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_BACKPROP_INPUT_FUSION_H_ 18 #define MINDSPORE_CORE_OPS_CONV2D_BACKPROP_INPUT_FUSION_H_ 19 #include <vector> 20 #include "mindapi/base/types.h" 21 #include "ops/grad/conv2d_backprop_input.h" 22 23 namespace mindspore { 24 namespace ops { 25 constexpr auto kNameConv2DBackpropInputFusion = "Conv2DBackpropInputFusion"; 26 /// \brief Conv2DBackpropInputFusion defined Conv2DBackpropInput operator prototype of lite. 27 class MIND_API Conv2DBackpropInputFusion : public Conv2DBackpropInput { 28 public: 29 MIND_API_BASE_MEMBER(Conv2DBackpropInputFusion); 30 /// \brief Constructor. Conv2DBackpropInputFusion()31 Conv2DBackpropInputFusion() : Conv2DBackpropInput(kNameConv2DBackpropInputFusion) {} 32 33 /// \brief Method to init the op's attributes. 34 /// 35 /// \param[in] in_channel Define the number of input channel. 36 /// \param[in] out_channel Define the number of output channel. 37 /// \param[in] kernel_size Define the size of the filter kernel. 38 /// \param[in] mode Define the category of conv, which is useless on lite. 39 /// \param[in] pad_mode Define the padding method. 40 /// \param[in] pad Define the concrete padding value on H and W dimension, which is replaced with pad_list. 41 /// \param[in] stride Define the moving size of the filter kernel. 42 /// \param[in] dilation Define the coefficient of expansion of the filter kernel, which is useful for dilated 43 /// convolution. 44 /// \param[in] group Define the number of group. 45 /// \param[in] format Define the format of input tensor. 46 /// \param[in] pad_list Define the concrete padding value on H and W dimension. 47 /// \param[in] activation_type Define the activation type. 48 void Init(int64_t in_channel, int64_t out_channel, const std::vector<int64_t> &kernel_size, int64_t mode = 1, 49 const PadMode &pad_mode = VALID, const std::vector<int64_t> &pad = {0, 0, 0, 0}, 50 const std::vector<int64_t> &stride = {1, 1, 1, 1}, const std::vector<int64_t> &dilation = {1, 1, 1, 1}, 51 int64_t group = 1, const Format &format = NCHW, const std::vector<int64_t> &pad_list = {0, 0, 0, 0}, 52 const ActivationType &activation_type = NO_ACTIVATION); 53 54 /// \brief Method to set in_channel attribute. 55 /// 56 /// \param[in] in_channel Define the number of input channel. 57 void set_in_channel(int64_t in_channel); 58 59 /// \brief Method to set activation type. 60 /// 61 /// \param[in] activation_type Define the activation type. 62 void set_activation_type(const ActivationType &activation_type); 63 64 /// \brief Method to get in_channel attribute. 65 /// 66 /// \return the number of input channel. 67 int64_t get_in_channel() const; 68 69 /// \brief Method to get activation type. 70 /// 71 /// \return activation type. 72 ActivationType get_activation_type() const; 73 }; 74 } // namespace ops 75 } // namespace mindspore 76 77 #endif // MINDSPORE_CORE_OPS_CONV2D_BACKPROP_INPUT_FUSION_H_ 78