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126 lines
4.2 KiB
C++
126 lines
4.2 KiB
C++
/*******************************************************************************
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* Copyright 2020-2025 Intel Corporation
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*******************************************************************************/
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/// @example binary.cpp
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/// > Annotated version: @ref binary_example_cpp
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/// @page binary_example_cpp_brief
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/// @brief This C++ API example demonstrates how to create and execute a
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/// [Binary](@ref dev_guide_binary) primitive.
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/// @page binary_example_cpp Binary Primitive Example
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/// \copybrief binary_example_cpp_brief
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///
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/// Key optimizations included in this example:
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/// - In-place primitive execution;
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/// - Primitive attributes with fused post-ops.
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///
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/// @include binary.cpp
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#include <algorithm>
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#include <cmath>
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#include <iostream>
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#include <string>
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#include <vector>
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#include "example_utils.hpp"
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#include "oneapi/dnnl/dnnl.hpp"
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using namespace dnnl;
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void binary_example(dnnl::engine::kind engine_kind) {
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// Create execution dnnl::engine.
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dnnl::engine engine(engine_kind, 0);
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// Create dnnl::stream.
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dnnl::stream engine_stream(engine);
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// Tensor dimensions.
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const memory::dim N = 3, // batch size
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IC = 3, // channels
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IH = 150, // tensor height
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IW = 150; // tensor width
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// Source (src_0 and src_1) and destination (dst) tensors dimensions.
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memory::dims src_0_dims = {N, IC, IH, IW};
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memory::dims src_1_dims = {N, IC, IH, 1};
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// Allocate buffers.
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std::vector<float> src_0_data(product(src_0_dims));
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std::vector<float> src_1_data(product(src_1_dims));
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// Initialize src_0 and src_1 (src).
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std::generate(src_0_data.begin(), src_0_data.end(), []() {
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static int i = 0;
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return std::cos(i++ / 10.f);
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});
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std::generate(src_1_data.begin(), src_1_data.end(), []() {
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static int i = 0;
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return std::sin(i++ * 2.f);
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});
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// Create src and dst memory descriptors.
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auto src_0_md = memory::desc(
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src_0_dims, memory::data_type::f32, memory::format_tag::nchw);
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auto src_1_md = memory::desc(
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src_1_dims, memory::data_type::f32, memory::format_tag::nchw);
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auto dst_md = memory::desc(
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src_0_dims, memory::data_type::f32, memory::format_tag::nchw);
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// Create src memory objects.
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auto src_0_mem = memory(src_0_md, engine);
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auto src_1_mem = memory(src_1_md, engine);
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// Write data to memory object's handle.
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write_to_dnnl_memory(src_0_data.data(), src_0_mem);
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write_to_dnnl_memory(src_1_data.data(), src_1_mem);
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// Create primitive post-ops (ReLU).
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const float alpha = 0.f;
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const float beta = 0.f;
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post_ops binary_ops;
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binary_ops.append_eltwise(algorithm::eltwise_relu, alpha, beta);
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primitive_attr binary_attr;
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binary_attr.set_post_ops(binary_ops);
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// Create primitive descriptor.
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auto binary_pd = binary::primitive_desc(engine, algorithm::binary_mul,
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src_0_md, src_1_md, dst_md, binary_attr);
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// Create the primitive.
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auto binary_prim = binary(binary_pd);
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// Primitive arguments. Set up in-place execution by assigning src_0 as DST.
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std::unordered_map<int, memory> binary_args;
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binary_args.insert({DNNL_ARG_SRC_0, src_0_mem});
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binary_args.insert({DNNL_ARG_SRC_1, src_1_mem});
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binary_args.insert({DNNL_ARG_DST, src_0_mem});
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// Primitive execution: binary with ReLU.
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binary_prim.execute(engine_stream, binary_args);
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// Wait for the computation to finalize.
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engine_stream.wait();
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// Read data from memory object's handle.
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read_from_dnnl_memory(src_0_data.data(), src_0_mem);
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}
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int main(int argc, char **argv) {
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return handle_example_errors(binary_example, parse_engine_kind(argc, argv));
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}
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