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16
17 /// @example pooling.cpp
18 /// > Annotated version: @ref pooling_example_cpp
19 ///
20 /// @page pooling_example_cpp_short
21 ///
22 /// This C++ API example demonstrates how to create and execute a
23 /// [Pooling](@ref dev_guide_pooling) primitive in forward training propagation
24 /// mode.
25 ///
26 /// @page pooling_example_cpp Pooling Primitive Example
27 /// @copydetails pooling_example_cpp_short
28 ///
29 /// @include pooling.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
40 using namespace dnnl;
41
42 using tag = memory::format_tag;
43 using dt = memory::data_type;
44
pooling_example(dnnl::engine::kind engine_kind)45 void pooling_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, // input channels
56 IH = 27, // input tensor height
57 IW = 27, // input tensor width
58 KH = 11, // kernel height
59 KW = 11, // kernel width
60 PH_L = 0, // height padding: left
61 PH_R = 0, // height padding: right
62 PW_L = 0, // width padding: left
63 PW_R = 0, // width padding: right
64 SH = 4, // height-wise stride
65 SW = 4, // width-wise stride
66 DH = 1, // height-wise dilation
67 DW = 1; // width-wise dilation
68
69 const memory::dim OH = (IH - ((KH - 1) * DH + KH) + PH_L + PH_R) / SH + 1;
70 const memory::dim OW = (IW - ((KW - 1) * DW + KW) + PW_L + PW_R) / SW + 1;
71
72 // Source (src) and destination (dst) tensors dimensions.
73 memory::dims src_dims = {N, IC, IH, IW};
74 memory::dims dst_dims = {N, IC, OH, OW};
75
76 // Kernel dimensions.
77 memory::dims kernel_dims = {KH, KW};
78
79 // Strides, padding dimensions.
80 memory::dims strides_dims = {SH, SW};
81 memory::dims padding_dims_l = {PH_L, PW_L};
82 memory::dims padding_dims_r = {PH_R, PW_R};
83 memory::dims dilation = {DH, DW};
84
85 // Allocate buffers.
86 std::vector<float> src_data(product(src_dims));
87 std::vector<float> dst_data(product(dst_dims));
88
89 std::generate(src_data.begin(), src_data.end(), []() {
90 static int i = 0;
91 return std::cos(i++ / 10.f);
92 });
93
94 // Create memory descriptors and memory objects for src and dst.
95 auto src_md = memory::desc(src_dims, dt::f32, tag::nchw);
96 auto src_mem = memory(src_md, engine);
97
98 auto dst_md = memory::desc(dst_dims, dt::f32, tag::nchw);
99 auto dst_mem = memory(dst_md, engine);
100
101 // Write data to memory object's handle.
102 write_to_dnnl_memory(src_data.data(), src_mem);
103
104 // Create operation descriptor.
105 auto pooling_d = pooling_v2_forward::desc(prop_kind::forward_training,
106 algorithm::pooling_max, src_md, dst_md, strides_dims, kernel_dims,
107 dilation, padding_dims_l, padding_dims_r);
108
109 // Create primitive descriptor.
110 auto pooling_pd = pooling_v2_forward::primitive_desc(pooling_d, engine);
111
112 // Create workspace memory objects using memory descriptor created by the
113 // primitive descriptor.
114 // NOTE: Here, the workspace is required to save the indices where maximum
115 // was found, and is used in backward pooling to perform upsampling.
116 auto workspace_mem = memory(pooling_pd.workspace_desc(), engine);
117
118 // Create the primitive.
119 auto pooling_prim = pooling_v2_forward(pooling_pd);
120
121 // Primitive arguments. Set up in-place execution by assigning src as DST.
122 std::unordered_map<int, memory> pooling_args;
123 pooling_args.insert({DNNL_ARG_SRC, src_mem});
124 pooling_args.insert({DNNL_ARG_DST, dst_mem});
125 pooling_args.insert({DNNL_ARG_WORKSPACE, workspace_mem});
126
127 // Primitive execution: pooling.
128 pooling_prim.execute(engine_stream, pooling_args);
129
130 // Wait for the computation to finalize.
131 engine_stream.wait();
132
133 // Read data from memory object's handle.
134 read_from_dnnl_memory(dst_data.data(), dst_mem);
135 }
136
main(int argc,char ** argv)137 int main(int argc, char **argv) {
138 return handle_example_errors(
139 pooling_example, parse_engine_kind(argc, argv));
140 }
141