wehub-resource-sync
346 lines
12 KiB
C++
346 lines
12 KiB
C++
// Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "paddle/fluid/eager/backward.h"
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#include <sstream>
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#include "glog/logging.h"
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#include "gtest/gtest.h"
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#include "paddle/fluid/eager/accumulation/accumulation_node.h"
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#include "paddle/fluid/eager/api/all.h"
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#include "paddle/fluid/eager/api/generated/eager_generated/backwards/scale_node.h"
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#include "paddle/fluid/eager/autograd_meta.h"
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#include "paddle/fluid/eager/grad_node_info.h"
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#include "paddle/phi/core/dense_tensor.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/core/tensor_meta.h"
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#include "test/cpp/eager/test_utils.h"
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PD_DECLARE_KERNEL(full, 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) {
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// Prepare Device Contexts
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eager_test::InitEnv(phi::CPUPlace());
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// Prepare Inputs
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phi::DDim ddim = common::make_ddim({4, 16, 16, 32});
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// Create Target Tensor
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paddle::Tensor target_tensor =
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eager_test::CreateTensorWithValue(ddim,
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phi::CPUPlace(),
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phi::DataType::FLOAT32,
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phi::DataLayout::NCHW,
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1.0 /*value*/,
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false /*is_leaf*/);
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paddle::Tensor leaf_tensor;
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{
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// Create Scale Node
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auto node0_ptr = std::make_shared<GradNodeScale>(1, 1);
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node0_ptr->SetAttributes_scale(5.0 /*scale*/);
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// Set grad in/out meta
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node0_ptr->SetDefaultGradInOutMeta();
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AutogradMeta* auto_grad_meta = EagerUtils::autograd_meta(&target_tensor);
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auto_grad_meta->SetGradNode(
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std::dynamic_pointer_cast<GradNodeBase>(node0_ptr));
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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 =
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std::make_shared<egr::GradNodeAccumulation>(leaf_tensor);
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auto_grad_meta1->SetGradNode(
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std::dynamic_pointer_cast<GradNodeBase>(acc_node_ptr));
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auto_grad_meta1->SetSingleOutRankWithSlot(0, 0);
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auto_grad_meta1->SetStopGradient(false);
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node0_ptr->SetGradOutMeta({leaf_tensor}, 0);
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}
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std::vector<paddle::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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}
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TEST(Backward, SingleNodeCustomGrad) {
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// Prepare Device Contexts
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eager_test::InitEnv(phi::CPUPlace());
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// Prepare Inputs
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std::vector<paddle::Tensor> target_tensors;
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phi::DDim ddim = common::make_ddim({4, 16, 16, 32});
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// Create Target Tensor
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paddle::Tensor tensor =
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eager_test::CreateTensorWithValue(ddim,
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phi::CPUPlace(),
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phi::DataType::FLOAT32,
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phi::DataLayout::NCHW,
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1.0 /*value*/,
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false /*is_leaf*/);
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target_tensors.emplace_back(std::move(tensor));
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std::vector<paddle::Tensor> grad_tensors;
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// Create Grad Tensor
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paddle::Tensor grad_tensor =
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eager_test::CreateTensorWithValue(ddim,
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phi::CPUPlace(),
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phi::DataType::FLOAT32,
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phi::DataLayout::NCHW,
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10.0 /*value*/,
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false /*is_leaf*/);
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grad_tensors.emplace_back(std::move(grad_tensor));
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paddle::Tensor leaf_tensor;
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{
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// Create Scale Node
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auto node0_ptr = std::make_shared<GradNodeScale>(1, 1);
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node0_ptr->SetAttributes_scale(5.0 /*scale*/);
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// Set grad in/out meta
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node0_ptr->SetDefaultGradInOutMeta();
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// Connect Tensor and Node via AutoGradMeta
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AutogradMeta* auto_grad_meta =
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EagerUtils::autograd_meta(&(target_tensors[0]));
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auto_grad_meta->SetGradNode(
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std::dynamic_pointer_cast<GradNodeBase>(node0_ptr));
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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 =
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std::make_shared<egr::GradNodeAccumulation>(leaf_tensor);
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auto_grad_meta1->SetGradNode(
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std::dynamic_pointer_cast<GradNodeBase>(acc_node_ptr));
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auto_grad_meta1->SetSingleOutRankWithSlot(0, 0);
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auto_grad_meta1->SetStopGradient(false);
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node0_ptr->SetGradOutMeta({leaf_tensor}, 0);
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}
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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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}
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/*
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Node1
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Node0
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inp0
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*/
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TEST(Backward, LinearNodes) {
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// Prepare Device Contexts
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eager_test::InitEnv(phi::CPUPlace());
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// Prepare Inputs
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std::vector<paddle::Tensor> target_tensors;
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phi::DDim ddim = common::make_ddim({4, 16, 16, 32});
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// Create Target Tensor
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paddle::Tensor tensor =
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eager_test::CreateTensorWithValue(ddim,
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phi::CPUPlace(),
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phi::DataType::FLOAT32,
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phi::DataLayout::NCHW,
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1.0 /*value*/,
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false /*is_leaf*/);
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target_tensors.emplace_back(std::move(tensor));
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paddle::Tensor leaf_tensor;
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{
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// Create Node0
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auto node0_ptr = std::make_shared<GradNodeScale>(1, 1);
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node0_ptr->SetAttributes_scale(5.0 /*scale*/);
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// Set grad in/out meta for node0
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node0_ptr->SetDefaultGradInOutMeta();
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// Create Node1
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auto node1_ptr = std::make_shared<GradNodeScale>(1, 1);
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node1_ptr->SetAttributes_scale(10.0 /*scale*/);
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// Set grad in/out meta for node1
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node1_ptr->SetDefaultGradInOutMeta();
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// Connect Input Tensor and Node0 via AutoGradMeta
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AutogradMeta* auto_grad_meta =
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EagerUtils::autograd_meta(&(target_tensors[0]));
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auto_grad_meta->SetGradNode(
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std::dynamic_pointer_cast<GradNodeBase>(node0_ptr));
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auto_grad_meta->SetSingleOutRankWithSlot(0, 0);
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auto_grad_meta->SetStopGradient(false);
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// Connect Node0 -> Node1 via Edge
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auto tmp_tensor = paddle::Tensor();
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auto* meta0 = EagerUtils::autograd_meta(&tmp_tensor);
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meta0->SetStopGradient(false);
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meta0->SetSingleOutRankWithSlot(0, 0);
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meta0->SetGradNode(node1_ptr);
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node0_ptr->SetGradOutMeta(tmp_tensor, 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 =
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std::make_shared<egr::GradNodeAccumulation>(leaf_tensor);
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auto_grad_meta1->SetGradNode(
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std::dynamic_pointer_cast<GradNodeBase>(acc_node_ptr));
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auto_grad_meta1->SetSingleOutRankWithSlot(0, 0);
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auto_grad_meta1->SetStopGradient(false);
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node1_ptr->SetGradOutMeta(leaf_tensor, 0);
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}
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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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}
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/*
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Node2
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Node0 Node1
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inp0 inp1
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*/
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TEST(Backward, WithAccumulation) {
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// Prepare Device Contexts
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eager_test::InitEnv(phi::CPUPlace());
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// Prepare Inputs
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phi::DDim ddim = common::make_ddim({4, 16, 16, 32});
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// Create Target Tensor
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std::vector<paddle::Tensor> target_tensors;
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paddle::Tensor tensor0 =
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eager_test::CreateTensorWithValue(ddim,
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phi::CPUPlace(),
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phi::DataType::FLOAT32,
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phi::DataLayout::NCHW,
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1.0 /*value*/,
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false /*is_leaf*/);
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paddle::Tensor tensor1 =
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eager_test::CreateTensorWithValue(ddim,
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phi::CPUPlace(),
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phi::DataType::FLOAT32,
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phi::DataLayout::NCHW,
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1.0 /*value*/,
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false /*is_leaf*/);
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target_tensors.emplace_back(std::move(tensor0));
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target_tensors.emplace_back(std::move(tensor1));
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// Create Grad Tensor
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std::vector<paddle::Tensor> grad_tensors;
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paddle::Tensor grad_tensor0 =
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eager_test::CreateTensorWithValue(ddim,
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phi::CPUPlace(),
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phi::DataType::FLOAT32,
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phi::DataLayout::NCHW,
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5.0 /*value*/,
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false /*is_leaf*/);
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paddle::Tensor grad_tensor1 =
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eager_test::CreateTensorWithValue(ddim,
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phi::CPUPlace(),
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phi::DataType::FLOAT32,
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phi::DataLayout::NCHW,
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10.0 /*value*/,
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false /*is_leaf*/);
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grad_tensors.emplace_back(std::move(grad_tensor0));
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grad_tensors.emplace_back(std::move(grad_tensor1));
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paddle::Tensor leaf_tensor;
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{
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// Create Node0
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auto node0_ptr = std::make_shared<GradNodeScale>(1, 1);
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node0_ptr->SetAttributes_scale(5.0 /*scale*/);
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node0_ptr->SetDefaultGradInOutMeta();
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// Create Node1
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auto node1_ptr = std::make_shared<GradNodeScale>(1, 1);
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node1_ptr->SetAttributes_scale(10.0 /*scale*/);
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node1_ptr->SetDefaultGradInOutMeta();
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// Create Node2
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auto node2_ptr = std::make_shared<GradNodeScale>(1, 1);
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node2_ptr->SetAttributes_scale(20.0 /*scale*/);
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node2_ptr->SetDefaultGradInOutMeta();
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// Connect Inp0 and Node0 via AutoGradMeta
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AutogradMeta* auto_grad_meta0 =
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EagerUtils::autograd_meta(&(target_tensors[0]));
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auto_grad_meta0->SetGradNode(
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std::dynamic_pointer_cast<GradNodeBase>(node0_ptr));
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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
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AutogradMeta* auto_grad_meta1 =
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EagerUtils::autograd_meta(&(target_tensors[1]));
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auto_grad_meta1->SetGradNode(
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std::dynamic_pointer_cast<GradNodeBase>(node1_ptr));
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auto_grad_meta1->SetSingleOutRankWithSlot(0, 0);
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auto_grad_meta1->SetStopGradient(false);
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// Connect Node0 -> Node2 via Edge
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auto tmp_tensor0 = paddle::Tensor();
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auto* meta0 = EagerUtils::autograd_meta(&tmp_tensor0);
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meta0->SetStopGradient(false);
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meta0->SetSingleOutRankWithSlot(0, 0);
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meta0->SetGradNode(node2_ptr);
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node0_ptr->SetGradOutMeta(tmp_tensor0, 0);
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// Connect Node1 -> Node2 via Edge
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auto tmp_tensor1 = paddle::Tensor();
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auto* meta1 = EagerUtils::autograd_meta(&tmp_tensor1);
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meta1->SetStopGradient(false);
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meta1->SetSingleOutRankWithSlot(0, 0);
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meta1->SetGradNode(node2_ptr);
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node1_ptr->SetGradOutMeta(tmp_tensor1, 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 =
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std::make_shared<egr::GradNodeAccumulation>(leaf_tensor);
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auto_grad_meta2->SetGradNode(
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std::dynamic_pointer_cast<GradNodeBase>(acc_node_ptr));
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auto_grad_meta2->SetSingleOutRankWithSlot(0, 0);
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auto_grad_meta2->SetStopGradient(false);
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std::vector<egr::AutogradMeta*> res2 = {auto_grad_meta2};
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node2_ptr->SetGradOutMeta(leaf_tensor, 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
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