oneAPI Deep Neural Network Library (oneDNN)
Performance library for Deep Learning
2.0.0
binary.cpp

Annotated version: Binary Primitive Example

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* Copyright 2020 Intel Corporation
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* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
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* http://www.apache.org/licenses/LICENSE-2.0
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#include <algorithm>
#include <cmath>
#include <iostream>
#include <string>
#include <vector>
#include "example_utils.hpp"
using namespace dnnl;
void binary_example(dnnl::engine::kind engine_kind) {
// Create execution dnnl::engine.
dnnl::engine engine(engine_kind, 0);
// Create dnnl::stream.
dnnl::stream engine_stream(engine);
// Tensor dimensions.
const memory::dim N = 3, // batch size
IC = 3, // channels
IH = 150, // tensor height
IW = 150; // tensor width
// Source (src_0 and src_1) and destination (dst) tensors dimensions.
memory::dims src_0_dims = {N, IC, IH, IW};
memory::dims src_1_dims = {N, IC, IH, 1};
// Allocate buffers.
std::vector<float> src_0_data(product(src_0_dims));
std::vector<float> src_1_data(product(src_1_dims));
// Initialize src_0 and src_1 (src).
std::generate(src_0_data.begin(), src_0_data.end(), []() {
static int i = 0;
return std::cos(i++ / 10.f);
});
std::generate(src_1_data.begin(), src_1_data.end(), []() {
static int i = 0;
return std::sin(i++ * 2.f);
});
// Create src and dst memory descriptors.
auto src_0_md = memory::desc(src_0_dims, dt::f32, tag::nchw);
auto src_1_md = memory::desc(src_1_dims, dt::f32, tag::nchw);
auto dst_md = memory::desc(src_0_dims, dt::f32, tag::nchw);
// Create src memory objects.
auto src_0_mem = memory(src_0_md, engine);
auto src_1_mem = memory(src_1_md, engine);
// Write data to memory object's handle.
write_to_dnnl_memory(src_0_data.data(), src_0_mem);
write_to_dnnl_memory(src_1_data.data(), src_1_mem);
// Create operation descriptor.
auto binary_d
= binary::desc(algorithm::binary_mul, src_0_md, src_1_md, dst_md);
// Create primitive post-ops (ReLU).
const float scale = 1.0f;
const float alpha = 0.f;
const float beta = 0.f;
post_ops binary_ops;
binary_ops.append_eltwise(scale, algorithm::eltwise_relu, alpha, beta);
primitive_attr binary_attr;
binary_attr.set_post_ops(binary_ops);
// Create primitive descriptor.
auto binary_pd = binary::primitive_desc(binary_d, binary_attr, engine);
// Create the primitive.
auto binary_prim = binary(binary_pd);
// Primitive arguments. Set up in-place execution by assigning src_0 as DST.
std::unordered_map<int, memory> binary_args;
binary_args.insert({DNNL_ARG_SRC_0, src_0_mem});
binary_args.insert({DNNL_ARG_SRC_1, src_1_mem});
binary_args.insert({DNNL_ARG_DST, src_0_mem});
// Primitive execution: binary with ReLU.
binary_prim.execute(engine_stream, binary_args);
// Wait for the computation to finalize.
engine_stream.wait();
// Read data from memory object's handle.
read_from_dnnl_memory(src_0_data.data(), src_0_mem);
}
int main(int argc, char **argv) {
return handle_example_errors(binary_example, parse_engine_kind(argc, argv));
}
dnnl::binary::primitive_desc
Primitive descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:9389
dnnl.hpp
C++ API.
dnnl::stream
An execution stream.
Definition: dnnl.hpp:975
dnnl::engine
An execution engine.
Definition: dnnl.hpp:859
dnnl::stream::wait
stream & wait()
Waits for all primitives executing in the stream to finish.
Definition: dnnl.hpp:1015
dnnl::engine::kind
kind
Kinds of engines.
Definition: dnnl.hpp:864
DNNL_ARG_DST
#define DNNL_ARG_DST
A special mnemonic for destination argument for primitives that have a single destination.
Definition: dnnl_types.h:2019
dnnl::primitive_attr::set_post_ops
void set_post_ops(const post_ops ops)
Sets post-ops.
Definition: dnnl.hpp:2750
dnnl::post_ops
Post-ops.
Definition: dnnl.hpp:2184
dnnl::memory::data_type
data_type
Data type specification.
Definition: dnnl.hpp:1120
DNNL_ARG_SRC_0
#define DNNL_ARG_SRC_0
Source argument #0.
Definition: dnnl_types.h:1992
dnnl::memory::format_tag
format_tag
Memory format tag specification.
Definition: dnnl.hpp:1195
dnnl::binary
Elementwise binary operator primitive.
Definition: dnnl.hpp:9362
DNNL_ARG_SRC_1
#define DNNL_ARG_SRC_1
Source argument #1.
Definition: dnnl_types.h:2004
dnnl::memory::dim
dnnl_dim_t dim
Integer type for representing dimension sizes and indices.
Definition: dnnl.hpp:1102
dnnl::primitive_attr
Primitive attributes.
Definition: dnnl.hpp:2520
dnnl::memory
Memory object.
Definition: dnnl.hpp:1098
dnnl::binary::desc
Descriptor for an elementwise binary operator primitive.
Definition: dnnl.hpp:9364
dnnl::memory::dims
std::vector< dim > dims
Vector of dimensions.
Definition: dnnl.hpp:1105
dnnl::memory::desc
A memory descriptor.
Definition: dnnl.hpp:1718
dnnl
oneDNN namespace
Definition: dnnl.hpp:74
dnnl::post_ops::append_eltwise
void append_eltwise(float scale, algorithm aalgorithm, float alpha, float beta)
Appends an elementwise post-op.
Definition: dnnl.hpp:2283