1/*******************************************************************************
2* Copyright 2020-2022 Intel Corporation
3*
4* Licensed under the Apache License, Version 2.0 (the "License");
5* you may not use this file except in compliance with the License.
6* You may obtain a copy of the License at
7*
8* http://www.apache.org/licenses/LICENSE-2.0
9*
10* Unless required by applicable law or agreed to in writing, software
11* distributed under the License is distributed on an "AS IS" BASIS,
12* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13* See the License for the specific language governing permissions and
14* limitations under the License.
15*******************************************************************************/
16
17/// @example eltwise.cpp
18/// > Annotated version: @ref eltwise_example_cpp
19///
20/// @page eltwise_example_cpp_short
21///
22/// This C++ API example demonstrates how to create and execute an
23/// [Element-wise](@ref dev_guide_eltwise) primitive in forward training
24/// propagation mode.
25///
26/// @page eltwise_example_cpp Element-Wise Primitive Example
27/// @copydetails eltwise_example_cpp_short
28///
29/// @include eltwise.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 eltwise_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 memory::dims dst_dims = {N, IC, IH, IW};
62
63 // Allocate buffers. In this example, out-of-place primitive execution is
64 // demonstrated since both src and dst are required for later backward
65 // propagation.
66 std::vector<float> src_data(product(src_dims));
67 std::vector<float> dst_data(product(dst_dims));
68
69 // Initialize src tensor.
70 std::generate(src_data.begin(), src_data.end(), []() {
71 static int i = 0;
72 return std::cos(i++ / 10.f);
73 });
74
75 // Create src and dst memory descriptors and memory objects.
76 auto src_md = memory::desc(src_dims, dt::f32, tag::nchw);
77 auto dst_md = memory::desc(dst_dims, dt::f32, tag::nchw);
78
79 auto src_mem = memory(src_md, engine);
80 auto dst_mem = memory(dst_md, engine);
81
82 // Write data to memory object's handle.
83 write_to_dnnl_memory(src_data.data(), src_mem);
84
85 // Create primitive descriptor.
86 auto eltwise_pd = eltwise_forward::primitive_desc(engine,
87 prop_kind::forward_training, algorithm::eltwise_relu, src_md,
88 dst_md, 0.f, 0.f);
89
90 // Create the primitive.
91 auto eltwise_prim = eltwise_forward(eltwise_pd);
92
93 // Primitive arguments.
94 std::unordered_map<int, memory> eltwise_args;
95 eltwise_args.insert({DNNL_ARG_SRC, src_mem});
96 eltwise_args.insert({DNNL_ARG_DST, dst_mem});
97
98 // Primitive execution: element-wise (ReLU).
99 eltwise_prim.execute(engine_stream, eltwise_args);
100
101 // Wait for the computation to finalize.
102 engine_stream.wait();
103
104 // Read data from memory object's handle.
105 read_from_dnnl_memory(dst_data.data(), dst_mem);
106}
107
108int main(int argc, char **argv) {
109 return handle_example_errors(
110 eltwise_example, parse_engine_kind(argc, argv));
111}
112