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chore: import upstream snapshot with attribution

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wehub-resource-sync
2026-07-13 12:40:42 +08:00
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test/cpp/eager/task_tests/backward_test.cc
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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 "paddle/fluid/eager/backward.h"
#include <sstream>
#include "glog/logging.h"
#include "gtest/gtest.h"
#include "paddle/fluid/eager/accumulation/accumulation_node.h"
#include "paddle/fluid/eager/api/all.h"
#include "paddle/fluid/eager/api/generated/eager_generated/backwards/scale_node.h"
#include "paddle/fluid/eager/autograd_meta.h"
#include "paddle/fluid/eager/grad_node_info.h"
#include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/core/tensor_meta.h"
#include "test/cpp/eager/test_utils.h"
PD_DECLARE_KERNEL(full, CPU, ALL_LAYOUT);
PD_DECLARE_KERNEL(add, CPU, ALL_LAYOUT);
namespace egr {
TEST(Backward, SingleNodeEmptyGrad) {
// Prepare Device Contexts
eager_test::InitEnv(phi::CPUPlace());
// Prepare Inputs
phi::DDim ddim = common::make_ddim({4, 16, 16, 32});
// Create Target Tensor
paddle::Tensor target_tensor =
eager_test::CreateTensorWithValue(ddim,
phi::CPUPlace(),
phi::DataType::FLOAT32,
phi::DataLayout::NCHW,
1.0 /*value*/,
false /*is_leaf*/);
paddle::Tensor leaf_tensor;
{
// 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);
auto_grad_meta->SetStopGradient(false);
AutogradMeta* auto_grad_meta1 = EagerUtils::autograd_meta(&leaf_tensor);
// Connect Tensor and AccumulationNode via AutoGradMeta
auto acc_node_ptr =
std::make_shared<egr::GradNodeAccumulation>(leaf_tensor);
auto_grad_meta1->SetGradNode(
std::dynamic_pointer_cast<GradNodeBase>(acc_node_ptr));
auto_grad_meta1->SetSingleOutRankWithSlot(0, 0);
auto_grad_meta1->SetStopGradient(false);
node0_ptr->SetGradOutMeta({leaf_tensor}, 0);
}
std::vector<paddle::Tensor> outs = {target_tensor};
// Run Backward
Backward(outs, {});
// Check Output Value
eager_test::CompareGradTensorWithValue<float>(leaf_tensor, 5.0);
}
TEST(Backward, SingleNodeCustomGrad) {
// Prepare Device Contexts
eager_test::InitEnv(phi::CPUPlace());
// Prepare Inputs
std::vector<paddle::Tensor> target_tensors;
phi::DDim ddim = common::make_ddim({4, 16, 16, 32});
// Create Target Tensor
paddle::Tensor tensor =
eager_test::CreateTensorWithValue(ddim,
phi::CPUPlace(),
phi::DataType::FLOAT32,
phi::DataLayout::NCHW,
1.0 /*value*/,
false /*is_leaf*/);
target_tensors.emplace_back(std::move(tensor));
std::vector<paddle::Tensor> grad_tensors;
// Create Grad Tensor
paddle::Tensor grad_tensor =
eager_test::CreateTensorWithValue(ddim,
phi::CPUPlace(),
phi::DataType::FLOAT32,
phi::DataLayout::NCHW,
10.0 /*value*/,
false /*is_leaf*/);
grad_tensors.emplace_back(std::move(grad_tensor));
paddle::Tensor leaf_tensor;
{
// 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);
auto_grad_meta->SetStopGradient(false);
AutogradMeta* auto_grad_meta1 = EagerUtils::autograd_meta(&leaf_tensor);
// Connect Tensor and AccumulationNode via AutoGradMeta
auto acc_node_ptr =
std::make_shared<egr::GradNodeAccumulation>(leaf_tensor);
auto_grad_meta1->SetGradNode(
std::dynamic_pointer_cast<GradNodeBase>(acc_node_ptr));
auto_grad_meta1->SetSingleOutRankWithSlot(0, 0);
auto_grad_meta1->SetStopGradient(false);
node0_ptr->SetGradOutMeta({leaf_tensor}, 0);
}
// Run Backward
Backward(target_tensors, grad_tensors);
// Check Output Value
eager_test::CompareGradTensorWithValue<float>(leaf_tensor, 50.0);
}
/*
Node1
|
Node0
|
inp0
*/
TEST(Backward, LinearNodes) {
// Prepare Device Contexts
eager_test::InitEnv(phi::CPUPlace());
// Prepare Inputs
std::vector<paddle::Tensor> target_tensors;
phi::DDim ddim = common::make_ddim({4, 16, 16, 32});
// Create Target Tensor
paddle::Tensor tensor =
eager_test::CreateTensorWithValue(ddim,
phi::CPUPlace(),
phi::DataType::FLOAT32,
phi::DataLayout::NCHW,
1.0 /*value*/,
false /*is_leaf*/);
target_tensors.emplace_back(std::move(tensor));
paddle::Tensor leaf_tensor;
{
// 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);
auto_grad_meta->SetStopGradient(false);
// Connect Node0 -> Node1 via Edge
auto tmp_tensor = paddle::Tensor();
auto* meta0 = EagerUtils::autograd_meta(&tmp_tensor);
meta0->SetStopGradient(false);
meta0->SetSingleOutRankWithSlot(0, 0);
meta0->SetGradNode(node1_ptr);
node0_ptr->SetGradOutMeta(tmp_tensor, 0);
AutogradMeta* auto_grad_meta1 = EagerUtils::autograd_meta(&leaf_tensor);
// Connect Tensor and AccumulationNode via AutoGradMeta
auto acc_node_ptr =
std::make_shared<egr::GradNodeAccumulation>(leaf_tensor);
auto_grad_meta1->SetGradNode(
std::dynamic_pointer_cast<GradNodeBase>(acc_node_ptr));
auto_grad_meta1->SetSingleOutRankWithSlot(0, 0);
auto_grad_meta1->SetStopGradient(false);
node1_ptr->SetGradOutMeta(leaf_tensor, 0);
}
// Use Empty Grad Tensor
Backward(target_tensors, {});
// Check Output Value
eager_test::CompareGradTensorWithValue<float>(leaf_tensor, 50.0);
}
/*
Node2
| |
Node0 Node1
| |
inp0 inp1
*/
TEST(Backward, WithAccumulation) {
// Prepare Device Contexts
eager_test::InitEnv(phi::CPUPlace());
// Prepare Inputs
phi::DDim ddim = common::make_ddim({4, 16, 16, 32});
// Create Target Tensor
std::vector<paddle::Tensor> target_tensors;
paddle::Tensor tensor0 =
eager_test::CreateTensorWithValue(ddim,
phi::CPUPlace(),
phi::DataType::FLOAT32,
phi::DataLayout::NCHW,
1.0 /*value*/,
false /*is_leaf*/);
paddle::Tensor tensor1 =
eager_test::CreateTensorWithValue(ddim,
phi::CPUPlace(),
phi::DataType::FLOAT32,
phi::DataLayout::NCHW,
1.0 /*value*/,
false /*is_leaf*/);
target_tensors.emplace_back(std::move(tensor0));
target_tensors.emplace_back(std::move(tensor1));
// Create Grad Tensor
std::vector<paddle::Tensor> grad_tensors;
paddle::Tensor grad_tensor0 =
eager_test::CreateTensorWithValue(ddim,
phi::CPUPlace(),
phi::DataType::FLOAT32,
phi::DataLayout::NCHW,
5.0 /*value*/,
false /*is_leaf*/);
paddle::Tensor grad_tensor1 =
eager_test::CreateTensorWithValue(ddim,
phi::CPUPlace(),
phi::DataType::FLOAT32,
phi::DataLayout::NCHW,
10.0 /*value*/,
false /*is_leaf*/);
grad_tensors.emplace_back(std::move(grad_tensor0));
grad_tensors.emplace_back(std::move(grad_tensor1));
paddle::Tensor leaf_tensor;
{
// 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);
auto_grad_meta0->SetStopGradient(false);
// 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);
auto_grad_meta1->SetStopGradient(false);
// Connect Node0 -> Node2 via Edge
auto tmp_tensor0 = paddle::Tensor();
auto* meta0 = EagerUtils::autograd_meta(&tmp_tensor0);
meta0->SetStopGradient(false);
meta0->SetSingleOutRankWithSlot(0, 0);
meta0->SetGradNode(node2_ptr);
node0_ptr->SetGradOutMeta(tmp_tensor0, 0);
// Connect Node1 -> Node2 via Edge
auto tmp_tensor1 = paddle::Tensor();
auto* meta1 = EagerUtils::autograd_meta(&tmp_tensor1);
meta1->SetStopGradient(false);
meta1->SetSingleOutRankWithSlot(0, 0);
meta1->SetGradNode(node2_ptr);
node1_ptr->SetGradOutMeta(tmp_tensor1, 0);
AutogradMeta* auto_grad_meta2 = EagerUtils::autograd_meta(&leaf_tensor);
// Connect Tensor and AccumulationNode via AutoGradMeta
auto acc_node_ptr =
std::make_shared<egr::GradNodeAccumulation>(leaf_tensor);
auto_grad_meta2->SetGradNode(
std::dynamic_pointer_cast<GradNodeBase>(acc_node_ptr));
auto_grad_meta2->SetSingleOutRankWithSlot(0, 0);
auto_grad_meta2->SetStopGradient(false);
std::vector<egr::AutogradMeta*> res2 = {auto_grad_meta2};
node2_ptr->SetGradOutMeta(leaf_tensor, 0);
}
Backward(target_tensors, grad_tensors);
eager_test::CompareGradTensorWithValue<float>(leaf_tensor, 2500.0);
}
} // namespace egr