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16
17/// @example layer_normalization.cpp
18/// > Annotated version: @ref layer_normalization_example_cpp
19///
20/// @page layer_normalization_example_cpp_short
21///
22/// This C++ API example demonstrates how to create and execute a
23/// [Layer normalization](@ref dev_guide_layer_normalization) primitive in
24/// forward propagation mode.
25///
26/// Key optimizations included in this example:
27/// - In-place primitive execution;
28/// - Creation of memory objects using the primitive descriptor.
29///
30/// @page layer_normalization_example_cpp Layer Normalization Primitive Example
31/// @copydetails layer_normalization_example_cpp_short
32///
33/// @include layer_normalization.cpp
34
35#include <algorithm>
36#include <cmath>
37#include <iostream>
38#include <string>
39#include <vector>
40
41#include "example_utils.hpp"
42#include "oneapi/dnnl/dnnl.hpp"
43
44using namespace dnnl;
45
46using tag = memory::format_tag;
47using dt = memory::data_type;
48
49void layer_normalization_example(dnnl::engine::kind engine_kind) {
50
51 /// Create execution dnnl::engine.
52 dnnl::engine engine(engine_kind, 0);
53
54 // Create dnnl::stream.
55 dnnl::stream engine_stream(engine);
56
57 // Tensor dimensions.
58 const memory::dim T = 12, // time steps
59 N = 3, // batch
60 C = 227; // channels
61
62 // Source (src) and destination (dst) tensors dimensions.
63 const memory::dims src_dims = {T, N, C};
64
65 // Scale/shift tensor dimensions.
66 memory::dims scaleshift_dims = {C};
67
68 // Allocate buffer.
69 std::vector<float> src_data(product(src_dims));
70 std::vector<float> scale_data(product(scaleshift_dims));
71 std::vector<float> shift_data(product(scaleshift_dims));
72
73 // Initialize src tensor.
74 std::generate(src_data.begin(), src_data.end(), []() {
75 static int i = 0;
76 return std::cos(i++ / 10.f);
77 });
78
79 // Initialize scale.
80 std::generate(scale_data.begin(), scale_data.end(), []() {
81 static int i = 0;
82 return std::sin(i++ * 2.f);
83 });
84
85 // Initialize shift.
86 std::generate(shift_data.begin(), shift_data.end(), []() {
87 static int i = 0;
88 return std::tan(float(i++));
89 });
90
91 // Create src memory descriptor and memory objects.
92 auto src_md = memory::desc(src_dims, dt::f32, tag::tnc);
93 auto dst_md = memory::desc(src_dims, dt::f32, tag::tnc);
94 auto scaleshift_md = memory::desc(scaleshift_dims, dt::f32, tag::x);
95
96 auto src_mem = memory(src_md, engine);
97 auto scale_mem = memory(scaleshift_md, engine);
98 auto shift_mem = memory(scaleshift_md, engine);
99
100 // Write data to memory object's handle.
101 write_to_dnnl_memory(src_data.data(), src_mem);
102 write_to_dnnl_memory(scale_data.data(), scale_mem);
103 write_to_dnnl_memory(shift_data.data(), shift_mem);
104
105 // Create primitive descriptor.
106 const float epsilon = 1.e-10f;
107 auto lnorm_pd = layer_normalization_forward::primitive_desc(engine,
108 prop_kind::forward_training, src_md, dst_md, epsilon,
109 normalization_flags::use_scale | normalization_flags::use_shift);
110
111 // Use the memory descriptors from the primitive to create memory objects
112 // required for the primitive: mean, variance, scale/shift.
113 auto mean_mem = memory(lnorm_pd.mean_desc(), engine);
114 auto variance_mem = memory(lnorm_pd.variance_desc(), engine);
115
116 // Create the primitive.
117 auto lnorm_prim = layer_normalization_forward(lnorm_pd);
118
119 // Primitive arguments. Set up in-place execution by assigning src as DST.
120 std::unordered_map<int, memory> lnorm_args;
121 lnorm_args.insert({DNNL_ARG_SRC, src_mem});
122 lnorm_args.insert({DNNL_ARG_MEAN, mean_mem});
123 lnorm_args.insert({DNNL_ARG_VARIANCE, variance_mem});
124 lnorm_args.insert({DNNL_ARG_SCALE, scale_mem});
125 lnorm_args.insert({DNNL_ARG_SHIFT, shift_mem});
126 lnorm_args.insert({DNNL_ARG_DST, src_mem});
127
128 // Primitive execution: layer normalization.
129 lnorm_prim.execute(engine_stream, lnorm_args);
130
131 // Wait for the computation to finalize.
132 engine_stream.wait();
133
134 // Read data from memory object's handle.s
135 read_from_dnnl_memory(src_data.data(), src_mem);
136}
137
138int main(int argc, char **argv) {
139 return handle_example_errors(
140 layer_normalization_example, parse_engine_kind(argc, argv));
141}
142