wehub-resource-sync
201 lines
7.2 KiB
C++
201 lines
7.2 KiB
C++
// 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/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/backward.h"
|
|
#include "paddle/fluid/eager/grad_node_info.h"
|
|
#include "paddle/fluid/eager/hooks.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);
|
|
|
|
namespace egr {
|
|
|
|
paddle::Tensor hook_function(const paddle::Tensor& t) {
|
|
auto t_dense = std::dynamic_pointer_cast<phi::DenseTensor>(t.impl());
|
|
|
|
auto ret_meta = phi::DenseTensorMeta(
|
|
t_dense->dtype(), t_dense->dims(), t_dense->layout());
|
|
auto place = t_dense->place();
|
|
size_t bytes_size =
|
|
common::product(t_dense->dims()) * SizeOf(t_dense->dtype());
|
|
auto ret_dense = std::make_shared<phi::DenseTensor>(
|
|
paddle::memory::Alloc(place, bytes_size), std::move(ret_meta));
|
|
|
|
float* t_ptr = t_dense->mutable_data<float>(place);
|
|
float* ret_ptr = ret_dense->mutable_data<float>(place);
|
|
for (int i = 0; i < ret_dense->numel(); i++) {
|
|
ret_ptr[i] = t_ptr[i] + 3.0f;
|
|
}
|
|
|
|
auto ret_impl = std::dynamic_pointer_cast<phi::TensorBase>(ret_dense);
|
|
paddle::Tensor ret = paddle::Tensor();
|
|
ret.set_impl(ret_impl);
|
|
|
|
return ret;
|
|
}
|
|
|
|
TEST(RetainGrad, HookBeforeRetainGrad) {
|
|
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& target_tensor = target_tensors[0];
|
|
|
|
// Create ScaleNode
|
|
auto scale_node_ptr = std::make_shared<GradNodeScale>(1, 1);
|
|
scale_node_ptr->SetAttributes_scale(5.0 /*scale*/);
|
|
|
|
// Set grad in/out meta for node0
|
|
scale_node_ptr->SetDefaultGradInOutMeta();
|
|
|
|
// Connect Input Tensor and ScaleNode via AutoGradMeta
|
|
// Apply RetainGrad
|
|
{
|
|
// ScaleNode Hook: +3
|
|
|
|
auto auto_grad_meta = std::make_shared<AutogradMeta>();
|
|
auto_grad_meta->SetGradNode(
|
|
std::dynamic_pointer_cast<GradNodeBase>(scale_node_ptr));
|
|
auto_grad_meta->SetSingleOutRankWithSlot(0, 0);
|
|
auto_grad_meta->SetStopGradient(false);
|
|
target_tensor.set_autograd_meta(
|
|
std::dynamic_pointer_cast<paddle::AbstractAutogradMeta>(
|
|
auto_grad_meta));
|
|
|
|
egr_utils_api::RegisterGradientHookForTensor(target_tensor, hook_function);
|
|
egr_utils_api::RetainGradForTensor(
|
|
target_tensor); // result: 1.0 + 3.0 = 4.0
|
|
egr_utils_api::RetainGradForTensor(
|
|
target_tensor); // result: 1.0 + 3.0 = 4.0
|
|
}
|
|
|
|
// Retain Grad for leaf tensor1
|
|
paddle::Tensor leaf_tensor = paddle::Tensor();
|
|
{
|
|
// AccumulationNode Hook: +3
|
|
auto tmp_tensor0 = paddle::Tensor();
|
|
auto auto_grad_meta = EagerUtils::autograd_meta(&tmp_tensor0);
|
|
|
|
auto acc_node_ptr = std::make_shared<GradNodeAccumulation>(tmp_tensor0);
|
|
|
|
auto_grad_meta->SetStopGradient(false);
|
|
auto_grad_meta->SetGradNode(acc_node_ptr);
|
|
auto_grad_meta->SetSingleOutRankWithSlot(0, 0);
|
|
std::vector<egr::AutogradMeta*> res = {auto_grad_meta};
|
|
scale_node_ptr->SetGradOutMeta(tmp_tensor0, 0);
|
|
|
|
leaf_tensor.set_autograd_meta(
|
|
std::dynamic_pointer_cast<paddle::AbstractAutogradMeta>(
|
|
tmp_tensor0.mutable_autograd_meta()));
|
|
|
|
egr_utils_api::RegisterGradientHookForTensor(leaf_tensor, hook_function);
|
|
egr_utils_api::RetainGradForTensor(
|
|
leaf_tensor); // result: 4.0*5.0 + 3.0 = 23.0
|
|
}
|
|
|
|
Backward(target_tensors, {});
|
|
|
|
eager_test::CompareGradTensorWithValue<float>(target_tensor, 4.0);
|
|
eager_test::CompareGradTensorWithValue<float>(leaf_tensor, 23.0);
|
|
}
|
|
|
|
TEST(RetainGrad, HookAfterRetainGrad) {
|
|
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& target_tensor = target_tensors[0];
|
|
|
|
// Create ScaleNode
|
|
auto scale_node_ptr = std::make_shared<GradNodeScale>(1, 1);
|
|
scale_node_ptr->SetAttributes_scale(5.0 /*scale*/);
|
|
// Set grad in/out meta for node0
|
|
scale_node_ptr->SetDefaultGradInOutMeta();
|
|
|
|
// Connect Input Tensor and ScaleNode via AutoGradMeta
|
|
// Apply RetainGrad
|
|
{
|
|
// ScaleNode Hook: +3
|
|
|
|
auto auto_grad_meta = std::make_shared<AutogradMeta>();
|
|
auto_grad_meta->SetGradNode(
|
|
std::dynamic_pointer_cast<GradNodeBase>(scale_node_ptr));
|
|
auto_grad_meta->SetSingleOutRankWithSlot(0, 0);
|
|
auto_grad_meta->SetStopGradient(false);
|
|
target_tensor.set_autograd_meta(
|
|
std::dynamic_pointer_cast<paddle::AbstractAutogradMeta>(
|
|
auto_grad_meta));
|
|
|
|
egr_utils_api::RetainGradForTensor(target_tensor); // result: 1.0
|
|
egr_utils_api::RegisterGradientHookForTensor(target_tensor, hook_function);
|
|
}
|
|
|
|
// Retain Grad for leaf tensor1
|
|
paddle::Tensor leaf_tensor = paddle::Tensor();
|
|
{
|
|
// AccumulationNode Hook: +3
|
|
auto tmp_tensor0 = paddle::Tensor();
|
|
auto auto_grad_meta = EagerUtils::autograd_meta(&tmp_tensor0);
|
|
auto acc_node_ptr = std::make_shared<GradNodeAccumulation>(tmp_tensor0);
|
|
auto_grad_meta->SetGradNode(acc_node_ptr);
|
|
auto_grad_meta->SetStopGradient(false);
|
|
scale_node_ptr->SetGradOutMeta(tmp_tensor0, 0);
|
|
|
|
auto_grad_meta->SetSingleOutRankWithSlot(0, 0);
|
|
leaf_tensor.set_autograd_meta(
|
|
std::dynamic_pointer_cast<paddle::AbstractAutogradMeta>(
|
|
tmp_tensor0.mutable_autograd_meta()));
|
|
|
|
egr_utils_api::RegisterGradientHookForTensor(leaf_tensor, hook_function);
|
|
}
|
|
|
|
Backward(target_tensors, {});
|
|
eager_test::CompareGradTensorWithValue<float>(target_tensor, 1.0);
|
|
eager_test::CompareGradTensorWithValue<float>(leaf_tensor, 23.0);
|
|
}
|
|
} // namespace egr
|