// Copyright (c) 2018 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/framework/details/gather_op_handle.h" #include "gtest/gtest.h" #include "paddle/fluid/platform/device_context.h" namespace paddle { namespace framework { namespace details { namespace f = paddle::framework; namespace p = paddle::platform; // test data amount const f::DDim kDims = {20, 20}; struct TestGatherOpHandle { std::vector> ctxs_; std::vector local_scopes_; std::vector param_scopes_; Scope g_scope_; std::unique_ptr op_handle_; std::vector> vars_; std::vector gpu_list_; void WaitAll() { for (size_t j = 0; j < ctxs_.size(); ++j) { ctxs_[j]->Wait(); } } void InitCtxOnGpu(bool use_gpu) { if (use_gpu) { #ifdef PADDLE_WITH_CUDA int count = p::GetCUDADeviceCount(); if (count <= 1) { LOG(WARNING) << "Cannot test multi-gpu Broadcast, because the CUDA " "device count is " << count; exit(0); } for (int i = 0; i < count; ++i) { auto p = p::CUDAPlace(i); gpu_list_.push_back(p); ctxs_.emplace_back(new p::CUDADeviceContext(p)); } #else PADDLE_THROW("CUDA is not support."); #endif } else { int count = 8; for (int i = 0; i < count; ++i) { auto p = p::CPUPlace(); gpu_list_.push_back(p); ctxs_.emplace_back(new p::CPUDeviceContext(p)); } } } void InitGatherOp(size_t input_scope_idx) { for (size_t j = 0; j < gpu_list_.size(); ++j) { local_scopes_.push_back(&(g_scope_.NewScope())); Scope& local_scope = local_scopes_.back()->NewScope(); *local_scopes_.back() ->Var(details::kLocalExecScopeName) ->GetMutable() = &local_scope; local_scope.Var("input"); param_scopes_.emplace_back(&local_scope); } param_scopes_[input_scope_idx]->Var("out"); op_handle_.reset(new GatherOpHandle(local_scopes_, gpu_list_)); // add input for (size_t j = 0; j < gpu_list_.size(); ++j) { op_handle_->SetDeviceContext(gpu_list_[j], ctxs_[j].get()); auto* in_var_handle = new VarHandle(1, j, "input", gpu_list_[j]); vars_.emplace_back(in_var_handle); op_handle_->AddInput(in_var_handle); } // add dummy var vars_.emplace_back(new DummyVarHandle()); DummyVarHandle* in_dummy_var_handle = static_cast(vars_.back().get()); in_dummy_var_handle->generated_op_ = nullptr; op_handle_->AddInput(in_dummy_var_handle); // add output auto* out_var_handle = new VarHandle(2, input_scope_idx, "out", gpu_list_[input_scope_idx]); vars_.emplace_back(out_var_handle); op_handle_->AddOutput(out_var_handle); // add dummy var vars_.emplace_back(new DummyVarHandle()); DummyVarHandle* dummy_var_handle = static_cast(vars_.back().get()); op_handle_->AddOutput(dummy_var_handle); } void TestGatherSelectedRows(size_t output_scope_idx) { int height = kDims[0] * 2; std::vector rows{0, 1, 2, 3, 3, 0, 14, 7, 3, 1, 2, 4, 6, 3, 1, 1, 1, 1, 3, 7}; std::vector send_vector(f::product(kDims)); for (size_t k = 0; k < send_vector.size(); ++k) { send_vector[k] = k; } for (size_t input_scope_idx = 0; input_scope_idx < gpu_list_.size(); ++input_scope_idx) { auto in_var = param_scopes_.at(input_scope_idx)->FindVar("input"); PADDLE_ENFORCE_NOT_NULL(in_var); auto in_selected_rows = in_var->GetMutable(); auto value = in_selected_rows->mutable_value(); value->mutable_data(kDims, gpu_list_[input_scope_idx]); in_selected_rows->set_height(height); in_selected_rows->set_rows(rows); paddle::framework::TensorFromVector( send_vector, *(ctxs_[input_scope_idx]), value); value->Resize(kDims); } auto out_var = param_scopes_.at(output_scope_idx)->FindVar("out"); PADDLE_ENFORCE_NOT_NULL(out_var); auto out_selected_rows = out_var->GetMutable(); auto in_var = param_scopes_.at(output_scope_idx)->FindVar("input"); auto in_selected_rows = in_var->GetMutable(); out_selected_rows->mutable_value()->ShareDataWith( in_selected_rows->value()); op_handle_->Run(false); WaitAll(); p::CPUPlace cpu_place; auto& out_select_rows = out_var->Get(); auto rt = out_select_rows.value(); PADDLE_ENFORCE_EQ(out_select_rows.height(), height, "height is not equal."); for (size_t k = 0; k < out_select_rows.rows().size(); ++k) { PADDLE_ENFORCE_EQ(out_select_rows.rows()[k], rows[k % rows.size()]); } f::Tensor result_tensor; f::TensorCopy(rt, cpu_place, *(ctxs_[output_scope_idx]), &result_tensor); float* ct = result_tensor.data(); for (int64_t j = 0; j < f::product(kDims) * static_cast(gpu_list_.size()); ++j) { ASSERT_NEAR(ct[j], send_vector[j % send_vector.size()], 1e-5); } } }; TEST(GatherTester, TestCPUGatherTestSelectedRows) { TestGatherOpHandle test_op; size_t input_scope_idx = 0; test_op.InitCtxOnGpu(false); test_op.InitGatherOp(input_scope_idx); test_op.TestGatherSelectedRows(input_scope_idx); } #ifdef PADDLE_WITH_CUDA TEST(GatherTester, TestGPUGatherTestSelectedRows) { TestGatherOpHandle test_op; size_t input_scope_idx = 0; test_op.InitCtxOnGpu(false); test_op.InitGatherOp(input_scope_idx); test_op.TestGatherSelectedRows(input_scope_idx); } #endif } // namespace details } // namespace framework } // namespace paddle