward
24/// training propagation mode.
25///
26/// @page lrn_example_cpp Local Response Normalization Primitive Example
27/// @copydetails lrn_example_cpp_short
28///
29/// @include lrn.cpp
30
31#include <algorithm>
32#include <cmath>
33#include <iostream>
34#include <string>
35#include <vector>
36
37#include "example_utils.hpp"
38#include "oneapi/dnnl/dnnl.hpp"
39
40using namespace dnnl;
41
42using tag = memory::format_tag;
43using dt = memory::data_type;
44
45void lrn_example(dnnl::engine::kind engine_kind) {
46
47 // Create execution dnnl::engine.
48 dnnl::engine engine(engine_kind, 0);
49
50 // Create dnnl::stream.
51 dnnl::stream engine_stream(engine);
52
53 // Tensor dimensions.
54 const memory::dim N = 3, // batch size
55 IC = 3, // channels
56 IH = 227, // tensor height
57 IW = 227; // tensor width
58
59 // Source (src) and destination (dst) tensors dimensions.
60 memory::dims src_dims = {N, IC, IH, IW};
61
62 // Allocate buffers.
63 std::vector<float> src_data(product(src_dims));
64 std::vector<float> dst_data(product(src_dims));
65
66 std::generate(src_data.begin(), src_data.end(), []() {
67 static int i = 0;
68 return std::cos(i++ / 10.f);
69 });
70
71 // Create src and dst memory descriptors and memory objects.
72 auto src_md = memory::desc(src_dims, dt::f32, tag::nchw);
73 auto dst_md = memory::desc(src_dims, dt::f32, tag::nchw);
74 auto src_mem = memory(src_md, engine);
75 auto dst_mem = memory(src_md, engine);
76
77 // Write data to memory object's handle.
78 write_to_dnnl_memory(src_data.data(), src_mem);
79
80 // Create operation descriptor.
81 const memory::dim local_size = 5;
82 const float alpha = 1.e-4f;
83 const float beta = 0.75f;
84 const float k = 1.f;
85 // Create primitive descriptor.
86 auto lrn_pd = lrn_forward::primitive_desc(engine,
87 prop_kind::forward_training, algorithm::lrn_across_channels, src_md,
88 dst_md, local_size, alpha, beta, k);
89
90 // Create workspace memory object using memory descriptors created by the
91 // primitive descriptor.
92 // NOTE: Here, workspace may or may not be required in forward training
93 // mode, and is used to speed-up the backward propagation.
94 auto workspace_mem = memory(lrn_pd.workspace_desc(), engine);
95
96 // Create the primitive.
97 auto lrn_prim = lrn_forward(lrn_pd);
98
99 // Primitive arguments.
100 std::unordered_map<int, memory> lrn_args;
101 lrn_args.insert({DNNL_ARG_SRC, src_mem});
102 lrn_args.insert({DNNL_ARG_WORKSPACE, workspace_mem});
103 lrn_args.insert({DNNL_ARG_DST, dst_mem});
104
105 // Primitive execution.
106 lrn_prim.execute(engine_stream, lrn_args);
107
108 // Wait for the computation to finalize.
109 engine_stream.wait();
110
111 // Read data from memory object's handle.
112 read_from_dnnl_memory(dst_data.data(), dst_mem);
113}
114
115int main(int argc, char **argv) {
116 return handle_example_errors(lrn_example, parse_engine_kind(argc, argv));
117}
118