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_CONV2D_FUSION_H_ 18 #define MINDSPORE_CORE_OPS_CONV2D_FUSION_H_ 19 #include <vector> 20 21 #include "mindapi/base/types.h" 22 #include "ops/conv2d.h" 23 24 namespace mindspore { 25 namespace ops { 26 constexpr auto kNameConv2DFusion = "Conv2DFusion"; 27 /// \brief Conv2DFusion defined Conv2D operator prototype of lite. 28 class MIND_API Conv2DFusion : public Conv2D { 29 public: 30 MIND_API_BASE_MEMBER(Conv2DFusion); 31 /// \brief Constructor. Conv2DFusion()32 Conv2DFusion() : Conv2D(kNameConv2DFusion) {} 33 34 /// \brief Method to init the op's attributes. 35 /// 36 /// \param[in] in_channel Define the number of input channel. 37 /// \param[in] out_channel Define the number of output channel. 38 /// \param[in] kernel_size Define the size of the filter kernel. 39 /// \param[in] mode Define the category of conv, which is useless on lite. 40 /// \param[in] pad_mode Define the padding method. 41 /// \param[in] pad Define the concrete padding value on H and W dimension, which is replaced with pad_list. 42 /// \param[in] stride Define the moving size of the filter kernel. 43 /// \param[in] dilation Define the coefficient of expansion of the filter kernel, which is useful for dilated 44 /// convolution. 45 /// \param[in] group Define the number of group. 46 /// \param[in] format Define the format of input tensor. 47 /// \param[in] pad_list Define the concrete padding value on H and W dimension. 48 /// \param[in] activation_type Define the activation type. 49 void Init(int64_t in_channel, int64_t out_channel, const std::vector<int64_t> &kernel_size, int64_t mode = 1, 50 const PadMode &pad_mode = VALID, const std::vector<int64_t> &pad = {0, 0, 0, 0}, 51 const std::vector<int64_t> &stride = {1, 1, 1, 1}, const std::vector<int64_t> &dilation = {1, 1, 1, 1}, 52 int64_t group = 1, const Format &format = NCHW, const std::vector<int64_t> &pad_list = {0, 0, 0, 0}, 53 const ActivationType &activation_type = NO_ACTIVATION); 54 55 /// \brief Method to set in_channel attribute. 56 /// 57 /// \param[in] in_channel Define the number of input channel. 58 void set_in_channel(const int64_t in_channel); 59 60 /// \brief Method to set pad_list attribute. 61 /// 62 /// \param[in] pad_list Define the concrete padding value on H and W dimension. 63 void set_pad_list(const std::vector<int64_t> &pad_list); 64 65 /// \brief Method to set activation type. 66 /// 67 /// \param[in] activation_type Define the activation type. 68 void set_activation_type(const ActivationType &activation_type); 69 70 /// \brief Method to get in_channel attribute. 71 /// 72 /// \return the number of input channel. 73 int64_t get_in_channel() const; 74 75 /// \brief Method to get pad_list attribute. 76 /// 77 /// \return padding value. 78 std::vector<int64_t> get_pad_list() const; 79 80 /// \brief Method to get activation type. 81 /// 82 /// \return activation type. 83 ActivationType get_activation_type() const; 84 }; 85 } // namespace ops 86 } // namespace mindspore 87 88 #endif // MINDSPORE_CORE_OPS_CONV2D_FUSION_H_ 89