1 /** 2 * Copyright 2020-2021 Huawei Technologies Co., Ltd 3 * 4 * Licensed under the Apache License, Version 2.0 (the "License"); 5 * you may not use this file except in compliance with the License. 6 * You may obtain a copy of the License at 7 * 8 * http://www.apache.org/licenses/LICENSE-2.0 9 * 10 * Unless required by applicable law or agreed to in writing, software 11 * distributed under the License is distributed on an "AS IS" BASIS, 12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 13 * See the License for the specific language governing permissions and 14 * limitations under the License. 15 */ 16 17 #ifndef MINDSPORE_CORE_OPS_MAX_POOL_FUSION_H_ 18 #define MINDSPORE_CORE_OPS_MAX_POOL_FUSION_H_ 19 #include <memory> 20 #include <vector> 21 22 #include "mindapi/base/types.h" 23 #include "ops/max_pool.h" 24 25 namespace mindspore { 26 namespace ops { 27 constexpr auto kNameMaxPoolFusion = "MaxPoolFusion"; 28 /// \brief MaxPoolFusion defined MaxPool operator prototype of lite. 29 class MIND_API MaxPoolFusion : public MaxPool { 30 public: 31 MIND_API_BASE_MEMBER(MaxPoolFusion); 32 /// \brief Constructor. MaxPoolFusion()33 MaxPoolFusion() : MaxPool(kNameMaxPoolFusion) { InitIOName({"x"}, {"output"}); } 34 35 /// \brief Method to init the op's attributes. 36 /// 37 /// \param[in] kernel_size Define the size of the kernel. 38 /// \param[in] stride Define the moving size of the kernel. 39 /// \param[in] pad_mode Define the padding method. 40 /// \param[in] format Define the format of input tensor. 41 /// \param[in] pad Define the concrete padding value on each dimension 42 /// \param[in] round_mode Define numerical operation mode of the output tensor. 43 /// \param[in] global Define a boolean value to indicate whether to do global pooling. If true, kernel_size will be 44 /// useless. 45 /// \param[in] activation_type Define the activation type. 46 void Init(const std::vector<int64_t> &kernel_size = {1}, const std::vector<int64_t> &stride = {1}, 47 const PadMode &pad_mode = VALID, const Format &format = NCHW, 48 const std::vector<int64_t> &pad = {0, 0, 0, 0}, const RoundMode &round_mode = RoundMode::FLOOR, 49 const bool global = false, const ActivationType activation_type = NO_ACTIVATION); 50 51 /// \brief Method to set global attribute. 52 /// 53 /// \param[in] global Define a boolean value to indicate whether to do global pooling. If true, kernel_size will be 54 /// useless. 55 void set_global(const bool global); 56 57 /// \brief Method to set activation type. 58 /// 59 /// \param[in] activation_type Define the activation type. 60 void set_activation_type(const ActivationType activation_type); 61 62 /// \brief Method to get global attribute. 63 /// 64 /// \return a boolean value to indicate whether to do global pooling. If true, kernel_size will be useless. 65 bool get_global() const; 66 67 /// \brief Method to get activation type. 68 /// 69 /// \return activation type. 70 ActivationType get_activation_type() const; 71 }; 72 73 abstract::AbstractBasePtr MaxPoolFusionInfer(const abstract::AnalysisEnginePtr &, const PrimitivePtr &primitive, 74 const std::vector<abstract::AbstractBasePtr> &input_args); 75 } // namespace ops 76 } // namespace mindspore 77 78 #endif // MINDSPORE_CORE_OPS_MAX_POOL_FUSION_H_ 79