text: /**
   * Copyright 2019 Huawei Technologies Co., Ltd
   *
   * Licensed under the Apache License, Version 2.0 (the "License");
   * you may not use this file except in compliance with the License.
   * You may obtain a copy of the License at
   *
   * http://www.apache.org/licenses/LICENSE-2.0
   *
   * Unless required by applicable law or agreed to in writing, software
   * distributed under the License is distributed on an "AS IS" BASIS,
   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   * See the License for the specific language governing permissions and
   * limitations under the License.
   */
  
  #ifndef MINDSPORE_CCSRC_PARALLEL_OPS_INFO_LOSS_INFO_H_
  #define MINDSPORE_CCSRC_PARALLEL_OPS_INFO_LOSS_INFO_H_
  
  #include <memory>
  #include <string>
  #include <unordered_map>
  #include <vector>
  
  #include "ir/value.h"
  #include "parallel/ops_info/activation_info.h"
  #include "parallel/ops_info/operator_info.h"
  #include "parallel/strategy.h"
  
  namespace mindspore {
  namespace parallel {
  // infer shape:
  // input_0 : [a, b],  input_1 : [a, b]
  // output_0 : [a],  output_1: [a, b]
  class SoftmaxCrossEntropyWithLogitsInfo : public OperatorInfo {
   public:
    SoftmaxCrossEntropyWithLogitsInfo(const std::string& name, const Shapes& inputs_shape, const Shapes& outputs_shape,
                                      const PrimitiveAttrs& attrs)
        : OperatorInfo(name, inputs_shape, outputs_shape, attrs,
                       std::make_shared<SoftmaxCrossEntropyWithLogitsCost>(false)) {}
    ~SoftmaxCrossEntropyWithLogitsInfo() override = default;
    Status Init(const StrategyPtr& strategy) override;
    Status InitForCostModel(const StrategyPtr& strategy) override;
  
    Status GenerateStrategies(int32_t stage_id) override;
    Status SetCostUnderStrategy(const StrategyPtr& strategy) override;
    void ReComputeBatchSplitFlagList() override;
  
   protected:
    Status CheckStrategy(const StrategyPtr& strategy) override;
    Status GetAttrs() override;
    Status InferMirrorOps() override { return SUCCESS; }
    Status InferForwardCommunication() override { return SUCCESS; }
    Status InferTensorMap() override;
    Status InferTensorInfo() override;
    Status InferDevMatrixShape() override;
    // There are two outputs for SoftmaxCrossEntropyWithLogits, and outputs[1] is used for grad and overload
    // the InferAsLossDivisor.
    Status InferAsLossDivisor() override;
  
   private:
    int32_t axis_ = -1;  // default -1
  };
  }  // namespace parallel
  }  // namespace mindspore
  
  #endif  // MINDSPORE_CCSRC_PARALLEL_OPS_INFO_LOSS_INFO_H_
  