backward_test.cc 11.4 KB
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// Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
//
// 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 <sstream>

#include "glog/logging.h"
#include "gtest/gtest.h"

#include "paddle/fluid/eager/accumulation/accumulation_node.h"
#include "paddle/fluid/eager/api/generated/eager_generated/backwards/scale_node.h"
#include "paddle/fluid/eager/api/utils/tensor_utils.h"
#include "paddle/fluid/eager/autograd_meta.h"
#include "paddle/fluid/eager/backward.h"
#include "paddle/fluid/eager/grad_node_info.h"
#include "paddle/fluid/eager/tests/test_utils.h"

#include "paddle/fluid/eager/api/all.h"

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#include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/core/tensor_meta.h"
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#include "paddle/phi/core/kernel_registry.h"

PD_DECLARE_KERNEL(full, CPU, ALL_LAYOUT);
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PD_DECLARE_KERNEL(copy, CPU, ALL_LAYOUT);
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PD_DECLARE_KERNEL(add, CPU, ALL_LAYOUT);
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namespace egr {
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TEST(Backward, SingleNodeEmptyGrad) {
  // Prepare Device Contexts
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  eager_test::InitEnv(paddle::platform::CPUPlace());
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  // Prepare Inputs
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  paddle::framework::DDim ddim = phi::make_ddim({4, 16, 16, 32});
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  // Create Target Tensor
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  paddle::experimental::Tensor target_tensor =
      egr_utils_api::CreateTensorWithValue(
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          ddim, paddle::platform::CPUPlace(), phi::DataType::FLOAT32,
          phi::DataLayout::NCHW, 1.0 /*value*/, false /*is_leaf*/);
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  paddle::experimental::Tensor leaf_tensor;
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  {
    // Create Scale Node
    auto node0_ptr = std::make_shared<GradNodeScale>(1, 1);
    node0_ptr->SetAttributes_scale(5.0 /*scale*/);

    // Set grad in/out meta
    node0_ptr->SetDefaultGradInOutMeta();
    AutogradMeta* auto_grad_meta = EagerUtils::autograd_meta(&target_tensor);
    auto_grad_meta->SetGradNode(
        std::dynamic_pointer_cast<GradNodeBase>(node0_ptr));
    auto_grad_meta->SetSingleOutRankWithSlot(0, 0);
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    auto_grad_meta->SetStopGradient(false);
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    AutogradMeta* auto_grad_meta1 = EagerUtils::autograd_meta(&leaf_tensor);

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    // Connect Tensor and AccumulationNode via AutoGradMeta
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    auto acc_node_ptr =
        std::make_shared<egr::GradNodeAccumulation>(auto_grad_meta1);
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    auto_grad_meta1->SetGradNode(
        std::dynamic_pointer_cast<GradNodeBase>(acc_node_ptr));
    auto_grad_meta1->SetSingleOutRankWithSlot(0, 0);
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    auto_grad_meta1->SetStopGradient(false);
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    std::vector<egr::AutogradMeta*> res = {auto_grad_meta1};
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    node0_ptr->AddEdges(&res, 0);
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  }
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  std::vector<paddle::experimental::Tensor> outs = {target_tensor};
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  // Run Backward
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  Backward(outs, {});
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  // Check Output Value
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  eager_test::CompareGradTensorWithValue<float>(leaf_tensor, 5.0);
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}

TEST(Backward, SingleNodeCustomGrad) {
  // Prepare Device Contexts
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  eager_test::InitEnv(paddle::platform::CPUPlace());
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  // Prepare Inputs
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  std::vector<paddle::experimental::Tensor> target_tensors;
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  paddle::framework::DDim ddim = phi::make_ddim({4, 16, 16, 32});
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  // Create Target Tensor
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  paddle::experimental::Tensor tensor = egr_utils_api::CreateTensorWithValue(
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      ddim, paddle::platform::CPUPlace(), phi::DataType::FLOAT32,
      phi::DataLayout::NCHW, 1.0 /*value*/, false /*is_leaf*/);
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  target_tensors.emplace_back(std::move(tensor));

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  std::vector<paddle::experimental::Tensor> grad_tensors;
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  // Create Grad Tensor
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  paddle::experimental::Tensor grad_tensor =
      egr_utils_api::CreateTensorWithValue(
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          ddim, paddle::platform::CPUPlace(), phi::DataType::FLOAT32,
          phi::DataLayout::NCHW, 10.0 /*value*/, false /*is_leaf*/);
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  grad_tensors.emplace_back(std::move(grad_tensor));

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  paddle::experimental::Tensor leaf_tensor;
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  {
    // Create Scale Node
    auto node0_ptr = std::make_shared<GradNodeScale>(1, 1);
    node0_ptr->SetAttributes_scale(5.0 /*scale*/);

    // Set grad in/out meta
    node0_ptr->SetDefaultGradInOutMeta();

    // Connect Tensor and Node via AutoGradMeta
    AutogradMeta* auto_grad_meta =
        EagerUtils::autograd_meta(&(target_tensors[0]));
    auto_grad_meta->SetGradNode(
        std::dynamic_pointer_cast<GradNodeBase>(node0_ptr));
    auto_grad_meta->SetSingleOutRankWithSlot(0, 0);
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    auto_grad_meta->SetStopGradient(false);
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    AutogradMeta* auto_grad_meta1 = EagerUtils::autograd_meta(&leaf_tensor);
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    // Connect Tensor and AccumulationNode via AutoGradMeta
    auto acc_node_ptr =
        std::make_shared<egr::GradNodeAccumulation>(auto_grad_meta1);

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    auto_grad_meta1->SetGradNode(
        std::dynamic_pointer_cast<GradNodeBase>(acc_node_ptr));
    auto_grad_meta1->SetSingleOutRankWithSlot(0, 0);
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    auto_grad_meta1->SetStopGradient(false);
    std::vector<egr::AutogradMeta*> res = {auto_grad_meta1};
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    node0_ptr->AddEdges(&res, 0);
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  }

  // Run Backward
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  Backward(target_tensors, grad_tensors);
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  // Check Output Value
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  eager_test::CompareGradTensorWithValue<float>(leaf_tensor, 50.0);
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}

/*
Node1
  |
Node0
  |
 inp0
*/
TEST(Backward, LinearNodes) {
  // Prepare Device Contexts
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  eager_test::InitEnv(paddle::platform::CPUPlace());
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  // Prepare Inputs
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  std::vector<paddle::experimental::Tensor> target_tensors;
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  paddle::framework::DDim ddim = phi::make_ddim({4, 16, 16, 32});
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  // Create Target Tensor
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  paddle::experimental::Tensor tensor = egr_utils_api::CreateTensorWithValue(
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      ddim, paddle::platform::CPUPlace(), phi::DataType::FLOAT32,
      phi::DataLayout::NCHW, 1.0 /*value*/, false /*is_leaf*/);
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  target_tensors.emplace_back(std::move(tensor));

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  paddle::experimental::Tensor leaf_tensor;
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  {
    // Create Node0
    auto node0_ptr = std::make_shared<GradNodeScale>(1, 1);
    node0_ptr->SetAttributes_scale(5.0 /*scale*/);

    // Set grad in/out meta for node0
    node0_ptr->SetDefaultGradInOutMeta();

    // Create Node1
    auto node1_ptr = std::make_shared<GradNodeScale>(1, 1);
    node1_ptr->SetAttributes_scale(10.0 /*scale*/);

    // Set grad in/out meta for node1
    node1_ptr->SetDefaultGradInOutMeta();

    // Connect Input Tensor and Node0 via AutoGradMeta
    AutogradMeta* auto_grad_meta =
        EagerUtils::autograd_meta(&(target_tensors[0]));
    auto_grad_meta->SetGradNode(
        std::dynamic_pointer_cast<GradNodeBase>(node0_ptr));
    auto_grad_meta->SetSingleOutRankWithSlot(0, 0);
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    auto_grad_meta->SetStopGradient(false);
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    // Connect Node0 -> Node1 via Edge
    auto meta0 = egr::AutogradMeta();
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    meta0.SetStopGradient(false);
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    meta0.SetSingleOutRankWithSlot(0, 0);
    meta0.SetGradNode(node1_ptr);
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    std::vector<egr::AutogradMeta*> res0 = {&meta0};
    node0_ptr->AddEdges(&res0, 0);
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    AutogradMeta* auto_grad_meta1 = EagerUtils::autograd_meta(&leaf_tensor);
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    // Connect Tensor and AccumulationNode via AutoGradMeta
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    auto acc_node_ptr =
        std::make_shared<egr::GradNodeAccumulation>(auto_grad_meta1);
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    auto_grad_meta1->SetGradNode(
        std::dynamic_pointer_cast<GradNodeBase>(acc_node_ptr));
    auto_grad_meta1->SetSingleOutRankWithSlot(0, 0);

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    auto_grad_meta1->SetStopGradient(false);
    std::vector<egr::AutogradMeta*> res1 = {auto_grad_meta1};
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    node1_ptr->AddEdges(&res1, 0);
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  }

  // Use Empty Grad Tensor
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  Backward(target_tensors, {});
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  // Check Output Value
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  eager_test::CompareGradTensorWithValue<float>(leaf_tensor, 50.0);
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}

/*
    Node2
    |   |
Node0   Node1
  |      |
 inp0   inp1
*/
TEST(Backward, WithAccumulation) {
  // Prepare Device Contexts
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  eager_test::InitEnv(paddle::platform::CPUPlace());
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  // Prepare Inputs
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  paddle::framework::DDim ddim = phi::make_ddim({4, 16, 16, 32});
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  // Create Target Tensor
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  std::vector<paddle::experimental::Tensor> target_tensors;
  paddle::experimental::Tensor tensor0 = egr_utils_api::CreateTensorWithValue(
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      ddim, paddle::platform::CPUPlace(), phi::DataType::FLOAT32,
      phi::DataLayout::NCHW, 1.0 /*value*/, false /*is_leaf*/);
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  paddle::experimental::Tensor tensor1 = egr_utils_api::CreateTensorWithValue(
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      ddim, paddle::platform::CPUPlace(), phi::DataType::FLOAT32,
      phi::DataLayout::NCHW, 1.0 /*value*/, false /*is_leaf*/);
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  target_tensors.emplace_back(std::move(tensor0));
  target_tensors.emplace_back(std::move(tensor1));

  // Create Grad Tensor
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  std::vector<paddle::experimental::Tensor> grad_tensors;
  paddle::experimental::Tensor grad_tensor0 =
      egr_utils_api::CreateTensorWithValue(
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          ddim, paddle::platform::CPUPlace(), phi::DataType::FLOAT32,
          phi::DataLayout::NCHW, 5.0 /*value*/, false /*is_leaf*/);
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  paddle::experimental::Tensor grad_tensor1 =
      egr_utils_api::CreateTensorWithValue(
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          ddim, paddle::platform::CPUPlace(), phi::DataType::FLOAT32,
          phi::DataLayout::NCHW, 10.0 /*value*/, false /*is_leaf*/);
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  grad_tensors.emplace_back(std::move(grad_tensor0));
  grad_tensors.emplace_back(std::move(grad_tensor1));

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  paddle::experimental::Tensor leaf_tensor;
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  {
    // Create Node0
    auto node0_ptr = std::make_shared<GradNodeScale>(1, 1);
    node0_ptr->SetAttributes_scale(5.0 /*scale*/);
    node0_ptr->SetDefaultGradInOutMeta();

    // Create Node1
    auto node1_ptr = std::make_shared<GradNodeScale>(1, 1);
    node1_ptr->SetAttributes_scale(10.0 /*scale*/);
    node1_ptr->SetDefaultGradInOutMeta();
    // Create Node2
    auto node2_ptr = std::make_shared<GradNodeScale>(1, 1);
    node2_ptr->SetAttributes_scale(20.0 /*scale*/);
    node2_ptr->SetDefaultGradInOutMeta();
    // Connect Inp0 and Node0 via AutoGradMeta
    AutogradMeta* auto_grad_meta0 =
        EagerUtils::autograd_meta(&(target_tensors[0]));
    auto_grad_meta0->SetGradNode(
        std::dynamic_pointer_cast<GradNodeBase>(node0_ptr));
    auto_grad_meta0->SetSingleOutRankWithSlot(0, 0);
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    auto_grad_meta0->SetStopGradient(false);
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    // Connect Inp1 and Node1 via AutoGradMeta
    AutogradMeta* auto_grad_meta1 =
        EagerUtils::autograd_meta(&(target_tensors[1]));
    auto_grad_meta1->SetGradNode(
        std::dynamic_pointer_cast<GradNodeBase>(node1_ptr));
    auto_grad_meta1->SetSingleOutRankWithSlot(0, 0);
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    auto_grad_meta1->SetStopGradient(false);
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    // Connect Node0 -> Node2 via Edge
    auto meta0 = egr::AutogradMeta();
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    meta0.SetStopGradient(false);
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    meta0.SetSingleOutRankWithSlot(0, 0);
    meta0.SetGradNode(node2_ptr);
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    std::vector<egr::AutogradMeta*> res0 = {&meta0};
    node0_ptr->AddEdges(&res0, 0);
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    // Connect Node1 -> Node2 via Edge
    auto meta1 = egr::AutogradMeta();
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    meta1.SetStopGradient(false);
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    meta1.SetSingleOutRankWithSlot(0, 0);
    meta1.SetGradNode(node2_ptr);
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    std::vector<egr::AutogradMeta*> res1 = {&meta1};
    node1_ptr->AddEdges(&res1, 0);
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    AutogradMeta* auto_grad_meta2 = EagerUtils::autograd_meta(&leaf_tensor);
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    // Connect Tensor and AccumulationNode via AutoGradMeta
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    auto acc_node_ptr =
        std::make_shared<egr::GradNodeAccumulation>(auto_grad_meta2);
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    auto_grad_meta2->SetGradNode(
        std::dynamic_pointer_cast<GradNodeBase>(acc_node_ptr));
    auto_grad_meta2->SetSingleOutRankWithSlot(0, 0);

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    auto_grad_meta2->SetStopGradient(false);
    std::vector<egr::AutogradMeta*> res2 = {auto_grad_meta2};
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    node2_ptr->AddEdges(&res2, 0);
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  }

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  Backward(target_tensors, grad_tensors);
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  eager_test::CompareGradTensorWithValue<float>(leaf_tensor, 2500.0);
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}

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}  // namespace egr