typhoonzero
7 years ago
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e834eb870a
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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// TODO(typhoonzero): add python bindings for this test as
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// a RemoteOptimizer.
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#include <unistd.h>
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#include <iostream>
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#include <thread>
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#include "gtest/gtest.h"
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#include "paddle/framework/op_registry.h"
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#include "paddle/framework/operator.h"
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#include "paddle/framework/program_desc.h"
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USE_NO_KERNEL_OP(send);
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USE_NO_KERNEL_OP(recv);
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USE_OP(sum);
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// global for simplicity.
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std::unique_ptr<paddle::framework::OperatorBase> recv_op;
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int benchmark_count = 1000;
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// FIXME(typhoonzero): protobuf message size limits the maximum tensor size
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int mat_size = 512;
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void InitTensorsInScope(paddle::framework::Scope &scope,
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paddle::platform::CPUPlace &place) {
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paddle::platform::CPUDeviceContext ctx(place);
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auto var = scope.Var("X");
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auto tensor = var->GetMutable<paddle::framework::LoDTensor>();
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tensor->Resize({mat_size, mat_size});
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float *expect = tensor->mutable_data<float>(place);
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for (int64_t i = 0; i < tensor->numel(); ++i) {
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expect[i] = static_cast<float>(i) / 1000.0f;
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}
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auto out_var = scope.Var("Out");
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auto out_tensor = out_var->GetMutable<paddle::framework::LoDTensor>();
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out_tensor->Resize({mat_size, mat_size});
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out_tensor->mutable_data<float>(place); // allocate
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}
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void AddOp(const std::string &type,
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const paddle::framework::VariableNameMap &inputs,
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const paddle::framework::VariableNameMap &outputs,
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paddle::framework::AttributeMap attrs,
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paddle::framework::BlockDescBind *block) {
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// insert output
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for (auto kv : outputs) {
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for (auto v : kv.second) {
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auto var = block->Var(v);
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var->SetDataType(paddle::framework::DataType::FP32);
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}
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}
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// insert op
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auto op = block->AppendOp();
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op->SetType(type);
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for (auto &kv : inputs) {
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op->SetInput(kv.first, kv.second);
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}
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for (auto &kv : outputs) {
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op->SetOutput(kv.first, kv.second);
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}
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op->SetAttrMap(attrs);
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}
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void StartServerNet() {
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paddle::framework::Scope scope;
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paddle::platform::CPUPlace place;
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InitTensorsInScope(scope, place);
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// sub program run in recv_op, for simple test we use sum
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paddle::framework::ProgramDescBind program;
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paddle::framework::BlockDescBind *block = program.MutableBlock(0);
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// X for server side tensors, RX for received tensers, must be of same shape.
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AddOp("sum", {{"X", {"X", "RX"}}}, {{"Out", {"Out"}}}, {}, block);
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paddle::framework::AttributeMap attrs;
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attrs.insert({"endpoint", std::string("127.0.0.1:6174")});
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attrs.insert({"OptimizeBlock", block});
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recv_op = paddle::framework::OpRegistry::CreateOp("recv", {{"RX", {"RX"}}},
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{{"Out", {"Out"}}}, attrs);
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paddle::platform::CPUDeviceContext ctx(place);
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recv_op->Run(scope, ctx);
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}
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TEST(SendRecvBenchmark, CPU) {
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std::thread server_thread(StartServerNet);
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sleep(5); // wait server to start
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// local net
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paddle::framework::Scope scope;
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paddle::platform::CPUPlace place;
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InitTensorsInScope(scope, place);
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paddle::framework::AttributeMap attrs;
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attrs.insert({"endpoint", std::string("127.0.0.1:6174")});
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auto send_op = paddle::framework::OpRegistry::CreateOp(
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"send", {{"X", {"X"}}}, {{"Out", {"Out"}}}, attrs);
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paddle::platform::CPUDeviceContext ctx(place);
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for (int i = 0; i < benchmark_count; ++i) {
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send_op->Run(scope, ctx);
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}
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recv_op.reset(); // dtor can shutdown and join server thread.
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server_thread.join();
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}
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