// 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 "paddle/fluid/framework/details/eager_deletion_op_handle.h"

#include <memory>
#include <unordered_set>
#include <utility>

#include "paddle/fluid/framework/ir/memory_optimize_pass/memory_optimization_var_info.h"
#include "paddle/fluid/framework/lod_tensor_array.h"
#include "paddle/fluid/framework/scope.h"
#include "paddle/fluid/framework/selected_rows.h"
#include "paddle/fluid/platform/profiler.h"
#ifdef PADDLE_WITH_CUDA
#include "paddle/fluid/platform/cuda_device_guard.h"
#endif

namespace paddle {
namespace framework {
namespace details {

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

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

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

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

std::string EagerDeletionOpHandle::Name() const { return "eager_deletion"; }

void EagerDeletionOpHandle::RunImpl() {
  if (vars_.size() != var_infos_.size()) {
    CallOnce();
  }

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

    VLOG(2) << "Erase variable " << var_info->Name() << " on " << place_;

    Variable *var = vars_[i];

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

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

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

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