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145 changes: 145 additions & 0 deletions
145
paddle/fluid/framework/details/reduce_blockop_handle.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. | ||
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| #include "paddle/fluid/framework/details/reduce_blockop_handle.h" | ||
| #include "paddle/fluid/framework/details/container_cast.h" | ||
| #include "paddle/fluid/framework/details/reduce_and_gather.h" | ||
| #include "paddle/fluid/framework/details/variable_visitor.h" | ||
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| namespace paddle { | ||
| namespace framework { | ||
| namespace details { | ||
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| void ReduceBlockOpHandle::RunImpl() { | ||
| if (places_.size() == 1) return; | ||
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| WaitInputVarGenerated(); | ||
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| auto in_var_handles = DynamicCast<VarHandle>(inputs_); | ||
| auto out_var_handles = DynamicCast<VarHandle>(outputs_); | ||
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| PADDLE_ENFORCE_EQ(in_var_handles.size(), | ||
| places_.size() * out_var_handles.size(), | ||
| "The number of input and output is not consistent."); | ||
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| #ifdef PADDLE_WITH_CUDA | ||
| std::vector<const LoDTensor *> lod_tensors = GetInputValues(); | ||
| auto type = lod_tensors[0]->type(); | ||
| auto numel = lod_tensors[0]->numel(); | ||
| std::vector<std::function<void()>> nccl_reduce_calls; | ||
| auto root_dev_id = | ||
| boost::get<platform::CUDAPlace>(places_[dst_scope_id_]).device; | ||
| for (size_t i = 0; i < local_scopes_.size(); ++i) { | ||
| int dev_id = | ||
| boost::get<platform::CUDAPlace>(lod_tensors[i]->place()).device; | ||
| auto &nccl_ctx = nccl_ctxs_->at(dev_id); | ||
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| void *buffer = const_cast<void *>(lod_tensors[i]->data<void>()); | ||
| void *recvbuffer = nullptr; | ||
| if (i == dst_scope_id_) { | ||
| auto reduce_var = local_scopes_[dst_scope_id_]->FindVar(var_name_); | ||
| recvbuffer = reduce_var->GetMutable<framework::LoDTensor>()->mutable_data( | ||
| lod_tensors[dst_scope_id_]->place()); | ||
| } | ||
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| int nccl_type = platform::ToNCCLDataType(type); | ||
| nccl_reduce_calls.emplace_back( | ||
| [buffer, recvbuffer, nccl_type, numel, root_dev_id, &nccl_ctx] { | ||
| PADDLE_ENFORCE(platform::dynload::ncclReduce( | ||
| buffer, recvbuffer, numel, static_cast<ncclDataType_t>(nccl_type), | ||
| ncclSum, root_dev_id, nccl_ctx.comm_, nccl_ctx.stream())); | ||
| }); | ||
| } | ||
| #endif | ||
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| std::vector<const Scope *> var_scopes; | ||
| for (auto *s : local_scopes_) { | ||
| auto var = s->FindVar(kLocalExecScopeName); | ||
| PADDLE_ENFORCE_NOT_NULL(var); | ||
| var_scopes.emplace_back(var->Get<Scope *>()); | ||
| } | ||
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| // Reduce the variable which is in CPU side. | ||
| std::vector<std::vector<const LoDTensor *>> cpu_lod_tensors; | ||
| std::vector<Variable *> cpu_out_vars; | ||
| for (auto out_var_h : out_var_handles) { | ||
| auto out_var = var_scopes[dst_scope_id_]->FindVar(out_var_h->name_); | ||
| PADDLE_ENFORCE_NOT_NULL(out_var); | ||
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| if (platform::is_cpu_place(out_var->Get<LoDTensor>().place())) { | ||
| std::vector<const LoDTensor *> lod_tensors; | ||
| for (size_t i = 0; i < places_.size(); ++i) { | ||
| lod_tensors.emplace_back( | ||
| &(var_scopes[i]->FindVar(out_var_h->name_)->Get<LoDTensor>())); | ||
| PADDLE_ENFORCE(platform::is_cpu_place(lod_tensors.back()->place())); | ||
| } | ||
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| cpu_lod_tensors.push_back(lod_tensors); | ||
| cpu_out_vars.push_back(out_var); | ||
| } | ||
| } | ||
| #ifdef PADDLE_WITH_CUDA | ||
| this->RunAndRecordEvent([&] { | ||
| { | ||
| platform::NCCLGroupGuard guard; | ||
| for (auto &call : nccl_reduce_calls) { | ||
| call(); | ||
| } | ||
| } | ||
| for (size_t i = 0; i < cpu_lod_tensors.size(); ++i) { | ||
| ReduceLoDTensor func(cpu_lod_tensors[i], | ||
| cpu_out_vars[i]->GetMutable<framework::LoDTensor>()); | ||
| VisitDataType(ToDataType(cpu_lod_tensors[i][0]->type()), func); | ||
| } | ||
| }); | ||
| #endif | ||
| } | ||
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| std::vector<const LoDTensor *> ReduceBlockOpHandle::GetInputValues() { | ||
| std::vector<const LoDTensor *> lod_tensors; | ||
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| auto &value_0 = GetInputValue(0); | ||
| lod_tensors.emplace_back(&value_0); | ||
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| std::unordered_set<int> dev_id_set; | ||
| auto dev_id = boost::get<platform::CUDAPlace>(value_0.place()).device; | ||
| dev_id_set.insert(dev_id); | ||
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| for (size_t i = 1; i < local_scopes_.size(); ++i) { | ||
| auto &value = GetInputValue(i); | ||
| PADDLE_ENFORCE_EQ(value_0.type(), value.type()); | ||
| PADDLE_ENFORCE_EQ(value_0.numel(), value.numel()); | ||
| lod_tensors.emplace_back(&value); | ||
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| auto dev_id = boost::get<platform::CUDAPlace>(value.place()).device; | ||
| if (dev_id_set.count(dev_id)) { | ||
| PADDLE_THROW("dev_%d has been in dev_id_set.", dev_id); | ||
| } | ||
| dev_id_set.insert(dev_id); | ||
| } | ||
| return lod_tensors; | ||
| } | ||
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| const LoDTensor &ReduceBlockOpHandle::GetInputValue(size_t idx) { | ||
| auto reduce_var = local_scopes_.at(idx)->FindVar(var_name_); | ||
| PADDLE_ENFORCE_NOT_NULL(reduce_var, "%s is not found.", var_name_); | ||
| auto &lod_tensor = reduce_var->Get<LoDTensor>(); | ||
| PADDLE_ENFORCE(platform::is_gpu_place(lod_tensor.place())); | ||
| return lod_tensor; | ||
| } | ||
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| std::string ReduceBlockOpHandle::Name() const { return "reduce_block"; } | ||
| } // namespace details | ||
| } // namespace framework | ||
| } // namespace paddle |
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