text: /* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
  
  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. */
  
  #include "paddle/framework/lod_tensor_array.h"
  #include "paddle/framework/op_registry.h"
  
  namespace paddle {
  namespace operators {
  
  class LoDArrayLengthOp : public framework::OperatorBase {
   public:
    LoDArrayLengthOp(const std::string &type,
                     const framework::VariableNameMap &inputs,
                     const framework::VariableNameMap &outputs,
                     const framework::AttributeMap &attrs)
        : OperatorBase(type, inputs, outputs, attrs) {}
    void Run(const framework::Scope &scope,
             const platform::Place &place) const override {
      auto &x = scope.FindVar(Input("X"))->Get<framework::LoDTensorArray>();
      auto &out =
          *scope.FindVar(Output("Out"))->GetMutable<framework::LoDTensor>();
      out.Resize({1});
      auto cpu = platform::CPUPlace();
      *out.mutable_data<int64_t>(cpu) = static_cast<int64_t>(x.size());
    }
  };
  
  class LoDArrayLengthProtoMaker : public framework::OpProtoAndCheckerMaker {
   public:
    LoDArrayLengthProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
        : OpProtoAndCheckerMaker(proto, op_checker) {
      AddInput("X", "(LoDTensorArray) The input tensor array.");
      AddOutput("Out", "(Tensor) 1x1 CPU Tensor of length, int64_t");
      AddComment(R"DOC(
  LoDArrayLength Operator.
  
  This operator obtains the length of lod tensor array:
  
  $$Out = len(X)$$
  
  NOTE: The output is a CPU Tensor since the control variable should be only in
  CPU and the length of LoDTensorArray should be used as control variables.
  
  )DOC");
    }
  };
  
  class LoDArrayLengthInferShape : public framework::InferShapeBase {
   public:
    void operator()(framework::InferShapeContext *context) const override {
      PADDLE_ENFORCE(context->HasInput("X"));
      PADDLE_ENFORCE(context->HasOutput("Out"));
      context->SetOutputDim("Out", {1});
    }
  };
  
  }  // namespace operators
  }  // namespace paddle
  
  namespace ops = paddle::operators;
  REGISTER_OPERATOR(lod_array_length, ops::LoDArrayLengthOp,
                    ops::LoDArrayLengthInferShape, ops::LoDArrayLengthProtoMaker,
                    paddle::framework::EmptyGradOpMaker);
  