Qiao Longfei
6 years ago
parent
9b74707cbf
commit
0fcdae8418
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// Copyright (c) 2019 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 <glog/logging.h>
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#include <gtest/gtest.h>
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#include <algorithm>
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#include <memory>
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#include <vector>
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#include "paddle/fluid/operators/distributed/communicator.h"
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namespace paddle {
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namespace operators {
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namespace distributed {
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using LoDTensor = framework::LoDTensor;
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using SelectedRows = framework::SelectedRows;
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TEST(communicator, merge_lod_tensors) {
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auto cpu_place = platform::CPUPlace();
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auto dims = framework::make_ddim({2, 3});
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std::vector<std::shared_ptr<framework::Variable>> in_vars;
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float out_value = 0;
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for (auto i = 0; i < 10; ++i) {
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auto var = std::make_shared<Variable>();
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in_vars.emplace_back(var);
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auto *tensor = var->GetMutable<LoDTensor>();
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auto *data = tensor->mutable_data<float>(dims, cpu_place);
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for (auto j = 0; j < tensor->numel(); ++j) {
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data[j] = static_cast<float>(i);
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}
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out_value += static_cast<float>(i);
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}
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const std::string out_name = "Out";
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std::unique_ptr<framework::Scope> scope;
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scope.reset(new framework::Scope());
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scope->Var(out_name);
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for (auto i = 0; i < 10; ++i) {
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MergeVars(out_name, in_vars, scope.get());
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}
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auto &out_tensor = scope->FindVar(out_name)->Get<LoDTensor>();
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auto *out_data = out_tensor.data<float>();
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ASSERT_EQ(out_tensor.dims(), dims);
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for (auto i = 0; i < out_tensor.numel(); ++i) {
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ASSERT_EQ(out_data[i], out_value);
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}
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}
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TEST(communicator, merge_selected_rows) {
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auto cpu_place = platform::CPUPlace();
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int64_t width = 10;
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std::vector<std::shared_ptr<framework::Variable>> in_vars;
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const int64_t height = 100;
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for (auto i = 0; i < 10; ++i) {
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std::vector<int64_t> rows;
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for (auto k = 0; k <= i; ++k) {
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rows.push_back(k);
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}
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auto var = std::make_shared<Variable>();
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in_vars.emplace_back(var);
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auto *slr = var->GetMutable<SelectedRows>();
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slr->set_height(height);
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slr->set_rows(rows);
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auto dims =
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framework::make_ddim({static_cast<int64_t>(rows.size()), width});
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auto *data = slr->mutable_value()->mutable_data<float>(dims, cpu_place);
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for (auto i = 0; i < rows.size(); ++i) {
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for (auto j = 0; j < width; ++j) {
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data[i * width + j] = static_cast<float>(rows[i]);
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}
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}
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}
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const std::string out_name = "Out";
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std::unique_ptr<framework::Scope> scope;
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scope.reset(new framework::Scope());
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scope->Var(out_name);
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for (auto i = 0; i < 10; ++i) {
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MergeVars(out_name, in_vars, scope.get());
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}
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auto &out_slr = scope->FindVar(out_name)->Get<SelectedRows>();
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auto &out_t = out_slr.value();
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auto *out_data = out_t.data<float>();
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ASSERT_EQ(out_t.dims(), framework::make_ddim({10, width}));
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std::vector<float> out_values;
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out_values.reserve(10);
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for (auto i = 0; i < 10; ++i) {
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out_values.push_back(static_cast<float>(i * (10 - i)));
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}
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for (auto i = 0; i < out_slr.rows().size(); ++i) {
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ASSERT_EQ(out_slr.rows()[i], i);
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for (auto j = 0; j < width; ++j) {
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ASSERT_EQ(out_data[i * width + j], out_values[i]);
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}
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}
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}
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} // namespace distributed
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} // namespace operators
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} // namespace paddle
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