eager_deletion_op_handle.cc 5.4 KB
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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/eager_deletion_op_handle.h"

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#include "paddle/fluid/framework/ir/memory_optimize_pass/memory_optimization_var_info.h"
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#include "paddle/fluid/platform/profiler.h"
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#ifdef PADDLE_WITH_CUDA
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#include "paddle/fluid/platform/cuda_device_guard.h"
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#endif
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namespace paddle {
namespace framework {
class Variable;
}  // namespace framework
}  // namespace paddle

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namespace paddle {
namespace framework {
namespace details {

EagerDeletionOpHandle::EagerDeletionOpHandle(
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    ir::Node *node, Scope *scope, size_t scope_idx,
    const platform::Place &place,
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    const std::unordered_set<ir::MemOptVarInfo *> &vars, GarbageCollector *gc)
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    : OpHandleBase(node),
      scope_(scope),
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      scope_idx_(scope_idx),
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      place_(place),
      var_infos_(vars.begin(), vars.end()),
      gc_(gc) {
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#ifdef PADDLE_WITH_CUDA
  if (platform::is_gpu_place(place)) {
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    dev_ctx_ = reinterpret_cast<platform::CUDADeviceContext *>(
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        platform::DeviceContextPool::Instance().Get(place));
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    if (dynamic_cast<StreamGarbageCollector *>(gc_)) {
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      platform::CUDADeviceGuard guard(
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          BOOST_GET_CONST(platform::CUDAPlace, place).device);
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      PADDLE_ENFORCE_CUDA_SUCCESS(
          cudaEventCreateWithFlags(&event_, cudaEventDisableTiming));
      PADDLE_ENFORCE_NOT_NULL(event_, platform::errors::InvalidArgument(
                                          "The cuda envet created is NULL."));
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    }
  }
#endif
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  PADDLE_ENFORCE_NE(vars.empty(), true,
                    platform::errors::InvalidArgument(
                        "The variables to be deleted are empty."));
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  for (auto *var : var_infos_) {
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    PADDLE_ENFORCE_NOT_NULL(var, platform::errors::InvalidArgument(
                                     "The memory optimization info is NULL."));
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  }
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}

EagerDeletionOpHandle::~EagerDeletionOpHandle() {
#ifdef PADDLE_WITH_CUDA
  if (event_) {
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    auto gpu_place = BOOST_GET_CONST(platform::CUDAPlace, dev_ctx_->GetPlace());
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    platform::CUDADeviceGuard guard(gpu_place.device);
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    PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventDestroy(event_));
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  }
#endif
}

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void EagerDeletionOpHandle::InitCUDA() {
#ifdef PADDLE_WITH_CUDA
  int dev_id =
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      BOOST_GET_CONST(platform::CUDAPlace, dev_ctxes_.begin()->first).device;
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  events_[dev_id] = nullptr;
#endif
}

void EagerDeletionOpHandle::CallOnce() {
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  PADDLE_ENFORCE_EQ(
      vars_.empty(), true,
      platform::errors::InvalidArgument(
          "The variables to be deleted should be initialized here."));
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  Scope *exec_scope = local_exec_scopes_[0];
  for (auto *var_info : var_infos_) {
    auto *var = exec_scope->FindVar(var_info->Name());
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    PADDLE_ENFORCE_NOT_NULL(
        var, platform::errors::NotFound(
                 "The variable(%s) to be inplaced is not found in scope.",
                 var_info->Name()));
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    vars_.emplace_back(var);
  }
}

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std::string EagerDeletionOpHandle::Name() const { return "eager_deletion"; }
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void EagerDeletionOpHandle::RunImpl() {
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  if (vars_.size() != var_infos_.size()) {
    CallOnce();
  }

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  platform::RecordEvent record_event(Name());
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  std::deque<std::shared_ptr<memory::Allocation>> garbages;
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  for (size_t i = 0; i < var_infos_.size(); ++i) {
    auto *var_info = var_infos_[i];
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    if (var_info->IsSkippedAllMemoryOptimization() ||
        !var_info->DecreaseRefCnt()) {
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      continue;
    }

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    VLOG(2) << "Erase variable " << var_info->Name() << " on " << place_;
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    Variable *var = vars_[i];
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    if (var->IsType<LoDTensor>()) {
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      garbages.emplace_back(var->GetMutable<LoDTensor>()->MoveMemoryHolder());
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    } else if (var->IsType<SelectedRows>()) {
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      garbages.emplace_back(
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          var->GetMutable<SelectedRows>()->mutable_value()->MoveMemoryHolder());
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    } else if (var->IsType<LoDTensorArray>()) {
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      auto *tensor_arr = var->GetMutable<LoDTensorArray>();
      for (auto &t : *tensor_arr) {
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        garbages.emplace_back(t.MoveMemoryHolder());
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      }
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    } else {
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      PADDLE_THROW(platform::errors::Unimplemented(
          "The variable(%s) of type %s is not supported in eager deletion.",
          framework::ToTypeName(var->Type()), var_info->Name()));
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    }
  }

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  if (!garbages.empty()) {
    ClearGarbages(&garbages);
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  }
}

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void EagerDeletionOpHandle::ClearGarbages(
    std::deque<std::shared_ptr<memory::Allocation>> *garbages) {
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#ifdef PADDLE_WITH_CUDA
  if (event_) {
    auto compute_stream = dev_ctx_->stream();
    auto callback_stream =
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        reinterpret_cast<StreamGarbageCollector *>(gc_)->stream();
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    auto callback_func = [=]() {
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      PADDLE_ENFORCE_CUDA_SUCCESS(cudaEventRecord(event_, compute_stream));
      PADDLE_ENFORCE_CUDA_SUCCESS(
          cudaStreamWaitEvent(callback_stream, event_, 0));
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    };
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    gc_->Add(std::move(*garbages), callback_func);
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  } else {
#endif
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    gc_->Add(std::move(*garbages));
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#ifdef PADDLE_WITH_CUDA
  }
#endif
}

}  // namespace details
}  // namespace framework
}  // namespace paddle