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107 lines
3.4 KiB
C++
107 lines
3.4 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 softmax.cpp
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/// > Annotated version: @ref softmax_example_cpp
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/// @page softmax_example_cpp_brief
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/// @brief This C++ API example demonstrates how to create and execute a
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/// [Softmax](@ref dev_guide_softmax) primitive in forward training propagation mode.
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/// @page softmax_example_cpp Softmax Primitive Example
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/// \copybrief softmax_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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/// - Softmax along axis 1 (C) for 2D tensors.
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///
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/// @include softmax.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 softmax_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 = 1000; // channels
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// Source (src) and destination (dst) tensors dimensions.
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memory::dims src_dims = {N, IC};
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// Allocate buffer.
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std::vector<float> src_data(product(src_dims));
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std::generate(src_data.begin(), src_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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// Create src memory descriptor and memory object.
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auto src_md = memory::desc(
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src_dims, memory::data_type::f32, memory::format_tag::nc);
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auto dst_md = memory::desc(
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src_dims, memory::data_type::f32, memory::format_tag::nc);
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auto src_mem = memory(src_md, engine);
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// Write data to memory object's handle.
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write_to_dnnl_memory(src_data.data(), src_mem);
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// Softmax axis.
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const int axis = 1;
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// Create primitive descriptor.
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auto softmax_pd = softmax_forward::primitive_desc(engine,
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prop_kind::forward_training, algorithm::softmax_accurate, src_md,
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dst_md, axis);
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// Create the primitive.
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auto softmax_prim = softmax_forward(softmax_pd);
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// Primitive arguments. Set up in-place execution by assigning src as DST.
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std::unordered_map<int, memory> softmax_args;
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softmax_args.insert({DNNL_ARG_SRC, src_mem});
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softmax_args.insert({DNNL_ARG_DST, src_mem});
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// Primitive execution.
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softmax_prim.execute(engine_stream, softmax_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_data.data(), src_mem);
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}
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int main(int argc, char **argv) {
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return handle_example_errors(
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softmax_example, parse_engine_kind(argc, argv));
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}
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