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Paddle/paddle/fluid/operators/distributed/parameter_recv.cc

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// 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 <memory>
#include <set>
#include <string>
#include <vector>
#include "paddle/fluid/operators/distributed/parameter_recv.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/scope.h"
#include "paddle/fluid/framework/selected_rows.h"
#include "paddle/fluid/framework/tensor.h"
#include "paddle/fluid/operators/distributed/distributed.h"
#include "paddle/fluid/operators/distributed/rpc_client.h"
#include "paddle/fluid/operators/distributed/variable_response.h"
#include "paddle/fluid/operators/distributed_ops/send_recv_util.h"
#include "paddle/fluid/operators/strided_memcpy.h"
namespace paddle {
namespace operators {
namespace distributed {
using LoDTensor = framework::LoDTensor;
using LoDTensor = framework::LoDTensor;
using SelectedRows = framework::SelectedRows;
using DDim = framework::DDim;
template <typename T>
void ParameterRecv<T>::operator()(const RpcContext &rpc_ctx,
const framework::Scope &scope) {
VLOG(3) << "ParameterRecv in";
std::unique_ptr<framework::Scope> local_scope = scope.NewTmpScope();
platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
auto &cpu_ctx = *pool.Get(platform::CPUPlace());
distributed::RPCClient *rpc_client =
distributed::RPCClient::GetInstance<RPCCLIENT_T>(0);
auto *recv_var = scope.FindVar(rpc_ctx.var_name);
std::vector<framework::Tensor *> recved_tensors;
// recv all vars to local scope
if (recv_var->IsType<framework::LoDTensor>()) {
std::vector<distributed::VarHandlePtr> rets;
for (size_t i = 0; i < rpc_ctx.splited_var_names.size(); i++) {
auto &recv_var_name = rpc_ctx.splited_var_names[i];
framework::Tensor *t =
local_scope->Var(recv_var_name)->GetMutable<framework::LoDTensor>();
recved_tensors.push_back(t);
VLOG(3) << "recv " << recv_var_name << " from " << rpc_ctx.epmap[i];
rets.push_back(rpc_client->AsyncGetVar(rpc_ctx.epmap[i], cpu_ctx,
*local_scope.get(), recv_var_name,
recv_var_name));
}
for (size_t i = 0; i < rets.size(); i++) {
PADDLE_ENFORCE(rets[i]->Wait(), "internal error in RPCClient");
}
} else {
PADDLE_THROW("unsupported var type to recv!");
}
// concat recved tensor into one var
{
size_t output_offset = 0;
framework::Tensor *recv_tensor =
recv_var->GetMutable<framework::LoDTensor>();
auto dev_ctx = paddle::platform::CPUDeviceContext();
int64_t recv_numel = 0;
for (auto *in : recved_tensors) {
recv_numel += in->numel();
auto in_stride = framework::stride_numel(in->dims());
auto out_stride = framework::stride_numel(recv_tensor->dims());
StridedNumelCopyWithAxis<T>(
dev_ctx, 0, recv_tensor->data<T>() + output_offset, out_stride,
in->data<T>(), in_stride, in_stride[0]);
output_offset += in_stride[0];
}
PADDLE_ENFORCE_EQ(recv_numel, recv_tensor->numel());
}
VLOG(3) << "ParameterRecv out";
}
template struct ParameterRecv<float>;
}; // namespace distributed
}; // namespace operators
}; // namespace paddle