// 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 #include "gtest/gtest.h" #include "paddle/fluid/eager/eager_tensor.h" #include "paddle/fluid/eager/grad_node_info.h" #include "paddle/fluid/eager/tests/data_structure_tests/grad_node_test.h" #include "paddle/fluid/eager/tests/test_utils.h" #include "paddle/fluid/eager/utils.h" #include "paddle/pten/api/lib/utils/allocator.h" namespace egr { TEST(EagerUtils, AutoGradMeta) { // Construct Eager Tensor pten::DenseTensorMeta meta = pten::DenseTensorMeta( pten::DataType::FLOAT32, paddle::framework::make_ddim({1, 1})); std::shared_ptr dt0 = std::make_shared( std::make_shared( paddle::platform::CPUPlace()), meta); dt0->mutable_data()[0] = 10.0; EagerTensor et0 = EagerTensor(dt0); std::shared_ptr dt1 = std::make_shared( std::make_shared( paddle::platform::CPUPlace()), meta); dt1->mutable_data()[0] = 20.0; EagerTensor et1 = EagerTensor(dt1); std::vector ets = {et0, et1}; auto test_node = std::make_shared(); // unsafe_autograd_meta() // autograd_meta() // multi_autograd_meta() AutogradMeta* autograd_meta0 = EagerUtils::autograd_meta(&et0); AutogradMeta* autograd_meta1 = EagerUtils::autograd_meta(&et1); AutogradMeta* unsafe_autograd_meta_after = EagerUtils::unsafe_autograd_meta(et0); CHECK_NOTNULL(unsafe_autograd_meta_after); std::vector autograd_metas = EagerUtils::multi_autograd_meta(&ets); std::vector unsafe_autograd_metas = EagerUtils::unsafe_autograd_meta(&ets); CHECK_NOTNULL(unsafe_autograd_metas[0]); CHECK_NOTNULL(unsafe_autograd_metas[1]); // Set Autograd Meta autograd_meta0->SetSingleOutRankWithSlot(0, 1); autograd_meta0->SetGradNode(test_node); // OutRankInfo() std::pair out_rank_info0 = EagerUtils::OutRankInfo(et0); CHECK_EQ(static_cast(out_rank_info0.first), 0); CHECK_EQ(static_cast(out_rank_info0.second), 1); // grad_node() std::shared_ptr grad_node0 = EagerUtils::grad_node(et0); CHECK_NOTNULL(grad_node0.get()); EagerUtils::SetHistory(autograd_meta1, test_node); EagerUtils::SetHistory({autograd_meta1}, test_node); std::shared_ptr grad_node1 = EagerUtils::grad_node(et1); CHECK_NOTNULL(grad_node1.get()); // SetOutRankWithSlot() EagerUtils::SetOutRankWithSlot(autograd_meta1, 0); std::pair out_rank_info1 = EagerUtils::OutRankInfo(et1); CHECK_EQ(static_cast(out_rank_info1.first), 0); CHECK_EQ(static_cast(out_rank_info1.second), 0); EagerUtils::SetOutRankWithSlot(&autograd_metas, 0); std::pair out_rank_info2 = EagerUtils::OutRankInfo(et0); CHECK_EQ(static_cast(out_rank_info2.first), 0); CHECK_EQ(static_cast(out_rank_info2.second), 0); std::pair out_rank_info3 = EagerUtils::OutRankInfo(et1); CHECK_EQ(static_cast(out_rank_info3.first), 0); CHECK_EQ(static_cast(out_rank_info3.second), 1); } template egr::EagerTensor CreateTestCPUTensor(T val, const paddle::framework::DDim& ddim) { pten::DenseTensorMeta meta = pten::DenseTensorMeta(pten::DataType::FLOAT32, ddim); egr::EagerTensor tensor; std::shared_ptr dt = std::make_shared( std::make_shared( paddle::platform::CPUPlace()), meta); auto* dt_ptr = dt->mutable_data(); for (int64_t i = 0; i < dt->numel(); i++) { dt_ptr[i] = val; } tensor.set_impl(dt); return tensor; } TEST(EagerUtils, ComputeRequireGrad) { auto auto_grad0 = std::make_shared(); auto auto_grad1 = std::make_shared(); auto auto_grad2 = std::make_shared(); auto auto_grad3 = std::make_shared(); CHECK_EQ(auto_grad0->NumericStopGradient(), -1); VLOG(6) << "Single Test ComputeRequireGrad"; auto_grad0->SetStopGradient(true); CHECK(egr::EagerUtils::ComputeRequireGrad(true, auto_grad0.get()) == false); CHECK(egr::EagerUtils::ComputeRequireGrad(false, auto_grad0.get()) == false); auto_grad0->SetStopGradient(false); CHECK(egr::EagerUtils::ComputeRequireGrad(false, auto_grad0.get()) == false); CHECK(egr::EagerUtils::ComputeRequireGrad(true, auto_grad0.get()) == true); VLOG(6) << "Multi Test ComputeRequireGrad"; auto_grad0->SetStopGradient(false); auto_grad1->SetStopGradient(true); CHECK(egr::EagerUtils::ComputeRequireGrad(true, auto_grad0.get(), auto_grad1.get()) == true); CHECK(egr::EagerUtils::ComputeRequireGrad(false, auto_grad0.get(), auto_grad1.get()) == false); auto_grad0->SetStopGradient(true); CHECK(egr::EagerUtils::ComputeRequireGrad(true, auto_grad0.get(), auto_grad1.get()) == false); CHECK(egr::EagerUtils::ComputeRequireGrad(false, auto_grad0.get(), auto_grad1.get()) == false); } TEST(EagerUtils, PassStopGradient) { auto auto_grad0 = std::make_shared(); auto auto_grad1 = std::make_shared(); auto auto_grad2 = std::make_shared(); auto auto_grad3 = std::make_shared(); CHECK_EQ(auto_grad0->NumericStopGradient(), -1); VLOG(6) << "Test PassStopGradient"; egr::EagerUtils::PassStopGradient(false, auto_grad0.get()); CHECK(auto_grad0->StopGradient() == false); egr::EagerUtils::PassStopGradient(true, auto_grad0.get(), auto_grad1.get(), auto_grad2.get(), auto_grad3.get()); CHECK(auto_grad0->StopGradient() == true); CHECK(auto_grad1->StopGradient() == true); CHECK(auto_grad2->StopGradient() == true); CHECK(auto_grad3->StopGradient() == true); } TEST(EagerUtils, SyncToVarsSingle) { paddle::framework::DDim ddim = paddle::framework::make_ddim({2, 4, 4, 4}); auto tensor = CreateTestCPUTensor(5.0f, ddim); std::vector> var_bases = egr::EagerUtils::SyncToVars(tensor); paddle::framework::Variable* var = var_bases[0]->MutableVar(); const auto& framework_tensor = var->Get(); const float* ptr = framework_tensor.data(); VLOG(6) << "Check Value for SyncToVarsSingle"; CHECK_EQ(framework_tensor.numel(), tensor.numel()); for (int i = 0; i < framework_tensor.numel(); i++) { CHECK_EQ(ptr[i], 5.0f); } } TEST(EagerUtils, SyncToVarsMultiple) { paddle::framework::DDim ddim = paddle::framework::make_ddim({2, 4, 4, 4}); std::vector tensors = {CreateTestCPUTensor(1.0f, ddim), CreateTestCPUTensor(2.0f, ddim)}; std::vector> var_bases = egr::EagerUtils::SyncToVars(tensors); { paddle::framework::Variable* var = var_bases[0]->MutableVar(); const auto& framework_tensor = var->Get(); const float* ptr = framework_tensor.data(); CHECK_EQ(framework_tensor.numel(), tensors[0].numel()); for (int i = 0; i < framework_tensor.numel(); i++) { CHECK_EQ(ptr[i], 1.0); } } { paddle::framework::Variable* var = var_bases[1]->MutableVar(); const auto& framework_tensor = var->Get(); const float* ptr = framework_tensor.data(); VLOG(6) << "Check Value for SyncToVarsMultiple"; CHECK_EQ(framework_tensor.numel(), tensors[0].numel()); for (int i = 0; i < framework_tensor.numel(); i++) { CHECK_EQ(ptr[i], 2.0); } } } TEST(EagerUtils, SyncToTensorSingle) { std::shared_ptr X(new egr::EagerTensor()); std::vector src_data(128, 5.0); std::vector dims = {2, 4, 4, 4}; paddle::platform::CPUPlace place; auto* x_tensor = X->MutableVar()->GetMutable(); x_tensor->Resize(paddle::framework::make_ddim(dims)); auto* mutable_x = x_tensor->mutable_data(place); paddle::memory::Copy(place, mutable_x, place, src_data.data(), sizeof(float) * src_data.size()); auto X_ = egr::EagerUtils::SyncToTensors(*(X.get())); egr::EagerTensor tensor = egr::EagerUtils::GetOutput(X_[0]); VLOG(6) << "Check Value for SyncToTensorSingle"; CHECK(eager_test::CompareTensorWithValue(tensor, 5.0)); } TEST(EagerUtils, SyncToTensorMultiple) { eager_test::InitEnv(paddle::platform::CPUPlace()); std::vector dims = {2, 4, 4, 4}; paddle::platform::CPUPlace place; std::vector egr_tensors; { auto egr_tensor = egr::EagerTensor(); std::vector src_data(128, 1.0); auto* x_tensor = egr_tensor.MutableVar()->GetMutable(); x_tensor->Resize(paddle::framework::make_ddim(dims)); auto* mutable_x = x_tensor->mutable_data(place); paddle::memory::Copy(place, mutable_x, place, src_data.data(), sizeof(float) * src_data.size()); egr_tensors.emplace_back(egr_tensor); } { auto egr_tensor = egr::EagerTensor(); std::vector src_data(128, 2.0); auto* x_tensor = egr_tensor.MutableVar()->GetMutable(); x_tensor->Resize(paddle::framework::make_ddim(dims)); auto* mutable_x = x_tensor->mutable_data(place); paddle::memory::Copy(place, mutable_x, place, src_data.data(), sizeof(float) * src_data.size()); egr_tensors.emplace_back(std::move(egr_tensor)); } std::vector tensors = egr::EagerUtils::GetOutputs(egr::EagerUtils::SyncToTensors(egr_tensors)); VLOG(6) << "Check Value for SyncToTensorMultiple"; CHECK(eager_test::CompareTensorWithValue(tensors[0], 1.0) == true); CHECK(eager_test::CompareTensorWithValue(tensors[1], 2.0) == true); } TEST(EagerUtils, ConstructDuplicableOutput) { VLOG(6) << "Check ConstructDuplicableOutput"; std::vector> outs = egr::EagerUtils::ConstructDuplicableOutput(2); CHECK_EQ(outs.size(), size_t(2)); CHECK(outs[0]->defined() == false); CHECK(outs[0]->initialized() == false); } } // namespace egr