Qiao Longfei
6 years ago
parent
be72940b76
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ca5d96bb3d
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// Copyright (c) 2018 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 <set>
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#include <string>
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#include <vector>
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#include "paddle/fluid/operators/distributed/parameter_send.h"
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#include "paddle/fluid/framework/lod_tensor.h"
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#include "paddle/fluid/framework/scope.h"
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#include "paddle/fluid/framework/selected_rows.h"
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#include "paddle/fluid/framework/tensor.h"
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#include "paddle/fluid/operators/distributed/distributed.h"
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#include "paddle/fluid/operators/distributed/rpc_client.h"
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#include "paddle/fluid/operators/distributed/variable_response.h"
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#include "paddle/fluid/operators/distributed_ops/send_recv_util.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 LoDTensor = framework::LoDTensor;
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using SelectedRows = framework::SelectedRows;
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using DDim = framework::DDim;
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static size_t GetSectionIndex(int64_t id,
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const std::vector<int64_t>& abs_sections) {
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for (size_t i = 1; i < abs_sections.size(); ++i) {
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if (id < abs_sections[i]) {
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return i - 1;
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}
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}
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return abs_sections.size() - 1;
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}
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static std::vector<int64_t> ToAbsoluteSection(
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const std::vector<int>& height_sections) {
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std::vector<int64_t> abs_sections;
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abs_sections.resize(height_sections.size());
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abs_sections[0] = 0;
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for (size_t i = 1; i < height_sections.size(); ++i) {
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abs_sections[i] = height_sections[i - 1] + abs_sections[i - 1];
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}
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return abs_sections;
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}
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static std::vector<std::vector<int64_t>> SplitIds(
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const std::vector<int64_t>& ids_vector,
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const std::vector<int>& height_section, framework::Scope* scope) {
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std::set<int64_t> all_ids;
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for (auto id : ids_vector) {
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all_ids.insert(id);
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}
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auto abs_sections = ToAbsoluteSection(height_section);
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std::vector<std::vector<int64_t>> splited_ids;
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splited_ids.resize(height_section.size() + 1);
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for (auto& id : all_ids) {
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auto section_index = GetSectionIndex(id, abs_sections);
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splited_ids[section_index].push_back(id - abs_sections[section_index]);
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}
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return splited_ids;
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}
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static void SplitIdsIntoMultipleVarsBySection(
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const std::vector<std::string>& in_var_names,
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const std::vector<int>& height_section,
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const std::vector<std::vector<int64_t>>& splited_ids,
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framework::Scope* scope) {
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PADDLE_ENFORCE_EQ(in_var_names.size(), height_section.size(), "");
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auto place = platform::CPUPlace();
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for (size_t i = 0; i < in_var_names.size(); ++i) {
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auto* id_tensor =
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scope->Var(in_var_names[i])->GetMutable<framework::LoDTensor>();
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auto& ids = splited_ids[i];
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if (!ids.empty()) {
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auto* id_tensor_data = id_tensor->mutable_data<int64_t>(
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framework::make_ddim({static_cast<int64_t>(ids.size()), 1}), place);
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memcpy(id_tensor_data, ids.data(), sizeof(int64_t) * ids.size());
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}
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}
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}
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void send(const std::string& var_name,
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const std::vector<std::string>& send_varnames,
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const std::vector<std::string>& epmap,
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const std::vector<int>& height_sections,
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const framework::ExecutionContext& context,
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const framework::Scope& scope, bool sync) {
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framework::Scope* local_scope = scope.NewTmpScope();
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platform::DeviceContextPool& pool = platform::DeviceContextPool::Instance();
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auto& cpu_ctx = *pool.Get(platform::CPUPlace());
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auto& actual_ctx = *pool.Get(context.GetPlace());
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distributed::RPCClient* rpc_client =
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distributed::RPCClient::GetInstance<RPCCLIENT_T>(
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context.Attr<int>("trainer_id"));
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auto* send_var = scope.FindVar(var_name);
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size_t out_num = send_varnames.size();
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if (send_var->IsType<framework::LoDTensor>()) {
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auto& send_tensor = send_var->Get<framework::LoDTensor>();
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auto& send_tensor_dims = send_tensor.dims();
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std::vector<framework::DDim> outs_dims;
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outs_dims.reserve(out_num);
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// infer output shape
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int num = context.Attr<int>("num");
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if (num > 0) {
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int64_t in_axis_dim = send_tensor_dims[0];
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PADDLE_ENFORCE_EQ(in_axis_dim % num, 0,
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"tensor split does not result"
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" in an equal division");
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size_t out_axis_dim = in_axis_dim / num;
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for (size_t i = 0; i < out_num; ++i) {
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auto dim = send_tensor_dims;
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dim[0] = out_axis_dim;
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outs_dims.push_back(dim);
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}
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} else if (height_sections.size() > 0) {
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PADDLE_ENFORCE_EQ(height_sections.size(), out_num,
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"tensor split sections size"
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"should be equal to output size.");
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for (size_t i = 0; i < out_num; ++i) {
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auto dim = send_tensor_dims;
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dim[0] = height_sections[i];
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outs_dims.push_back(dim);
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}
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}
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// create output var in local scope
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size_t row_offset = 0;
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for (auto i = 0; i < out_num; ++i) {
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auto* out =
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local_scope->Var(send_varnames[i])->GetMutable<framework::Tensor>();
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*out = send_tensor.Slice(row_offset, row_offset + outs_dims[i][0]);
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row_offset += outs_dims[i][0];
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}
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} else if (send_var->IsType<framework::LoDTensor>()) {
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// create output var in local scope
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for (auto& name : send_varnames) {
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local_scope->Var(name)->GetMutable<framework::SelectedRows>();
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}
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} else {
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PADDLE_THROW("unsupported var type");
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}
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std::vector<distributed::VarHandlePtr> rets;
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for (size_t i = 0; i < send_varnames.size(); i++) {
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auto& send_var_name = send_varnames[i];
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auto& endpoint = epmap[i];
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if (NeedSend(*local_scope, send_var_name)) {
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VLOG(3) << "sending " << send_var_name << " to " << endpoint;
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rets.push_back(rpc_client->AsyncSendVar(endpoint, cpu_ctx, *local_scope,
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send_var_name));
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} else {
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VLOG(3) << "don't send non-initialized variable: " << send_varnames[i];
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}
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}
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if (sync) {
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for (size_t i = 0; i < rets.size(); i++) {
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PADDLE_ENFORCE(rets[i]->Wait(), "internal error in RPCClient");
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}
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}
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delete local_scope;
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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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@ -0,0 +1,35 @@
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// Copyright (c) 2018 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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#pragma once
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#include <string>
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#include <vector>
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#include "paddle/fluid/framework/operator.h"
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namespace paddle {
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namespace operators {
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namespace distributed {
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void send(const std::string& var_name,
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const std::vector<std::string>& send_varnames,
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const std::vector<std::string>& epmap,
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const std::vector<int>& height_sections,
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const framework::ExecutionContext& context,
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const framework::Scope& scope, bool sync);
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}; // namespace distributed
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}; // namespace operators
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}; // namespace paddle
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