mirror of
https://github.com/uxlfoundation/oneDNN.git
synced 2025-10-20 18:43:49 +08:00
110 lines
3.6 KiB
C++
110 lines
3.6 KiB
C++
/*******************************************************************************
|
|
* Copyright 2020-2025 Intel Corporation
|
|
*
|
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
|
* you may not use this file except in compliance with the License.
|
|
* You may obtain a copy of the License at
|
|
*
|
|
* http://www.apache.org/licenses/LICENSE-2.0
|
|
*
|
|
* Unless required by applicable law or agreed to in writing, software
|
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
* See the License for the specific language governing permissions and
|
|
* limitations under the License.
|
|
*******************************************************************************/
|
|
|
|
/// @example eltwise.cpp
|
|
/// > Annotated version: @ref eltwise_example_cpp
|
|
|
|
/// @page eltwise_example_cpp_brief
|
|
/// @brief This C++ API example demonstrates how to create and execute an
|
|
/// [Element-wise](@ref dev_guide_eltwise) primitive in forward training
|
|
/// propagation mode.
|
|
|
|
/// @page eltwise_example_cpp Element-Wise Primitive Example
|
|
/// \copybrief eltwise_example_cpp_brief
|
|
///
|
|
/// @include eltwise.cpp
|
|
|
|
#include <algorithm>
|
|
#include <cmath>
|
|
#include <iostream>
|
|
#include <string>
|
|
#include <vector>
|
|
|
|
#include "example_utils.hpp"
|
|
#include "oneapi/dnnl/dnnl.hpp"
|
|
|
|
using namespace dnnl;
|
|
|
|
void eltwise_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 = 227, // tensor height
|
|
IW = 227; // tensor width
|
|
|
|
// Source (src) and destination (dst) tensors dimensions.
|
|
memory::dims src_dims = {N, IC, IH, IW};
|
|
memory::dims dst_dims = {N, IC, IH, IW};
|
|
|
|
// Allocate buffers. In this example, out-of-place primitive execution is
|
|
// demonstrated since both src and dst are required for later backward
|
|
// propagation.
|
|
std::vector<float> src_data(product(src_dims));
|
|
std::vector<float> dst_data(product(dst_dims));
|
|
|
|
// Initialize src tensor.
|
|
std::generate(src_data.begin(), src_data.end(), []() {
|
|
static int i = 0;
|
|
return std::cos(i++ / 10.f);
|
|
});
|
|
|
|
// Create src and dst memory descriptors and memory objects.
|
|
auto src_md = memory::desc(
|
|
src_dims, memory::data_type::f32, memory::format_tag::nchw);
|
|
auto dst_md = memory::desc(
|
|
dst_dims, memory::data_type::f32, memory::format_tag::nchw);
|
|
|
|
auto src_mem = memory(src_md, engine);
|
|
auto dst_mem = memory(dst_md, engine);
|
|
|
|
// Write data to memory object's handle.
|
|
write_to_dnnl_memory(src_data.data(), src_mem);
|
|
|
|
// Create primitive descriptor.
|
|
auto eltwise_pd = eltwise_forward::primitive_desc(engine,
|
|
prop_kind::forward_training, algorithm::eltwise_relu, src_md,
|
|
dst_md, 0.f, 0.f);
|
|
|
|
// Create the primitive.
|
|
auto eltwise_prim = eltwise_forward(eltwise_pd);
|
|
|
|
// Primitive arguments.
|
|
std::unordered_map<int, memory> eltwise_args;
|
|
eltwise_args.insert({DNNL_ARG_SRC, src_mem});
|
|
eltwise_args.insert({DNNL_ARG_DST, dst_mem});
|
|
|
|
// Primitive execution: element-wise (ReLU).
|
|
eltwise_prim.execute(engine_stream, eltwise_args);
|
|
|
|
// Wait for the computation to finalize.
|
|
engine_stream.wait();
|
|
|
|
// Read data from memory object's handle.
|
|
read_from_dnnl_memory(dst_data.data(), dst_mem);
|
|
}
|
|
|
|
int main(int argc, char **argv) {
|
|
return handle_example_errors(
|
|
eltwise_example, parse_engine_kind(argc, argv));
|
|
}
|