/* Copyright 2016 The TensorFlow 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 "tensorflow/core/distributed_runtime/rpc/rpc_rendezvous_mgr.h"

#include <unordered_set>

#include "tensorflow/core/common_runtime/device.h"
#include "tensorflow/core/common_runtime/device_mgr.h"
#include "tensorflow/core/common_runtime/dma_helper.h"
#include "tensorflow/core/common_runtime/process_util.h"
#include "tensorflow/core/distributed_runtime/tensor_coding.h"
#include "tensorflow/core/distributed_runtime/worker_cache.h"
#include "tensorflow/core/distributed_runtime/worker_interface.h"
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/strings/numbers.h"
#include "tensorflow/core/lib/strings/str_util.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/macros.h"
#include "tensorflow/core/platform/types.h"

namespace tensorflow {

namespace {

class RpcRemoteRendezvous : public BaseRemoteRendezvous {
 public:
  RpcRemoteRendezvous(const WorkerEnv* env, WorkerCacheInterface* cache,
                      int64 step_id)
      : BaseRemoteRendezvous(env, step_id, false), cache_(cache) {}

 protected:
  void RecvFromRemoteAsync(const Rendezvous::ParsedKey& parsed,
                           const Rendezvous::Args& args,
                           DoneCallback done) override;

 private:
  ~RpcRemoteRendezvous() override {}

  WorkerCacheInterface* cache_;  // Not owned.
  TF_DISALLOW_COPY_AND_ASSIGN(RpcRemoteRendezvous);
};

// Used only to retrieve tensors from remote processes.
class RpcRecvTensorCall : public BaseRecvTensorCall {
 public:
  RpcRecvTensorCall() : wi_(nullptr), dst_device_(nullptr) {}

  void Init(WorkerInterface* wi, int64 step_id, StringPiece key,
            AllocatorAttributes alloc_attrs, Device* dst_device,
            const Rendezvous::Args& recv_args, Rendezvous::DoneCallback done) {
    wi_ = wi;
    alloc_attrs_ = alloc_attrs;
    dst_device_ = dst_device;
    recv_args_ = recv_args;
    done_ = std::move(done);
    req_.set_step_id(step_id);
    req_.set_rendezvous_key(key.data(), key.size());
  }

  void Reset() {
    delete wi_;
    wi_ = nullptr;
    alloc_attrs_ = AllocatorAttributes();
    dst_device_ = nullptr;
    // We don't clear opts_ and assume that Init will set up the state for
    // opts_ appropriately.
    req_.Clear();
    resp_.Clear();
    {
      mutex_lock l(mu_);
      status_ = Status::OK();
    }
    done_ = nullptr;
  }

  ~RpcRecvTensorCall() override { delete wi_; }

  void Start(std::function<void()> recv_done) override {
    StartRTCall(std::move(recv_done));
  }

  void StartAbort(const Status& s) override {
    {
      mutex_lock l(mu_);
      status_.Update(s);
    }
    opts_.StartCancel();
  }

  Status status() const override {
    mutex_lock l(mu_);
    return status_;
  }

  const Tensor& tensor() const { return resp_.tensor(); }

  bool is_dead() const { return resp_.metadata().is_dead(); }

  Device* dst_device() const { return dst_device_; }
  const Rendezvous::Args& recv_args() const { return recv_args_; }
  const Rendezvous::DoneCallback& done() const { return done_; }

 private:
  friend class RpcRemoteRendezvous;

  // Start the main RecvTensor call, checking for an async abort.
  void StartRTCall(std::function<void()> recv_done) {
    resp_.InitAlloc(dst_device_, alloc_attrs_);
    using namespace std::placeholders;
    StatusCallback cb = std::bind(
        [this](std::function<void()> recv_done,
               // Begin unbound arguments.
               const Status& s) {
          if (!s.ok()) {
            mutex_lock l(mu_);
            status_.Update(s);
          }
          recv_done();
        },
        std::move(recv_done), _1);
    wi_->RecvTensorAsync(&opts_, &req_, &resp_, std::move(cb));
  }

  string src_worker_;
  string src_rel_device_;
  WorkerInterface* wi_;
  AllocatorAttributes alloc_attrs_;
  Device* dst_device_;
  CallOptions opts_;
  RecvTensorRequest req_;
  TensorResponse resp_;
  Rendezvous::Args recv_args_;
  Rendezvous::DoneCallback done_;

  mutable mutex mu_;
  Status status_ GUARDED_BY(mu_);

  TF_DISALLOW_COPY_AND_ASSIGN(RpcRecvTensorCall);
};

class RpcRecvTensorFreeList {
 public:
  RpcRecvTensorFreeList() {}
  ~RpcRecvTensorFreeList() {
    for (int i = 0; i < objects_.size(); i++) {
      delete objects_[i];
    }
  }

  RpcRecvTensorCall* New() {
    {
      mutex_lock l(mu_);
      if (!objects_.empty()) {
        RpcRecvTensorCall* result = objects_.back();
        objects_.pop_back();
        return result;
      }
    }
    return new RpcRecvTensorCall;
  }

  void Release(RpcRecvTensorCall* obj) {
    obj->Reset();
    {
      mutex_lock l(mu_);
      if (objects_.size() < kMaxObjects) {
        objects_.push_back(obj);
        return;
      }
    }
    delete obj;
  }

 private:
  static const int kMaxObjects = 1000;

  mutex mu_;
  std::vector<RpcRecvTensorCall*> objects_ GUARDED_BY(mu_);
};

static RpcRecvTensorFreeList* get_call_freelist() {
  static RpcRecvTensorFreeList* call_freelist = new RpcRecvTensorFreeList();
  return call_freelist;
}

// A private cache that wraps env->worker_cache and allows reuse of
// WorkerInterface objects.
class WorkerFreeListCache : public WorkerCacheInterface {
 public:
  explicit WorkerFreeListCache(WorkerCacheInterface* w) : wrapped_(w) {}

  ~WorkerFreeListCache() {
    for (auto p : workers_) {
      delete p.second.worker;
    }
  }

  void ListWorkers(std::vector<string>* workers) override {
    wrapped_->ListWorkers(workers);
  }

  WorkerInterface* CreateWorker(const string& target) override {
    mutex_lock l(mu_);
    auto p = workers_.find(target);
    if (p != workers_.end()) {
      return p->second.worker;
    }
    WorkerState state;
    state.worker = wrapped_->CreateWorker(target);
    if (state.worker != nullptr) {
      workers_.insert(make_pair(target, state));
    }
    return state.worker;
  }

  void ReleaseWorker(const string& target, WorkerInterface* worker) override {
    // TODO(jeff,sanjay): Should decrement ref-count when we implement eviction.
  }

  bool GetDeviceBusNonBlocking(const string& device,
                               BusAdjacency* ba) override {
    return wrapped_->GetDeviceBusNonBlocking(device, ba);
  }

  void GetDeviceBusAsync(const string& device, BusAdjacency* ba,
                         StatusCallback done) override {
    wrapped_->GetDeviceBusAsync(device, ba, done);
  }

  void SetLogging(bool active) override { wrapped_->SetLogging(active); }

  void ClearLogs() override { wrapped_->ClearLogs(); }

  bool RetrieveLogs(int64 step_id, StepStats* ss) override {
    return wrapped_->RetrieveLogs(step_id, ss);
  }

 private:
  WorkerCacheInterface* wrapped_;

  // Information kept per created WorkerInterface.
  struct WorkerState {
    WorkerInterface* worker;
    // TODO(jeff,sanjay): Add reference count if we support eviction.
  };

  // TODO(jeff,sanjay): Eviction when the map becomes too big.
  mutex mu_;
  std::unordered_map<string, WorkerState> workers_ GUARDED_BY(mu_);
};

void RpcRemoteRendezvous::RecvFromRemoteAsync(
    const Rendezvous::ParsedKey& parsed, const Rendezvous::Args& recv_args,
    DoneCallback done) {
  Status s;

  // TODO(jeff): Consider checking for a valid worker_cache during the
  // constructor of RpcRemoteRendezvous, rather than here, to simplify
  // the twisty logic below.
  if (env_->worker_cache == nullptr) {
    s = errors::Internal("No remote worker cache available.");
    done(s, Args(), recv_args, Tensor{}, false);
    return;
  }

  // Prepare a RecvTensor call that can handle being aborted.
  RpcRecvTensorCall* call = get_call_freelist()->New();

  // key.src_device identifies a remote device.
  if (!DeviceNameUtils::SplitDeviceName(parsed.src_device, &call->src_worker_,
                                        &call->src_rel_device_)) {
    s = errors::Internal(parsed.src_device,
                         " is invalid remote source device.");
  }
  WorkerInterface* rwi = cache_->CreateWorker(call->src_worker_);
  if (s.ok() && rwi == nullptr) {
    s = errors::Internal("No worker known as ", call->src_worker_);
  }

  Device* dst_device;
  if (s.ok()) {
    s = env_->device_mgr->LookupDevice(parsed.dst_device, &dst_device);
  }
  if (!s.ok()) {
    get_call_freelist()->Release(call);
    done(s, Args(), recv_args, Tensor{}, false);
    return;
  }

  call->Init(rwi, step_id_, parsed.FullKey(), recv_args.alloc_attrs, dst_device,
             recv_args, std::move(done));

  // Record "call" in active_ so that it can be aborted cleanly.
  RegisterCall(call);

  // Start "call".
  Ref();
  call->Start([this, call]() {
    // Removes "call" from active_. Prevent StartAbort().
    DeregisterCall(call);
    // If StartAbort was called prior to DeregisterCall, then the
    // current status should be bad.
    Status s = call->status();
    call->done()(s, Args(), call->recv_args(), call->tensor(), call->is_dead());
    cache_->ReleaseWorker(call->src_worker_, call->wi_);
    call->wi_ = nullptr;
    get_call_freelist()->Release(call);
    Unref();
  });
}

}  // namespace

RpcRendezvousMgr::RpcRendezvousMgr(const WorkerEnv* env)
    : BaseRendezvousMgr(env),
      cache_(new WorkerFreeListCache(env->worker_cache)) {}

BaseRemoteRendezvous* RpcRendezvousMgr::Create(int64 step_id,
                                               const WorkerEnv* worker_env) {
  return new RpcRemoteRendezvous(worker_env, cache_.get(), step_id);
}

}  // end namespace tensorflow
