1 /** 2 * Copyright 2019 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_CCSRC_FRONTEND_PARALLEL_TENSOR_LAYOUT_TENSOR_INFO_H_ 18 #define MINDSPORE_CCSRC_FRONTEND_PARALLEL_TENSOR_LAYOUT_TENSOR_INFO_H_ 19 20 #include <cstdint> 21 #include <string> 22 #include <utility> 23 #include <vector> 24 25 #include "frontend/parallel/device_matrix.h" 26 #include "frontend/parallel/tensor_layout/tensor_layout.h" 27 28 namespace mindspore { 29 namespace parallel { 30 using Shapes = std::vector<Shape>; 31 32 class TensorInfo { 33 public: TensorInfo(const TensorLayout & tensor_layout,Shape shape,Shape slice_shape)34 TensorInfo(const TensorLayout &tensor_layout, Shape shape, Shape slice_shape) 35 : tensor_layout_(tensor_layout), shape_(std::move(shape)), slice_shape_(std::move(slice_shape)) {} TensorInfo(const TensorLayout & tensor_layout)36 explicit TensorInfo(const TensorLayout &tensor_layout) : tensor_layout_(tensor_layout) { 37 shape_ = tensor_layout.tensor_shape().array(); 38 slice_shape_ = tensor_layout.slice_shape().array(); 39 } 40 // trivial default constructor will not initialize c language types. 41 TensorInfo() = default; 42 ~TensorInfo() = default; tensor_layout()43 TensorLayout tensor_layout() const { return tensor_layout_; } slice_shape()44 Shape slice_shape() const { return slice_shape_; } shape()45 Shape shape() const { return shape_; } set_reduce_dim(const std::vector<int64_t> & dim)46 void set_reduce_dim(const std::vector<int64_t> &dim) { reduce_dim_ = dim; } reduce_dim()47 std::vector<int64_t> reduce_dim() const { return reduce_dim_; } InferStrategy()48 Dimensions InferStrategy() const { 49 Dimensions stra; 50 for (size_t i = 0; i < shape_.size(); ++i) { 51 if ((slice_shape_[i] == 0) || (shape_[i] % slice_shape_[i] != 0)) { 52 return stra; 53 } 54 int64_t dim = shape_[i] / slice_shape_[i]; 55 stra.push_back(dim); 56 } 57 return stra; 58 } 59 bool operator==(const TensorInfo &other) { 60 if (this->slice_shape_ != other.slice_shape_) { 61 return false; 62 } 63 if (this->tensor_layout_ != other.tensor_layout_) { 64 return false; 65 } 66 return true; 67 } 68 69 private: 70 TensorLayout tensor_layout_; 71 Shape shape_; 72 Shape slice_shape_; 73 // reduce method's reduce dim 74 std::vector<int64_t> reduce_dim_; 75 }; 76 } // namespace parallel 77 } // namespace mindspore 78 79 #endif // MINDSPORE_CCSRC_FRONTEND_PARALLEL_TENSOR_LAYOUT_TENSOR_INFO_H_ 80