backward_test.cc 13.1 KB
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/* 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. */

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#include "paddle/framework/backward.h"
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#include <gtest/gtest.h>
#include "paddle/framework/op_registry.h"
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#include "paddle/operators/net_op.h"
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namespace paddle {
namespace framework {

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using OperatorBase = framework::OperatorBase;
using OpProtoAndCheckerMaker = framework::OpProtoAndCheckerMaker;
using OpProto = framework::OpProto;
using OpAttrChecker = framework::OpAttrChecker;
using Scope = framework::Scope;
using DeviceContext = platform::DeviceContext;

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class EmptyOp : public OperatorBase {
 public:
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  void InferShape(const Scope &scope) const override {}
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  void Run(const Scope &scope, const DeviceContext &dev_ctx) const override {}
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};

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class RowWiseAddOpMaker : public OpProtoAndCheckerMaker {
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 public:
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  RowWiseAddOpMaker(OpProto *proto, OpAttrChecker *op_checker)
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      : OpProtoAndCheckerMaker(proto, op_checker) {
    AddInput("X", "Input X of Add").IgnoreGradient();
    AddInput("b", "Bias of Add").IgnoreGradient();
    AddOutput("Out", "Out of Add").IgnoreGradient();
    AddComment("Add Op");
  }
};

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class MulOpMaker : public OpProtoAndCheckerMaker {
 public:
  MulOpMaker(OpProto *proto, OpAttrChecker *op_checker)
      : OpProtoAndCheckerMaker(proto, op_checker) {
    AddInput("A", "A");
    AddInput("B", "B");
    AddOutput("Out", "Out");
    AddComment("Mul");
  }
};

class SigmoidOpMaker : public OpProtoAndCheckerMaker {
 public:
  SigmoidOpMaker(OpProto *proto, OpAttrChecker *op_checker)
      : OpProtoAndCheckerMaker(proto, op_checker) {
    AddInput("X", "X");
    AddOutput("Y", "Y");
    AddComment("Sigmoid");
  }
};

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class NoGradOpMaker : public OpProtoAndCheckerMaker {
 public:
  NoGradOpMaker(OpProto *proto, OpAttrChecker *op_checker)
      : OpProtoAndCheckerMaker(proto, op_checker) {
    AddInput("X", "X input");
    AddOutput("Y", "Y output");
    AddComment("NoGradOp, same input output. no Grad");
  }
};

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class FcOp : public operators::NetOp {
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 public:
  void Init() override {
    AddOp(OpRegistry::CreateOp("mul", {Input("X"), Input("W")},
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                               {Output("mul_result")}, {}));
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    auto b_name = Input("b");
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    std::string before_act = "mul_result";
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    if (b_name != kEmptyVarName) {
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      AddOp(OpRegistry::CreateOp("rowwise_add", {Output("mul_result"), b_name},
                                 {Output("add_result")}, {}));
      before_act = "add_result";
    } else {
      auto out_varname = Output("add_result");
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      if (out_varname != kEmptyVarName) {
        this->Rename(out_varname, kEmptyVarName);
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      }
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    }
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    AddOp(OpRegistry::CreateOp("sigmoid", {Output(before_act)}, {Output("Out")},
                               {}));
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    CompleteAddOp(false);
  }
};

class FcOpMaker : public OpProtoAndCheckerMaker {
 public:
  FcOpMaker(OpProto *proto, OpAttrChecker *op_checker)
      : OpProtoAndCheckerMaker(proto, op_checker) {
    AddInput("X", "x");
    AddInput("W", "w");
    AddInput("b", "b");
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    AddOutput("mul_result", "").SetTemporary();
    AddOutput("add_result", "").SetTemporary();
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    AddOutput("Out", "");
    AddComment("");
  }
};

class ManyOutputOpMaker : public OpProtoAndCheckerMaker {
 public:
  ManyOutputOpMaker(OpProto *proto, OpAttrChecker *op_checker)
      : OpProtoAndCheckerMaker(proto, op_checker) {
    AddInput("x", "x");
    AddOutput("y", "y");
    AddOutput("z", "z");
    AddComment("");
  }
};

class FillZeroOpMaker : public OpProtoAndCheckerMaker {
 public:
  FillZeroOpMaker(OpProto *proto, OpAttrChecker *op_checker)
      : OpProtoAndCheckerMaker(proto, op_checker) {
    AddInput("x", "x");
    AddOutput("out", "out");
    AddComment("");
  }
};
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class AddOpMaker : public OpProtoAndCheckerMaker {
 public:
  AddOpMaker(OpProto *proto, OpAttrChecker *op_checker)
      : OpProtoAndCheckerMaker(proto, op_checker) {
    AddInput("X", "x").SetMultiple();
    AddOutput("Y", "y");
    AddComment("");
  }
};
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}  // namespace framework
}  // namespace paddle

namespace f = paddle::framework;
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namespace ops = paddle::operators;
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using EnforceNotMet = paddle::platform::EnforceNotMet;
REGISTER_OP(rowwise_add, f::EmptyOp, f::RowWiseAddOpMaker);
REGISTER_GRADIENT_OP(rowwise_add, rowwise_add_grad, f::EmptyOp);
REGISTER_OP(mul, f::EmptyOp, f::MulOpMaker);
REGISTER_GRADIENT_OP(mul, mul_grad, f::EmptyOp);
REGISTER_OP(sigmoid, f::EmptyOp, f::SigmoidOpMaker);
REGISTER_GRADIENT_OP(sigmoid, sigmoid_grad, f::EmptyOp);
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REGISTER_OP(nograd, f::EmptyOp, f::NoGradOpMaker);
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REGISTER_OP(fill_zeros_like, f::EmptyOp, f::FillZeroOpMaker);
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REGISTER_OP(add, f::EmptyOp, f::AddOpMaker);
REGISTER_GRADIENT_OP(add, add_grad, f::EmptyOp);
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REGISTER_OP(fc, f::FcOp, f::FcOpMaker);
REGISTER_OP(many_output_op, f::EmptyOp, f::ManyOutputOpMaker);
REGISTER_GRADIENT_OP(many_output_op, many_output_op_grad, f::EmptyOp);
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TEST(Backward, simple_op_grad) {
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  auto fwd = f::OpRegistry::CreateOp("rowwise_add", {"X", "b"}, {"Out"}, {});
  ASSERT_NE(fwd, nullptr);
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  auto gop = f::OpRegistry::CreateGradOp(*fwd);
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  ASSERT_EQ(4UL, gop->inputs_.size());
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  ASSERT_EQ(f::kEmptyVarName, gop->inputs_[0]);
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  ASSERT_EQ("rowwise_add_grad", gop->type_);
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  ASSERT_EQ(f::GradVarName("X"), gop->outputs_[0]);
  ASSERT_EQ(f::GradVarName("b"), gop->outputs_[1]);
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  ASSERT_EQ(f::GradVarName("X"), gop->Output(f::GradVarName("X")));
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}

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TEST(Backward, simple_op_not_need_grad) {
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  auto fwd = f::OpRegistry::CreateOp("rowwise_add", {"X", "b"}, {"Out"}, {});
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  ASSERT_NE(fwd, nullptr);
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  auto gop = f::Backward(*fwd, {"X"});
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  ASSERT_EQ(std::find(gop->outputs_.begin(), gop->outputs_.end(),
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                      f::GradVarName("X")),
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            gop->outputs_.end());
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  auto no_input_gop = f::Backward(*fwd, {"X", "b"});
  ASSERT_NE(no_input_gop, nullptr);
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  ASSERT_TRUE(no_input_gop->IsNetOp());
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  ASSERT_EQ(0UL,
            std::static_pointer_cast<ops::NetOp>(no_input_gop)->ops_.size());
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}

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TEST(Backward, net_fc_backward_normal) {
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  std::shared_ptr<f::OperatorBase> fwd = f::OpRegistry::CreateOp(
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      "fc", {"X", "w", "b"}, {"mul_result", "add_result", "out"}, {});
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  ASSERT_NE(fwd, nullptr);
  std::shared_ptr<f::OperatorBase> gop = f::Backward(*fwd, {});
  ASSERT_TRUE(gop->IsNetOp());
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  auto net = static_cast<ops::NetOp *>(gop.get());
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  ASSERT_NO_THROW(net->DebugString());

  ASSERT_EQ(3UL, net->ops_.size());

  f::OperatorBase &d_sigmoid = *net->ops_[0];
  ASSERT_EQ("sigmoid_grad", d_sigmoid.type_);

  f::OperatorBase &d_add = *net->ops_[1];
  ASSERT_EQ("rowwise_add_grad", d_add.type_);

  f::OperatorBase &d_mul = *net->ops_[2];
  ASSERT_EQ("mul_grad", d_mul.type_);
}

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TEST(Backward, net_fc_backward_not_have_b) {
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  std::shared_ptr<f::OperatorBase> fwd =
      f::OpRegistry::CreateOp("fc", {"X", "w", f::kEmptyVarName},
                              {"mul_result", "add_result", "tmp"}, {});
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  ASSERT_NE(fwd, nullptr);
  std::shared_ptr<f::OperatorBase> gop = f::Backward(*fwd, {});
  ASSERT_TRUE(gop->IsNetOp());
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  auto net = static_cast<ops::NetOp *>(gop.get());
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  ASSERT_NO_THROW(net->DebugString());

  ASSERT_EQ(2UL, net->ops_.size());

  f::OperatorBase &d_sigmoid = *net->ops_[0];
  ASSERT_EQ("sigmoid_grad", d_sigmoid.type_);

  f::OperatorBase &d_mul = *net->ops_[1];
  ASSERT_EQ("mul_grad", d_mul.type_);
}

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TEST(Backward, net_input_of_network_not_need_grad) {
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  ops::NetOp net;
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  net.AddOp(f::OpRegistry::CreateOp("fc", {"X", "W1", "b1"},
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                                    {"mul_tmp_0", "add_tmp_0", "hidden0"}, {}));
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  net.AddOp(f::OpRegistry::CreateOp("fc", {"hidden0", "W2", "b2"},
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                                    {"mul_tmp_1", "add_tmp_1", "hidden1"}, {}));
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  net.CompleteAddOp();
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  auto bwd = Backward(net, {"X"});  // X@GRAD is not need.
  ASSERT_TRUE(bwd->IsNetOp());
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  auto bwd_net = static_cast<ops::NetOp *>(bwd.get());
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  std::unordered_set<std::string> all_output = std::unordered_set<std::string>(
      bwd_net->outputs_.begin(), bwd_net->outputs_.end());
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  all_output.erase(f::kEmptyVarName);
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  for (auto &out : {"W1", "b1", "hidden0", "W2", "b2"}) {
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    ASSERT_NE(all_output.find(f::GradVarName(out)), all_output.end());
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  }
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  // Not Generated X
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  ASSERT_EQ(all_output.find(f::GradVarName("X")), all_output.end());
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  ASSERT_EQ(2UL, bwd_net->ops_.size());
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  ASSERT_TRUE(bwd_net->ops_[1]->IsNetOp());
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  auto first_fc_grad = static_cast<ops::NetOp *>(bwd_net->ops_[1].get());
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  ASSERT_EQ(3UL, first_fc_grad->ops_.size());
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  ASSERT_EQ(f::kEmptyVarName,
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            first_fc_grad->ops_[2]->Output(f::GradVarName("A")));
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}

TEST(Backward, net_shared_weight) {
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  ops::NetOp net;
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  net.AddOp(f::OpRegistry::CreateOp("mul", {"X", "W"}, {"Out"}, {}));
  net.AddOp(f::OpRegistry::CreateOp("mul", {"Out", "W"}, {"FinalOut"}, {}));
  net.CompleteAddOp();

  auto bwd = f::Backward(net, {});
  ASSERT_TRUE(bwd->IsNetOp());
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  auto bwd_net = static_cast<ops::NetOp *>(bwd.get());
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  ASSERT_EQ(3UL, bwd_net->ops_.size());
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  ASSERT_EQ("add", bwd_net->ops_[2]->type_);
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}

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TEST(Backward, op_register_grad_not_for_network) {
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  auto fwd = f::OpRegistry::CreateOp(
      "fc", {"X", "W", "b"}, {"mul_out", "add_out", "out1"},
      {{"temporary_index", std::vector<int>{0, 1}}});
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  ASSERT_THROW(f::OpRegistry::CreateGradOp(*fwd), EnforceNotMet);
}

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TEST(Backward, op_all_input_are_not_need) {
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  auto fwd = f::OpRegistry::CreateOp("rowwise_add", {"X", "b"}, {"Out"}, {});
  auto backward = f::Backward(*fwd, {"X", "b"});
  ASSERT_TRUE(backward->IsNetOp());
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  auto net = static_cast<ops::NetOp *>(backward.get());
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  ASSERT_TRUE(net->ops_.empty());
}

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TEST(Backward, op_all_output_are_not_need) {
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  auto fwd = f::OpRegistry::CreateOp("rowwise_add", {"X", "b"}, {"Out"}, {});
  auto backward = f::Backward(*fwd, {"Out"});
  ASSERT_TRUE(backward->IsNetOp());
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  auto net = static_cast<ops::NetOp *>(backward.get());
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  ASSERT_TRUE(net->ops_.empty());
}

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TEST(Backward, op_part_of_output_are_not_need) {
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  auto fwd = f::OpRegistry::CreateOp("many_output_op", {"X"}, {"Y", "Z"}, {});
  auto backward = f::Backward(*fwd, {"Z"});
  ASSERT_TRUE(backward->IsNetOp());
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  auto net = static_cast<ops::NetOp *>(backward.get());
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  ASSERT_EQ(net->ops_.size(), 2UL);
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  auto &fill_zero = *net->ops_[0];
  ASSERT_EQ("fill_zeros_like", fill_zero.type_);
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  ASSERT_EQ(1UL, fill_zero.inputs_.size());
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  ASSERT_EQ("Z", fill_zero.inputs_[0]);
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  ASSERT_EQ(1UL, fill_zero.outputs_.size());
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  ASSERT_EQ(std::string("Z") + f::kZeroVarSuffix, fill_zero.outputs_[0]);
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  auto &d_many_out = *net->ops_[1];
  ASSERT_EQ("many_output_op_grad", d_many_out.type_);
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  ASSERT_EQ(1UL + 2UL + 2UL, d_many_out.inputs_.size());  // I/O/OG
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  ASSERT_EQ(std::string("Z") + f::kZeroVarSuffix,
            d_many_out.Input(f::GradVarName("z")));
  ASSERT_EQ(f::GradVarName("Y"), d_many_out.Input(f::GradVarName("y")));
  ASSERT_EQ(f::GradVarName("X"), d_many_out.Output(f::GradVarName("x")));
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}

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TEST(Backward, op_part_of_input_are_not_need) {
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  auto fwd = f::OpRegistry::CreateOp("mul", {"a", "b"}, {"out"}, {});
  auto backward = f::Backward(*fwd, {"a"});
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  auto &grad_mul = *backward;
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  ASSERT_EQ(grad_mul.type_, "mul_grad");
  ASSERT_EQ(grad_mul.inputs_.size(), 2UL + 1UL + 1UL);
  ASSERT_EQ(grad_mul.outputs_.size(), 2UL);
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  ASSERT_EQ(grad_mul.Output(f::GradVarName("A")), f::kEmptyVarName);
  ASSERT_EQ(grad_mul.Output(f::GradVarName("B")), f::GradVarName("b"));
  ASSERT_EQ(grad_mul.Input(f::GradVarName("Out")), f::GradVarName("out"));
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  ASSERT_EQ(grad_mul.Input("A"), "a");
  ASSERT_EQ(grad_mul.Input("B"), "b");
  ASSERT_EQ(grad_mul.Input("Out"), "out");
}

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TEST(Backward, linear_net_intermediate_variable_has_no_grad) {
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  ops::NetOp net;
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  net.AddOp(f::OpRegistry::CreateOp("fc", {"x1", "w1", "b1"},
                                    {"mul_out1", "add_out1", "out1"}, {}));
  net.AddOp(f::OpRegistry::CreateOp("fc", {"out1", "w2", "b2"},
                                    {"mul_out2", "tmp_out2", "out2"}, {}));
  net.AddOp(f::OpRegistry::CreateOp("fc", {"out2", "w3", "b3"},
                                    {"mul_out3", "tmp_out3", "out3"}, {}));
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  net.CompleteAddOp();
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  auto backward = f::Backward(net, {"mul_out2", "tmp_out2", "out2"});
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  ASSERT_TRUE(backward->IsNetOp());
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  auto bwd_net = static_cast<ops::NetOp *>(backward.get());
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  ASSERT_EQ(bwd_net->ops_.size(), 3UL);
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  auto &grad_fc = *bwd_net->ops_[0];
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  EXPECT_EQ(grad_fc.inputs_.size(),
            3UL       /* external input number */
                + 1UL /* external output number*/
                + 1UL /* number of gradient of external output*/
                + 2U /* internal variable number*/);
  EXPECT_EQ(grad_fc.outputs_.size(), 2UL       /* input number of mul*/
                                         + 2UL /* input number of rowwise_add */
                                         + 1UL /* input number of sigmod */);
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  EXPECT_EQ(bwd_net->ops_[1]->inputs_.size(), 0UL);
  EXPECT_EQ(bwd_net->ops_[1]->outputs_.size(), 0UL);
  EXPECT_EQ(bwd_net->ops_[2]->inputs_.size(), 0UL);
  EXPECT_EQ(bwd_net->ops_[2]->outputs_.size(), 0UL);
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}