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87 lines
2.0 KiB
87 lines
2.0 KiB
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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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#pragma once
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#include "paddle/fluid/platform/macros.h"
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namespace paddle {
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namespace operators {
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namespace jit {
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typedef enum {
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vmul = 0,
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vadd = 1,
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vaddrelu,
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vsub,
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vscal,
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vaddbias,
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vrelu,
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videntity,
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vexp,
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vsigmoid,
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vtanh
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} KernelType;
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template <typename T>
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struct XYZNTuples {
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typedef T data_type;
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typedef int attr_type;
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typedef void (*func_type)(const T*, const T*, T*, int);
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};
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template <typename T>
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struct AXYNTuples : public XYZNTuples<T> {};
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template <typename T>
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struct XYNTuples {
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typedef T data_type;
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typedef int attr_type;
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typedef void (*func_type)(const T*, T*, int);
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};
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// Just for adding to kernel pool without template
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class Kernel {
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public:
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Kernel() = default;
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virtual ~Kernel() = default;
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DISABLE_COPY_AND_ASSIGN(Kernel);
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};
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template <typename KernelTuples>
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class KernelImpl : public Kernel {
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using T = typename KernelTuples::data_type;
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using Func = typename KernelTuples::func_type;
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using Attr = typename KernelTuples::attr_type;
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public:
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virtual Func GetFunc() const { return func; }
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virtual bool UseMe(Attr attr) const = 0;
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protected:
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Func func{nullptr};
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};
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template <typename KernelTuples>
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class ReferKernel : public KernelImpl<KernelTuples> {
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public:
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// Refer code can always be used
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bool UseMe(typename KernelTuples::attr_type attr) const override {
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return true;
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}
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};
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} // namespace jit
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} // namespace operators
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} // namespace paddle
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