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_TRANSPOSE_FUSION_H_ 18 #define MINDSPORE_CORE_OPS_CONV2D_TRANSPOSE_FUSION_H_ 19 #include <vector> 20 21 #include "mindapi/base/types.h" 22 #include "ops/conv2d_transpose.h" 23 24 namespace mindspore { 25 namespace ops { 26 constexpr auto kNameConv2dTransposeFusion = "Conv2dTransposeFusion"; 27 /// \brief Conv2dTransposeFusion defined Conv2dTranspose operator prototype of lite. 28 class MIND_API Conv2dTransposeFusion : public Conv2DTranspose { 29 public: 30 MIND_API_BASE_MEMBER(Conv2dTransposeFusion); 31 /// \brief Constructor. Conv2dTransposeFusion()32 Conv2dTransposeFusion() : Conv2DTranspose(kNameConv2dTransposeFusion) { 33 InitIOName({"out_backprop", "filter", "input_sizes"}, {"output"}); 34 } 35 36 /// \brief Method to init the op's attributes. 37 /// 38 /// \param[in] in_channel Define the number of input channel. 39 /// \param[in] out_channel Define the number of output channel. 40 /// \param[in] kernel_size Define the size of the filter kernel. 41 /// \param[in] mode Define the category of conv, which is useless on lite. 42 /// \param[in] pad_mode Define the padding method. 43 /// \param[in] pad Define the concrete padding value on H and W dimension, which is replaced with pad_list. 44 /// \param[in] stride Define the moving size of the filter kernel. 45 /// \param[in] dilation Define the coefficient of expansion of the filter kernel, which is useful for dilated 46 /// convolution-transpose. 47 /// \param[in] group Define the number of group. 48 /// \param[in] format Define the format of input tensor. 49 /// \param[in] pad_list Define the concrete padding value on H and W dimension. 50 /// \param[in] output_paddings Define the additional elements added to the side with higher coordinate indices in the 51 /// output, which is used to control the selection-range of the output tensor. 52 /// \param[in] activation_type Define the activation type. 53 void Init(int64_t in_channel, int64_t out_channel, const std::vector<int64_t> &kernel_size, int64_t mode = 1, 54 const PadMode &pad_mode = VALID, const std::vector<int64_t> &pad = {0, 0, 0, 0}, 55 const std::vector<int64_t> &stride = {1, 1}, const std::vector<int64_t> &dilation = {1, 1}, 56 int64_t group = 1, const Format &format = NCHW, const std::vector<int64_t> &pad_list = {0, 0, 0, 0}, 57 const std::vector<int64_t> &output_paddings = {0}, ActivationType activation_type = NO_ACTIVATION); 58 59 /// \brief Method to set kernel_size attribute. 60 /// 61 /// \param[in] kernel_size Define the size of the filter kernel. 62 void set_kernel_size(const std::vector<int64_t> &kernel_size) override; 63 64 /// \brief Method to set dilation attribute. 65 /// 66 /// \param[in] dilation Define the coefficient of expansion of the filter kernel, which is useful for dilated 67 /// convolution-transpose. 68 void set_dilation(const std::vector<int64_t> &dilation) override; 69 70 /// \brief Method to set output_paddings attribute. 71 /// 72 /// \param[in] output_paddings Define the additional elements added to the side with higher coordinate indices in the 73 /// output, which is used to control the selection-range of the output tensor. 74 void set_output_paddings(const std::vector<int64_t> &output_paddings); 75 76 /// \brief Method to set activation type. 77 /// 78 /// \param[in] activation_type Define the activation type. 79 void set_activation_type(ActivationType activation_type); 80 81 /// \brief Method to get output_paddings attribute. 82 /// 83 /// \return output_paddings value. 84 std::vector<int64_t> get_output_paddings() const; 85 86 /// \brief Method to get activation type. 87 /// 88 /// \return activation type. 89 ActivationType get_activation_type() const; 90 }; 91 } // namespace ops 92 } // namespace mindspore 93 94 #endif // MINDSPORE_CORE_OPS_CONV2D_TRANSPOSE_FUSION_H_ 95