/* Copyright (c) 2016 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/platform/device_context.h"

#include <set>
#include <string>
#include <unordered_set>
#include <vector>

#include "paddle/fluid/memory/memory.h"

namespace paddle {
namespace platform {

DeviceContextPool* DeviceContextPool::pool = nullptr;

platform::DeviceContext* DeviceContextPool::Get(const platform::Place& place) {
  auto it = device_contexts_.find(place);
  if (it == device_contexts_.end()) {
    PADDLE_THROW(
        "'Place' is not supported, Please re-compile with WITH_GPU "
        "option");
  }
  return it->second.get();
}

DeviceContextPool::DeviceContextPool(
    const std::vector<platform::Place>& places) {
  PADDLE_ENFORCE_GT(places.size(), 0);
  using PtrType = std::unique_ptr<DeviceContext>;
  std::set<Place> set;
  for (auto& p : places) {
    set.insert(p);
  }
VLOG(3) << "pool start";
  for (auto& p : set) {
    if (platform::is_cpu_place(p)) {
#ifdef PADDLE_WITH_MKLDNN
      device_contexts_.emplace(
          p, PtrType(new MKLDNNDeviceContext(boost::get<CPUPlace>(p))));
#else
VLOG(3) << "cpu context start";
      device_contexts_.emplace(
          p, PtrType(new CPUDeviceContext(boost::get<CPUPlace>(p))));
#endif
    } else if (platform::is_gpu_place(p)) {
#ifdef PADDLE_WITH_CUDA
VLOG(3) << "gpu context start";
      device_contexts_.emplace(
          p, PtrType(new CUDADeviceContext(boost::get<CUDAPlace>(p))));
#else
      PADDLE_THROW(
          "'CUDAPlace' is not supported, Please re-compile with WITH_GPU "
          "option");
#endif
    } else if (platform::is_cuda_pinned_place(p)) {
#ifdef PADDLE_WITH_CUDA
VLOG(3) << "gpu pin start";
      device_contexts_.emplace(
          p,
          PtrType(new CUDAPinnedDeviceContext(boost::get<CUDAPinnedPlace>(p))));
#else
      PADDLE_THROW(
          "'CUDAPlace' is not supported, Please re-compile with WITH_GPU "
          "option");
#endif
    }
VLOG(3) << "pool finish";
  }
}

CPUDeviceContext::CPUDeviceContext() {
  eigen_device_.reset(new Eigen::DefaultDevice());
}

CPUDeviceContext::CPUDeviceContext(CPUPlace place) : place_(place) {
  eigen_device_.reset(new Eigen::DefaultDevice());
}

Eigen::DefaultDevice* CPUDeviceContext::eigen_device() const {
  return eigen_device_.get();
}

Place CPUDeviceContext::GetPlace() const { return place_; }

#ifdef PADDLE_WITH_CUDA

class EigenCudaStreamDevice : public Eigen::StreamInterface {
 public:
  EigenCudaStreamDevice() : scratch_(nullptr), semaphore_(nullptr) {
    Eigen::initializeDeviceProp();
  }
  ~EigenCudaStreamDevice() override {}

  void Reinitialize(const cudaStream_t* cuda_stream, CUDAPlace place) {
    stream_ = cuda_stream;
    place_ = place;
    device_prop_ = &Eigen::m_deviceProperties[place.device];
  }

  const cudaStream_t& stream() const override { return *stream_; }

  const cudaDeviceProp& deviceProperties() const override {
    return *device_prop_;
  }

  void* allocate(size_t num_bytes) const override {
    return paddle::memory::Alloc(place_, num_bytes);
  }

  void deallocate(void* buffer) const override {
    paddle::memory::Free(place_, buffer);
  }

  void* scratchpad() const override {
    if (scratch_ == NULL) {
      scratch_ = allocate(Eigen::kCudaScratchSize + sizeof(unsigned int));
    }
    return scratch_;
  }

  unsigned int* semaphore() const override {
    if (semaphore_ == NULL) {
      char* scratch =
          static_cast<char*>(scratchpad()) + Eigen::kCudaScratchSize;
      semaphore_ = reinterpret_cast<unsigned int*>(scratch);
      PADDLE_ENFORCE(
          cudaMemsetAsync(semaphore_, 0, sizeof(unsigned int), *stream_));
    }
    return semaphore_;
  }

 private:
  CUDAPlace place_;
  const cudaStream_t* stream_;         // not owned;
  const cudaDeviceProp* device_prop_;  // not owned;
  mutable void* scratch_;
  mutable unsigned int* semaphore_;
};

CUDADeviceContext::CUDADeviceContext(CUDAPlace place) : place_(place) {
  SetDeviceId(place_.device);
  compute_capability = GetCUDAComputeCapability(place_.device);
  multi_process = GetCUDAMultiProcessors(place_.device);
  max_threads_per_mp = GetCUDAMaxThreadsPerMultiProcessor(place_.device);
  VLOG(3) << "cuda info pass";
  PADDLE_ENFORCE(cudaStreamCreate(&stream_));
  VLOG(3) << "cuda stream pass";
  eigen_stream_.reset(new EigenCudaStreamDevice());
  eigen_stream_->Reinitialize(&stream_, place);
  eigen_device_.reset(new Eigen::GpuDevice(eigen_stream_.get()));

  VLOG(3) << "eigen pass";
    if (dynload::HasCUDNN()) {
  VLOG(3) << "cudnn start";
    PADDLE_ENFORCE(dynload::cudnnCreate(&cudnn_handle_));
    VLOG(3) << "cudnn create pass";
    PADDLE_ENFORCE(dynload::cudnnSetStream(cudnn_handle_, stream_));
  } else {
    cudnn_handle_ = nullptr;
  }
  VLOG(3) << "cudnn pass";
  PADDLE_ENFORCE(dynload::cublasCreate(&cublas_handle_));
  VLOG(3) << "cublas pass";
  PADDLE_ENFORCE(dynload::cublasSetStream(cublas_handle_, stream_));
  VLOG(3) << "cublas pass";

}

CUDADeviceContext::~CUDADeviceContext() {
  SetDeviceId(place_.device);
  Wait();
  PADDLE_ENFORCE(dynload::cublasDestroy(cublas_handle_));
  if (cudnn_handle_ != nullptr) {
    PADDLE_ENFORCE(dynload::cudnnDestroy(cudnn_handle_));
  }
  eigen_stream_.reset();
  eigen_device_.reset();
  PADDLE_ENFORCE(cudaStreamDestroy(stream_));
}

Place CUDADeviceContext::GetPlace() const { return place_; }

void CUDADeviceContext::Wait() const {
  PADDLE_ENFORCE(cudaStreamSynchronize(stream_));
  PADDLE_ENFORCE(cudaGetLastError());
}

int CUDADeviceContext::GetComputeCapability() const {
  return compute_capability;
}

int CUDADeviceContext::GetMaxPhysicalThreadCount() const {
  return multi_process * max_threads_per_mp;
}

Eigen::GpuDevice* CUDADeviceContext::eigen_device() const {
  return eigen_device_.get();
}

cublasHandle_t CUDADeviceContext::cublas_handle() const {
  return cublas_handle_;
}

cudnnHandle_t CUDADeviceContext::cudnn_handle() const { return cudnn_handle_; }

cudaStream_t CUDADeviceContext::stream() const { return stream_; }

CUDAPinnedDeviceContext::CUDAPinnedDeviceContext() {
  eigen_device_.reset(new Eigen::DefaultDevice());
}

CUDAPinnedDeviceContext::CUDAPinnedDeviceContext(CUDAPinnedPlace place)
    : place_(place) {
  eigen_device_.reset(new Eigen::DefaultDevice());
}

Eigen::DefaultDevice* CUDAPinnedDeviceContext::eigen_device() const {
  return eigen_device_.get();
}

Place CUDAPinnedDeviceContext::GetPlace() const { return place_; }
#endif

#ifdef PADDLE_WITH_MKLDNN
MKLDNNDeviceContext::MKLDNNDeviceContext(CPUPlace place)
    : CPUDeviceContext(place), engine_(mkldnn::engine::cpu, 0), p_blobs_() {
  p_blobs_.reset(new std::unordered_map<std::string, std::shared_ptr<void>>());
}

void MKLDNNDeviceContext::SetBlob(const std::string& name,
                                  std::shared_ptr<void> data) const {
  std::unordered_map<std::string, std::shared_ptr<void>>* p;
  p = p_blobs_.get();

  auto it = p->find(name);

  if (it == p->end()) {
    (*p)[name] = data;  // create new blob
  } else {
    it->second = data;  // set data to existing blob
  }

  return;
}

std::shared_ptr<void> MKLDNNDeviceContext::GetBlob(
    const std::string& name) const {
  std::unordered_map<std::string, std::shared_ptr<void>>* p;
  p = p_blobs_.get();

  auto it = p->find(name);

  if (it != p->end()) {
    return it->second;
  }

  return nullptr;
}

#endif

}  // namespace platform
}  // namespace paddle