forked from huawei/mindspore2022
53 lines
2.1 KiB
C++
53 lines
2.1 KiB
C++
/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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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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#ifndef MINDSPORE_CCSRC_KERNEL_CPU_REDUCE_CPU_KERNEL_H_
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#define MINDSPORE_CCSRC_KERNEL_CPU_REDUCE_CPU_KERNEL_H_
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#include <vector>
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#include <memory>
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#include <string>
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#include "kernel/cpu/cpu_kernel.h"
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#include "kernel/cpu/cpu_kernel_factory.h"
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namespace mindspore {
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namespace kernel {
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class ReduceCPUKernel : public CPUKernel {
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public:
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ReduceCPUKernel() = default;
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~ReduceCPUKernel() override = default;
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void InitKernel(const CNodePtr &kernel_node) override;
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bool Launch(const std::vector<AddressPtr> &inputs, const std::vector<AddressPtr> &workspace,
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const std::vector<AddressPtr> &outputs) override;
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private:
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void Transpose(const int size, const float *input, const std::vector<size_t> &input_shape,
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const std::vector<size_t> &input_axis, const int shape_size, float *output);
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size_t reduce_type_;
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std::vector<size_t> axis_;
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std::vector<size_t> shape_;
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size_t left_dims_ = 1;
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size_t stride_ = 1;
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};
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MS_REG_CPU_KERNEL(ReduceMean, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),
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ReduceCPUKernel);
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MS_REG_CPU_KERNEL(ReduceMax, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),
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ReduceCPUKernel);
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MS_REG_CPU_KERNEL(ReduceSum, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),
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ReduceCPUKernel);
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} // namespace kernel
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} // namespace mindspore
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#endif // MINDSPORE_CCSRC_KERNEL_CPU_REDUCE_CPU_KERNEL_H_
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