onednn-src 0.1.13

/*******************************************************************************
* Copyright 2023 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.
*******************************************************************************/

#ifndef GRAPH_BACKEND_DNNL_KERNELS_DUMMY_HPP
#define GRAPH_BACKEND_DNNL_KERNELS_DUMMY_HPP

#include <algorithm>
#include <memory>
#include <string>
#include <utility>
#include <vector>

#include "graph/backend/dnnl/kernels/kernel_base.hpp"

#include "graph/backend/dnnl/dnnl_partition_impl.hpp"
#include "graph/backend/dnnl/subgraph.hpp"

namespace dnnl {
namespace impl {
namespace graph {
namespace dnnl_impl {

struct dummy_kernel_t : public kernel_base_t {
private:
    std::shared_ptr<subgraph_t> subgraph_;

public:
    dummy_kernel_t() = default;

    ~dummy_kernel_t() override = default;

    status_t compile_impl(const dnnl_partition_impl_t *part,
            const engine_t *g_engine,
            const std::vector<logical_tensor_t> &inputs,
            const std::vector<logical_tensor_t> &outputs) override;

    status_t execute_impl(const stream_t *g_stream,
            const std::vector<tensor_t> &inputs,
            const std::vector<tensor_t> &outputs) override;

#ifdef DNNL_WITH_SYCL
    status_t sycl_execute_impl(const stream_t *g_stream,
            const std::vector<tensor_t> &inputs,
            const std::vector<tensor_t> &outputs,
            const std::vector<::sycl::event> &sycl_deps,
            ::sycl::event *sycl_event) override;
#endif

#if DNNL_GPU_RUNTIME == DNNL_RUNTIME_OCL
    status_t ocl_execute_impl(const stream_t *g_stream,
            const std::vector<tensor_t> &inputs,
            const std::vector<tensor_t> &outputs,
            const std::vector<cl_event> &cl_deps, cl_event *ret_event) override;
#endif

    DEF_KERNEL_METHOD_STR(dummy_kernel_t)
    DNNL_DISALLOW_COPY_AND_ASSIGN(dummy_kernel_t)
};

kernel_ptr dummy_kernel_creator();

} // namespace dnnl_impl
} // namespace graph
} // namespace impl
} // namespace dnnl

#endif